Precision Oncology: Targeting Molecular Subtypes in Cancer Therapy

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: 30 October 2025 | Viewed by 613

Special Issue Editors


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Guest Editor
1. Department of Internal Medicine (Clinical Oncology), Yamagata Prefectural Shinjo Hospital, 720-1 Kanazawa, Shinjo 996-8585, Japan
2. Yamagata Hereditary Tumor Research Center, Yamagata University, 1-4-12 Kojirakawa, Yamagata 990-8560, Japan
3. Department of Clinical Oncology, School of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan
4. Department of Molecular Cancer Science, Yamagata University, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan
Interests: drug resistance; cancer stem cells; drug repositioning; cancer genomic testing; germline mutation; genetic cancer; genetic counseling

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Guest Editor
Department of Pharmacology, Yamagata University, 2-2-2 Iida-Nishi, Yamagata 990-9585, Japan
Interests: pharmaceutical sciences; pharmacokinetics; drug development; drug metabolic enzymes; drug transporters

Special Issue Information

Dear Colleagues,

Precision oncology has revolutionized cancer treatment by identifying specific molecular alterations that drive tumor growth and developing targeted therapies against these alterations. This shift from the traditional approach to personalized medicine has led to remarkable improvements in patient outcomes across multiple cancer types.

This Special Issue, entitled "Precision Oncology: Targeting Molecular Subtypes in Cancer Therapy", aims to explore current challenges and future directions in molecular subtyping for cancer treatment. We seek to highlight innovative approaches for identifying and targeting specific molecular subtypes, overcoming resistance mechanisms, and implementing precision diagnostics in clinical practice.

Recent technological advances in genomic profiling, liquid biopsies, and artificial intelligence have dramatically enhanced our ability to identify actionable molecular alterations and monitor treatment response in real time. These developments create unprecedented opportunities for refining treatment selection and developing novel therapeutic strategies for molecularly defined patient subgroups.

We invite the submission of original research articles and comprehensive reviews addressing molecular subtyping methodologies, biomarker discovery, resistance mechanisms, multi-omics integration, emerging diagnostic technologies, and innovative clinical trial designs for molecular subtypes in oncology.

Dr. Shuhei Suzuki
Dr. Jiro Ogura
Guest Editors

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Keywords

  • cancer chemotherapy
  • cancer genomic profiling test
  • next-generation sequencing
  • genetic variants
  • molecular targeted therapy
  • molecular tumor board
  • liquid biopsy

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Published Papers (1 paper)

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Research

17 pages, 6308 KiB  
Article
PARP Inhibition in Colorectal Cancer—A Comparison of Potential Predictive Biomarkers for Therapy
by Abdulaziz Alfahed
Pharmaceuticals 2025, 18(6), 905; https://doi.org/10.3390/ph18060905 - 17 Jun 2025
Viewed by 459
Abstract
Background/Objectives: PARP inhibitors (PARPis) currently play frontline roles in the management of prostate, pancreatic, ovarian and breast cancers, but their roles in colorectal cancer (CRC) management have yet to be clarified. Importantly, the specific predictive biomarkers for PARPis in CRC are still [...] Read more.
Background/Objectives: PARP inhibitors (PARPis) currently play frontline roles in the management of prostate, pancreatic, ovarian and breast cancers, but their roles in colorectal cancer (CRC) management have yet to be clarified. Importantly, the specific predictive biomarkers for PARPis in CRC are still matters of investigations. The aim of this study is to identify the potential predictive biomarkers of PARP inhibition in CRC. Methods: Gene set enrichment analyses (GSEAs) and drug ontology enrichment analyses (DOEAs) of PARPi response gene sets were applied as the surrogates of PARPi response to two CRC cohorts in order to compare the predictive capacities of TP53 mutation status, MSI status, as well as PARP1 and PARP2 expression for PARP inhibition to those of a homologous repair deficiency surrogate, and large-scale state transition (LST). Differential enrichment score (ES) and ontology enrichment (OE) analyses were used to interrogate the differential correlation of the predictive biomarkers with PARPi response, relative to LST. Results: The results demonstrated that LST-low, rather than LST-high, CRC subsets exhibited an enrichment of the PARPi response, in contrast to what has been established for other cancers. Furthermore, CRC subsets with wild-type TP53, positive MSI, as well as high PARP1 and PARP2 expression exhibited an enrichment of the PARPi response gene sets. Moreover, there was no differential enrichment of the PARPi response between LST and each of the MSI statuses, PARP1 expression and PARP2 expression. Furthermore, the preliminary differential enrichment observed between the LST-based and TP53 mutation status-based PARPi responses could not be validated with further testing. Conclusions: MSI status, TP53 mutation status as well as PARP1 and PARP2 expression may be substitutes for low LST as predictive biomarkers of PARPi response in CRC. Full article
(This article belongs to the Special Issue Precision Oncology: Targeting Molecular Subtypes in Cancer Therapy)
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