Review Open Access
Copyright ©2014 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Gastrointest Oncol. Apr 15, 2014; 6(4): 83-97
Published online Apr 15, 2014. doi: 10.4251/wjgo.v6.i4.83
Use of blood-based biomarkers for early diagnosis and surveillance of colorectal cancer
Ganepola AP Ganepola, Joel Nizin, John R Rutledge, David H Chang, Center for Cancer Research and Genomic Medicine, The Daniel and Gloria Blumenthal Cancer Center, Paramus, NJ 07652, United States
Ganepola AP Ganepola, Joel Nizin, Department of Surgery, The Valley Hospital, Ridgewood, NJ 07450, United States
Author contributions: All the authors wrote the manuscript.
Supported by The Valley Hospital Foundation Research Fund; The community of The Valley Hospital in Ridgewood, NJ, especially Ms. Audrey Meyers, CEO, Mr. Anastasios Kozaitis, president of the Valley Hospital Foundation
Correspondence to: David H Chang, PhD, Research Scientist, Center for Cancer Research and Genomic Medicine, The Daniel and Gloria Blumenthal Cancer Center, The Valley Hospital, 1 Valley Health Plaza, Paramus, NJ 07652, United States.
Telephone: +1-201-6345542 Fax: +1-201-6345383
Received: November 5, 2013
Revised: March 8, 2014
Accepted: March 17, 2014
Published online: April 15, 2014


Early screening for colorectal cancer (CRC) holds the key to combat and control the increasing global burden of CRC morbidity and mortality. However, the current available screening modalities are severely inadequate because of their high cost and cumbersome preparatory procedures that ultimately lead to a low participation rate. People simply do not like to have colonoscopies. It would be ideal, therefore, to develop an alternative modality based on blood biomarkers as the first line screening test. This will allow for the differentiation of the general population from high risk individuals. Colonoscopy would then become the secondary test, to further screen the high risk segment of the population. This will encourage participation and therefore help to reach the goal of early detection and thereby reduce the anticipated increasing global CRC incidence rate. A blood-based screening test is an appealing alternative as it is non-invasive and poses minimal risk to patients. It is easy to perform, can be repeated at shorter intervals, and therefore would likely lead to a much higher participation rate. This review surveys various blood-based test strategies currently under investigation, discusses the potency of what is available, and assesses how new technology may contribute to future test design.

Key Words: Colorectal neoplasms, Early detection of cancer, Colonoscopy, Biological markers, Blood, Messenger RNA, MicroRNA, Long non-coding RNA, DNA methylation, Microsatellite instability, Loss of heterozygosity, High-throughput nucleotide sequencing, Mass spectrometry, Real-time polymerase chain reaction, Microarray analysis

Core tip: Current colorectal cancer screening modalities are severely inadequate for global application because of high costs and a low participation rate. The alternative is to develop a blood-based screening test based on biomarkers which can replace colonoscopy as a first-line screening tool. The blood-based test should identify the high risk population, which will then be followed by colonoscopy as a secondary test. This review surveys the various experimental approaches and latest research into ideal biomarkers for the initial screening test, the pros and cons of each method and their potential to lead to a future screening test.


Colorectal cancer (CRC) is the third most common cancer and fourth most common cause of cancer death in the world[1]. It is anticipated that as global communities become more developed and the world population ages, the morbidity and mortality rates due to CRC will increase substantially[2]. Although a number of early detection screening modalities have been used extensively in developed nations to lower the incidence and mortality rate, their overall high cost and low participation rate render them to be ineffective in controlling CRC on the global scale. Therefore, an alternative first line screening modality that has high sensitivity, high specificity, is relatively inexpensive and easily implemented, is urgently needed to help reduce the expected increase in global CRC burden. The main purpose of this review is to investigate the potential application of blood-based biomarkers in early diagnosis and surveillance of CRC cases.


Cancer is the leading cause of death in countries with a very high human development index and is poised to become a major cause of morbidity and mortality in every region of the world in the next few decades[3]. The United Nations has forecasted that the global population will reach 7.2 billion by July 2013, but population growth will slow in the next few decades, reaching 9.6 billion in 2050 and 10.9 billion in 2100 according to the medium-variant projection[4]. The United Nations report further delineated that the population growth will trend toward a balance between declining fertility rate and increasing population longevity. The increase in the aged population is expected to translate into an increasing global burden of cancer incidence[3,5]. In particular, it is anticipated that when the global population as a whole becomes more developed through rapid societal and economic changes, infection-related cancers (i.e., cervical, stomach and liver cancers) will continue to decline but will be replaced with an increasing number of cancers associated with reproductive, dietary, and hormonal factors (i.e., breast, colorectal, lung, and prostate cancers) as is typically found in high human development index regions.

Therefore, it is crucial to develop an early diagnostic modality for CRC that can be adaptable, economical, and implemented en masse by the global community.

Current screening options and their pros and cons

In the United States, CRC is the third most common cancer diagnosed among men and women and the second leading cause of cancer death with the estimation of 142280 new cases and 50830 deaths in 2013[6]. The five-year survival rate is 90% for cancer found localized or confined to the bowel wall, 70% for cancer with lymph node involvement, and 10% for cancer that has metastasized. Clearly, these numbers demonstrate that screening and early detection would lead to better survival, prognosis, treatment options, and hence quality of life. In 1980, the American Cancer Society (ACS) issued a formal guideline for CRC screening in average-risk adults, including an annual digital rectal exam and stool guaiac slide test in addition to the performance of a sigmoidoscopy every three to five years[7]. Since the guideline was issued, the cancer morbidity and mortality rates, which peaked around 1985 in the United States, have been in steady decline[6]. It is conceivable that the decline of CRC rates is at least partially attributable to the implementation of early screening and surveillance programs[8].

As of 2008, the basic screening modalities remain remarkably similar to those used in 1980 when the original guideline was issued, even when taking into account the development of newer technology in subsequent years[8]. In general, ACS, American College of Radiology (ACR), and the United States Preventive Services Task Force (USPSTF)[9] all agree on and emphasize the importance of CRC screening[8,10-12]. The recommended CRC screening modalities can be roughly divided into two different categories: fecal tests and direct structural exams.

The fecal tests are essentially “blood in the stool” tests. They can be performed using either a hemoglobin test [the guaiac-based Fecal Occult Blood Test (gFOBT)] or a newer and more sensitive version of an antibody-based globin test, known as the immunochemical FOBT or Fecal Immunochemical Test (FIT)[13]. In general, the gFOBT test is a non-invasive, inexpensive and easily applicable screening test which patients can readily perform in the comfort of their own home. Specimens from a FIT must be submitted to a laboratory for testing. The fecal tests help to reduce the risk of CRC death but has no effect on all-cause mortality[14]. They are not specific tests for CRC markers, and if found positive, the presence of CRC must still be confirmed by a direct structural exam such as colonoscopy or imaging procedures[15]. The fecal tests have high false positive rate for detecting CRC as gastrointestinal bleeding may occur in other conditions like colitis and hemorrhoids[16-18]. This, therefore, increases the burden of unnecessary colonoscopies and anxiety among patients[19]. It also may not detect precancerous lesions or early stage adenomas as bleeding may not be readily detectable in the presence of these conditions[20,21]. Regarding the fecal tests in general, the opportunity for CRC prevention is both limited and incidental and they are therefore not recommended as the solo screening test for CRC[8].

Direct structural exams include endoscopic procedures, such as flexible sigmoidoscopy and colonoscopy, and imaging procedures, such as double-contrast barium enema and computed tomographic colonography. In general, both flexible sigmoidoscopy and colonoscopy are invasive procedures using a colonoscope. Sigmoidoscopy is a small-scale colonoscopy which can be performed with a simple preparation without sedation, and is used to examine the lower half of the colon lumen as opposed to the entire colon. The complete colonoscopy allows direct mucosal inspection of the entire colon from the appendiceal orifice to the dentate line. Same-session biopsy sampling or definitive treatment by polypectomy in the case of precancerous polyps and some early-stage cancers can also be performed. The double-contrast barium enema and computed tomographic colonography are both imaging examinations of the colon in its entirety and are either noninvasive or minimally invasive. However, although they allow for complete examination of the colon, there is no opportunity for biopsy or polypectomy and must therefore be followed up by therapeutic colonoscopy when polyps are found.

Inadequacy of colonoscopy

In the United States, colonoscopy has become the gold standard of CRC screening. It is one of the critical screening procedures recommended by ACS, ACR, and USPSTF, and it is also recommended by the American College of Gastroenterology as the preferred screening test[22]. The principal benefit of colonoscopy is that it allows for a full structural examination of the colon and rectum in a single session and for the detection of colorectal polyps and cancers accompanied by biopsy or polypectomy. Therefore, it has been performed with much higher frequency than all other procedures[23].

However, even in the United States where the technology and procedure are widely available, the colorectal screening participation is still low among average-risk adults in the range of 29.8% to 55.2%[24]. The participation rate is also surprisingly low at 40% for people at increased risk of CRC[25,26]. The majority of United States adults are not receiving regular age- and risk-appropriate screening due to concerns of cost, risk, and the discomfort and cumbersome preparation associated with the procedure[27-29]. The same is true in other European and Asian nations[2,30-32].

Although colonoscopy is the most effective screening method for CRC, there are various reported risks associated with the procedure, including bleeding (1.64 per 1000 patients), perforation (0.85 per 1000), death (0.074 per 1000), missed adenoma (6%-12%), and missed cancer (5%)[33]. The observed rate of missed polyps and/or cancer are largely due to variations in polyp size and other factors such as sub-optimal bowel preparation, experience of the endoscopists, and patient anatomical variations[34]. When it is taken into consideration that the guideline for the average-risk adult is to undergo colonoscopy every 10 years beginning at age 50[8,22] coupled with the rate of missed polyps being between 6% and 12%, there is still risk of developing CRC even when regular colonoscopy screening guidelines are followed.

Importance of an alternative screening method for CRC

The goals of any test are to detect disease early, improve duration and quality of life, reduce mortality and/or morbidity, and augment patient participation for that disease process-all at a very low risk and cost. To this end, the current CRC screening modality based on colonoscopy is severely inadequate. Despite all of the benefits that colonoscopy can offer as a screening procedure for CRC, concerns about its cost, risks, cumbersome preparatory procedure, and willingness of the general public to participate seriously compromise its effect in undermining the global CRC burden[35-37].

In an ideal world, the first line screening should be performed to identify a high risk segment of the population and then use a more extensive test (colonoscopy) on this sub group to reduce incidence of advanced diseases. In other words, it is crucial for the first line screening program to separate the following three entities: the general population (average risk), high risk group, and cancer group. Despite its non-specific nature, the simple FIT, when coupled with colonoscopy, has helped to dramatically reduce cancer incidence and number of deaths - In 100000 average risk patients, this screening has helped to reduce the number of cancer cases from 4875 to 1393, and number of cancer deaths from 1782 to 457[38]. Therefore, a more effective and sensitive blood-based biomarker test, supported by evidence from larger studies with solid results, can readily replace the stool-based test.

