Cancer Research

TP53 mutations occur in 80-90% of triple-negative breast cancers (TNBCs) and drive genomic instability and metastatic progression. Poly (ADP-ribose) polymerase (PARP) is critical for DNA repair and replication fork stability. How oncogenic signaling influences PARP function to sustain proliferation during replication stress remains unclear. Mutant p53 (mtp53) R273H associates tightly with chromatin, forms complexes with PARP, and enhances PARP recruitment to replication forks [1-3]. The C-terminal region of mtp53 mediates mtp53-PARP and mtp53-Poly (ADP-ribose) (PAR) interactions that facilitate S phase progression [4, 5]. The PARP inhibitor talazoparib (TAL) combined with the alkylating agent temozolomide (TMZ) produces synergistic cytotoxicity selectively in mtp53, but not wild-type p53 (wtp53), breast cancer cells and organoids. Herein we evaluated the mechanism of mtp53-associated cell death and tested if this could translate to a preclinical xenograft model. We found that TMZ+TAL treatment induced elevated cleaved PARP and {gamma}H2AX and reduced the metastasis-promoting oncoprotein MDMX. In orthotopic xenografts expressing mtp53 R273H, but not wtp53, combination therapy significantly decreased circulating tumor cells (CTCs) and lung metastases. Transcriptomic profiling of tumors from combination treated animals demonstrated downregulation of MDMX, VEGF, and NF-{kappa}B, consistent with the observed suppression of CTCs and lung metastasis, and increased {gamma}H2AX, indicative of replication stress in mtp53 xenografts. Inhibition of metastasis was also observed in mtp53 R273H WHIM25 and p53-undetectable WHIM6 TNBC patient-derived xenografts (PDX). The mtp53 C-terminal domain (347-393) demonstrated a critical tumor promoting function, as CRISPR-mediated deletion impaired replication fork progression, tumor growth, and metastatic dissemination. DNA fiber combing showed that expression of full-length mtp53 R273H, but not C-terminal deleted {Delta}347-393, supported sustained single-stranded DNA gaps (ssGAPs) following Poly (ADP-ribose) glycohydrolase (PARG) inhibition. These findings support that mtp53 uses C-terminal amino acids to exploit PARP to enable replication stress adaptation and that mtp53 is a predictive biomarker for combined PARP inhibitor and DNA damaging therapies targeting TNBC. Significance statementTP53 mutations are the most common genetic alterations in TNBC and a major driver of replication stress and metastasis. This study shows that missense mutant p53 uses C-terminal amino acids to reprogram PARP activity to maintain tumor cell survival under replication stress. We demonstrate that p53 status governs the response to combined PARP inhibitor (PARPi) and DNA-damaging chemotherapy, establishing an additional molecular basis beyond BRCA1 mutations for treating TNBC with PARPi therapy. These findings reveal a previously unrecognized mechanism by which the mutant p53-PARP axis enables replication stress tolerance and drives cancer metastasis. We show mutation of p53 in TNBC provides an additional biomarker-guided framework to improve PARPi therapeutic outcomes.

Osteosarcoma (OS) genomes are characterized by complex genomic rearrangements (CGRs) that drive genomic instability and clonal diversification early in tumor evolution. As a result, OS tumors display high inter-patient variability, which has hindered molecular stratification and targeted therapeutic development. To study genomic complexity in OS and credential a genetically engineered mouse model of the disease (Sp7-Cre Trp53fl Rb1fl), we performed high-depth and multi-region whole genome sequencing (WGS) of 35 tumor samples from 24 mice. Similar to human OS, the murine OS tumors (mOS) had a high number of somatic structural variants (158 per tumor) with low tumor mutational burden of single nucleotide variants (0.87 mutations/MB). CGRs were identified in 63% (15/24) of mOS cases, most frequently affecting chromosome 15 (33%, 8/24 mice) and resulting in Myc amplification in 6 mice, ranging from 5 to 104 copies. Myc amplification was verified with DNA FISH, long-read sequencing and gene expression data, which revealed examples of Myc amplification in both extrachromosomal circular DNA (ecDNA) and in derivative chromosomes generated by CGRs. PTEN loss occurred frequently (59% 12/22 mice), and contributed to osteosarcomagenesis, as demonstrated by tumor initiation with in vivo CRISPR/Cas9-mediated deletion experiments (2 mice). Together, these results demonstrate that a preclinical model of osteosarcoma can generate the genomic heterogeneity and complexity of the human disease, thereby facilitating research into mechanisms of tumor initiation and drivers of progression and relapse.

