Selected Articles from This Issue

Despite the prevalence of the BCOR mutation in retinoblastoma, its function is not well characterized. To gain a comprehensive understanding of the interactome and role of BCOR mutations, Zhang and colleagues employed high-throughput techniques and in vitro assays. Immunoprecipitation, mass spectrometry, and pathway enrichment analysis of BCOR wildtype retinoblastoma cell lines revealed interaction between BCOR and noncanonical polycomb repressive complex 1.1 components RING1B and KDM2B, as well as association with mitosis and cell cycle pathways. BCOR enrichment at loci marked by histone markers H3K27ac and H3K27me3 was observed through ChIP-sequencing. Additional Cluster analysis found colocalization of BCOR and activating histone marks with KDM2B and RING1B in the active chromatin state. RNA sequencing and GSEA of BCOR knockdown cells showed that BCOR may function as a transcriptional regulator of genes that are associated with the cell cycle and cytoskeleton. Proliferation assays of BCOR-deficient cells also had reduced proliferative capabilities compared to the control. Pathway enrichment of upregulated genes in BCOR knockdown cells further found BCOR gene targets associated with hypoxia, metabolism, and neuronal processing. ChIP sequencing and RNA sequencing in BCOR wild-type and mutant retinoblastoma cell lines revealed BCOR-dependent suppression of ESRRG activity under normoxia and hypoxia. Together, this study demonstrates the function of BCOR and identifies the components of BCOR-mediated epigenetic modulation of retinoblastoma progression.The temporal role of proteins in cancer development and progression remains poorly understood. In their study, Kirk and colleagues evaluated the role of SMARCA4 in small cell lung cancer (SCLC) using mouse models that recapitulate the neuroendocrine subtype of SCLC. Smarca4 knockout in both RPR2 and RPM mice had significantly reduced tumor burden. In addition, inhibition of SMARCA4 diminished the colony-forming capacity of precancerous immortalized neuroendocrine cells. These Smarca4-deficient mice and preSCs exhibited decreased expression of neuroendocrine markers CGRP and ASCL1 and lacked characteristic neuroendocrine morphology. These findings suggest the necessity of SMARCA4 for SCLC tumor initiation and development. However, this idea seems to contrast other observations, including the spontaneous and gradual loss of SMARCA4 in primary tumor cells in culture and an inverse relationship between SMARCA4 expression and SCLC progression in the transcriptome of SCLC PDXs. To address this discrepancy, the authors tested a potential role for SMARCA4 specific to late-stage tumor progression. Acute knockdown of SMARCA4 increased the tumorigenic potential of tumor cells in an allograft model. Notably, this effect was associated with loss of NK/T cell-interacting ligand PVR rather than increased proliferative capacity. Overall, this study demonstrates the importance of interrogating the temporal function of cancer-associated proteins and suggests that SMARCA4 has a dual role in SCLC development and malignant progression.Systematic interrogation of transcriptomic datasets is a vital aspect of cancer research, but there are limited user-friendly tools that allow unbiased, cross-cancer evaluation of gene-level prognostic relevance. To address this, Cao and colleagues developed CGPA, a pan-cancer online tool for comprehensive prognostic biomarker discovery. CGPA has three modules tailored to a user-specific need, including single-gene prognostic discovery, gene-pair interactions, and multigene panel discovery. The single-gene module uses a hazard-ratio ranked forest plot, Kaplan–Meier plots, and STRING protein–protein interaction network annotations to demonstrate the prognostic significance of a queried gene across multiple cancer types. They introduce univariable missed-opportunity prognostic (UMOP) genes, a newly defined category of biomarkers that are undetected by univariable Cox analysis but become significant after adjusting for clinical and tumor-related covariates. Analysis of gene-hallmark interactions including frequently mutated genes, CNV, TMB, and immune scores is also integrated. The gene-pair module uses combined Kaplan-Meier plots and bivariable Cox regression analyses to assess the prognostic contribution of two user-designated genes. By integrating immune checkpoint inhibitor (ICI) datasets, CGPA enables cross-context survival interrogation in immunotherapy-treated cohorts, extending its translational impact.