In order to establish a screening test, it must be evaluated for the following elements: frequency of performance, risk of complications, limitations, and false positive and negative rates. A blood-based test could be ideally used as a first line screening if all these elements were reliably determined and optimized. Colonoscopy would then become the secondary test, not the primary one. There will be greater willingness, by physicians and patients alike, to perform a blood test every several years than to justify the bowel preparation and complications of colonoscopy every 5-10 years.


Blood vessels are the human body’s internal superhighways, for transporting nutrients to all cells in the body and carrying away waste products to avoid toxin buildup. Furthermore, they are also the body’s chief communication channel into which signaling molecules such as hormones and cytokines are secreted and released in order to regulate a cascade of effector cell functions on distant sites. It would be ideal, therefore, to take advantage of this superhighway, with all of its abundant signaling molecules, to gauge a patient’s health status.

The idea of a blood-based molecular test is appealing because the specimens can be obtained readily in a non-invasive manner, and it can be easily performed for any patient with minimal risk. If it were available, a blood-based test for CRC would reduce the overall cost, risk, and low patient participation issues that are typically associated with colonoscopy[39]. The key to developing a useful blood-based molecular test is to find specific molecular indicators in the blood that are sensitive and specific for the detection of CRC. These indicators can be present in plasma or serum, and any form of molecules, including RNA, DNA, and protein[40-44].

Recent advances in the development of molecular diagnostic technology have allowed an expanding list of potential new screening modalities based on blood specimens to emerge. The available technologies, their current status, and their potential application will be discussed in further detail below.

Circulating RNA markers

RNA was originally thought to be highly labile, easily degradable, and therefore not likely to be stable or detectable outside of the protective cellular environment. However, numerous recent studies have shown that RNA are actually stable outside of cells[45,46], and all species of RNA, including both coding messenger RNA (mRNA)[47] and non-coding RNA, which includes microRNA (miRNA) and long non-coding RNA (lncRNA)[48,49], can be extracted and detected in the circulating blood plasma, serum, and other bodily fluids[50-52]. Furthermore, RNA expression is highly regulated in normal state but becomes increasingly dysregulated in a pathological state such as cancer[48,53]. Therefore, numerous studies have focused on profiling RNA expression, which may correspond to cancer state, and finding the indicator biomarkers for cancers[54-57].

mRNA markers

Various research groups have investigated the potential use of circulating mRNA as markers for cancer. The general experimental strategy is to employ microarray technology for mRNA expression profiling, which is then followed by validation using real time quantitative reverse transcription polymerase chain reaction (RT-qPCR). The specimens used are either mRNA extracted directly from blood serum/plasma or from peripheral blood cells[58]. Kopreski et al[47] demonstrated the possibility of detecting tumor mRNA, tyrosinase, in the serum of malignant melanoma patients although the result remains controversial[59]. Tsouma et al[60] extracted RNA from peripheral blood cells and used the multiplex RT-qPCR technology to determine the expression of three transcripts (carcinoembryonic antigen, cytokeratin 20 and epidermal growth factor receptor) to determine the disease stage and overall survival of CRC patients. DePrimo et al[61] and Twine et al[62] performed microarray-based mRNA expression profiling in peripheral blood mononuclear cells in 2003 and proposed some potential markers. However, this research generally remained at a proof-of-concept or pilot study stage, and further follow-up study has been sparse as the strategy they originally employed is now gradually being replaced by the new technology of Next Generation Sequencing (NGS), which will be discussed in more detail later.

ColonSentry as CRC screening or risk-assessment test?

Marshall et al[63] from GeneNews Ltd. developed a blood-based test using a seven-gene biomarker panel (ANXA3, CLEC4D, LMNB1, PRRG4, TNFAIP6, VNN1 and IL2RB) testing RNA extracted from peripheral blood cells. This seven-gene panel was derived from a 196-gene expression profile using 112 CRC patients (including those with stage I, II, III, and IV disease) and 120 controls. The panel was confirmed using 202 CRC patients (from all stages) and 208 controls, all from the Canadian population. They reported a sensitivity of 72% and specificity of 70% for this initial study. Then, they validated the seven-gene profile using 99 CRC patients (presumably from all stages) and 111 controls from the Malaysian population and reported 61% sensitivity and 77% specificity[64]. The researchers further validated their panel with an even larger population of 314 CRC patients (from all stages) and 328 controls from Canada and the United States, and they reported a sensitivity of 78% and specificity of 66%[65]. GeneNews now offers the ColonSentry test, presumably based on this seven-gene profile, as the world’s first commercially available blood test for colon cancer screening, which is licensed to Enzo Clinical Labs of Enzo Biochem for the United States market. The test has recently been approved by the New York State Department of Health as a test to determine a person’s risk of having CRC[66].

The ColonSentry molecular diagnostic test is marketed as a risk assessment tool rather than a cancer detection test. Although the experimental design for this seven-gene profile appeared to focus on identifying a pan-CRC marker panel when it profiled and validated a total of 727 CRC patients from all stages (estimated to be 30% stage I, 30% stage II, 30% stage III, and 10% stage IV), there is no mention of any study on high risk individuals, advanced adenomas (AA), or patients with colon polyps that ultimately turned cancerous. It is therefore unclear how a set of pan-CRC markers for all CRC stages can be marketed as a risk assessment test. In any case, the test is considered experimental and investigational with many independent experts still questioning its effectiveness.

MiRNA as blood-based cancer markers

MiRNA are small non-coding RNA about 18-25 nucleotides in size[67]. A large body of publications indicates that miRNA regulate gene expression at the post-translational level in almost every biological event and play important roles in tumorigenesis, cancer development, migration and metastasis[68]. The differential expression of miRNA has been related to various cancers[69], and efforts have been made to profile the global and circulating miRNA expression patterns associated with various cancers, including breast cancer[70], lung cancer[71], lymphoma[72], ovarian cancer[73], and pancreatic cancer[74,75].

For CRC, studies have accumulated over the past five years that focus on profiling circulating blood plasma or serum miRNA and validating the findings with RT-qPCR. Ng et al[76] was the first group to profile 95 miRNA using a real-time PCR-based array on 5 CRC patients and 5 controls (presumably from the Chinese population in Hong Kong) and to validate the results with 90 CRC patients and 50 healthy controls. They identified miR-17-3p and miR-92 to be elevated significantly in CRC patients with 89% sensitivity and 70% specificity. Wang et al[77] profiled 742 miRNA using a miRNA microarray on 10 CRC patients and 10 normal controls from the Chinese population and validated the results with 90 CRC patients, 43 AA patients, and 58 healthy donors. They found miR-601 and miR-760 to be decreased in both CRC and AA patients when compared to healthy controls with 83.3% sensitivity and 69.1% specificity. Giráldez et al[78] performed a genome-wide profiling of 743 miRNA using a miRNA microarray on 21 CRC patients, 20 AA patients, and 20 healthy controls from the Spanish population, and they validated the findings using RT-qPCR with 42 CRC patients, 40 AA patients, and 53 controls. They identified a six-miRNA panel (miR-15b, miR-18a, miR-19a, miR-19b, miR-29a, and miR-335) as being able to differentiate CRC patients from healthy individuals with 78.57% sensitivity and 79.25% specificity, and miR-18a could also differentiate AA patients from healthy individuals with both 80% sensitivity and specificity. Luo et al[79] used a TaqMan MiRNA array to profile 667 miRNAs on 50 CRC patients and 50 controls from the German population and validated the results with new cohorts of 80 CRC patients compared to 144 controls and 50 AA patients compared to 50 controls. They identified nine miRNA (miR-18a, miR-20a, miR-21, miR-29a, miR-92a, miR-106b, miR-133a, miR-143, and miR145) to be differentially expressed in CRC patients and controls with the area under the accompanying receiver operating characteristic curve reported to be 0.745. The panel of miRNA did not, however, differentiate AA patients from the controls. Kanaan et al[80] screened for 380 miRNA using microfluidic TaqMan array technology on 20 CRC patients, 9 AA patients (referred to as colorectal adenomas), and 12 healthy donors of mixed racial background in the United States. They then validated the findings with a new cohort of 45 CRC patients, 16 AA patients, and 26 healthy controls; they derived an eight-miRNA panel (miR-15b, miR-17, miR-142-3p, miR-195, miR-331, miR-532-5p and 532-3p, and miR-652) that can distinguish AA patients from controls with 88% sensitivity and 64% specificity, and a three-miRNA panel (miR-431, miR-15b, and miR-139-3p) to differentiate stage IV CRC patients from controls with 93% sensitivity and 74% specificity. Ahmed et al[81] performed a profiling using miRNA microarray chips covering miRNA based on the published miRBase v17 list (presumed to be 1733 human miRNA) and validated their results using TaqMan RT-qPCR to analyze a panel of miRNA expression both in CRC patient plasma and tissues. They found nine miRNA (miR-7, miR-17-3p, miR-20a, miR-21, miR-92a, miR-96, miR-183, miR-196a and miR-214) to have increased expression and six miRNA (miR-124, miR-127-3p, miR-138, miR-143, miR-146a, and miR-222) to have reduced expression in both CRC patient plasma and tissues with 90% sensitivity and 95% specificity.

A few studies selected their miRNA markers based on published literature and re-confirmed the results with RT-qPCR assays. Huang et al[82] measured the levels of twelve miRNAs (miR-17-3p, -25, -29a, -92a, -134, -146a, -181d, -191, -221, -222, -223, and -320a) studied in the literature in 120 CRC patients, 37 AA patients, and 59 healthy controls from the Chinese population, and they confirmed miR-29a and miR-92a as potential indicators for CRC with 83% sensitivity and 84.7% specificity. Similarly, Liu et al[83] measured the levels of five miRNAs (miR-18a, -21, -31, -92a, and -106a) in serum samples from 200 CRC patients, 50 AA patients, and 80 healthy controls from the Chinese population and identified miR-92a along with miR-21 to be both significantly higher in CRC patients with 68% sensitivity and 91.2% specificity. Pu et al[84] measured miRNA expression levels of three target miRNAs (miR-21, -221, and -222) in 103 CRC patients and 37 controls from the Chinese population and found elevated expression of miR-221 in CRC patients with 86% sensitivity and 41% specificity. Wang et al[85] screened three miRNAs (miR-29a, -92a, and -17-3p) in 38 metastatic CRC and 36 primary CRC patients, assumed to be from the Chinese population, but did not utilize healthy controls. They found miR-29a to be higher in CRC patients with liver metastases than in primary CRC patients with sensitivity and specificity of 75%, and hence miR-29a may be useful in discriminating metastatic from non-metastatic CRC patients. Cheng et al[86] screened three miRNAs (miR-21, -92, and -141) using a cohort of 102 CRC patients and an age-matched cohort of healthy donors of mixed racial background from the United States population, validated their findings using 156 CRC patients and matched controls from the Chinese population, and found miR-141 to be higher in cases of advanced CRC (stage IV) with 90.9% sensitivity and 77.1% specificity.