Precision oncology lacks scalable tools to assess, at the patient level, systems-level tumor microenvironment (TME) programs driving therapeutic resistance. To address this gap, we trained a weakly-supervised deep learning model that uses routine H&E whole-slide images (WSIs) to derive quantitative activity for therapeutically-relevant TME phenotypes, spanning immune, metabolic, and tumor cell-intrinsic programs. Using 3111 breast cancer H&E WSIs with matched bulk transcriptomics, our model accurately infers these biological states, defined by pathway enrichment scores (AUROC>0.80; PCC>0.64). Validation spanned three levels: (i) tissue-matched multiplexed immunofluorescence, showing concordance between inferred functional states and immune cell fractions (p=0.006-0.106), (ii) blinded reader assessments, confirming localization of phenotype-specific morphology (p<3x10-5), and (iii) multi-institutional patient cohorts, where model-derived phenotypes stratified for clinical response (p<0.045). Unlike methods requiring resource-intensive spatial profiling data for training, our approach leverages widely-available therapeutic outcomes or bulk profiling as slide-level labels to assess functional biology. This strategy offers a scalable complement to spatial Omics for investigating therapeutic resistance across the pan-cancer landscape through using WSIs and clinical outcomes from massive legacy biobanks.

Macrophages are abundant in the colorectal tumour microenvironment and can alter drug response. Using mouse Apc/Kras/Trp53 (AKP) colorectal cancer organoids, we found that macrophages and/or macrophage-conditioned medium reduced sensitivity to the MEK inhibitor trametinib and the pan-RAS inhibitor RMC-6236. In contrast, macrophage-conditioned medium had little effect on regorafenib and increased sensitivity to dabrafenib, suggesting that resistance depends on the inhibitory profile of each drug. Secretome profiling identified PDGF-BB and GDF-15 as candidate mediators. Adding both ligands to organoid medium reproduced much of the conditioned-medium effect, whereas either ligand alone was insufficient. Inhibition of PDGFR or RET partially reduced drug resistance, suggesting that PDGF-BB and GDF-15 likely act through canonical signalling by that additional macrophage-derived signals also contribute. Kinome profiling pointed to increased tyrosine kinase signalling during trametinib treatment, with SRC family kinases emerging as a key downstream node. Consistent with this, SRC inhibition reduced the difference between control and conditioned-medium responses. The multi-kinase inhibitor masitinib--which targets several kinases along this resistance network--strongly restored sensitivity to trametinib and RMC-6236. Together, these data define a macrophage-driven resistance network in KRAS-mutant colorectal cancer organoids and support combined inhibition of RAS-pathway and tyrosine kinase signalling.

Genotoxic cancer therapies introduce DNA damage that can be fixed as somatic mutations in surviving tumor cells. However, the impact of therapy-associated mutagenesis on regulatory elements remains unclear. CTCF binding sites (CBS) are chromatin architectural elements that exhibit recurrent localized mutation enrichment in cancer genomes. We asked whether treatment exposure is associated with increased mutagenesis at CBS in 4,870 whole-genome sequences from metastatic tumors across 17 cancer types and 45 therapies. Radiotherapy and trifluridine exposure in metastatic colorectal cancer were associated with increased mutation enrichment at CBS. This enrichment was pronounced at motif-containing sites and in low-expression or late-replicating genomic contexts. Alterations in DNA damage response genes, including BRCA2, were associated with increased CBS mutation enrichment following radiotherapy. Together, these findings indicate that therapy-associated mutagenesis at CTCF binding sites is shaped by chromatin context and DNA repair capacity, extending the mutational consequences of cancer treatment to regulatory genome architecture.

