Personalized medicine: Clinical oncology on molecular view of treatment

Abstract

Cancer, the second leading global cause of death, impacts both physically and emotionally. Conventional treatments such as surgeries, chemotherapy, and radiotherapy have adverse effects, driving the need for more precise approaches. Precision medicine enables more targeted treatments. Genetic mapping, alongside other molecular biology approaches, identifies specific genes, contributing to accurate prognoses. The review addresses, in clinical use, a molecular perspective on treatment. Biomarkers like alpha-fetoprotein, beta-human chorionic gonadotropin, 5-hydroxyindoleacetic acid, programmed death-1, and cytotoxic T lymphocyte-associated protein 4 are explored, providing valuable information. Bioinformatics, with an emphasis on artificial intelligence, revolutionizes the analysis of biological data, offering more accurate diagnoses. Techniques like liquid biopsy are emphasized for early detection. Precision medicine guides therapeutic strategies based on the molecular characteristics of the tumor, as evidenced in the molecular subtypes of breast cancer. Classifications allow personalized treatments, highlighting the role of trastuzumab and endocrine therapies. Despite the benefits, challenges persist, including high costs, tumor heterogeneity, and ethical issues. Overcoming obstacles requires collaboration, ensuring that advances in molecular biology translate into accessible benefits for all.

Key Words: Oncology; Neoplasia; Molecular biology; Personalized medicine; Molecular Markers; Cancer

Core Tip: This review emphasizes the importance of precision medicine in cancer treatment, highlighting the role of molecular biology in identifying specific genetic markers for more accurate prognosis and targeted therapies. We discuss the main biomarkers, such as alpha-fetoprotein and programmed death-1, and the revolutionary impact of bioinformatics in the diagnosis of neoplasms. Techniques such as liquid biopsy and immunohistochemistry gain prominence for early detection as a directional tool for therapies. The review also addresses challenges, including costs and tumor heterogeneity, advocating collaborative efforts to ensure these advances are accessible to all.

INTRODUCTION

Commonly known as cancer or neoplasms, the pathological group of malignant neoplasms. Cancer is the second leading cause of death worldwide, affecting not only the physical health of the individual but also their emotional well-being, psychologically weakening their entire support community. One of the main aggravating factors in this process is conventional treatments such as surgeries, chemotherapy and radiotherapy, despite being efficient, they are invasive procedures that cause various adverse effects, even when considering the type of cancer and the patient’s individuality[1].

Due to these adverse effects, innovations in personalized medicine have proven to be highly efficient in providing more precise treatment, considering the individual’s peculiarities and the characteristics of the cancer, and aiming to cause less harm to the body during the therapeutic process. Among these personalized treatments, the genetic mapping of the patient proves to be a great ally in the clinical management of cancer, due to its ability to make accurate prognoses and identify individualities that enhance the success of treatments[2].

Genetic mapping, along with other molecular approaches, comprises biotechnological tools that allow the identification of genes in a particular individual, often used in locating a gene sequence indicative of genetically based diseases. In the context of cancer, its applications include the potential to contribute to more effective treatment through personalized therapy, predict a response to a specific treatment based on individual genetic profiles, and track the progression of the disease.

This critical review seeks to comprehensively organize data regarding the clinical use of molecular approaches in the current treatment of cancers and compile the latest data derived from scientific research on molecular markers involved in the onset and maintenance of the disease. Additionally, it aims to examine the practical implementation of these tools in formulating personalized medical strategies and reflect on the population profile that has access to these innovative techniques.

RELEVANCE OF MAPPING

The most significant milestone in the history of global genetic mapping is the Human Genome Project, which lasted nearly 15 years and aimed to identify and sequence all the human genes. This research was conducted collaboratively by laboratories and scientists from various parts of the world, given its extensive, intricate, and crucial nature. The predominant molecular biology technique employed in this process was genetic sequencing, enabling the identification of the nucleotide arrangement in a DNA strand.