As summarized in Table 1, there are a total of 38 miRNA that have been studied and proposed as potential biomarkers for CRC in the publications discussed above. In general, most of these studies focused on early stage CRC patients while some also included borderline AA patients. When pooling from all the studies mentioned here, sensitivities in the range of 68%-91% were reported, but the majority (in 9 out of 12 cases) observed sensitivities in the 83%-91% range. Reported specificities were in the range of 41%-95%, but the majority (also in 9 out of 12 cases) were in the 70%-95% range. Some miRNA, including miR-15b, miR-17-3p, miR-18a, miR-20a, miR-21, miR-29a, and miR-92a, have been proposed by more than one group of investigators. One unique miRNA, miR-21, might actually be a useful pan-cancer marker as it is similarly up regulated in other cancers[87]. However, most of these studies have not yet been evaluated beyond the proof-of-principle and pilot stage, and not all miRNA markers were subsequently studied and confirmed by other groups. For example, Faltejskova et al[88] was not able to confirm the potency of miR-17-3p, miR-29a, miR-92a, and miR-135b as biomarkers for CRC. Luo et al[79] and Ahmed et al[81] found differential miR-143 expression in their respective studies. Other potential markers such as miR-17-3p, miR-18a, miR-21, miR-92, and miR-221 were not confirmed in follow-up studies by other groups[82-84,86].

Table 1 Potential blood microRNA markers.
Upregulated in primary CRC
Upregulated in metastatic CRC
Downregulated in primary CRC

Clearly, it is comprehensible that different experimental designs, procedures and methods, endogenous controls, patient populations, instrumentation and lab personnel could contribute to the seemingly contradicting results that have been published thus far. Nevertheless, the 38 candidate miRNA markers together can be further investigated using currently available technology, such as the TaqMan RT-qPCR profile platform already utilized by some of the research groups. It is possible, therefore, to coordinate a multicenter clinical trial involving different research groups and incorporating patient populations from a wide variety of backgrounds. It would be critical to synchronize specimen collection, processing procedures, and storage conditions for the collected specimens. The experimental design should also be based on a coordinated and synchronized set of experimental procedures and instrumentation that utilize the same endogenous control(s). The validity of each of the 38 miRNA markers as a tool for diagnosing CRC can then be evaluated for their potential future application.


Since the first drafts of the human genome were published in 2001, sequencing technology has advanced at an ever rapid pace[89]. The cost of sequencing has decreased from about $1000 per megabase of DNA sequence when the first generation Sanger-based sequencing machine was used in 2001, down to $0.1 per megabase of DNA sequence using the next generation sequencing machine in 2013[90,91]. The cost for personal whole-genome sequencing has dropped from $100000000 in 2001 to $4000 (sequencing offered by Illumina, Inc.) in 2013, and it could possibly be driven further down to $1000 in the imminent future[92]. The availability of the NGS has revolutionized biomarker studies[93]. It is now possible to perform direct RNA sequencing (RNA-seq)[94] to sequence the whole transcriptome, which includes the entire set of all RNA molecules-coding RNA (mRNA, rRNA, tRNA) and noncoding RNA (miRNA, lncRNA, and other small RNA species)[94,95].

RNA-seq is very versatile and has been used to analyze tissue RNA biomarkers in breast cancer[96], hepatocellular carcinoma[97], lymphoma[98,99], melanoma[100,101], and prostate cancer[100]. RNA-seq has also been used to analyze gene expression signatures associated with survival[100], smoking status[102], and altered expression associated with KRAS mutation[103] in lung cancer. In terms of CRC, Wu et al[104] have performed transcriptome profiling comparing CRC, adjacent normal, and distant normal tissues and have identified 5 differentially expressed genes, including ITGB5, COL1A1, FN1, SPP1, and COL3A1, as well as alternative splicing, isoforms, and gene fusion events. It is anticipated that with the ability to extract and sequence RNA from blood plasma, more studies on blood-based RNA markers, based on RNA-seq technology, will soon emerge.

lncRNA markers

Given the increased availability of RNA-seq technology, it is now possible to study the lncRNA, which was dismissed as “junk” in the past but has now been found to regulate gene expression and cellular functions[105]. LncRNA, like its miRNA counterpart, plays major roles in tumor suppression and oncogenic functions and has been found to be dysregulated in human cancers[106]. Therefore, its potential role as biomarkers for cancer and other diseases has been investigated extensively[107,108]. As an example, Prostate cancer antigen (PCA3, also known as DD3) is a non-coding RNA that is highly sensitive and now used as a biomarker for the urine diagnostic test of prostate cancer[109-111].

In terms of CRC, research is currently focused on the role of lncRNA as tissue biomarkers. Ge et al[112] found that Prostate cancer-associated ncRNA transcripts 1 was upregulated in CRC tissue but not in adjacent normal tissue. Zhai et al[113] found that long intergenic noncoding RNA-p21 was upregulated in CRC tissue, and the expression level seemingly correlated with tumor progression (higher expression in later stages). Ling et al[114] showed a novel lncRNA-CCAT2 was highly overexpressed in CRC, and it was shown to be promoting tumor growth, metastasis and chromosomal instability. Kogo et al[115] demonstrated that expression of lncRNA-HOTAIR, which is known to reprogram chromatin organization and promote breast cancer metastasis[116], is also higher in stage IV CRC patients with liver metastases. Xu et al[117] found the lncRNA-human metastasis associated lung adenocarcinoma transcript 1 (MALAT-1) to be dysregulated in cancer, and the mutation on the 3’ end of MALAT-1 is apparently tumorigenic. It is conceivable that RNA-seq technology can help facilitate further investigation into lncRNA functions and exploration of blood-circulating lncRNA as potential biomarkers for CRC and other cancers in the future.


The presence of tumor DNA in circulating blood (plasma or serum) has been documented dating back to 1977[118]. Cell-free DNA (cfDNA) was thought to be released from either apoptotic or necrotic cancer cells, from direct secretion or as a byproduct of phagocytosis from macrophages or other scavenger cells[119,120]. Originally, it received little attention, but with recent advances in next generation sequencing (NGS) technology, it has been explored extensively for the potential application to cancer detection[121]. In general, the studies of cfDNA as cancer biomarkers focus on monitoring the presence of promoter hypermethylation, aberrant tumor DNA mutation, microsatellite alternations, and mitochondria DNA in blood circulation. The validity of each approach will be discussed below.

Aberrant DNA methylation as markers

Aberrant DNA methylation has been associated with tumorigenesis as a consequence of the alteration it causes in gene expression[122,123]. For example, hypermethylation of tumor suppressor promoter genes would cause inappropriate gene silencing and therefore lead to cancer[124]. In general, DNA methylation is thought to be associated with an early event in tumorigenesis and has therefore been proposed as a potential early cancer detection marker[123,125]. The research strategy typically focuses on using methylation specific PCR (MSP) to study hypermethylation of methylation sites, in CpG dinucleotides or in CpG islands, in the promoters of tumor suppressor genes[124,126]. In the context of CRC, Nakayama et al[127] and Lecomte et al[128] both monitored the hypermethylation of the promoter of tumor suppressor gene p16 and found the plasma in 21 of 31 (68%) patients and 31 of 45 (69%) patients, respectively, to be positive. Grady et al[129] found aberrant hypermethylation of the human MutL homolog 1 (hMLH1) promoter in the sera of 9 out of 19 (47%) cases of CRC. Leung et al[130] monitored promoter hypermethylation in three genes, adenomatous polyposis coli (APC), hMLH1, and helicase-like transcription factor, and found at least one of the three genes with methylated promoter DNA in the sera of 28 out of 49 (57%) CRC patients. Additional genes monitored for tumor-related promoter hypermethylation, including the putative metastasis suppressor gene death-associated protein kinase, the detoxification gene glutathione S-transferase P1, the DNA repair gene O6-methylguanine-DNA-methyltransferase, and p14-ARF in other cancers exhibit a detection rate that is generally in the range of 42% to 73%[131-133]. It is conceivable that NGS technology can be coupled with MSP to identify a pool of tumor suppressing genes silenced in association with early stage CRC and AA, test their corresponding promoter methylation, and generate a set of candidate markers based on epigenetic changes as a screening panel for CRC in the future.

Aberrant tumor DNA mutation markers

The NGS technology has been employed for somatic mutation analysis in CRC[134], particularly on several high mutation frequency genes, such as K-RAS[128,135,136], TP53[137], and APC[138]. However, the percentage of circulating tumor DNA is relatively low when compared to wild-type DNA[139]. For example, Diehl et al[138] has shown that in advanced CRC, the mutated APC DNA fragment is found to be in the range of 1.9% to 27% of cfDNA but only 0.01% to 0.12% in early stage CRC. Even with direct sequencing technology, it does not allow reliable detection of less than 25% mutant signal in a background of wild-type DNA[140]. Furthermore, the tumor-associated mutations are often unique with each patient[141,142], and therefore, based on the current available technology, it is less likely to develop a low cost and highly sensitive comprehensive test to cover all somatic mutations for early cancer detection.

Microsatellite alterations as markers

Microsatellite alterations, which include microsatellite instability (MSI) and loss of heterozygosity (LOH), are known to be associated with tumorigenesis and cancer progression and therefore were proposed as potential tumor markers detectable in cfDNA[143]. MSI analysis focuses on measuring the specific polymorphic tetranucleotide repeat and/or dinucleotide markers that are located in regions frequently shifted or altered in cancer, and LOH analysis focuses on the loss of specific chromosomal regions bearing tumor suppressors. Hibi et al[141] examined microsatellite alterations and found LOH or microsatellite shift of at least one locus (18a, 17p, and 8p) in 35 of 44 (80%) primary CRC tumors, but none of the LOH or microsatellite shifts were detected in the corresponding serum DNA. Several other groups focused on different cancers with most success in metastatic cancers[143,144]. In general, microsatellite alteration analysis exhibits relatively low sensitivity and specificity in detecting early stage cancer.

Circulating mitochondrial DNA as markers

There are generally a few hundreds of copies of mitochondrial DNA in each cell[145]. Due to its multi-copy nature, mtDNA is frequently found to be heteroplasmic, with a heterogeneous mixture of polymorphic variants. In cancer cells, mtDNA harbor further heteroplasmic alterations associated specifically with cancer, especially in the highly variable D-loop (displacement loop) region. With the NGS, the approaches generally focused on either differential copy number of mtDNA versus gDNA, or mtDNA alteration and tumor-associated mtDNA mutations[146]. For CRC, Hibi et al[147] has studied mtDNA alternation in early CRC patients and found that 7 out of 77 (9%) CRC tissues contained true somatic mutations in the D-loop region, but only one out of these 7 positive patients (14%) were noted to have mtDNA alterations in their serum DNA. Due to of the relatively low detection rate of early stage cancer, most studies therefore focused on its potential application in metastatic cancers[148-153].