A substantial proportion of cancer patients fail to benefit from their prescribed combination regimens, yet identifying superior alternatives from the vast pharmacological space prior to treatment failure remains an unsolved clinical challenge. Existing computational approaches either rely on multi-omics profiles unavailable in standard oncological practice or reduce drug efficacy to scalar metrics that discard the dose-dependent resolution essential for therapeutic optimization. Here, we present XACT, a hierarchical deep learning framework that reconstructs full dose-dependent drug responses for both monotherapy and drug combinations using only clinically accessible transcriptomic profiles. By leveraging an asymmetric X-Linear Attention mechanism that models second-order interactions between molecular drug substructures and intracellular signaling pathway activities, XACT captures concentration-dependent pharmacodynamics with state-of-the-art accuracy and generalizability to unseen transcriptomic landscapes. When applied to the TCGA pan-cancer cohort, XACT-derived resistance scores were significantly associated with clinical treatment outcomes and stratified overall survival as the strongest independent prognostic factor after multivariate adjustment for tumor stage and cancer type. Systematic virtual screening revealed therapeutic vulnerabilities and nominated alternative regimens for treatment-refractory sarcoma and pancreatic adenocarcinoma. These results establish XACT as a scalable, interpretable, and clinically translatable framework that advances precision oncology from computational prediction toward data-driven therapeutic prescription.

Increased matrix metalloproteinase (MMP) expression has long been recognized as a common feature of colorectal cancers (CRCs), yet less is known about how these enzymes interact to impact cancer progression. Taking advantage of single-cell and spatial transcriptomic data, we analyzed the cell-type-specific and spatial expression of MMPs in CRCs. Distinct colon cancer-associated fibroblast (CAF) subtypes were found to express different MMP combinations, including MMP1/3-expressing and MMP11-expressing CAFs. Conversely, myeloid cells (monocytes, macrophages, and dendritic cells) expressed varying levels of the "myeloid MMPs" 9, 12, and 14, which correlated closely with secretory gene expression. Finally, a small population of cancer cells expressed high levels of MMP7. The MMP7-expressing cancer cells frequently co-expressed MMP1, MMP14, and several Wnt-related genes, consistent with a cancer cell type at high risk of malignancy and metastasis. Spatial transcriptomic data showed MMP expression in discernible clusters driven in part by cell-type localization, including fibroblast-heavy stromal regions and inflammatory cell hubs. Epithelial-rich areas showed subregions of MMP7-expressing cancer cells, including areas where cancer cell and myeloid MMP expression overlap. Tumors showed a wide variation in MMP1-expressing CAFs, a variation reflected in primary CAF cell lines. In vitro, MMP1 expression was a stable phenotype that persisted through multiple rounds of division. MMP1-expressing CAFs were frequently positioned at the stromal interface, suggesting a role in facilitating cell movement across the tumor boundary. Our analysis indicates that cell-type and positional MMP expression varies between tumors and may play a role in determining lesion progression and cancer spread.

