This suggestive pattern converges with a phase II trial of azacitidine/carboplatin priming before anti-programmed death-ligand 1 rechallenge in ICB-resistant melanoma, supporting prospective evaluation.
Abstract
Immune-cold melanomas respond poorly to immune checkpoint blockade (ICB). We assessed whether RNA-seq-based immune subtyping and connectivity mapping could nominate repurposable compounds to shift immune-depleted melanoma toward an immune-enriched phenotype. Using RNA-seq from 432 The Cancer Genome Atlas Skin Cutaneous Melanoma cases, we assigned published molecular functional portrait subtypes and compared depleted (D, n = 169) with combined immune-enriched (IE + IE/F, n = 184) subtypes using limma-voom. The resulting 300-up/300-down signature underwent Library of Integrated Network-based Cellular Signatures L1000 connectivity mapping, with compound-level aggregation and mechanism-of-action annotation. The pipeline was rerun on two stratified split-half folds. Canonical cytotoxic and antigen-presentation genes (CD8A, PDCD1, CXCL9, CXCL10, CD3D, GZMB, PRF1) were depleted in D, validating the contrast. Raw connectivity-mapping hits were dominated by generic cytotoxic-stress compounds. After aggregation and filtering, DNA methyltransferase (DNMT) inhibitors showed the most consistent positive pattern; fdcyd, azacitidine, and RG-108, but not decitabine, were robust to sample-type sensitivity analysis. Class enrichment was not significant after correction [false discovery rate (FDR) q = 0.126]. Indoleamine 2,3-dioxygenase inhibitors trended negative (FDR q = 0.095), and mitogen-activated protein kinase kinase inhibitors showed no class-level pattern (FDR q = 0.698). Across both folds, all seven canonical genes replicated and all four DNMT inhibitors retained above-median ranks, but the cold-elevated signature module was markedly less stable than the hot-elevated module (25.7 vs. 88.7% overlap). This suggestive pattern converges with a phase II trial of azacitidine/carboplatin priming before anti-programmed death-ligand 1 rechallenge in ICB-resistant melanoma, supporting prospective evaluation.
ABSTRACT Aims This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high‐risk neuroblastoma, elucidating key mechanisms underlying immune evasion. Methods We performed an integrated multi‐omics analysis of bulk RNA‐seq (n = 721), single‐cell RNA‐se...
Jia-Jian Hu, Wenjuan Kang, Jiatong Hu et al.· CNS Neuroscience & Therapeut...· 0 citations
Effective T cell–based immunotherapies require functional receptors that can be engineered and redeployed to recognize tumor-restricted antigens. Noncanonical peptides arising from transcription outside annotated protein-coding regions expand the antigenic landscape of cancer; however, systematic strategies to biologic...
T. Hulen, M. D. Crowther, Luke Schuster et al.· Signal Transduction and Targ...· 0 citations
The CMLS translates spatial immune-exclusion dynamics into a quantifiable metric, outperforming tumor mutational burden in predicting ICB benefits, providing a robust tool for patient stratification in ccRCC.
Zhe Wang, Ying-Jian Wang, Jia-Yi Zhang et al.· Human Genomics· 0 citations
Background: Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality, and responses to immune checkpoint blockade are often limited. Casein kinase 2 beta (CK2beta), encoded by CSNK2B, has established tumor-intrinsic functions, but its relationship with immune states in HCC remains unclear. Metho...
Renal cell carcinoma (RCC) is amongst the most immune-infiltrated solid tumours, but only a small subset of patients achieves durable response to immune checkpoint blockade therapy. Efforts to characterize the immune microenvironment and molecular regulators responsible for treatment responses have explored numerous fa...
Jennifer Q. Pfeil, Shirley Hui, Daniel Stueckmann et al.· bioRxiv· 0 citations
GPRC5A perturbation affected CRC proliferation, migration/invasion, EMT, and xenograft tumorigenicity, supporting a functionally important role in the tested models.
Wei-Chun Tang, Peng-Chen Xu, Sheng-Li Wang et al.· Journal of Translational Med...· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.