The study of blood-based protein markers in general focuses on proteins secreted, shed or leaking from cancer cells into the blood stream. This is generally referred to as “cancer secretome”[154]. The cancer secretome can be studied comprehensively by several mass spectrometric technologies. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and HPLC-electrospray ionization mass spectrometry (ESI-MS) analyze biomolecules in biological fluids[155,156]. Surface-enhanced laser desorption ionization-time of flight mass spectrometry (SELDI-TOF MS) can be used as a serum protein profiler to identify new biomarkers[157]. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) can fractionate and identify the specific molecules of interest[154]. There is also an Aptamer proteomic technology that can be used to identify biomarkers for cancer[158]. Many candidate protein biomarkers have been generated based on these technologies.

However, the application of these technologies remains research-oriented. The potency of their translational capability in clinical and diagnostic application requires further investigation[159].


Early screening of CRC is clearly the most effective way to combat the anticipated increase of global CRC morbidity and mortality. Despite all recent technological advances, the currently available screening modalities remain archaically similar to 33 years ago. The most effective screening modality today is through the invasive procedure of colonoscopy. However, even in the United States, where the procedure is widely available and publicized, covered by most medical insurance plans, and recommended by medical professionals and practitioners, the participation rate is still pathetically low. It is conceivable that the participation rate would not fare better even if it were widely available on a global scale. Clearly, a new first line CRC screening procedure that is inexpensive, low risk, highly sensitive, and does not require cumbersome preparation is desirable.

A blood-based screening test for CRC would be an attractive alternative to colonoscopy if it were available because it is essentially non-invasive and relatively painless to the patient. Ideally, a blood-based test can be a useful first line screening tool for the general population at average risk, thereby separating out high risk and CRC patient groups. However, for patients with known high risk factors, including family history of CRC, familial adenomatous polyposis, hereditary nonpolyposis CRC, inflammatory bowel disease, history of polyps, or previous CRC, colonoscopy should still be the primary method of screening and follow-up starting at age 50, although a blood-based test can still be used for screening these patients earlier at age 40. In short, circumstances under which a blood-based screening test is used should be determined based on the sensitivity and specificity of the methodology developed in the future.

The key to establishing a good blood-based test is to find highly sensitive and specific biomarkers in the blood. As discussed in this review, various types of biomarkers have been proposed and explored by many research groups to varying degrees. Table 2 summarizes the sensitivity, specificity, and estimated cost for the types of stool-based tests, structural exams, and potential blood-based tests as discussed in this review. The ColonSentry® seven-gene mRNA biomarker panel is the first commercially available blood test that is supposed to determine the risk of developing CRC. The sensitivity and specificity for this “risk assessment” are 78% and 66% respectively. As shown in Table 2, among all the biomarker types, the miRNA markers demonstrated the greatest potential because most publications reported a relatively high sensitivity (83%-91%) and specificity (70%-95%) rate, utilized mostly AA and early stage CRC patient, and studied a wide variety of patient populations. Therefore, a multi-center clinical trial with synchronized experimental procedures that tested all 38 miRNA listed in Table 1 could be considered. On the other hand, the aberrant DNA methylation analyses on promoters of tumor suppressors also demonstrated a high potential to be developed into a cancer screening test. With available NGS technology and MSP showing relatively high sensitivity and specificity (42%-73%), it is now possible to explore more tumor-specific promoters, which might have higher sensitivity and specificity and eventually be developed into a screening test.

Table 2 Comparison of colorectal cancer screening tests.
Test nameCostProcedure typePrep?SensitivitySpecificityNoteRef.
gFOBT$53Stool testYes112%2 and 40%98%Hemoccult II[165]
iFOBT/FIT$223Stool testYes122%2 and 70%95%[165]
Fx. Sigmoidoscopy$500-$7503InvasiveYes95%2 and 95%92%[165]
Colonoscopy$800-$16003InvasiveYes95%2 and 98%90%[165,166]
DCBE$250-$5003X-rayYes48%290%Not recommended by USPSTF[166]
CTC$400-$8003CT-scanYes59%296%Not recommended by USPSTF[166]
Blood-based test
ColonSentry®$350blood-testNo78%66%GeneNews/Enzo Biochem[66]
MiRNA (5-gene)Est. $2504blood-testNoEst. 83%-91%Est. 70%-95%
LncRNA (1-gene)$385.005blood-testNoN/AN/A
DNA methylationEst. $2504blood-testNoEst. 42%-73%Est. 42%-73%

On the other hand, although research studies of lncRNA markers using NGS are still at the early stage, it has a great potential to be developed into a CRC screening test as well. It is especially encouraging to see one of the lncRNA, PCA3, is now used routinely as a prognostic marker for prostate cancer. With the wider availability of NGS, it is anticipated that more studies will be undertaken to generate new candidate genes and biomarkers, which would possibly lead to a future diagnostic test for CRC.


We thank the Research Cancer Committee, Dr. Barbara Heerdt, PhD for the helpful discussion and input, and Dr. Madhuri Ramanathan, PhD of the Valley Hospital Histology Lab for input on lab tests. We also thank Mr. Ankur A. Patel for his assistance during the writing process.


P- Reviewers: Nishiyama M, Stanojevic GZ S- Editor: Zhai HH L- Editor: A E- Editor: Liu SQ