SUMMARYChordoma, a rare malignant notochordal tumor of the skull base and spine, is typically resistant to chemotherapy and radiotherapy and exhibits aggressive local recurrence. Here we show that chordoma recurrence correlates with a coordinated upregulation of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs), a low PFA/MUFA ratio and an adaptive, lipid peroxidation-resistant state that protects against DNA damage and cell death. Single-cell metabolic profiling identified a tumor subpopulation marked by a fatty acid biosynthesis-high state coupled to stemness. RT-tolerance was directly linked to elevated FASN and lipid droplet (LD) expansion, and MUFA-loading phenocopied RT-tolerance in chordoma cells. Mechanistically, LDs accumulated in response to RT via generation of ROS, and subsequent activation of ER-stress, SREBP1 and Fatty Acid Synthetase (FASN). DESI-MS showed that low-dose irradiation was sufficient to increase MUFAs early and build peroxidation resistant MUFA-LDs, whereas PUFA induction required a higher radiation dose. In a spatially defined manner in a patient-derived xenograft. Finally, in silico knockout and pharmacologic FASN blockade restored radiosensitivity and apoptosis in vitro and in vivo. Collectively, our result support a unifying model in which RT resistance in chordoma is shaped by an adaptive fatty acid metabolic program that buffers oxidative injury and increases survival of RT-resistant, stem-like tumor subpopulations. These findings further support FASN inhibition as a practical radiosensitization strategy for chordoma particulary where RT dose escalation is constrained by anatomy. KEYPOINTSO_LIRecurrent chordoma exhibits fatty acid-associated metabolic reprogramming. C_LIO_LIMUFA-associated lipid droplet accumulation is linked to radioresistance in chordoma cells. C_LIO_LITargeting FASN restores radiotherapy sensitivity of chordoma in vitro and in vivo. C_LI IMPORTANCE OF STUDYThis study underscores the clinical importance of targeting metabolic vulnerabilities to restore radiosensitivity in chordoma. By integrating transcriptomics, metabolomics, and in vitro and in vivo models, we identified adaptive fatty acid metabolic reprogramming as a central mechanism of RT resistance in chordoma. Recurrent tumors were characterized by coordinated enrichment of unsaturated fatty acids, especially monounsaturated fatty acids (MUFAs), together with a low PUFA/MUFA ratio and a lipid peroxidation-resistant state. Mechanistically, RT-tolerance chordoma cells exhibited a high-FASN state driven by activation of the ROS-ER stress-PERK/SREBP1/FASN axis, leading to intracellular lipid droplet expansion. Importantly, genetic and pharmacologic inhibition of FASN restored radiosensitivity and enhanced apoptosis in both in vitro and in vivo models, suggesting a translatable therapeutic strategy. Together, these findings link adaptive metabolic reprogramming to RT resistance and support new therapeutic approaches for chordoma management.

Estrogen receptor positive (ER+) breast cancer is primarily treated with endocrine therapies targeting ER signaling. Although endocrine therapy has substantially improved survival in ER+ breast cancer, metastatic disease remains largely incurable, underscoring the need to elucidate additional mechanisms driving growth and proliferation. Here, we show that the homeobox protein IRX3 is selectively overexpressed in ER+ breast cancer and define the molecular function of IRX3 in ER+ breast cancer using an integrated combination of in vitro, in vivo and in silico approaches. We uncover a previously uncharacterized distal regulatory region that controls IRX3 transcription via ER and associated steroid receptor coactivators. Consistent with this regulatory axis, anti-estrogen treatment resulted in marked downregulation of cellular IRX3 levels. Functionally, depletion of IRX3 suppresses proliferation of the human ER+ breast cancer cells in vitro, but paradoxically promotes tumor growth and metastatic dissemination in orthotopic xenografts in vivo by stimulating enhanced tumor vascularization. Finally, low tumor expression of IRX3 correlates with poorer survival outcomes in patients with ER+ breast cancer. Collectively, these findings establish IRX3 as an important regulator of ER+ breast tumor biology and reveal an ER-dependent role for IRX3 in modulating proliferative and vascular programs in tumor progression. SignificanceBy identifying a novel ER-dependent regulatory pathway, this work refines our understanding of how hormone signaling shapes both breast tumor growth and the surrounding microenvironment.

