• C-RADS
• CT colonography
• Dose reduction
• Image display
• Reimbursement
• Reporting
• Staging
• Technique

• Humans
• Colonography, Computed Tomographic/methods
• Colonography, Computed Tomographic/trends
• Colorectal Neoplasms/diagnostic imaging
• Colorectal Neoplasms/pathology
• Colon/diagnostic imaging
• Early Detection of Cancer/methods

• CT Colonography
• Cancer screening
• Machine learning
• Polyps

• Colon polyps
• Colonoscopy
• Fecal immunohistochemical test
• Fecal occult blood test
• Surveillance

• Humans
• Colonoscopy
• Colorectal Neoplasms/epidemiology
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/pathology
• Female
• Male
• Middle Aged
• Adenoma/epidemiology
• Adenoma/diagnosis
• Adenoma/pathology
• Aged
• Early Detection of Cancer/methods
• Incidence
• Occult Blood
• Risk Factors
• Texas/epidemiology
• Retrospective Studies
• Colonic Polyps/epidemiology
• Colonic Polyps/diagnosis

• K23 DK129776 NIDDK NIH HHS
• P30 DK056338 NIDDK NIH HHS
• K23DK129776 The National Institute of Diabetes And Digestive And Kidney Diseases

• Adenocarcinoma
• Adolescentes
• Adolescents
• Children
• Colorectal cancer
• Cáncer colorrectal
• Niños
• Oncología pediátrica
• Pediatric oncology

• RNA profiling
• advanced adenoma
• cancer biology
• colorectal cancer
• exosomes
• extracellular vesicles
• genetics
• genomics
• human

• Humans
• Colorectal Neoplasms/genetics
• Colorectal Neoplasms/blood
• Colorectal Neoplasms/pathology
• Colorectal Neoplasms/diagnosis
• Extracellular Vesicles/genetics
• Extracellular Vesicles/metabolism
• Adenoma/genetics
• Adenoma/blood
• Adenoma/pathology
• Biomarkers, Tumor/blood
• Biomarkers, Tumor/genetics
• Male
• Female
• Middle Aged
• Aged
• Liquid Biopsy/methods
• Precancerous Conditions/genetics
• Precancerous Conditions/blood
• Precancerous Conditions/pathology
• Neoplasm Staging

• Z191100001119128 Beijing Nova Program
• Z191100006619081 Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park
• 82073390 National Natural Science Foundation of China
• QML20180108 Beijing Municipal Administration of Hospitals
• XXZ02 Beijing Municipal Administration of Hospitals
• XXZ01 Beijing Municipal Administration of Hospitals

• biomarkers
• colorectal cancer
• early detection
• liquid biopsy
• methylation
• screening

• CT colonography
• computed tomography
• fibrocolonoscopy
• gastrointestinal diseases
• incomplete colonoscopy
• tumor
• virtual colonoscopy

• BG-RRP-2.004-0008 European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria

• Colorectal cancer
• HSP90
• Hsa-miR-485–5p
• LncRNA NNT-AS1
• Prognositic molecular biomarkers
• in silico

• CEACAM-1
• Colon cancer
• ICAM-1
• Machine learning
• Raman spectroscopy

• Colonoscopy
• Diagnostic accuracy
• Fecal immunochemical test

• 5 mm
• adenoma detection rate
• colonoscopy
• linked color image
• polyp detection rate

• Humans
• Colonic Polyps/diagnosis
• Colonic Polyps/pathology
• Colonoscopy/methods
• Colorectal Neoplasms/pathology
• Adenoma/diagnosis
• Adenoma/pathology
• Image Enhancement/methods
• Color

• Artifacts
• CT
• Colonography, computed tomographic
• DECT
• Spectral CT

• Humans
• Middle Aged
• Aged
• Colonography, Computed Tomographic/methods
• Retrospective Studies
• Algorithms
• Cathartics
• Artifacts
• Iodine

• R01 CA226868 NCI NIH HHS
• R01CA226868 NIH HHS

• Colon cancer screening
• Colonoscopy
• Fecal immunoglobulin test
• Meta-analysis

• Adenoma/diagnosis
• Colorectal Neoplasms/diagnosis
• Early Detection of Cancer/methods
• Guaiac
• Hemoglobins
• Humans
• Occult Blood
• Prospective Studies
• Retrospective Studies
• Sensitivity and Specificity

• P30 CA008748 NCI NIH HHS

• Biomarker
• Colorectal cancer
• Feces
• SYPL1

• Adenoma/diagnosis
• Adenoma/metabolism
• Biomarkers, Tumor/metabolism
• Carcinoembryonic Antigen/metabolism
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/metabolism
• Feces/chemistry
• Humans
• Synaptophysin/metabolism

• Colonoscopy
• Colorectal cancer
• Colorectal polyps
• Computed tomographic colonography

To investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning.