1.  Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010;127:2893-2917.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11128]  [Cited by in F6Publishing: 11614]  [Article Influence: 893.4]  [Reference Citation Analysis (4)]
2.  Pourhoseingholi MA. Increased burden of colorectal cancer in Asia. World J Gastrointest Oncol. 2012;4:68-70.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 92]  [Cited by in F6Publishing: 95]  [Article Influence: 7.9]  [Reference Citation Analysis (0)]
3.  Bray F, Jemal A, Grey N, Ferlay J, Forman D. Global cancer transitions according to the Human Development Index (2008-2030): a population-based study. Lancet Oncol. 2012;13:790-801.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1245]  [Cited by in F6Publishing: 1344]  [Article Influence: 112.0]  [Reference Citation Analysis (0)]
4.  Population Division World Population Prospects: The 2012 Revision, Highlights and Advance Tables. New York: United Nations Department of Economic and Social Affairs 2013; .  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Murray CJ, Lopez AD. Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet. 1997;349:1269-1276.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2466]  [Cited by in F6Publishing: 2329]  [Article Influence: 86.3]  [Reference Citation Analysis (0)]
6.  Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63:11-30.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9215]  [Cited by in F6Publishing: 9719]  [Article Influence: 883.5]  [Reference Citation Analysis (3)]
7.  Eddy D. ACS report on the cancer-related health checkup. CA Cancer J Clin. 1980;30:193-240.  [PubMed]  [DOI]  [Cited in This Article: ]
8.  Levin B, Lieberman DA, McFarland B, Smith RA, Brooks D, Andrews KS, Dash C, Giardiello FM, Glick S, Levin TR. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. CA Cancer J Clin. 2008;58:130-160.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1169]  [Cited by in F6Publishing: 1163]  [Article Influence: 72.7]  [Reference Citation Analysis (0)]
9.  U.S. Preventive Services Task Force. Screening for colorectal cancer: recommendation and rationale. Am Fam Physician. 2002;66:2287-2290.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  Winawer SJ, Zauber AG, Fletcher RH, Stillman JS, O’Brien MJ, Levin B, Smith RA, Lieberman DA, Burt RW, Levin TR. Guidelines for colonoscopy surveillance after polypectomy: a consensus update by the US Multi-Society Task Force on Colorectal Cancer and the American Cancer Society. Gastroenterology. 2006;130:1872-1885.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 516]  [Cited by in F6Publishing: 546]  [Article Influence: 30.3]  [Reference Citation Analysis (0)]
11.  Diaz JA, Slomka T. State of the Art Review: Colorectal Cancer Screening. Am J Lifestyle Med. 2012;6:196-203.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 5]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
12.  Steinwachs D, Allen JD, Barlow WE, Duncan RP, Egede LE, Friedman LS, Keating NL, Kim P, Lave JR, Laveist TA. National Institutes of Health state-of-the-science conference statement: Enhancing use and quality of colorectal cancer screening. Ann Intern Med. 2010;152:663-667.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 72]  [Article Influence: 5.1]  [Reference Citation Analysis (0)]
13.  Fraser CG, Matthew CM, Mowat NA, Wilson JA, Carey FA, Steele RJ. Immunochemical testing of individuals positive for guaiac faecal occult blood test in a screening programme for colorectal cancer: an observational study. Lancet Oncol. 2006;7:127-131.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 52]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
14.  Hewitson P, Glasziou P, Watson E, Towler B, Irwig L. Cochrane systematic review of colorectal cancer screening using the fecal occult blood test (hemoccult): an update. Am J Gastroenterol. 2008;103:1541-1549.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 676]  [Cited by in F6Publishing: 690]  [Article Influence: 43.1]  [Reference Citation Analysis (0)]
15.  Health Quality Ontario. Fecal occult blood test for colorectal cancer screening: an evidence-based analysis. Ont Health Technol Assess Ser. 2009;9:1-40.  [PubMed]  [DOI]  [Cited in This Article: ]
16.  Schnell T, Aranha GV, Sontag SJ, Tode R, Reid S, Chejfec G, Karpf J, Levine G. Fecal occult blood testing: a false sense of security? Surgery. 1994;116:798-802; discussion 802-803.  [PubMed]  [DOI]  [Cited in This Article: ]
17.  Wong CK, Fedorak RN, Prosser CI, Stewart ME, van Zanten SV, Sadowski DC. The sensitivity and specificity of guaiac and immunochemical fecal occult blood tests for the detection of advanced colonic adenomas and cancer. Int J Colorectal Dis. 2012;27:1657-1664.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 48]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
18.  Roslani AC, Abdullah T, Arumugam K. Screening for colorectal neoplasias with fecal occult blood tests: false-positive impact of non-dietary restriction. Asian Pac J Cancer Prev. 2012;13:237-241.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Mant D, Fitzpatrick R, Hogg A, Fuller A, Farmer A, Verne J, Northover J. Experiences of patients with false positive results from colorectal cancer screening. Br J Gen Pract. 1990;40:423-425.  [PubMed]  [DOI]  [Cited in This Article: ]
20.  Allison JE, Tekawa IS, Ransom LJ, Adrain AL. A comparison of fecal occult-blood tests for colorectal-cancer screening. N Engl J Med. 1996;334:155-159.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 430]  [Cited by in F6Publishing: 387]  [Article Influence: 13.8]  [Reference Citation Analysis (0)]
21.  Heresbach D, Manfredi S, D’halluin PN, Bretagne JF, Branger B. Review in depth and meta-analysis of controlled trials on colorectal cancer screening by faecal occult blood test. Eur J Gastroenterol Hepatol. 2006;18:427-433.  [PubMed]  [DOI]  [Cited in This Article: ]
22.  Rex DK, Johnson DA, Anderson JC, Schoenfeld PS, Burke CA, Inadomi JM. American College of Gastroenterology guidelines for colorectal cancer screening 2009 [corrected]. Am J Gastroenterol. 2009;104:739-750.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 981]  [Cited by in F6Publishing: 1035]  [Article Influence: 69.0]  [Reference Citation Analysis (0)]
23.  Meissner HI, Breen N, Klabunde CN, Vernon SW. Patterns of colorectal cancer screening uptake among men and women in the United States. Cancer Epidemiol Biomarkers Prev. 2006;15:389-394.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 416]  [Cited by in F6Publishing: 434]  [Article Influence: 24.1]  [Reference Citation Analysis (0)]
24.  Beydoun HA, Beydoun MA. Predictors of colorectal cancer screening behaviors among average-risk older adults in the United States. Cancer Causes Control. 2008;19:339-359.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 229]  [Cited by in F6Publishing: 260]  [Article Influence: 15.3]  [Reference Citation Analysis (0)]
25.  Ait Ouakrim D, Lockett T, Boussioutas A, Hopper JL, Jenkins MA. Screening participation for people at increased risk of colorectal cancer due to family history: a systematic review and meta-analysis. Fam Cancer. 2013;12:459-472.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 39]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
26.  Cummings LC, Cooper GS. Colorectal cancer screening: update for 2011. Semin Oncol. 2011;38:483-489.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 13]  [Cited by in F6Publishing: 17]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
27.  Wee CC, McCarthy EP, Phillips RS. Factors associated with colon cancer screening: the role of patient factors and physician counseling. Prev Med. 2005;41:23-29.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 207]  [Cited by in F6Publishing: 231]  [Article Influence: 12.2]  [Reference Citation Analysis (0)]
28.  Boehm JE, Rohan EA, Preissle J, DeGroff A, Glover-Kudon R. Recruiting patients into the CDC’s Colorectal Cancer Screening Demonstration Program: strategies and challenges across 5 sites. Cancer. 2013;119 Suppl 15:2914-2925.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 16]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
29.  Ling BS, Moskowitz MA, Wachs D, Pearson B, Schroy PC. Attitudes toward colorectal cancer screening tests. J Gen Intern Med. 2001;16:822-830.  [PubMed]  [DOI]  [Cited in This Article: ]
30.  Zavoral M, Suchanek S, Zavada F, Dusek L, Muzik J, Seifert B, Fric P. Colorectal cancer screening in Europe. World J Gastroenterol. 2009;15:5907-5915.  [PubMed]  [DOI]  [Cited in This Article: ]
31.  Sieg A, Friedrich K. Perspectives of colorectal cancer screening in Germany 2009. World J Gastrointest Endosc. 2009;1:12-16.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 3]  [Cited by in F6Publishing: 5]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
32.  Deng SX, Gao J, An W, Yin J, Cai QC, Yang H, Li ZS. Colorectal cancer screening behavior and willingness: an outpatient survey in China. World J Gastroenterol. 2011;17:3133-3139.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 10]  [Reference Citation Analysis (0)]
33.  Levin TR, Corley DA. Colorectal-cancer screening--coming of age. N Engl J Med. 2013;369:1164-1166.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 9]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
34.  Steele SR, Johnson EK, Champagne B, Davis B, Lee S, Rivadeneira D, Ross H, Hayden DA, Maykel JA. Endoscopy and polyps-diagnostic and therapeutic advances in management. World J Gastroenterol. 2013;19:4277-4288.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 11]  [Cited by in F6Publishing: 11]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
35.  Frazier AL, Colditz GA, Fuchs CS, Kuntz KM. Cost-effectiveness of screening for colorectal cancer in the general population. JAMA. 2000;284:1954-1961.  [PubMed]  [DOI]  [Cited in This Article: ]
36.  Sonnenberg A, Delcò F, Inadomi JM. Cost-effectiveness of colonoscopy in screening for colorectal cancer. Ann Intern Med. 2000;133:573-584.  [PubMed]  [DOI]  [Cited in This Article: ]
37.  Tsoi KK, Ng SS, Leung MC, Sung JJ. Cost-effectiveness analysis on screening for colorectal neoplasm and management of colorectal cancer in Asia. Aliment Pharmacol Ther. 2008;28:353-363.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 22]  [Reference Citation Analysis (0)]
38.  Heitman SJ, Hilsden RJ, Au F, Dowden S, Manns BJ. Colorectal cancer screening for average-risk North Americans: an economic evaluation. PLoS Med. 2010;7:e1000370.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 86]  [Cited by in F6Publishing: 102]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
39.  Debey-Pascher S, Chen J, Voss T, Staratschek-Jox A. Blood-based miRNA preparation for noninvasive biomarker development. Methods Mol Biol. 2012;822:307-338.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 12]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
40.  Kumar S, Mohan A, Guleria R. Biomarkers in cancer screening, research and detection: present and future: a review. Biomarkers. 2006;11:385-405.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 85]  [Cited by in F6Publishing: 75]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
41.  Chatterjee SK, Zetter BR. Cancer biomarkers: knowing the present and predicting the future. Future Oncol. 2005;1:37-50.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 163]  [Cited by in F6Publishing: 148]  [Article Influence: 8.2]  [Reference Citation Analysis (0)]
42.  Tänzer M, Liebl M, Quante M. Molecular biomarkers in esophageal, gastric, and colorectal adenocarcinoma. Pharmacol Ther. 2013;140:133-147.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 22]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
43.  Goulart BH, Clark JW, Pien HH, Roberts TG, Finkelstein SN, Chabner BA. Trends in the use and role of biomarkers in phase I oncology trials. Clin Cancer Res. 2007;13:6719-6726.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 92]  [Cited by in F6Publishing: 95]  [Article Influence: 5.9]  [Reference Citation Analysis (0)]
44.  Zeestraten EC, Kuppen PJ, van de Velde CJ, Marijnen CA. Prediction in rectal cancer. Semin Radiat Oncol. 2012;22:175-183.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 20]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