BackgroundTumors exhibit substantial cellular and molecular diversity driven by genetic and epigenetic mechanisms. Large-scale profiling efforts have established aberrant DNA methylation as a universal hallmark of cancer. Beyond changes in mean methylation levels, tumor tissues exhibit elevated DNA methylation variability at specific genomic regions within and across tumors. This constitutes a fundamental dimension of cancer epigenomes, reflecting disrupted maintenance of epigenomic states and stochastic drift, which may enable adaptation to the microenvironment, phenotypic plasticity, invasion, disease progression, and treatment resistance. However, the genome-wide organization and functional consequences of DNA methylation variability across cancer types remain incompletely understood. MethodsWe analyzed paired tumor-normal DNA methylation profiles across 16 cancer types to systematically quantify DNA methylation variability. Pan-cancer DNA methylation variability was consistently observed using complementary statistical approaches and multiple modes of data representation. We identified cancer-specific and pan-cancer differentially variable regions and evaluated their associations with genomic features, transcriptional and chromatin regulators, and biological processes. Variability was quantified using three measures per sample: the proportion of intermediately methylated sites (PIM), genome-wide Shannon entropy, and a DNA methylation-based stemness index. Associations with genomic instability, tumor biological features, and clinical outcomes were subsequently assessed. ResultsTumor samples consistently exhibited higher DNA methylation variability than matched normal tissues, reflected by increased dispersion and wider interquartile ranges. Pan-cancer variably methylated regions were depleted in promoters and enriched in open sea regions, in heterochromatic H3K27me3-decorated PRC2-repressed domains, and at enhancers. They preferentially contained motifs for transcription factors involved in developmental regulation. Elevated DNA methylation variability, captured by higher PIM, entropy, and stemness scores, was associated with increased genomic instability manifested by higher aneuploidy, increased DNA break points, a greater fraction of the genome altered, and increased tumor mutational burden, as well as with aggressive tumor features such as lymph node involvement, post-therapy neoplasm events, and elevated hypoxia scores. Importantly, tumors with high DNA methylation variability exhibited significantly worse overall, progression-free, and disease-free survival. ConclusionsDNA methylation variability is a pervasive and clinically relevant feature of tumor epigenomes, reflecting epigenetic and genetic instability, expanded regulatory plasticity, and tumor aggressiveness.

Soft tissue leiomyosarcoma (STLMS) is an aggressive malignancy for which robust molecular subclassification and mechanism-based therapeutic strategies still remain limited. We performed integrative proteogenomic analyses of primary and metastatic STLMS to define subtype-associated molecular programs. Joint analysis of the proteome and phosphoproteome identified 3 biologically distinct subtypes. P1 was characterized by relative genomic stability, low proliferative activity, and enrichment of FGFR2- and PDK-associated signaling. In contrast, P2 and P3 showed greater chromosomal instability and more aggressive clinical behavior, but with distinct molecular features. Notably, P2 was associated with inflammatory and RTK-RAS pathway programs, activation of CDK-AURKA/B-mTOR-ERK kinase networks, IGF1R/PDGFRA alterations, and the poorest outcomes. On the other hand, P3 showed strong cell cycle and DNA repair programs, elevated NCOR1 expression, and increased expression of nonhomologous end joining components, including PARP1. Homologous recombination deficiency analyses distinguished HRD-low P1 from HRD-high P2/P3, and paired analyses suggested increased HRD-related features in metastatic lesions within P3. Immune profiling identified an immune-hot yet potentially suppressive state in P2, marked by higher LGALS9 expression and M2-like macrophage infiltration. To support clinical translation, we developed a tissue microarray-based immunohistochemical classifier that enabled surrogate assignment of proteome-defined subtypes in an independent cohort and showed recurrence-free survival differences across inferred subtypes. These findings together establish a proteogenomic framework for STLMS heterogeneity and nominate subtype-associated biological vulnerabilities for future translational and clinical investigation.

