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Cancers
Special Issues
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: 30 December 2024 | Viewed by 1865

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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 (1 paper)

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Review

13 pages, 1408 KiB  
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
Viewed by 1565
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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