Biology subjects

Chan, I. S.

Publications and source records attributed to Chan, I. S..

4 recordsLinked to original sources

bioRxiv2026

Tumor control of lysosomal acidification promotes lipoprotein assimilationand ferroptosis resistance

Lysosomes are acidic organelles that fuel cancer progression by facilitating nutrient acquisition and metabolic adaptation, yet the determinants through which cancer cells sustain specialized lysosomal functions are not fully delineated. Notably, assimilation of dietary antioxidants within lipoproteins, a lysosome-dependent process, protects tumors from ferroptosis, an oxidative form of cell death, raising the possibility that tumors evolve mechanisms to enhance this process. Here, we applied genetic screens to identify regulators of lysosome-dependent lipoprotein assimilation and ferroptosis resistance and identified ZNF217, a frequently amplified transcriptional regulator in human cancers, as a driver of tumor lysosomal function and ferroptosis resistance. ZNF217 promoted lipoprotein assimilation through transcriptional maintenance of RAB11FIP4, an endolysosomal protein. Loss of either ZNF217 or RAB11FIP4 impaired lysosomal acidification across multiple cancer types, leading to defective lipoprotein assimilation, increased lipid peroxidation, ferroptosis sensitivity, and impaired tumor growth. Mechanistically, RAB11FIP4 boosts lysosomal acidity through maintenance of RAB7A activity. Finally, disruption of ZNF217 in breast cancer cell lines and patient-derived organoids, a tumor context linked to ZNF217 expression, reduced lysosomal acidity and impaired cancer growth through increased ferroptosis sensitivity. Together, we identify transcriptional regulation of lysosomal acidification as a key metabolic adaptation that enables extracellular antioxidant acquisition and tumor progression.

cancer biology↗

bioRxiv2026

Tumor context determines ARID1A effects on gastric cancer immunity

The role of ARID1A in cancer immune evasion remains uncertain, with prior studies reaching opposing conclusions. In addition, previous work has shown that the role of ARID1A in cell-autonomous tumorigenesis is context-dependent. Using isogenic murine gastric cancer models, we found that in vivo Arid1a loss in an autochthonous genetically engineered mouse model of gastric cancer conferred T cell-dependent immune evasion, while in vitro deletion did not. Mechanistically, tumor Arid1a loss reprogrammed the tumor microenvironment into an immune desert through suppression of GM-CSF secretion and interferon-{gamma} responsiveness. These changes were not observed when Arid1a was deleted in vitro. In human gastric cancer, an immune-cold phenotype was restricted to ARID1A mutants in the genomically stable subtype, while ARID1A loss in the chromosomal instability subtype was associated with variable immune profiles. These results demonstrate that tumor ARID1A loss does not intrinsically confer pro- or anti-tumor immune properties and instead is determined by tissue context.

cancer biology↗

bioRxiv2023

Organoid generation from mouse mammary tumors captures the genetic heterogeneity of clinically relevant copy number alterations

Breast cancer metastases exhibit many different genetic alterations, including copy number amplifications. Using publicly available datasets, we identify copy number amplifications in metastatic breast tumor samples and using our organoid-based metastasis assays, and we validate FGFR1 is amplified in collectively migrating organoids. Because the heterogeneity of breast tumors is increasingly becoming relevant to clinical practice, we demonstrate our organoid method captures genetic heterogeneity of individual tumors.

cancer biology↗

bioRxiv2022

A comprehensive single-cell breast tumor atlas defines cancer epithelial and immune cell heterogeneity and interactions predicting anti-PD-1 therapy response

We present an integrated single-cell RNA-seq resource of the breast tumor microenvironment consisting of 236,363 cells from 119 biopsy samples across 8 publicly available datasets. In this computational study, we first leverage this novel resource to define cancer epithelial cell heterogeneity based on two clinically relevant markers and identify six new and distinct subsets of natural killer cells. We then illustrate how cancer epithelial cell heterogeneity impacts immune cell interactions. We develop T cell InteractPrint, which considers how cancer epithelial cell heterogeneity shifts the predicted strength of T cell interactions. We use InteractPrint to predict response to immune checkpoint inhibition (ICI) in two clinical trials testing immunotherapy in patients with breast cancer. T cell InteractPrint was predictive in both trials (AUC = 0.81 and 0.84), versus PD-L1 expression (AUC = 0.54 and 0.72). This result provides an alternative predictive biomarker to PD-L1 to select patients who should receive ICI. STATEMENT OF SIGNIFICANCEWe developed a novel integrated single-cell atlas of the breast tumor microenvironment to interrogate breast tumor cell heterogeneity and define how heterogenous cancer epithelial cell and immune cell interactions predict response to anti-PD-1 therapy.

cancer biology↗