Epigenetic deregulation can alter the expression of cancer-related genes in tumor cells and may promote metastasis by influencing interactions between tumor cells and their immune microenvironment. However, the underlying immune mechanisms remain poorly understood. LSD1 (KDM1A) is a histone demethylase that has been proposed to function as a tumor and metastasis suppressor in breast cancer. Here, using the MMTV-PyMT breast cancer mouse model, we show that natural killer (NK) cells play a critical role in suppressing tumor cell metastasis to the lung, and that ablation of LSD1 leads to increased lung metastasis. This phenotype is accompanied by pronounced upregulation of immune-related genes, including major histocompatibility complex class I (MHC-I) genes, in tumor cells and by extensive remodeling of the tumor immune microenvironment, characterized by reduced abundance and maturation of NK cells. Consistent with these observations, NK cells exhibit reduced cytotoxicity toward Lsd1-null PyMT tumor cells. Notably, NK cell-mediated killing can be restored by disrupting expression of the non-classical MHC-I molecule Qa-1, a ligand for the inhibitory NK receptor CD94/NKG2A, in tumor cells. In transplantation experiments, Lsd1-null PyMT tumor cells formed significantly larger lung metastatic lesions than Lsd1-wildtype tumor cells in SCID mice, which possess functional NK cells, but not in NSG mice that lack NK cells. Collectively, these findings suggest that epigenetic deregulation in LSD1-deficient mammary tumor cells reprograms the tumor immune microenvironment, resulting in impaired NK cell-mediated tumor surveillance and enhanced metastatic progression.

Squamous cell carcinomas (SCCs) in the lung, head and neck, cervix, and esophagus are characterized by widespread chromosome-arm aneuploidies, most frequently recurrent 3q-gain. However, how these alterations influence cancer development and therapeutic vulnerabilities remains unclear. To identify aneuploidy-driven therapeutic targets, we performed genome-wide CRISPR interference (CRISPRi) and drug-repurposing screens in isogenic immortalized lung epithelial cells harboring chromosome 3-disomy or 3q-gain. Both screens converged on a mevalonate pathway dependency specific to 3q-gain cells, which exhibited heightened sensitivity to sterol regulatory element-binding protein (SREBP) disruption. Rescue experiments demonstrated that these vulnerabilities were on target and that pathway inhibition preferentially causes apoptosis in 3q-gain cells. Transcriptomic and lipidomic profiling revealed 3q-gain-associated alterations in SREBP activation, cholesterol and fatty-acid biosynthesis, and lipid composition. Perturbing SREBP signaling impaired viability in SCC cell lines and suppressed tumor growth in xenografts with 3q-gain. These findings identify an aneuploidy-driven, targetable vulnerability in SCC. SignificanceHere, we demonstrate that SCC-recurrent 3q-gain is a selective vulnerability to SREBP-pathway inhibition. We identify an aneuploidy-driven therapeutic liability in squamous tumors for lipid-targeted precision therapies, providing a framework for targeted treatment in SCC.