In this retrospective analysis of an average risk colorectal cancer screening sample, polyps of all size categories and morphologies were manually segmented on supine and prone CT colonography images and classified as premalignant (adenoma) or benign (hyperplastic polyp or regular mucosa) according to histopathology. Two deep learning models SEG and noSEG were trained on 3D CT colonography image subvolumes to predict polyp class, and model SEG was additionally trained with polyp segmentation masks. Diagnostic performance was validated in an independent external multicentre test sample. Predictions were analysed with the visualisation technique Grad-CAM++.

The training set consisted of 107 colorectal polyps in 63 patients (mean age: 63 ± 8 years, 40 men) comprising 169 polyp segmentations. The external test set included 77 polyps in 59 patients comprising 118 polyp segmentations. Model SEG achieved a ROC-AUC of 0.83 and 80% sensitivity at 69% specificity for differentiating premalignant from benign polyps. Model noSEG yielded a ROC-AUC of 0.75, 80% sensitivity at 44% specificity, and an average Grad-CAM++ heatmap score of ≥ 0.25 in 90% of polyp tissue.

In this proof-of-concept study, deep learning enabled the differentiation of premalignant from benign colorectal polyps detected with CT colonography and the visualisation of image regions important for predictions. The approach did not require polyp segmentation and thus has the potential to facilitate the identification of high-risk polyps as an automated second reader.

• Non-invasive deep learning image analysis may differentiate premalignant from benign colorectal polyps found in CT colonography scans.

• Deep learning autonomously learned to focus on polyp tissue for predictions without the need for prior polyp segmentation by experts.

• Deep learning potentially improves the diagnostic accuracy of CT colonography in colorectal cancer screening by allowing for a more precise selection of patients who would benefit from endoscopic polypectomy, especially for patients with polyps of 6–9 mm size.

The online version contains supplementary material available at 10.1007/s00330-021-08532-2.

• Colonic polyp
• Colonography
• Computed tomographic
• Deep learning
• Early detection of cancer

Background:SDC2 methylation is a feasible biomarker for colorectal cancer detection. Its specificity for colorectal cancer is higher than 90%, but the sensitivity is normally lower than 90%. This study aims to improve the sensitivity of SDC2 detection through finding a high positive target from the false-negative samples of SDC2 detection based on analysis of the bowel subsite difference in methylation.

Methods: Hypermethylated TFPI2 was identified in SDC2 hypomethylated colorectal cancer samples retrieved from TCGA database with the methylation level lower than 0.2. The methylation-specific PCR assay was developed and then evaluated using tissue samples (184 cancer and 54 healthy control samples) and stool samples (289 cancer, 190 adenoma, and 217 healthy control samples).

Results:TFPI2 was hypermethylated in most SDC2 hypomethylated colorectal cancer samples. When the SDC2/TFPI2-combined PCR assay was performed in stool specimens, the AUC value of cancer vs. control was 0.98, with the specificity of 96.40% and sensitivity of 96.60%, and the AUC value of adenoma vs. control was 0.87, with the specificity of 95.70% and the sensitivity of 80.00%. The improvement in sensitivity was the most momentous in the left colon. As the detection index, the Ct value was better in improving the sensitivity of detection than the methylation level based on the 2^−ΔΔCt value.

Conclusion:TFPI2 can improve the sensitivity of SDC2 methylation–specific detection of colorectal tumorous lesions while maintaining high specificity, in particular reducing the missed detection of left colon cancer and adenoma.

• SDC2
• TFPI2
• adenomas
• colorectal cancer
• methylation

This study aimed to validate and reanalyze urinary biomarkers for detecting colorectal cancers (CRCs). We previously conducted urinary metabolomic analyses using capillary electrophoresis-mass spectrometry and found a significant difference in various metabolites, especially polyamines, between patients with CRC and healthy controls (HC). We analyzed additional samples and confirmed consistency between the newly and previously analyzed data. In total, we included 36 HC, 34 adenoma (AD), and 214 CRC samples, which were used for subsequent analyses. Among the 132 quantified metabolites, 16 exhibited consistent differences in both datasets, which included polyamines, etc. Pathway analyses of the integrated data revealed significant differences in many metabolites, such as glutamine, and metabolites of the TCA (tricarboxylic acid cycle) and urea cycles. The discrimination ability of the combination of multiple metabolites among the three groups was evaluated, which yielded higher sensitivity than tumor markers. The Mann–Whitney test was employed to evaluate the prognosis predictivity of the assessed metabolites and the difference between the patients with or without recurrence, which yielded 16 significantly different metabolites. Among these 16 metabolites, 11 presented significant prognosis predictivity. These data indicated the potential of metabolite-based discrimination of patients with CRC and AD from HC and prognosis predictivity of the monitored metabolites.