Another pivotal tool that propelled the project forward was bioinformatics, essential for analyzing all the collected data and arranging DNA fragments during genome assembly. Its conclusion in 2003 stimulated the development of studies exploring the implications of genetic mutations and the onset of diseases. In the field of oncology, the genetic alterations of interest are those seeking to explore pathogenic mutations responsible for the uncontrolled development of cells, resulting in the invasion of adjacent tissues and organs.

It is undeniable that the field of gene mapping is still growing exponentially and holds significant potential to become a fundamental area for cancer diagnosis and prevention. In addition to enabling the identification of pathogenic alterations, it aims to ensure individualized treatment, early diagnosis, and anticipates the possibility of secondary neoplasms. An example of the newfound importance attributed to genomics is the data from the Global Cancer Observatory, under the auspices of the International Agency for Research on Cancer, indicating a worldwide incidence of approximately 19.3 million cases documented in 2020, with breast (11.7%), lung (11.4%), colorectal (10%), and prostate (7.3%) cancers being the most frequent.

An incorporation of this technology into the daily clinical practice of cancer has proven effective when the attending physician requests genetic mapping of their patient. Molecular alterations induced by the disease may be challenging to observe through microscopy, and the genomic approach assumes a novel role in enhancing the precision of the applied treatment. Indeed, “clinical tumor genomic profiling is now broadly viewed as necessary by oncologists to ensure optimal therapy selection in patients with advanced lung cancer”, for example[3]. During this process, genomic data, clinical information, and patient preferences are integrated to inform the most suitable therapy for each individual in treating their cancer[4].

In addition to assisting in the selection of treatment, “spatial mapping of nucleic acids, proteins and metabolites in tumor tissues can help in understanding the molecular mechanisms involved in tumorigenesis, early detection of cancers and initiating possible preventative measures”[5]. The very understanding of what we perceive as cancer may be influenced in the near future by the promising use of large-scale genetic mapping, facilitating prevention, optimizing treatment, and primarily in the pursuit of reducing medication side effects through personalized medicine. Finally, analyzing the DNA of previously treated cells can provide valuable insights into their mechanisms of action, resistance to therapies, and potentially assist in the development of alternative therapeutic options[6].

BIOMARKERS

In clinical oncology, the search for biomarkers stands out as a tool for identifying, stratifying, and monitoring patients[7]. Defined as molecules that objectively assess characteristics of biological processes, biomarkers play a fundamental role in the era of personalized medicine, given that advances in the fields of bioinformatics, genomics, and proteomics have enabled the mapping of a variety of potential biomarkers[8]. However, the transition of these markers from the laboratory to clinical practice remains challenging. The complexity in developing specific and economically viable tests capable of identifying desired molecules in different types of samples often results in the rejection of several biomarkers during the clinical validation phase[7].

The immune system plays a crucial role in the control and elimination of cancer. However, tumor-utilized immunosuppressive mechanisms can compromise the body’s ability to effectively combat the disease[9]. The integration of biomarkers into clinical practice not only revolutionizes the approach to cancer, allowing for more precise and stratified diagnoses but also paves the way for personalized and targeted therapies, promoting significant advancements in cancer treatment.

Alpha-fetoprotein

Alpha-fetoprotein (AFP) is widely recognized as a biomarker for hepatocellular carcinoma (HCC). AFP is abnormally expressed in various classes of HCC, serving as a reference for specific pathological characteristics[10]. Consistently elevated AFP levels, above 100 ng/mL without a concomitant increase in alanine aminotransferase levels, have a sensitivity of 98.7% and specificity of 66.7% for predicting and identifying HCC[11].

Beyond diagnosis and prognosis, AFP is explored in various therapeutic strategies. Playing a crucial role in combination with models like the model for end-stage liver disease in assessing patients with cirrhosis, it allows for a comprehensive analysis of the patient’s preoperative status and potential outcomes. AFP use is integrated into models evaluating response to locoregional therapies and other factors, contributing to a more comprehensive and specific approach to HCC treatment[12,13]. Serving as a significant target for immunotherapy, AFP acts both as a biomarker for immune checkpoint inhibitors (ICIs) and as a potential tumor antigen, targets for vaccines, and therapies[11,12].