HER2 heterogeneity and reversible phenotypic plasticity play a central role in breast cancer progression and therapeutic resistance, yet how their interaction shapes treatment response remains poorly understood. Experimental and clinical evidence indicates that HER2-positive and HER2-negative tumor cell states can dynamically interconvert, enabling compensatory population shifts that undermine monotherapies targeting a single phenotype. Because stochastic lineage effects, phenotypic switching, and local cell interactions are averaged out in mean-field population-level ODE models, we develop a spatially resolved agent-based model (ABM) that explicitly represents individual-cell dynamics and heterogeneous tumor growth. The model incorporates phenotype-specific proliferation, migration, and death, division-coupled HER2 state transitions, and therapy-induced selective pressures. We consider two therapeutic interventions with complementary mechanisms of action: paclitaxel, which preferentially suppresses HER2-positive proliferation, and Notch inhibition, which targets HER2-negative populations and alters phenotypic composition. Starting from single-cell lineages, we validate the ABM against theoretical predictions from a population-level switching model and against single-cell-derived experimental measurements, demonstrating quantitative agreement with early lineage dynamics and long-term phenotypic equilibria. Simulation results show that monotherapies induce compensatory phenotypic shifts and spatial reorganization that permit tumor persistence. In contrast, combination therapy simultaneously targeting HER2-positive and HER2-negative populations disrupts phenotypic replenishment, fragments spatial structure, and can achieve sustained tumor control across a broad range of treatment strengths. To quantify robustness across heterogeneous tumor parameter regimes, we pair the ABM with an interpretable Random Forest surrogate trained on ensemble simulation data. Using only pre-treatment and early-trajectory features, the surrogate predicts long-term response, identifies growth-rate asymmetries as dominant drivers of resistance, and interpolates across previously unseen parameter combinations within the sampled domain. Together, this integrated mechanistic and data-driven framework clarifies how HER2-mediated plasticity, spatial organization, and competitive growth dynamics shape therapy resistance and provides a scalable approach for predicting and optimizing treatment strategies in HER2-heterogeneous breast cancer. Sample MATLAB code for the agent-based model (ABM) used in this study is available on GitHub.

The RNA polymerase-associated factor 1 complex (PAF1C) is an evolutionarily conserved transcription elongation complex that regulates RNA polymerase II-mediated transcription and chromatin modification. LEO1, a core subunit of PAF1C, has been implicated in developmental gene regulation, WNT signaling, and leukemogenesis; however, its role in solid tumor progression remains poorly understood. In this study, we found that although LEO1 expression is generally elevated in colorectal cancer (CRC), its expression is reduced in stage IV tumors and is associated with poor clinical outcomes. To investigate its function, we established LEO1 -deficient HCT116 cell line and performed transcriptomic analyses. Loss of LEO1 suppressed epithelial differentiation and developmental gene programs while inducing cell cycle delay. Despite these changes, LEO1-deficient cells exhibited aggressive phenotypes, including enlarged nuclei and increased expression of migration-associated genes, which were further enhanced under glucose deprivation. Motif analysis identified FOXM1 as a key regulator of these migration-related genes. Mechanistically, LEO1 deficiency promoted accelerated transcriptional activation of GRP78, a central regulator of endoplasmic reticulum (ER) stress adaptation. GRP78 was required for survival under ER stress conditions, and its inhibition suppressed both migration and migration-associated gene expression. In addition, transcriptomic analyses revealed upregulation of cholesterol metabolism-related genes in LEO1-deficient cells. Consistently, treatment with the HMG-CoA reductase inhibitor atorvastatin selectively impaired their survival, indicating cholesterol metabolic dependency. Collectively, these findings demonstrate that LEO1 loss promotes ER stress-adapted migration and cholesterol metabolic dependency in CRC, suggesting that these pathways may represent therapeutic vulnerabilities in metastatic LEO1-low CRC.

Hormone therapies are frequently used to reduce breast cancer risk in individuals at increased risk for primary or subsequent disease; however, tissue-level responses to these therapies are heterogeneous and incompletely understood. Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) provides a non-invasive radiologic readout of breast tissue features associated with endocrine responsiveness and cancer risk. Although BPE is associated with hormonal exposure, a subset of patients with BPE do not show a response to preventive endocrine therapy and therefore may remain at increased breast cancer risk. In this study, we integrated single-nucleus RNA sequencing and spatial transcriptomics to define the determinants of endocrine responsiveness in the setting of BPE. We identify hormone-driven epithelial cells with high levels of estrogen signaling and endocrine responsiveness, together with immune-associated epithelial programs characterized by diminished luminal identity and increased expression of immune-modulatory pathways, including major histocompatibility complex (MHC) class II and CD74. Functional organoid assays validate that these epithelial states exhibit differential sensitivity to tamoxifen and demonstrate that inflammatory signals can induce immune-modulatory epithelial programs. Together, our findings identify hormone signaling and immune programs as key determinants of endocrine responsiveness in breast tissue and provide a biological basis for interpreting radiologic markers relevant to cancer prevention.