• adenoma
• capillary electrophoresis-mass spectrometry
• colorectal cancer
• metabolome

• Age Factors
• Aged
• Aged, 80 and over
• Colonoscopy/methods
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/mortality
• Early Detection of Cancer/adverse effects
• Early Detection of Cancer/methods
• Female
• Humans
• Male
• Middle Aged
• Occult Blood
• Practice Guidelines as Topic
• Risk
• Sigmoidoscopy
• Tomography, X-Ray Computed

Even though colorectal cancer (CRC) is one of the most preventable cancers, it is currently one of the deadliest. Worryingly, incidence in people <50 years has increased unexpectedly, and for unknown causes, despite the successful implementation of screening programs in the population aged >50 years. Thus, there is a need to improve early diagnosis detection strategies by identifying more precise biomarkers. In this scenario, the analysis of exosomes is given considerable attention. Previously, we demonstrated the exosome lipidome was able to classify CRC cell lines according to their malignancy. Herein, we investigated the use of the lipidome of plasma extracellular vesicles as a potential source of non-invasive biomarkers for CRC. A plasma exosome-enriched fraction was analyzed from patients undergoing colonoscopic procedure. Patients were divided into a healthy group and four pathological groups (patients with hyperplastic polyps; adenomatous polyps; invasive neoplasia (CRC patients); or hereditary non-polyposis CRC. The results showed a shift from 34:1- to 38:4-containing species in the pathological groups. We demonstrate that the ratio Σ34:1-containing species/Σ38:4-containing species has the potential to discriminate between healthy and pathological patients. Altogether, the results reinforce the utility of plasma exosome lipid fingerprint to provide new non-invasive biomarkers in a clinical context.

• colorectal cancer
• exosomes
• lipidome
• monounsaturated fatty acids
• polyunsaturated fatty acids

• Chemotherapy
• anti-cancer agent
• nanodiagnostics
• nanotherapy
• targeted therapy

• advanced neoplasia
• cancer prevention
• colorectal cancer screening
• meta-analysis

Aberrant DNA methylation has emerged as a class of promising biomarkers for early colorectal cancer (CRC) detection, but the performance of methylated C9orf50 and methylated KCNQ5 in stool DNA has never been evaluated.

Methylation specific quantitative PCR (qPCR) assays for methylated C9orf50 and methylated KCNQ5 were developed. The methylation levels of C9orf50 and KCNQ5 in 198 CRC patients, 20 advanced adenoma (AA) patients, 101 small polyp (SP) patients, and 141 no evidence of disease (NED) subjects were analyzed.

The methylation levels of both KCNQ5 and C9orf50 genes were significantly higher in CRC and AA groups than those in SP and NED groups, but showed no significant difference among different stages of CRC. The sensitivities of methylated KCNQ5 and methylated C9orf50 for CRC detection were 77.3% (95% CI: 70.7–82.8%) and 85.9% (95% CI: 80.0–90.2%) with specificities of 91.5% (95% CI: 85.3–95.3%) and 95.0% (95% CI: 89.7–97.8%), respectively. When C9orf50 and methylated KCNQ5 were combined, the clinical performance for CRC detection was similar to that of methylated C9orf50 alone.

Stool DNA based methylated C9orf50 test has the potential to become an alternative approach for CRC screening and prevention.

• colorectal cancer
• early detection
• methylated C9orf50
• methylated KCNQ5
• stool DNA

• Accuracy
• Site
• T Stage
• uicc Stage

The diagnostic performance of serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA) 19-9 levels for multiple-organ cancer screening has not been fully elucidated. However, they are widely used for real-world opportunistic screening of multiple-organ cancers. This study aimed to examine the diagnostic performance of these serum markers in multiple-organ cancer screening. Data from asymptomatic individuals subjected to opportunistic cancer screening were analyzed. The diagnostic performance of CEA and CA 19-9 was assessed for (A) upper/lower gastrointestinal cancers and (B) whole-body cancers (including both gastrointestinal and other organ cancers) using the results of upper/lower gastrointestinal endoscopy and whole-body imaging as reference. Data from 12,349 and 7616 screened individuals were used to assess the diagnostic performance of CEA and CA 19-9 for (A) and (B), respectively. For (A), the sensitivity and positive predictive value (PPV) of CEA (cut-off: 5 ng/mL) were 7.8% and 3.7%, respectively; those of CA19-9 (cut-off: 37 U/mL) were 7.4% and 2.7%, respectively. For (B), the sensitivity and PPV of CEA were 6.6% and 4.1%, respectively, and those of CA19-9 were 10.8% and 5.8%, respectively. Considering even multiple cancers, the sensitivity and PPV of CEA and CA 19-9 were low, thus confirming their limited usefulness in multiple-organ cancer screening.