Beta-human chorionic gonadotropin

Beta-human chorionic gonadotropin (beta-hCG) is a biomarker with performance in the early detection and prognosis of various types of cancer. Primarily originating from syncytiotrophoblast tissue of the placenta during pregnancy, this hormonal glycoprotein is also expressed in certain non-trophoblastic neoplasms[14]. The study of its immunohistochemical expression in different grades of carcinomas, such as oral squamous cell carcinoma (SqCC), shows an association between beta-hCG positivity and tumor aggressiveness, especially in poorly differentiated carcinomas[15,16].

Measuring beta-hCG levels in saliva and urine samples presents innovative potential. This non-invasive and accessible approach highlights the biomarker’s versatility in clinical practice, providing a unique opportunity for monitoring and diagnosing oral SqCC patients[15]. The variation in beta-hCG levels across different carcinoma differentiation grades suggests that this biomarker may play a fundamental role in patient stratification and prognostic assessment, thus contributing to a more personalized and effective approach in the oncological context for the detection and clinical management of various neoplasms[16].

5-hydroxyindoleacetic acid

5-hydroxyindoleacetic acid (5-HIAA) is a biomarker used in the identification and monitoring of carcinoid tumors. As the main metabolite of serotonin, 5-HIAA is used as an indicator in 24-hour urine tests to measure serotonin levels[17,18]. This application is essential in identifying carcinoid tumors, a subcategory of neuroendocrine tumors that secrete serotonin[19].

The synthesis process of 5-HIAA from tryptophan is a crucial part of serotonin metabolism. Tryptophan, an amino acid, serves as the precursor to serotonin[19]. The first step of the conversion involves the hydroxylation of tryptophan, catalyzed by the enzyme tryptophan hydroxylase. This step is considered limiting, determining the overall rate of serotonin synthesis. The resulting molecule is 5-hydroxytryptophan, which is then decarboxylated by amino acid decarboxylase, such as pyridoxal phosphate as a coenzyme, to form serotonin[18,19].

Enzymatic deactivation of serotonin to produce 5-HIAA mainly occurs in the synaptic transmission process. Monoamine oxidase A is the enzyme responsible for catalyzing this reaction, converting serotonin into 5-HIAA in the synaptic space. The speed at which this occurs is an important consideration, as it influences the levels of serotonin available for neuronal communication[18]. In the liver, serotonin is generally metabolized before entering the general circulation, being converted into 5-HIAA. This hepatic process is essential for regulating serotonin levels in the body. Both 5-HIAA and serotonin are used as biomarkers in liver tumors[17,18].

Programmed death-1

Programmed death-1 (PD-1) is an inhibitory receptor induced in activated T cells. The binding of PD-1 to its ligand (PD-L1), PD-L1, through phosphatase activity is a key immune checkpoint that downregulates T cells, as shown in Figure 1, leading to reduced proliferation and production of essential cytokines[20]. PD-L1 can be found on tumor cells in various cancer types, aiding in immune evasion. Blocking the PD-1/PD-L1 interaction with anti-PD-1 antibodies allows T cells targeted to the tumor to effectively eliminate cancer cells. Several antibodies disrupting the PD-1 axis have entered clinical development, such as nivolumab, pidilizumab, curetech, and pembrolizumab[21]. Both nivolumab and pembrolizumab have demonstrated highly durable response rates with minimal toxicity in large phase I studies involving patients with advanced melanoma, non-small cell lung cancer, colorectal cancer, renal cell carcinoma, prostate cancer, and other solid tumors. In a study with melanoma patients who progressed with ipilimumab, nivolumab resulted in an overall response rate of 32% compared to 11% for chemotherapy. Another phase I clinical study of the anti-PD-1 antibody in 42 patients showed that 36% of patients with PD-L1-positive tumors exhibited an objective response, while none of the PD-L1-negative patients showed an objective response. It was reported that patients with low or negative PD-L1 expression in tumors have less or no clinical benefit from anti-PD-1/PD-L1 treatment compared to those with high PD-L1 expression[22].

