❌

Normal view

Systematic Identification of Molecular Signatures Dictating Therapeutic Effects of Clinically First-Line Chemotherapy Regimens for Human Gastric Cancer Patients Based on Organoid Model

MedComm (2020). 2026 Mar 2;7(3):e70656. doi: 10.1002/mco2.70656. eCollection 2026 Mar.

ABSTRACT

Chemotherapy is the mainstay in the treatment of advanced gastric cancer (GC); yet, GC showed diverse responses to first-line chemotherapy regimens and the underlying molecular basis is still not clear. Here, we established a system that combined organoid-based chemotherapy regimen screening and transcriptome-based evaluation to identify underlying molecular signatures of different responses to chemotherapy. We generated 19 GC patient-derived organoids (PDOs) from surgically resected specimens with corresponding histological characteristics of parent tumors and tested all of the five most commonly used first-line chemotherapy regimens. Based on the treatment responses, PDOs were classified into double-sensitive, single-sensitive, and not-sensitive groups. PDOs that responded well to chemotherapy presented high expression levels of the P53 pathway genes and low expression levels of cell proliferative activity genes. Furthermore, the chemotherapy-based tumor classification of GC was established. The GC tumor classification was verified by multi-omics features from the TCGA dataset and public drug response datasets. In conclusion, this study systematically evaluated clinical chemotherapy regimens for GC and identified chemotherapy response-associated molecular signatures based on human GC organoids, which are beneficial to the precise treatments of GC.

PMID:41782964 | PMC:PMC12954136 | DOI:10.1002/mco2.70656

Cancer-Associated Fibroblasts: Heterogeneity, Cancer Pathogenesis, and Therapeutic Targets

MedComm (2020). 2025 Jul 11;6(7):e70292. doi: 10.1002/mco2.70292. eCollection 2025 Jul.

ABSTRACT

Cancer-associated fibroblasts (CAFs) are functionally diverse stromal regulators that orchestrate tumor progression, metastasis, and therapy resistance through dynamic crosstalk within the tumor microenvironment (TME). Recent advances in single-cell multiomics and spatial transcriptomics have identified conserved CAF subtypes with distinct molecular signatures, spatial distributions, and context-dependent roles, highlighting their dual capacity to promote immunosuppression or restrain tumor growth. However, therapeutic strategies struggle to reconcile this functional duality, hindering clinical translation. This review systematically categorizes CAF subtypes by origin, biomarkers, and TME-specific functions, focusing on their roles in chemoresistance, maintenance of stemness, and formation of immunosuppressive niches. We evaluate emerging targeting approaches, including selective depletion of tumor-promoting subsets (e.g., fibroblast activation protein+ CAFs), epigenetic reprogramming toward antitumor phenotypes, and inhibition of CXCL12/CXCR4 or transforming growth factor-beta signaling pathways. Spatial multiomics-driven combinatorial therapies, such as the synergistic use of CAFs and immune checkpoint inhibitors, are highlighted as strategies to overcome microenvironment-driven resistance. By integrating CAF biology with translational advances, this work provides a roadmap for developing subtype-specific biomarkers and precision stromal therapies, directly informing efforts to disrupt tumor-stroma coevolution. Key concepts include spatial transcriptomics, stromal reprogramming, and tumor-stroma coevolution, offering actionable insights for both mechanistic research and clinical innovation.

PMID:40656546 | PMC:PMC12246558 | DOI:10.1002/mco2.70292

Detection of ovarian cancer using plasma cell-free DNA methylomes

Ovarian cancer (OC) is a highly lethal gynecologic cancer, and it is hard to diagnose at an early stage. Clinically, there are no ovarian cancer-specific markers for early detection. Here, we demonstrate the u...
❌