45.  Lo KW, Lo YM, Leung SF, Tsang YS, Chan LY, Johnson PJ, Hjelm NM, Lee JC, Huang DP. Analysis of cell-free Epstein-Barr virus associated RNA in the plasma of patients with nasopharyngeal carcinoma. Clin Chem. 1999;45:1292-1294.  [PubMed]  [DOI]  [Cited in This Article: ]
46.  Tsui NB, Ng EK, Lo YM. Stability of endogenous and added RNA in blood specimens, serum, and plasma. Clin Chem. 2002;48:1647-1653.  [PubMed]  [DOI]  [Cited in This Article: ]
47.  Kopreski MS, Benko FA, Kwak LW, Gocke CD. Detection of tumor messenger RNA in the serum of patients with malignant melanoma. Clin Cancer Res. 1999;5:1961-1965.  [PubMed]  [DOI]  [Cited in This Article: ]
48.  Cortez MA, Bueso-Ramos C, Ferdin J, Lopez-Berestein G, Sood AK, Calin GA. MicroRNAs in body fluids--the mix of hormones and biomarkers. Nat Rev Clin Oncol. 2011;8:467-477.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1009]  [Cited by in F6Publishing: 1071]  [Article Influence: 82.4]  [Reference Citation Analysis (0)]
49.  Van Roosbroeck K, Pollet J, Calin GA. miRNAs and long noncoding RNAs as biomarkers in human diseases. Expert Rev Mol Diagn. 2013;13:183-204.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 100]  [Cited by in F6Publishing: 108]  [Article Influence: 9.8]  [Reference Citation Analysis (0)]
50.  Sourvinou IS, Markou A, Lianidou ES. Quantification of circulating miRNAs in plasma: effect of preanalytical and analytical parameters on their isolation and stability. J Mol Diagn. 2013;15:827-834.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 157]  [Cited by in F6Publishing: 170]  [Article Influence: 15.5]  [Reference Citation Analysis (0)]
51.  Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’Briant KC, Allen A. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105:10513-10518.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5636]  [Cited by in F6Publishing: 6065]  [Article Influence: 379.1]  [Reference Citation Analysis (0)]
52.  Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K. The microRNA spectrum in 12 body fluids. Clin Chem. 2010;56:1733-1741.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1810]  [Cited by in F6Publishing: 1937]  [Article Influence: 138.4]  [Reference Citation Analysis (0)]
53.  Nicoloso MS, Spizzo R, Shimizu M, Rossi S, Calin GA. MicroRNAs--the micro steering wheel of tumour metastases. Nat Rev Cancer. 2009;9:293-302.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 601]  [Cited by in F6Publishing: 618]  [Article Influence: 41.2]  [Reference Citation Analysis (0)]
54.  Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, Guo J, Zhang Y, Chen J, Guo X. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 2008;18:997-1006.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3218]  [Cited by in F6Publishing: 3384]  [Article Influence: 211.5]  [Reference Citation Analysis (0)]
55.  Shen J, Stass SA, Jiang F. MicroRNAs as potential biomarkers in human solid tumors. Cancer Lett. 2013;329:125-136.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 168]  [Cited by in F6Publishing: 186]  [Article Influence: 15.5]  [Reference Citation Analysis (0)]
56.  Coskun M, Bjerrum JT, Seidelin JB, Nielsen OH. MicroRNAs in inflammatory bowel disease--pathogenesis, diagnostics and therapeutics. World J Gastroenterol. 2012;18:4629-4634.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 69]  [Cited by in F6Publishing: 75]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
57.  Ganepola GA, Mazziotta RM, Weeresinghe D, Corner GA, Parish CJ, Chang DH, Tebbutt NC, Murone C, Ahmed N, Augenlicht LH. Gene expression profiling of primary and metastatic colon cancers identifies a reduced proliferative rate in metastatic tumors. Clin Exp Metastasis. 2010;27:1-9.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 18]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
58.  Chang DH, Rutledge JR, Patel AA, Heerdt BG, Augenlicht LH, Korst RJ. The effect of lung cancer on cytokine expression in peripheral blood mononuclear cells. PLoS One. 2013;8:e64456.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 20]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
59.  Quaglino P, Savoia P, Osella-Abate S, Bernengo MG. RT-PCR tyrosinase expression in the peripheral blood of melanoma patients. Expert Rev Mol Diagn. 2004;4:727-741.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 22]  [Cited by in F6Publishing: 23]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
60.  Tsouma A, Aggeli C, Lembessis P, Zografos GN, Korkolis DP, Pectasides D, Skondra M, Pissimissis N, Tzonou A, Koutsilieris M. Multiplex RT-PCR-based detections of CEA, CK20 and EGFR in colorectal cancer patients. World J Gastroenterol. 2010;16:5965-5974.  [PubMed]  [DOI]  [Cited in This Article: ]
61.  DePrimo SE, Wong LM, Khatry DB, Nicholas SL, Manning WC, Smolich BD, O’Farrell AM, Cherrington JM. Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification. BMC Cancer. 2003;3:3.  [PubMed]  [DOI]  [Cited in This Article: ]
62.  Twine NC, Stover JA, Marshall B, Dukart G, Hidalgo M, Stadler W, Logan T, Dutcher J, Hudes G, Dorner AJ. Disease-associated expression profiles in peripheral blood mononuclear cells from patients with advanced renal cell carcinoma. Cancer Res. 2003;63:6069-6075.  [PubMed]  [DOI]  [Cited in This Article: ]
63.  Marshall KW, Mohr S, Khettabi FE, Nossova N, Chao S, Bao W, Ma J, Li XJ, Liew CC. A blood-based biomarker panel for stratifying current risk for colorectal cancer. Int J Cancer. 2010;126:1177-1186.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 75]  [Article Influence: 5.4]  [Reference Citation Analysis (0)]
64.  Yip KT, Das PK, Suria D, Lim CR, Ng GH, Liew CC. A case-controlled validation study of a blood-based seven-gene biomarker panel for colorectal cancer in Malaysia. J Exp Clin Cancer Res. 2010;29:128.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 37]  [Cited by in F6Publishing: 42]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
65.  Chao S, Ying J, Liew G, Marshall W, Liew CC, Burakoff R. Blood RNA biomarker panel detects both left- and right-sided colorectal neoplasms: a case-control study. J Exp Clin Cancer Res. 2013;32:44.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 15]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
66.  Novak DJ, Liew GJ, Liew CC. GeneNews Limited: bringing the blood transcriptome to personalized medicine. Pharmacogenomics. 2012;13:381-385.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 3]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
67.  Sayed D, Abdellatif M. MicroRNAs in development and disease. Physiol Rev. 2011;91:827-887.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 755]  [Cited by in F6Publishing: 814]  [Article Influence: 62.6]  [Reference Citation Analysis (0)]
68.  Lee YS, Dutta A. MicroRNAs in cancer. Annu Rev Pathol. 2009;4:199-227.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1021]  [Cited by in F6Publishing: 1089]  [Article Influence: 72.6]  [Reference Citation Analysis (0)]
69.  Krutovskikh VA, Herceg Z. Oncogenic microRNAs (OncomiRs) as a new class of cancer biomarkers. Bioessays. 2010;32:894-904.  [PubMed]  [DOI]  [Cited in This Article: ]
70.  Chen XQ, Bonnefoi H, Pelte MF, Lyautey J, Lederrey C, Movarekhi S, Schaeffer P, Mulcahy HE, Meyer P, Stroun M. Telomerase RNA as a detection marker in the serum of breast cancer patients. Clin Cancer Res. 2000;6:3823-3826.  [PubMed]  [DOI]  [Cited in This Article: ]
71.  Shen J, Todd NW, Zhang H, Yu L, Lingxiao X, Mei Y, Guarnera M, Liao J, Chou A, Lu CL. Plasma microRNAs as potential biomarkers for non-small-cell lung cancer. Lab Invest. 2011;91:579-587.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 286]  [Cited by in F6Publishing: 309]  [Article Influence: 23.8]  [Reference Citation Analysis (0)]
72.  Lawrie CH, Gal S, Dunlop HM, Pushkaran B, Liggins AP, Pulford K, Banham AH, Pezzella F, Boultwood J, Wainscoat JS. Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br J Haematol. 2008;141:672-675.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1258]  [Cited by in F6Publishing: 1278]  [Article Influence: 79.9]  [Reference Citation Analysis (0)]
73.  Kulasingam V, Pavlou MP, Diamandis EP. Integrating high-throughput technologies in the quest for effective biomarkers for ovarian cancer. Nat Rev Cancer. 2010;10:371-378.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 112]  [Cited by in F6Publishing: 119]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
74.  Liu R, Chen X, Du Y, Yao W, Shen L, Wang C, Hu Z, Zhuang R, Ning G, Zhang C. Serum microRNA expression profile as a biomarker in the diagnosis and prognosis of pancreatic cancer. Clin Chem. 2012;58:610-618.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 276]  [Cited by in F6Publishing: 294]  [Article Influence: 22.6]  [Reference Citation Analysis (0)]
75.  Ganepola GA, Rutledge JR, Suman P, Yiengpruksawan A, Chang DH. Novel blood-based microRNA biomarker panel for early diagnosis of pancreatic cancer. World J Gastrointest Oncol. 2014;6:22-33.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 88]  [Cited by in F6Publishing: 81]  [Article Influence: 8.1]  [Reference Citation Analysis (0)]
76.  Ng EK, Chong WW, Jin H, Lam EK, Shin VY, Yu J, Poon TC, Ng SS, Sung JJ. Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut. 2009;58:1375-1381.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 855]  [Cited by in F6Publishing: 938]  [Article Influence: 62.5]  [Reference Citation Analysis (0)]
77.  Wang Q, Huang Z, Ni S, Xiao X, Xu Q, Wang L, Huang D, Tan C, Sheng W, Du X. Plasma miR-601 and miR-760 are novel biomarkers for the early detection of colorectal cancer. PLoS One. 2012;7:e44398.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 156]  [Cited by in F6Publishing: 178]  [Article Influence: 14.8]  [Reference Citation Analysis (0)]
78.  Giráldez MD, Lozano JJ, Ramírez G, Hijona E, Bujanda L, Castells A, Gironella M. Circulating microRNAs as biomarkers of colorectal cancer: results from a genome-wide profiling and validation study. Clin Gastroenterol Hepatol. 2013;11:681-8.e3.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 127]  [Cited by in F6Publishing: 130]  [Article Influence: 11.8]  [Reference Citation Analysis (0)]
79.  Luo X, Stock C, Burwinkel B, Brenner H. Identification and evaluation of plasma microRNAs for early detection of colorectal cancer. PLoS One. 2013;8:e62880.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 117]  [Cited by in F6Publishing: 130]  [Article Influence: 11.8]  [Reference Citation Analysis (0)]
80.  Kanaan Z, Roberts H, Eichenberger MR, Billeter A, Ocheretner G, Pan J, Rai SN, Jorden J, Williford A, Galandiuk S. A plasma microRNA panel for detection of colorectal adenomas: a step toward more precise screening for colorectal cancer. Ann Surg. 2013;258:400-408.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 140]  [Cited by in F6Publishing: 158]  [Article Influence: 14.4]  [Reference Citation Analysis (0)]
81.  Ahmed FE, Amed NC, Vos PW, Bonnerup C, Atkins JN, Casey M, Nuovo GJ, Naziri W, Wiley JE, Allison RR. Diagnostic microRNA markers to screen for sporadic human colon cancer in blood. Cancer Genomics Proteomics. 2012;9:179-192.  [PubMed]  [DOI]  [Cited in This Article: ]
82.  Huang Z, Huang D, Ni S, Peng Z, Sheng W, Du X. Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer. 2010;127:118-126.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 680]  [Cited by in F6Publishing: 722]  [Article Influence: 51.6]  [Reference Citation Analysis (0)]
83.  Liu GH, Zhou ZG, Chen R, Wang MJ, Zhou B, Li Y, Sun XF. Serum miR-21 and miR-92a as biomarkers in the diagnosis and prognosis of colorectal cancer. Tumour Biol. 2013;34:2175-2181.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 143]  [Cited by in F6Publishing: 158]  [Article Influence: 14.4]  [Reference Citation Analysis (0)]
84.  Pu XX, Huang GL, Guo HQ, Guo CC, Li H, Ye S, Ling S, Jiang L, Tian Y, Lin TY. Circulating miR-221 directly amplified from plasma is a potential diagnostic and prognostic marker of colorectal cancer and is correlated with p53 expression. J Gastroenterol Hepatol. 2010;25:1674-1680.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 214]  [Cited by in F6Publishing: 240]  [Article Influence: 17.1]  [Reference Citation Analysis (0)]
