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Cancers
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Novel Computational Approaches for Molecular Target Discovery in Colorectal Cancer
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Novel Computational Approaches for Molecular Target Discovery in Colorectal Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 5948

Special Issue Editor

Dr. Giovanni Crisafulli

E-Mail Website
Guest Editor
IFOM ETS—The AIRC Institute of Molecular Oncology, Milan, Italy
Interests: mutations; tumor heterogeneity; genetics; bioinformatics; clonal evolution; target therapy; secondary resistance; tumor burden; next-generation sequencing; liquid biopsy; colorectal cancers; clinical trial; immunotherapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Colorectal cancer (CRC) remains a global health challenge, ranking as the third-most prevalent and lethal cancer worldwide. While progress in CRC incidence and mortality reduction has been made through screening programs, lifestyle interventions, and advancements in diagnostic and therapeutic modalities, there is still a pressing need for novel and more effective treatment strategies. Technology plays a pivotal role in this context, enabling physicians to enhance diagnostic accuracy, patient monitoring, and the development of individualized, less invasive therapies.

Moreover, technological advancements have empowered the accumulation of vast genetic datasets, which can be harnessed using innovative bioinformatic approaches to identify new therapeutic targets and refine patient stratification for personalized care. We dedicate this Special Issue to the exploration of novel genetic targets through advanced bioinformatic methods, aiming to revolutionize patient stratification and potentially harboring clinical translation.

Original articles are welcome as well as methodology reports related to recently published groundbreaking publications addressing the specific field of this Special Issue.

Dr. Giovanni Crisafulli
Guest Editor

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Keywords

  • colorectal cancer
  • genetics
  • bioinformatics
  • therapeutic targets
  • cancer evolution
  • personalized medicine
  • patient stratification
  • technological advancements
  • precision oncology
  • big data
  • computational approach

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Published Papers (2 papers)

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27 pages, 2824 KB  
Article
Exploring the Impact of DNA Methylation on Gene Expression in CRC: A Computational Approach for Identifying Epigenetically Regulated Genes in Multi-Omic Datasets
by Andrei Stefan Blindu, Silvia Berardelli, Federica De Paoli, Federico Manai, Rossella Tricarico, Susanna Zucca and Paolo Magni
Cancers 2026, 18(2), 211; https://doi.org/10.3390/cancers18020211 - 9 Jan 2026
Viewed by 720
Abstract
Background/Objectives: DNA methylation is a key epigenetic process that regulates gene expression and is often disrupted in colorectal cancer (CRC). Aberrant methylation of promoter CpG islands can silence tumor suppressor genes and drive tumorigenesis. A subset of CRCs exhibits the CpG Island Methylator [...] Read more.
Background/Objectives: DNA methylation is a key epigenetic process that regulates gene expression and is often disrupted in colorectal cancer (CRC). Aberrant methylation of promoter CpG islands can silence tumor suppressor genes and drive tumorigenesis. A subset of CRCs exhibits the CpG Island Methylator Phenotype (CIMP), characterized by widespread hypermethylation and distinct clinical outcomes. Identifying genes whose expression is epigenetically regulated by methylation is important for prioritizing candidate biomarkers and therapeutic targets in CRC. Methods: We developed and compared a series of computational approaches to identify genes whose expression is regulated by DNA methylation in The Cancer Genome Atlas (TCGA) cohort of Colon Adenocarcinoma (COAD) patients. Samples were stratified according to their CpG Island Methylator Phenotype (CIMP) level to capture distinct epigenetic subgroups. The proposed framework integrates methylation and transcriptomic data to systematically detect methylation–expression associations indicative of epigenetic regulation. Results: The best-performing method identified gene sets strongly associated with promoter methylation–expression relationships and enriched for pathways relevant to colorectal cancer progression and patient stratification. To evaluate the robustness and transferability of the approach, it was further validated on independent datasets, including Stomach Adenocarcinoma (STAD), Glioblastoma Multiforme (GBM), and Mesothelioma (MESO), supporting its robustness and potential generalizability across multiple tumor types. Conclusions: Our study highlights the potential of computational pipelines to uncover epigenetically regulated genes in colorectal cancer. The identified candidate genes provide a hypothesis-generating foundation for refining molecular stratification and guiding future studies aimed at epigenetic biomarker discovery and therapeutic hypothesis development. Full article
(This article belongs to the Special Issue Novel Computational Approaches for Molecular Target Discovery in Colorectal Cancer)
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Review

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13 pages, 1408 KB  
Review
Mutational Signatures in Colorectal Cancer: Translational Insights, Clinical Applications, and Limitations
by Giovanni Crisafulli
Cancers 2024, 16(17), 2956; https://doi.org/10.3390/cancers16172956 - 24 Aug 2024
Cited by 6 | Viewed by 4447
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Novel Computational Approaches for Molecular Target Discovery in Colorectal Cancer)
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