Figure 1 Mechanism of programmed death-1/programmed death ligand 1 interaction. The T cell recognize the tumor antigen presented on major histocompatibility complex class I. Programmed death ligand 1 (PD-L1) on tumor cells interact with PD-1 on T-cells, leading to inhibition of T-cell receptor signaling pathway, downregulating T-cell responses. Blocking the PD-1/PD-L1 interaction with anti-PD-1 antibodies allows T cells targeted to the tumor to effectively eliminate cancer cells. The graphical abstract was generated using Servier Medical Art. MHC: Major histocompatibility complex; PDL1: Programmed death ligand 1; TCR: T-cell receptor; PD1: Programmed death 1.

Cytotoxic T lymphocyte-associated protein 4

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4) is a classical immune checkpoint molecule, acting as a CD28 homolog with a stronger binding affinity to its receptor B7-1 (CD80) or B7-2 (CD86). As the first available ICI, the humanized CTLA-4 antibody ipilimumab has revolutionized the clinical treatment of cancer, extending the survival from 10 years to metastatic melanoma. Combined treatment with PD-L1 and CTLA-4 antibodies could be a robust and effective response to future cancer treatments. Although the combined anti-CTLA-4/B7 and anti-PD1/PD-L1 therapy has shown promising clinical efficacy, only a small percentage of patients who received the therapy had prolonged survival. The regulation of PD-L1 and CTLA-4 expression significantly impacts treatment effectiveness. Understanding the in-depth mechanisms and interactions of PD-L1 and CTLA-4 could help identify patients with better responses to immunotherapy and promote their clinical care[21,23].

ICIs, as mentioned above, have shown long-lasting clinical responses in multiple cancers. However, ICI as single agents demonstrated low response rates in patients with various cancers[24]. Further research is needed to evaluate ICIs effectiveness and conduct more clinical trials in order to fully understand their potential impact on cancer prognosis and treatment. A combination therapy of ICIs can improve the response rate, but is associated with increased immune-related toxicity and treatment costs. Although the aforementioned techniques are promising tools in precision oncology, it is important to mention that many other tools are worthy of discussion, such as circulating tumor DNA and circulating tumor cells.

ADVANCES IN BIOINFORMATIC

Bioinformatics has emerged as an indispensable tool in oncology, fundamentally transforming the approach to the study and treatment of cancer. The rapid progress in analytical technology, genomic sequencing, and other molecular biology techniques has led to a better understanding and an increased volume of biological data. Additionally, it has facilitated the emergence of new tools for even more advanced treatments.

The correlation of certain types of cancers through gene expressions has become feasible thanks to bioinformatics. A notable example is the study conducted by the Shaanxi Chinese Medicine University, which investigated the relationship between esophageal cancer and iron mortality. The integrative analysis of gene expression profiles of esophageal cancer and motor genes associated with iron death revealed the identification of 9 genes, among which COD1 and YAP1 stood out as potential prognostic markers for esophageal cancer. The study, conducted in 2023, highlighted that reduced expression of YAP1 correlated with a low survival rate among patients[25].

Another highly promising field of bioinformatics in oncology is the application of artificial intelligence in deep learning, capable of learning deeply, interpreting, and analyzing a variety of data through supervised neural networks. This approach has proven useful in various aspects of oncology, such as histopathology, diagnostics, prognostics, and pharmacogenomics[26]. Deep learning has been applied in personalized medicine since 2018, with Food and Drug Administration-approved tools assisting doctors in tracking tumors based on magnetic resonance imaging and computed tomography scans of patients with liver and lung cancer[27].

