Arul M. Chinnaiyan

This study shows lactate epigenetically regulates cell states in H3K27M diffuse midline gliomas by modifying histones, and targeting CBP/p300 reduces tumor heterogeneity and improves preclinical outcomes.

This study modifies a molecule to create two variants with different target selectivity, showing how small structural changes can control degradation activity.

This paper identifies a druggable chromatin vulnerability in suppressive neutrophils that can restore antitumor immunity through mSWI/SNF antagonists.

A bifunctional AR–p300/CBP molecule, DALTAC-1, forces a non-native contact between AR and p300 domains, silences AR enhancers and regresses AR-driven prostate tumors in mice while sparing AR-negative lines.

This study identifies a stress-lipid kinase axis in NEPC driven by PIKfyve, revealing a synthetic vulnerability between PIKfyve and FASN that can be exploited for therapeutic targeting.

This study identifies NNMT as a tumor suppressor in prostate cancer that regulates SAM availability, mTORC1 signaling, and chromatin methylation, revealing a therapeutic strategy using dietary methionine restriction and mTORC1 inhibition.

This study identifies genomic drivers of progression and therapeutic outcomes in mCRPC and develops a multi-omic classifier to predict patient survival across multiple therapies.

This paper harmonizes single-cell RNA-seq data from 17 studies to create a comprehensive atlas of human prostate cancer and benign tissues, identifying 17 cell types and providing standardized resources for analysis.

This paper identifies LINC00941 as an oncogenic lncRNA regulated by FOSL1 in lung cancer, showing its dual-compartment role in sustaining tumor growth through SAM68 and QKI interactions.

This study identifies MMP14 as essential for cancer cell invasion through ECM barriers, showing that its proteolytic activity is required for maintaining nuclear integrity and facilitating invasion in both synthetic and human tissue models.

This study shows that degrading p300/CBP in prostate cancer suppresses tumor growth more effectively than inhibiting their activity, highlighting their role in maintaining the active AR enhanceosome.

This study maps the mouse prostate's cellular organization and identifies key determinants of castration resistance using single-cell and spatial transcriptomics.

This study identifies PCAHIT, a lncRNA linked to poor outcomes in prostate cancer, showing it promotes aggressive phenotypes by affecting steroid biosynthesis and immune response.

This study identifies PIKfyve as a targetable vulnerability in pancreatic cancer by showing its role in lipid metabolism and synthetic lethality with KRAS-MAPK inhibitors.

This study identifies lineage-specific transcription factor profiles in prostate cancer progression, revealing dynamic shifts during NE transdifferentiation and proposing a three-phase model.

This paper uses spatial transcriptomics to identify low-risk and high-risk expression programs in IPMN that correlate with exocrine and basal-like PDAC signatures, improving risk stratification.

This study shows CDK12 loss drives prostate cancer development and identifies CDK13 as a therapeutic target through paralog-based synthetic lethality in CDK12-mutant tumors.

This study shows EphA2 overexpression and loss of its ligands in prostate cancer promote bone metastasis through noncanonical signaling in a ligand-deficient bone microenvironment.

This study identifies NSD2 as a critical component of the AR neo-enhanceosome in prostate cancer, showing its role in AR enhancer circuitry and tumor progression.

This study shows that PIKfyve inhibition enhances dendritic cell function and improves immunotherapy efficacy in tumor models.

This paper develops an orally bioavailable PROTAC degrader of mSWI/SNF ATPases for prostate cancer and identifies resistance mechanisms through long-term treatment.

The paper tracks RNA localization to processing bodies using single-molecule microscopy and shows that RNA functionality influences their dynamic recruitment to PBs.

MechRNA predicts lncRNA mechanisms by integrating RNA-RNA and RNA-protein interaction predictions to identify potential targets and mechanisms for cancer-related lncRNAs.