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This review provides a comprehensive overview of the evolving role of minimal residual disease (MRD) for patients with Colon Cancer (CC). Currently, the standard of care for patients with non-metastatic CC is adjuvant chemotherapy (ACT) for all patients with stage III and high-risk stage II CC following surgical intervention. Despite a 5–20% improvement in long-term survival outcomes, this approach also results in a significant proportion of patients receiving ACT without any therapeutic benefit and being unnecessarily exposed to the risks of secondary side effects. This underscores an unmet clinical need for more precise stratification to distinguish patients who necessitate ACT from those who can be treated with surgery alone. By employing liquid biopsy, it is possible to discern MRD enabling the categorization of patients as MRD-positive or MRD-negative, potentially revolutionizing the management of ACT. This review aimed to examine the heterogeneity of methodologies currently available for MRD detection, encompassing the state-of-the-art technologies, their respective advantages, limitations, and the technological challenges and multi-omic approaches that can be utilized to enhance assay performance. Furthermore, a discussion was held regarding the clinical trials that employ an MRD assay focusing on the heterogeneity of the assays used. These differences in methodology, target selection, and performance risk producing inconsistent results that may not solely reflect biological/clinical differences but may be the consequence of the preferential use of particular products in studies conducted in different countries. Standardization and harmonization of MRD assays will be crucial to ensure the liquid revolution delivers reliable and clinically actionable outcomes for patients. [ABSTRACT FROM AUTHOR]

Simple Summary: This review provides a comprehensive overview of the current knowledge on mutational signatures in colorectal cancer (CRC), highlighting their potential clinical applications. It discusses the challenges and limitations in translating these analyses into clinical practice and proposes strategies to overcome these obstacles. Additionally, it provides insights into future directions and emerging proof-of-concept studies that highlight the translational potential of mutational signature analysis in improving patient care and outcomes in CRC. A multitude of exogenous and endogenous processes have the potential to result in DNA damage. While the repair mechanisms are typically capable of correcting this damage, errors in the repair process can result in mutations. The findings of research conducted in 2012 indicate that mutations do not occur randomly but rather follow specific patterns that can be attributed to known or inferred mutational processes. The process of mutational signature analysis allows for the inference of the predominant mutational process for a given cancer sample, with significant potential for clinical applications. A deeper comprehension of these mutational signatures in CRC could facilitate enhanced prevention strategies, facilitate the comprehension of genotoxic drug activity, predict responses to personalized treatments, and, in the future, inform the development of targeted therapies in the context of precision oncology. The efforts of numerous researchers have led to the identification of several mutational signatures, which can be categorized into different mutational signature references. In CRC, distinct mutational signatures are identified as correlating with mismatch repair deficiency, polymerase mutations, and chemotherapy treatment. In this context, a mutational signature analysis offers considerable potential for enhancing minimal residual disease (MRD) tests in stage II (high-risk) and stage III CRC post-surgery, stratifying CRC based on the impacts of genetic and epigenetic alterations for precision oncology, identifying potential therapeutic vulnerabilities, and evaluating drug efficacy and guiding therapy, as illustrated in a proof-of-concept clinical trial. [ABSTRACT FROM AUTHOR]

Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures. [ABSTRACT FROM AUTHOR]