In the specific context of molecular biology and personalized medicine, intelligences have also demonstrated excellent results in predicting colon cancer. With an average accuracy of 91.5%, it was possible to diagnose not only the presence of colon cancer but also its different stages. Using the least absolute shrinkage and selection operator algorithm, gene modules exhibiting a significant correlation with cancer were extracted and analyzed. Survival analysis was then conducted, followed by the combination of genes in the identified modules along with extracted characteristic genes. This process allowed for the extraction of genes for colon cancer diagnosis and comparisons with healthy controls, employing techniques such as random forest, support vector machines, and decision trees. Furthermore, for a more comprehensive approach, protein-protein interaction networks involving 289 genes were constructed. This step aimed to identify clusters of proteins relevant for a more in-depth survival analysis. These results highlight the effectiveness of the employed approaches, integrating various analytical techniques for a comprehensive and accurate understanding of colon cancer[28]. The convergence of advancements and innovative technologies in bioinformatics opens the doors to a new era of promising approaches to cancer treatment. These developments not only offer optimistic prospects for the future but represent significant benefits for both patients and healthcare professionals when these technologies are applied to analyze mapping data.

PRECISION MEDICINE AS A TOOL TO IDENTIFY THERAPEUTIC TARGETS

Precision medicine means the specific prescription of a particular treatment that is most suitable for an individual[29]. In this context, precision medicine has brought about an evolution in cancer treatment, moving from genealogical studies to a possible treatment based on the molecular characteristics of a tumor or its tumor environment[30]. Thus, the genealogical investigation of a patient with breast cancer, for example, has emerged as a crucial prognostic tool. This approach aims to determine whether a patient has a higher genetic risk of developing breast cancer, providing valuable insights for prevention and treatment strategies. Established studies support the importance of family history as a significant risk factor for the development of breast cancer[31]. Furthermore, recent advances in precision medicine have considerably expanded our understanding of the genetic aspects surrounding breast cancer, enabling a more personalized and effective approach in identifying specific therapeutic targets[32,33], representing a significant milestone in oncology.

As a result, currently, through the technique of immunohistochemistry, based on the expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2), breast tumors are predominantly classified into four molecular subtypes: Luminal A, luminal B, HER-2 overexpression, and basal-like tumors, consisting of triple-negative breast cancer[34]. Knowing this, the therapeutic approach can be personalized based on the molecular subtype of breast cancer. For instance, trastuzumab, a pioneer among drugs targeting HER-2 cells[35], is indicated for HER-2 positive patients, combined with chemotherapy. On the other hand, for triple-negative breast cancer patients, a combination of taxane and anthracycline is recommended[36]. Individuals diagnosed with breast cancer positive for estrogen receptors or progesterone receptors generally receive endocrine therapy as part of their treatment[37]. This therapy may involve prescribing an aromatase inhibitor (such as anastrozole, exemestane, or letrozole) or tamoxifen, with the choice being individualized based on the patient’s condition. Evidence shows that the decision between using tamoxifen or an aromatase inhibitor depends on whether the woman is premenopausal or postmenopausal[38].

Another highly prevalent neoplasm is lung cancer, which represents a significant challenge to public health, largely due to its primary risk factor: Smoking. Lung cancer is the leading cause of cancer-related mortality worldwide. Among different types of neoplasms, lung cancer has the highest incidence and is considered the most lethal among malignant tumors[39,40]. In this context, the pursuit of greater efficacy in prognosis, diagnosis, and drug treatment is currently the goal in precision oncology. Within different types of lung neoplasms, lung cancer is categorized into two main groups: Small cell carcinomas and non-small cell carcinomas, with the latter having subtypes such as adenocarcinoma and SqCC. It is crucial to know the specific nature of the neoplasm, as therapeutic protocols vary[41]. Thus, precision medicine, exemplified by comprehensive genomic profiling, emerges as a promising tool in clinical practice. This tool provides greater chances of directing therapies to specific genomic mutations, such as the epidermal growth factor receptor genomic mutation. A practical application of genomic profiling tests is in detecting this mutation, which can be done through next-generation sequencing. In this case, the drug gefitinib is recommended for treatment after the detection of the epidermal growth factor receptor mutation, a significant biomarker for lung cancer[42,43].