85.  Wang LG, Gu J. Serum microRNA-29a is a promising novel marker for early detection of colorectal liver metastasis. Cancer Epidemiol. 2012;36:e61-e67.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 142]  [Cited by in F6Publishing: 159]  [Article Influence: 12.2]  [Reference Citation Analysis (0)]
86.  Cheng H, Zhang L, Cogdell DE, Zheng H, Schetter AJ, Nykter M, Harris CC, Chen K, Hamilton SR, Zhang W. Circulating plasma MiR-141 is a novel biomarker for metastatic colon cancer and predicts poor prognosis. PLoS One. 2011;6:e17745.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 303]  [Cited by in F6Publishing: 326]  [Article Influence: 25.1]  [Reference Citation Analysis (0)]
87.  Wang B, Zhang Q. The expression and clinical significance of circulating microRNA-21 in serum of five solid tumors. J Cancer Res Clin Oncol. 2012;138:1659-1666.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 155]  [Cited by in F6Publishing: 150]  [Article Influence: 12.5]  [Reference Citation Analysis (0)]
88.  Faltejskova P, Bocanek O, Sachlova M, Svoboda M, Kiss I, Vyzula R, Slaby O. Circulating miR-17-3p, miR-29a, miR-92a and miR-135b in serum: Evidence against their usage as biomarkers in colorectal cancer. Cancer Biomark. 2012;12:199-204.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 22]  [Cited by in F6Publishing: 37]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
89.  Mardis ER. A decade’s perspective on DNA sequencing technology. Nature. 2011;470:198-203.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 585]  [Cited by in F6Publishing: 484]  [Article Influence: 37.2]  [Reference Citation Analysis (0)]
90.  Human genome at ten: The sequence explosion Nature. 2010;464:670-671.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 37]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
91.  Wetterstrand KA. DNA Sequencing Costts: Data from the NHGRI Genome Sequencing Program (GSP).  Available from: http: //  [PubMed]  [DOI]  [Cited in This Article: ]
92.  Peters BA, Kermani BG, Sparks AB, Alferov O, Hong P, Alexeev A, Jiang Y, Dahl F, Tang YT, Haas J. Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells. Nature. 2012;487:190-195.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 194]  [Cited by in F6Publishing: 207]  [Article Influence: 17.3]  [Reference Citation Analysis (0)]
93.  Su Z, Ning B, Fang H, Hong H, Perkins R, Tong W, Shi L. Next-generation sequencing and its applications in molecular diagnostics. Expert Rev Mol Diagn. 2011;11:333-343.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 115]  [Cited by in F6Publishing: 125]  [Article Influence: 9.6]  [Reference Citation Analysis (0)]
94.  Ozsolak F, Milos PM. RNA sequencing: advances, challenges and opportunities. Nat Rev Genet. 2011;12:87-98.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1414]  [Cited by in F6Publishing: 1319]  [Article Influence: 94.2]  [Reference Citation Analysis (0)]
95.  Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet. 2008;9:387-402.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1467]  [Cited by in F6Publishing: 1177]  [Article Influence: 73.6]  [Reference Citation Analysis (0)]
96.  Sinicropi D, Qu K, Collin F, Crager M, Liu ML, Pelham RJ, Pho M, Dei Rossi A, Jeong J, Scott A. Whole transcriptome RNA-Seq analysis of breast cancer recurrence risk using formalin-fixed paraffin-embedded tumor tissue. PLoS One. 2012;7:e40092.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 62]  [Article Influence: 5.2]  [Reference Citation Analysis (0)]
97.  Lin KT, Shann YJ, Chau GY, Hsu CN, Huang CY. Identification of latent biomarkers in hepatocellular carcinoma by ultra-deep whole-transcriptome sequencing. Oncogene. 2013;Epub ahead of print.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 31]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
98.  Iacobucci I, Ferrarini A, Sazzini M, Giacomelli E, Lonetti A, Xumerle L, Ferrari A, Papayannidis C, Malerba G, Luiselli D. Application of the whole-transcriptome shotgun sequencing approach to the study of Philadelphia-positive acute lymphoblastic leukemia. Blood Cancer J. 2012;2:e61.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 7]  [Article Influence: 0.6]  [Reference Citation Analysis (0)]
99.  Xiao W, Tran B, Staudt LM, Schmitz R. High-throughput RNA sequencing in B-cell lymphomas. Methods Mol Biol. 2013;971:295-312.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 5]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
100.  Berger MF, Levin JZ, Vijayendran K, Sivachenko A, Adiconis X, Maguire J, Johnson LA, Robinson J, Verhaak RG, Sougnez C. Integrative analysis of the melanoma transcriptome. Genome Res. 2010;20:413-427.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 210]  [Cited by in F6Publishing: 225]  [Article Influence: 16.1]  [Reference Citation Analysis (0)]
101.  Kunz M, Dannemann M, Kelso J. High-throughput sequencing of the melanoma genome. Exp Dermatol. 2013;22:10-17.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 20]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
102.  Cheng P, Cheng Y, Li Y, Zhao Z, Gao H, Li D, Li H, Zhang T. Comparison of the gene expression profiles between smokers with and without lung cancer using RNA-Seq. Asian Pac J Cancer Prev. 2012;13:3605-3609.  [PubMed]  [DOI]  [Cited in This Article: ]
103.  Kalari KR, Rossell D, Necela BM, Asmann YW, Nair A, Baheti S, Kachergus JM, Younkin CS, Baker T, Carr JM. Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations. Front Oncol. 2012;2:12.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 37]  [Cited by in F6Publishing: 42]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
104.  Wu Y, Wang X, Wu F, Huang R, Xue F, Liang G, Tao M, Cai P, Huang Y. Transcriptome profiling of the cancer, adjacent non-tumor and distant normal tissues from a colorectal cancer patient by deep sequencing. PLoS One. 2012;7:e41001.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 49]  [Cited by in F6Publishing: 59]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
105.  Atkinson SR, Marguerat S, Bähler J. Exploring long non-coding RNAs through sequencing. Semin Cell Dev Biol. 2012;23:200-205.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 81]  [Cited by in F6Publishing: 85]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
106.  Guenzl PM, Barlow DP. Macro lncRNAs: a new layer of cis-regulatory information in the mammalian genome. RNA Biol. 2012;9:731-741.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 54]  [Cited by in F6Publishing: 59]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
107.  Prensner JR, Chinnaiyan AM. The emergence of lncRNAs in cancer biology. Cancer Discov. 2011;1:391-407.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1266]  [Cited by in F6Publishing: 1431]  [Article Influence: 119.3]  [Reference Citation Analysis (0)]
108.  Shi X, Sun M, Liu H, Yao Y, Song Y. Long non-coding RNAs: a new frontier in the study of human diseases. Cancer Lett. 2013;339:159-166.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 823]  [Cited by in F6Publishing: 912]  [Article Influence: 82.9]  [Reference Citation Analysis (0)]
109.  de Kok JB, Verhaegh GW, Roelofs RW, Hessels D, Kiemeney LA, Aalders TW, Swinkels DW, Schalken JA. DD3(PCA3), a very sensitive and specific marker to detect prostate tumors. Cancer Res. 2002;62:2695-2698.  [PubMed]  [DOI]  [Cited in This Article: ]
110.  Hessels D, Klein Gunnewiek JM, van Oort I, Karthaus HF, van Leenders GJ, van Balken B, Kiemeney LA, Witjes JA, Schalken JA. DD3(PCA3)-based molecular urine analysis for the diagnosis of prostate cancer. Eur Urol. 2003;44:8-15; discussion 15-16.  [PubMed]  [DOI]  [Cited in This Article: ]
111.  Day JR, Jost M, Reynolds MA, Groskopf J, Rittenhouse H. PCA3: from basic molecular science to the clinical lab. Cancer Lett. 2011;301:1-6.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 62]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
112.  Ge X, Chen Y, Liao X, Liu D, Li F, Ruan H, Jia W. Overexpression of long noncoding RNA PCAT-1 is a novel biomarker of poor prognosis in patients with colorectal cancer. Med Oncol. 2013;30:588.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 137]  [Cited by in F6Publishing: 137]  [Article Influence: 12.5]  [Reference Citation Analysis (0)]
113.  Zhai H, Fesler A, Schee K, Fodstad O, Flatmark K, Ju J. Clinical significance of long intergenic noncoding RNA-p21 in colorectal cancer. Clin Colorectal Cancer. 2013;12:261-266.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 87]  [Cited by in F6Publishing: 88]  [Article Influence: 8.0]  [Reference Citation Analysis (0)]
114.  Ling H, Spizzo R, Atlasi Y, Nicoloso M, Shimizu M, Redis RS, Nishida N, Gafà R, Song J, Guo Z. CCAT2, a novel noncoding RNA mapping to 8q24, underlies metastatic progression and chromosomal instability in colon cancer. Genome Res. 2013;23:1446-1461.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 456]  [Cited by in F6Publishing: 491]  [Article Influence: 44.6]  [Reference Citation Analysis (0)]
115.  Kogo R, Shimamura T, Mimori K, Kawahara K, Imoto S, Sudo T, Tanaka F, Shibata K, Suzuki A, Komune S. Long noncoding RNA HOTAIR regulates polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers. Cancer Res. 2011;71:6320-6326.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 922]  [Cited by in F6Publishing: 1004]  [Article Influence: 77.2]  [Reference Citation Analysis (0)]
116.  Lu L, Zhu G, Zhang C, Deng Q, Katsaros D, Mayne ST, Risch HA, Mu L, Canuto EM, Gregori G. Association of large noncoding RNA HOTAIR expression and its downstream intergenic CpG island methylation with survival in breast cancer. Breast Cancer Res Treat. 2012;136:875-883.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 127]  [Cited by in F6Publishing: 145]  [Article Influence: 12.1]  [Reference Citation Analysis (0)]
117.  Xu C, Yang M, Tian J, Wang X, Li Z. MALAT-1: a long non-coding RNA and its important 3’ end functional motif in colorectal cancer metastasis. Int J Oncol. 2011;39:169-175.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 178]  [Article Influence: 13.7]  [Reference Citation Analysis (0)]
118.  Leon SA, Shapiro B, Sklaroff DM, Yaros MJ. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Res. 1977;37:646-650.  [PubMed]  [DOI]  [Cited in This Article: ]
119.  Choi JJ, Reich CF, Pisetsky DS. The role of macrophages in the in vitro generation of extracellular DNA from apoptotic and necrotic cells. Immunology. 2005;115:55-62.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 127]  [Cited by in F6Publishing: 149]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
120.  Schwarzenbach H, Hoon DS, Pantel K. Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer. 2011;11:426-437.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1954]  [Cited by in F6Publishing: 1989]  [Article Influence: 153.0]  [Reference Citation Analysis (0)]
121.  Kaiser J. Medicine. Keeping tabs on tumor DNA. Science. 2010;327:1074.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 30]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
122.  Feinberg AP, Vogelstein B. Hypomethylation distinguishes genes of some human cancers from their normal counterparts. Nature. 1983;301:89-92.  [PubMed]  [DOI]  [Cited in This Article: ]
123.  Sandoval J, Esteller M. Cancer epigenomics: beyond genomics. Curr Opin Genet Dev. 2012;22:50-55.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 344]  [Cited by in F6Publishing: 321]  [Article Influence: 26.8]  [Reference Citation Analysis (0)]
124.  Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nat Rev Genet. 2002;3:415-428.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3397]  [Cited by in F6Publishing: 3614]  [Article Influence: 164.3]  [Reference Citation Analysis (0)]
125.  Gyparaki MT, Basdra EK, Papavassiliou AG. DNA methylation biomarkers as diagnostic and prognostic tools in colorectal cancer. J Mol Med (Berl). 2013;91:1249-1256.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 43]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
126.  Goessl C, Krause H, Müller M, Heicappell R, Schrader M, Sachsinger J, Miller K. Fluorescent methylation-specific polymerase chain reaction for DNA-based detection of prostate cancer in bodily fluids. Cancer Res. 2000;60:5941-5945.  [PubMed]  [DOI]  [Cited in This Article: ]
127.  Nakayama H, Hibi K, Takase T, Yamazaki T, Kasai Y, Ito K, Akiyama S, Nakao A. Molecular detection of p16 promoter methylation in the serum of recurrent colorectal cancer patients. Int J Cancer. 2003;105:491-493.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 50]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