• BRAF
• KRAS
• colorectal cancer
• mast cells
• microRNAs
• precision medicine
• translational research

• CRC screening
• CT colonography
• Capsule colon
• Sigmoidoscopy
• Virtual colonoscopy

Colorectal cancer (CRC) is one of the most common illnesses that seriously threatens human health; many papers have reported that microRNAs (miRNAs) are promising biomarkers for cancer detection. However, miRNAs have not been used in clinical practice even though they are superior to the currently used screening tools, such as the fecal occult blood test (FOBT) and carcinoembryonic antigen (CEA) measurement.

In this study, we focused on the usefulness of a panel of miRNAs and the combination of miRNAs with the FOBT and CEA measurement, the currently used general diagnosis methods, to improve the accuracy of CRC diagnosis.

The results showed that the miRNA panel has great potential value as a diagnostic biomarker with high specificity and sensitivity, and further analysis demonstrated that the miRNA panel had higher sensitivity and specificity than the FOBT and CEA measurement, even when these methods were combined. More importantly, although the miRNA panel is superior to the FOBT and CEA measurement, it cannot replace them.

In this research, we investigated whether complementarity exists between the miRNA panel and the FOBT and CEA measurement for CRC diagnosis. Interestingly, the results indicated that the FOBT and CEA measurement could improve the positivity rate of the miRNA panel as a biomarker and vice versa.

• biomarker
• colorectal cancer
• microRNAs

• Adenoma
• Colon Cancer
• Early Detection
• Removal
• Tumor

• Colonoscopy
• Colorectal Neoplasms/diagnosis
• Early Detection of Cancer
• Feces/chemistry
• Hemoglobins/analysis
• Humans
• Middle Aged
• Occult Blood
• Prospective Studies

• P30 CA023100 NCI NIH HHS
• R37 CA222866 NCI NIH HHS

• 3D visualization
• CT colonography
• colon cancer

The Dutch colorectal cancer (CRC) screening program started in 2014, inviting the target population biennially to perform a fecal immunochemical test (FIT). We obtained prospectively collected data from the national screening information‐system to present the results of the second round (2016) and evaluate the impact of increasing the FIT cut‐off halfway through the first round from 15 to 47 μg Hb/g feces on outcomes in the second round. Second round screening was done with a 47 μg Hb/g feces FIT cut‐off. Participants were classified based on first round participation status as either FIT (15,47) or FIT (47,47) participants, and previous nonparticipants. In total, 348,891 (75.9%) out of 459,740 invitees participated in the second round. Participation rates were 93.4% among previous participants and 21.0% among previous non‐participants. FIT(47,47) participants had a significantly higher detection rate of AN (15.3 vs. 10.4 per 1,000 participants) compared to FIT(15,47) participants in the second round, while their cumulative detection rate of AN over two rounds was significantly lower (45.6 vs. 52.6 per 1,000 participants). Our results showed that participation in the Dutch CRC screening program was consistently high and that second round detection rates depended on the first round FIT cut‐off. The cumulative detection over two rounds was higher among FIT(15,47) participants. These findings suggest that a substantial part of, but not all the missed findings in the first round due to the increased FIT cut‐off were detected in the subsequent round.

What's new?

In 2014, the Netherlands implemented colorectal cancer (CRC) screening based on non‐invasive fecal immunochemical testing (FIT), which offers a practical approach for population‐based CRC detection. In the Dutch program's first round, to match local resources, FIT cut‐off was increased, resulting in reduced positivity rates and reduced colonoscopy referrals, at the cost of missing advanced neoplasias. The current study shows that many of these missed advanced neoplasias were detected in subsequent screening, suggesting that increased FIT cut‐off had marginal impact on screening outcome. The findings could benefit other CRC screening programs in establishing effective FIT cut‐offs.

• colonoscopy
• colorectal cancer
• colorectal cancer screening
• colorectal neoplasia
• fecal immunochemical test

• Advanced Neoplasia
• Colon Cancer
• Diagnostic Performance
• Fecal Occult Blood Test

• Adenoma/diagnosis
• Age Factors
• Colonoscopy
• Colorectal Neoplasms/diagnosis
• Early Detection of Cancer/methods
• Early Detection of Cancer/standards
• Hemoglobins/analysis
• Humans
• Mass Screening/methods
• Mass Screening/standards
• Occult Blood
• Reference Standards
• Sensitivity and Specificity
• Sex Factors

• K07 CA212057 NCI NIH HHS
• R01 CA213645 NCI NIH HHS
• U54 CA163262 NCI NIH HHS
• UM1 CA222035 NCI NIH HHS

• colorectal cancer
• screening test
• sensitivity

• CT colonography
• Colorectal adenoma
• Early detection
• Screening
• Virtual colonoscopy

• Bowel preparation
• Colonoscopy
• Oral sulfate solution
• Sodium picosulfate with magnesium citrate

• Computed tomographic colonography
• Laxatives
• Polyethylene glycols