In this context, the technique called liquid biopsy emerges as a promising tool in precision oncology, offering a non-invasive and comprehensive approach to cancer diagnosis and treatment[44,45]. Liquid biopsy serves as an alternative capable of quantifying the response to a specific treatment and detecting emerging resistances in real-time, eliminating the need for conventional serial biopsies. This technique allows the analysis of circulating tumor DNA, circulating tumor cells, and tumor-derived exosomes, collectively referred to as “liquid biopsies”[46]. Growing evidence suggests that in the analysis of these exosomes, nanometer-sized extracellular vesicles circulating in the bloodstream, transferring molecular signals from tissue to tissue, it is possible to identify the presence of biological biomarkers for early-stage prostate or pancreatic cancer[47-49]. Therefore, this allows for an early initiation of treatment and consequently, the extension of survival. However, it is still emphasized in the literature that standardization of assays and analytical and clinical validation are necessary before the implementation of liquid biopsy in clinical routine[44,49].

Furthermore, it is essential to highlight the ongoing need for research and clinical trials to address relevant issues in oncological clinical practice. Research focusing on the identification of biomarkers as therapeutic targets, as well as the detection of possible genetic mutations associated with histopathological analysis, is crucial for the accurate diagnosis of neoplasms. In this context, the advancement of personalized medicine techniques is important tools to assist in the daily practice of oncological clinical care. To complement, Table 1 below presents information provided by precision medicine specific to some molecular subtypes of cancer, genomic mutations, biomarkers in exosomes, and treatment options[50-55].

Table 1 Various neoplasms and precision medicine findings associated with therapeutic choices: Identifying genes, receptors, and tumor biomarkers or pharmacological targets.

Ref.	Neoplasm	Findings through precision medicine	Conclusion
Terry et al[50], 2021	Clear-cell renal cell carcinoma	AXL gene	High levels of AXL in advanced renal tumors indicate a reduced response to anti-PD-1 treatment and rapid progression. Elevated expression of AXL, especially in cases with gene von hippel-lindau inactivation associated with PD-L1, is linked to poorer overall survival. AXL may act as a resistance factor to PD-1 blockade, highlighting the importance of assessing both expressions in the treatment of advanced clear cell renal carcinoma
Hoyer et al[51], 2021	Early stage of pancreatic cancer	SMAD4	The study identified genetic subgroups in patients with advanced pancreatic cancer, revealing different responses to treatment with gemcitabine ± erlotinib. Changes in gene SMAD4 emerged as a potential biomarker to predict the response to erlotinib, with clinical implications. Additional validations are needed, and the study suggests exploring combinations of EGFR inhibitors with immunotherapies in patients with SMAD4 alterations
Megías-Vericat et al[52], 2020	Acute myeloid leukemia	Mutation in the TP53 gene	A promising target in acute myeloid leukemia and myelodysplastic syndrome is the poor-prognosis in gene TP53 mutation (mTP53), currently treated with hypomethylating agents. The anti-cancer agent APR-246 is a novel drug that selectively induces apoptosis in mTP53 cells. Phase 1b/2 trial results suggested that APR-246 combined with azacitidine is well-tolerated and achieved a complete remission rate of 82% in 11 evaluable patients with mTP53 MDS/AML
Soares et al[53], 2021	Prostate cancer	MicroRNA biomarkers	In prostate cancer, there is a dysregulation in the expression of microRNAs, which can modulate the expression of oncogenes and tumor suppressor genes. In a study conducted by Soares et al[53], the potential of microRNAs to improve cancer diagnosis and staging was demonstrated. Based on the information collected from microRNAs, treatments can be categorized according to the radioresistance or radiosensitivity of the cancer, allowing for the determination of the most appropriate therapy. Radical prostatectomy is indicated in cases of radioresistant cancer, while radiotherapy is preferable for radiosensitive tumors
Xin et al[54], 2023	Colorectal cancer	Genetic impact on the incidence of colorectal cancer	In Xin et al[54], the authors conducted a data collection to investigate the influence of genetic architecture on colorectal cancer in different populations. This genetic influence, associated with a positive outcome in colorectal cancer development, is referred to as PRS. Considering that the genetic factor contributes to 7%-16% of the heritability for colorectal cancer development in European and East Asian populations, the crucial importance of collecting information on genetic variants for colorectal cancer screening is emphasized, especially in patients with high PRS. Knowledge of the patient’s PRS makes it feasible to develop personalized prevention strategies
Hill et al[55], 2020	Mantle cell lymphoma	Genes ATM, IGHV, TP53, RB1, CDKN2A, and CCND	Mantle cell lymphoma is a rare and incurable subtype of non-Hodgkin lymphoma. In this meta-analysis, patient data regarding prevalent mutations in MCL provide additional evidence highlighting potential genes for prognosis and precision treatments based on each patient’s unique tumor profile. Potential prognostic targets identified through cytogenetics include the genes ATM, IGHV, TP53, RB1, CDKN2A, and CCND, all found at higher prevalence in the studied patients who already had MCL. Therefore, understanding somatic mutations in MCL can assist in patient stratification based on prognostic risk

