Ching, C. Y. | Search bioRxiv

bioRxiv2026

The Y chromosome gene KDM5D restrains CD8+ T cell antitumor immunity through TCR and cholesterol-exhaustion programs

Sex differences in immunity shape cancer risk, autoimmunity, and responses to immunotherapy, yet the sex-chromosome genes that regulate antitumor T cell function remain incompletely defined. Here, we identify the Y chromosome-encoded KDM5D histone demethylase as a male-specific suppressor of CD8+ T cell antitumor immunity. In murine colorectal cancer (CRC) models, male CD8+ T cells displayed reduced cytokine production, proliferation, cytotoxicity, TCR{beta} abundance, and proximal TCR signaling relative to female CD8+ T cells. CRISPR-RNP-mediated KDM5D depletion in male CD8+ T cells enhanced effector function, increased TCR{beta} expression, augmented TCR signaling, and improved tumor control after adoptive transfer. Transcriptomic and functional analyses further linked KDM5D to cholesterol biosynthesis and exhaustion-associated programs, with KDM5D depletion reducing SREBP2/XBP1-associated cholesterol and exhaustion signatures. Correspondingly, human CRC single-cell analyses supported the clinical relevance of this axis, showing enrichment of exhausted and cholesterol-associated CD8+ T cell states in male tumors. Pharmacologic inhibition of cholesterol biosynthesis with lovastatin partially attenuated select exhaustion-associated markers in male CD8+ T cells and delayed tumor growth in vivo. Together, these findings define KDM5D as a sex chromosome-encoded regulator of male CD8+ T cell dysfunction and point to cholesterol-exhaustion programs as a potential therapeutic vulnerability in male CRC.

cancer biology↗

bioRxiv2026

Arborist: Prioritizing Bulk DNA Inferred Tumor Phylogenies via Low-pass Single-cell DNA Sequencing Data

Cancer arises from an evolutionary process that can be reconstructed from DNA sequencing and modeled by tumor phylogenies. High coverage bulk DNA sequencing (bulk DNA-seq) is widely available, but tumor phylogeny inference requires deconvolution, often resulting in non-uniqueness in the solution space. Single-cell DNA sequencing (scDNA-seq) holds potential to yield higher resolution tumor phylogenies, but the sparsity of emerging low-pass sequencing technologies poses challenges for the study of single-nucleotide variants. Increasing availability of data sequenced with both modalities provides an opportunity to capitalize on the advantages of these technologies. While inference methods exist for bulk DNA-seq and for low-pass scDNA-seq, no joint inference methods currently exist. As a first step, we propose a method named ARBORIST that prioritizes tumor phylogenies inferred via bulk DNA-seq using low-pass scDNA-seq data. ARBORIST takes as input a candidate set of trees with corresponding SNV clustering, along with variant and total read count data from scDNA-seq and uses variational inference to approximate a lower bound on the marginal likelihood of each tree in the candidate set. On simulated data, matching characteristics of current scDNA-seq data, ARBORIST outperforms both bulk and low-pass single-cell reconstruction methods. On a biological dataset, ARBORIST conclusively resolves the evolutionary relationship between different SNV clusters on a malignant peripheral nerve sheath tumor, which is supported by orthogonal validation via a proxy for copy number. ARBORIST provides a principled framework for integrating bulk DNA-seq and low-pass scDNA-seq data, improving confidence in tumor phylogeny reconstruction. Availabilityhttps://github.com/VanLoo-lab/Arborist

bioinformatics↗