128.  Lecomte T, Berger A, Zinzindohoué F, Micard S, Landi B, Blons H, Beaune P, Cugnenc PH, Laurent-Puig P. Detection of free-circulating tumor-associated DNA in plasma of colorectal cancer patients and its association with prognosis. Int J Cancer. 2002;100:542-548.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 211]  [Cited by in F6Publishing: 217]  [Article Influence: 9.9]  [Reference Citation Analysis (0)]
129.  Grady WM, Rajput A, Lutterbaugh JD, Markowitz SD. Detection of aberrantly methylated hMLH1 promoter DNA in the serum of patients with microsatellite unstable colon cancer. Cancer Res. 2001;61:900-902.  [PubMed]  [DOI]  [Cited in This Article: ]
130.  Leung WK, To KF, Man EP, Chan MW, Bai AH, Hui AJ, Chan FK, Sung JJ. Quantitative detection of promoter hypermethylation in multiple genes in the serum of patients with colorectal cancer. Am J Gastroenterol. 2005;100:2274-2279.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 101]  [Cited by in F6Publishing: 114]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
131.  Esteller M, Sanchez-Cespedes M, Rosell R, Sidransky D, Baylin SB, Herman JG. Detection of aberrant promoter hypermethylation of tumor suppressor genes in serum DNA from non-small cell lung cancer patients. Cancer Res. 1999;59:67-70.  [PubMed]  [DOI]  [Cited in This Article: ]
132.  Sanchez-Cespedes M, Esteller M, Wu L, Nawroz-Danish H, Yoo GH, Koch WM, Jen J, Herman JG, Sidransky D. Gene promoter hypermethylation in tumors and serum of head and neck cancer patients. Cancer Res. 2000;60:892-895.  [PubMed]  [DOI]  [Cited in This Article: ]
133.  Domínguez G, Carballido J, Silva J, Silva JM, García JM, Menéndez J, Provencio M, España P, Bonilla F. p14ARF promoter hypermethylation in plasma DNA as an indicator of disease recurrence in bladder cancer patients. Clin Cancer Res. 2002;8:980-985.  [PubMed]  [DOI]  [Cited in This Article: ]
134.  Yin H, Liang Y, Yan Z, Liu B, Su Q. Mutation spectrum in human colorectal cancers and potential functional relevance. BMC Med Genet. 2013;14:32.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 9]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
135.  Sorenson GD, Pribish DM, Valone FH, Memoli VA, Bzik DJ, Yao SL. Soluble normal and mutated DNA sequences from single-copy genes in human blood. Cancer Epidemiol Biomarkers Prev. 1994;3:67-71.  [PubMed]  [DOI]  [Cited in This Article: ]
136.  Vasioukhin V, Anker P, Maurice P, Lyautey J, Lederrey C, Stroun M. Point mutations of the N-ras gene in the blood plasma DNA of patients with myelodysplastic syndrome or acute myelogenous leukaemia. Br J Haematol. 1994;86:774-779.  [PubMed]  [DOI]  [Cited in This Article: ]
137.  Szymańska K, Lesi OA, Kirk GD, Sam O, Taniere P, Scoazec JY, Mendy M, Friesen MD, Whittle H, Montesano R. Ser-249TP53 mutation in tumour and plasma DNA of hepatocellular carcinoma patients from a high incidence area in the Gambia, West Africa. Int J Cancer. 2004;110:374-379.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 72]  [Cited by in F6Publishing: 77]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
138.  Diehl F, Li M, Dressman D, He Y, Shen D, Szabo S, Diaz LA, Goodman SN, David KA, Juhl H. Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proc Natl Acad Sci USA. 2005;102:16368-16373.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 840]  [Cited by in F6Publishing: 898]  [Article Influence: 47.3]  [Reference Citation Analysis (0)]
139.  Diehl F, Schmidt K, Choti MA, Romans K, Goodman S, Li M, Thornton K, Agrawal N, Sokoll L, Szabo SA. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14:985-990.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1719]  [Cited by in F6Publishing: 1896]  [Article Influence: 111.5]  [Reference Citation Analysis (0)]
140.  Gormally E, Caboux E, Vineis P, Hainaut P. Circulating free DNA in plasma or serum as biomarker of carcinogenesis: practical aspects and biological significance. Mutat Res. 2007;635:105-117 .  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 315]  [Cited by in F6Publishing: 325]  [Article Influence: 19.1]  [Reference Citation Analysis (0)]
141.  Hibi K, Robinson CR, Booker S, Wu L, Hamilton SR, Sidransky D, Jen J. Molecular detection of genetic alterations in the serum of colorectal cancer patients. Cancer Res. 1998;58:1405-1407.  [PubMed]  [DOI]  [Cited in This Article: ]
142.  Ito S, Hibi K, Nakayama H, Kodera Y, Ito K, Akiyama S, Nakao A. Detection of tumor DNA in serum of colorectal cancer patients. Jpn J Cancer Res. 2002;93:1266-1269.  [PubMed]  [DOI]  [Cited in This Article: ]
143.  Chen XQ, Stroun M, Magnenat JL, Nicod LP, Kurt AM, Lyautey J, Lederrey C, Anker P. Microsatellite alterations in plasma DNA of small cell lung cancer patients. Nat Med. 1996;2:1033-1035.  [PubMed]  [DOI]  [Cited in This Article: ]
144.  Nawroz H, Koch W, Anker P, Stroun M, Sidransky D. Microsatellite alterations in serum DNA of head and neck cancer patients. Nat Med. 1996;2:1035-1037.  [PubMed]  [DOI]  [Cited in This Article: ]
145.  He Y, Wu J, Dressman DC, Iacobuzio-Donahue C, Markowitz SD, Velculescu VE, Diaz LA, Kinzler KW, Vogelstein B, Papadopoulos N. Heteroplasmic mitochondrial DNA mutations in normal and tumour cells. Nature. 2010;464:610-614.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 406]  [Cited by in F6Publishing: 393]  [Article Influence: 28.1]  [Reference Citation Analysis (0)]
146.  Kuo SJ, Chen M, Ma GC, Chen ST, Chang SP, Lin WY, Chen YC, Lee TH, Lin TT, Liu CS. Number of somatic mutations in the mitochondrial D-loop region indicates poor prognosis in breast cancer, independent of TP53 mutation. Cancer Genet Cytogenet. 2010;201:94-101.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 16]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
147.  Hibi K, Nakayama H, Yamazaki T, Takase T, Taguchi M, Kasai Y, Ito K, Akiyama S, Nakao A. Detection of mitochondrial DNA alterations in primary tumors and corresponding serum of colorectal cancer patients. Int J Cancer. 2001;94:429-431.  [PubMed]  [DOI]  [Cited in This Article: ]
148.  Kohler C, Radpour R, Barekati Z, Asadollahi R, Bitzer J, Wight E, Bürki N, Diesch C, Holzgreve W, Zhong XY. Levels of plasma circulating cell free nuclear and mitochondrial DNA as potential biomarkers for breast tumors. Mol Cancer. 2009;8:105.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 144]  [Cited by in F6Publishing: 157]  [Article Influence: 10.5]  [Reference Citation Analysis (0)]
149.  Mehra N, Penning M, Maas J, van Daal N, Giles RH, Voest EE. Circulating mitochondrial nucleic acids have prognostic value for survival in patients with advanced prostate cancer. Clin Cancer Res. 2007;13:421-426.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 80]  [Cited by in F6Publishing: 81]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
150.  Zachariah RR, Schmid S, Buerki N, Radpour R, Holzgreve W, Zhong X. Levels of circulating cell-free nuclear and mitochondrial DNA in benign and malignant ovarian tumors. Obstet Gynecol. 2008;112:843-850.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 92]  [Cited by in F6Publishing: 95]  [Article Influence: 5.9]  [Reference Citation Analysis (0)]
151.  Takeuchi H, Fujimoto A, Hoon DS. Detection of mitochondrial DNA alterations in plasma of malignant melanoma patients. Ann N Y Acad Sci. 2004;1022:50-54.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 34]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
152.  Okochi O, Hibi K, Uemura T, Inoue S, Takeda S, Kaneko T, Nakao A. Detection of mitochondrial DNA alterations in the serum of hepatocellular carcinoma patients. Clin Cancer Res. 2002;8:2875-2878.  [PubMed]  [DOI]  [Cited in This Article: ]
153.  Polyak K, Li Y, Zhu H, Lengauer C, Willson JK, Markowitz SD, Trush MA, Kinzler KW, Vogelstein B. Somatic mutations of the mitochondrial genome in human colorectal tumours. Nat Genet. 1998;20:291-293.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 625]  [Cited by in F6Publishing: 656]  [Article Influence: 25.2]  [Reference Citation Analysis (0)]
154.  Schaaij-Visser TB, de Wit M, Lam SW, Jiménez CR. The cancer secretome, current status and opportunities in the lung, breast and colorectal cancer context. Biochim Biophys Acta. 2013;1834:2242-2258.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 75]  [Cited by in F6Publishing: 83]  [Article Influence: 7.5]  [Reference Citation Analysis (0)]
155.  Lleonart ME, Kirk GD, Villar S, Lesi OA, Dasgupta A, Goedert JJ, Mendy M, Hollstein MC, Montesano R, Groopman JD. Quantitative analysis of plasma TP53 249Ser-mutated DNA by electrospray ionization mass spectrometry. Cancer Epidemiol Biomarkers Prev. 2005;14:2956-2962.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 38]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
156.  Taguchi A, Hanash SM. Unleashing the power of proteomics to develop blood-based cancer markers. Clin Chem. 2013;59:119-126.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 42]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
157.  Engwegen JY, Helgason HH, Cats A, Harris N, Bonfrer JM, Schellens JH, Beijnen JH. Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry. World J Gastroenterol. 2006;12:1536-1544.  [PubMed]  [DOI]  [Cited in This Article: ]
158.  Ostroff RM, Bigbee WL, Franklin W, Gold L, Mehan M, Miller YE, Pass HI, Rom WN, Siegfried JM, Stewart A. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS One. 2010;5:e15003.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 157]  [Cited by in F6Publishing: 166]  [Article Influence: 11.9]  [Reference Citation Analysis (0)]
159.  de Wit M, Fijneman RJ, Verheul HM, Meijer GA, Jimenez CR. Proteomics in colorectal cancer translational research: biomarker discovery for clinical applications. Clin Biochem. 2013;46:466-479.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 71]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
160.  Kanaan Z, Rai SN, Eichenberger MR, Roberts H, Keskey B, Pan J, Galandiuk S. Plasma miR-21: a potential diagnostic marker of colorectal cancer. Ann Surg. 2012;256:544-551.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 195]  [Cited by in F6Publishing: 220]  [Article Influence: 18.3]  [Reference Citation Analysis (0)]
161.  Toiyama Y, Takahashi M, Hur K, Nagasaka T, Tanaka K, Inoue Y, Kusunoki M, Boland CR, Goel A. Serum miR-21 as a diagnostic and prognostic biomarker in colorectal cancer. J Natl Cancer Inst. 2013;105:849-859.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 345]  [Cited by in F6Publishing: 378]  [Article Influence: 34.4]  [Reference Citation Analysis (0)]
162.  Menéndez P, Padilla D, Villarejo P, Palomino T, Nieto P, Menéndez JM, Rodríguez-Montes JA. Prognostic implications of serum microRNA-21 in colorectal cancer. J Surg Oncol. 2013;108:369-373.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 64]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
163.  Huang Y, Yang YB, Zhang XH, Yu XL, Wang ZB, Cheng XC. MicroRNA-21 gene and cancer. Med Oncol. 2013;30:376.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 77]  [Article Influence: 7.0]  [Reference Citation Analysis (0)]
164.  Baraniskin A, Nöpel-Dünnebacke S, Ahrens M, Jensen SG, Zöllner H, Maghnouj A, Wos A, Mayerle J, Munding J, Kost D. Circulating U2 small nuclear RNA fragments as a novel diagnostic biomarker for pancreatic and colorectal adenocarcinoma. Int J Cancer. 2013;132:E48-E57.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 106]  [Cited by in F6Publishing: 110]  [Article Influence: 9.2]  [Reference Citation Analysis (0)]
165.  Zauber AG, Lansdorp-Vogelaar I, Knudsen AB, Wilschut J, van Ballegooijen M, Kuntz KM. Evaluating test strategies for colorectal cancer screening: a decision analysis for the U.S. Preventive Services Task Force. Ann Intern Med. 2008;149:659-669.  [PubMed]  [DOI]  [Cited in This Article: ]
166.  Rockey DC, Paulson E, Niedzwiecki D, Davis W, Bosworth HB, Sanders L, Yee J, Henderson J, Hatten P, Burdick S. Analysis of air contrast barium enema, computed tomographic colonography, and colonoscopy: prospective comparison. Lancet. 2005;365:305-311.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 231]  [Cited by in F6Publishing: 217]  [Article Influence: 11.4]  [Reference Citation Analysis (1)]