AXL: AXL receptor tyrosine kinase; SMAD4: Mothers against decapentaplegic homolog 4; EGFR: Epidermal growth factor receptor; AML: Myeloid leukemia; MDS: Myelodysplastic syndrome; PRS: Polygenic risk scores; MCL: Mantle cell lymphoma; IGHV: Immunoglobulin heavy chain.

LIMITATIONS AND CHALLENGES

It is known that the search for unconventional tools for cancer treatment has been expanding along with technological advances. Genetic mapping is a promising source of information to direct and even assist in cancer diagnosis. However, despite being a high-precision process, some limitations imply the use of these techniques. The high cost of genetic mapping techniques is a challenge that prevents their access. For example, the cost of applying precision medicine per sick individual can range from $20000 in European countries to $200000 in the United States, which results in limitations for low-income individuals or in regions with fewer resources[56]. Another limiting factor is the heterogeneity presented by cancer cells, which demonstrates intercellular variability that implies both in the treatment, since the pharmaceutical response may be ineffective, and in the sensitivity of the results obtained, since cancer cells have polymorphism, that is, may present different profiles, which makes it difficult to identify genes related to this disease[57].

Furthermore, as genetic mapping and other techniques grow, ethical issues linked to human integrity increase proportionately. One of the problems that raises concerns is the misuse of these techniques since they can be used for means other than diagnosis and gene therapy. Methods used in gene therapy, such as the use of viral vectors as carriers, are related to immunogenicity, which can pose risks to human health[58]. Therefore, the development of new approaches, expansion, and innovation of genetic mapping techniques is necessary so that these challenges can be overcome, ensuring that these tools are used more effectively in the diagnosis and treatment of cancer.

CONCLUSION

It is undeniable that molecular approaches play a fundamental role in the field of clinical oncology. These applications encompass the use of drugs, biomarkers, and bioinformatics, which, when combined, have the potential to guide therapeutic choices for patients and provide more accurate and timely prognosis for treatment decisions. Furthermore, the incorporation of artificial intelligence into clinical methodology significantly accelerates this process, allowing for efficient and personalized analysis based on the patient’s sequenced gene information.

Despite the promising perspectives offered by these techniques, their implementation needs more studies to comprise the efficiency and has various limitations. The main hurdle lies in the financial aspect, as the involved techniques incur high costs as treatments become more personalized. This limits access, particularly for low-income populations and regions with limited resources. In addition to the financial challenge, the heterogeneity of cancer cells poses another significant obstacle. The distinct characteristics of cellular profiles make effective treatment more challenging. Alongside the financial and biological aspects limiting technology implementation, ethical issues also arise. Genetic sequencing provides personal patient information, raising concerns about the non-therapeutic use of this data.

Therefore, addressing these complexities requires broad cooperation across various sectors, from healthcare professionals and researchers to lawmakers and society at large. Only through collaborative efforts, guided by ethics, equity, and scientific advancement, can we overcome challenges and ensure that the benefits of molecular biology technologies are shared fairly and accessibly. This will lead to substantial advancements in cancer care and promote a more inclusive and healthier future for all.