Melanoma is a highly plastic cancer characterized by distinct cellular phenotypes associated with broadly unique gene expression profiles. TRIM9 is a brain-enriched E3 ubiquitin ligase detected in melanoma, but how TRIM9 expression regulates melanoma phenotype is unknown. Using two metastatic human melanoma cell lines and a mouse melanoma model, we found that TRIM9 promoted melanoma proliferation and altered cell morphology. In cell lines, TRIM9 promoted cellular blebbing and negatively regulated adhesion, secretion, and mesenchymal motility. TRIM9 interacted with VASP in melanoma cells, altering VASP modification, localization, and dynamics. In the absence of TRIM9, cells had an altered actin organization and more focal adhesions, where VASP accumulated and exhibited rapid turnover. We find the alterations in actin architecture and adhesion associated with TRIM9 deletion were coincident with increased motile and contractile mesenchymal behavior in vitro. In vivo loss of TRIM9 in melanoma slowed tumor growth and altered metastasis frequency, size, and destination. Our findings indicate TRIM9 alters the proliferative and morphological phenotypes of metastatic melanoma cells to influence disease progression.

High-grade serous ovarian carcinoma (HGSC) is an aggressive malignancy for which bulk transcriptomic subtypes are used to stratify tumors, interpret biology, and guide biomarker development. The four TCGA-derived subtypes, mesenchymal (C1.MES), immunoreactive (C2.IMM), proliferative (C5.PRO), and differentiated (C4.DIF), are consistently observed across cohorts. However, despite their prominence, these subtypes have not translated into therapeutic utility, and their biological basis remains unresolved. Here, we show that HGSC transcriptomic subtypes are largely determined by tumor cellular composition rather than intrinsic malignant transcriptional programs. By integrating controlled single-cell-derived pseudobulk simulations with deconvolution-based analysis of 1,834 primary HGSC tumors across RNA-seq and microarray cohorts, we demonstrate that subtype probabilities align along a composition-driven axis of stromal and immune variation. Cellular composition alone predicted subtype labels with high accuracy (ROC-AUC = 0.81-0.95) and explained a substantial fraction of subtype-associated transcriptomic variation, with the mesenchymal (C1.MES) subtype representing the most robust and reproducible example of composition-driven signal. Although a secondary, composition-independent expression signal is detectable, it does not define the dominant structure of subtype classification. These findings redefine HGSC transcriptomic subtypes as features of the tumor ecosystem rather than discrete malignant states. This reinterpretation has immediate implications for studies that use subtype labels to infer tumor-intrinsic biology and provides a generalizable framework for separating composition-driven and intrinsic signals in bulk tumor data. Significance StatementHGSC transcriptomic subtypes lack consistent clinical utility and remain biologically ambiguous. We show subtype assignments are largely driven by tumor cellular composition, and less so by distinct intrinsic tumor states.

AbstractRecurrent loss-of-function mutations in RUNX1 occur in estrogen receptor-positive (ER+) breast cancers, yet how RUNX1-loss contributes to breast tumorigenesis remains unclear. Here we used genetically engineered mouse models with luminal mammary epithelial cell (MEC)-restricted gene disruption to investigate its role in breast cancer initiation. Loss of RUNX1 alone, or together with RB1, was insufficient to drive tumor formation. In contrast, combined loss of RUNX1 and p53 induced mammary tumors with full penetrance. These tumors contained ER+ cancer cells and exhibited extensive T cell and macrophage infiltration, indicative of an immune hot microenvironment. Mechanistically, RUNX1-deficiency activated interferon signaling in luminal MECs, associated with derepression of RUNX1 target STAT1 and enhanced inflammatory responses. Consistent with these findings, human ER+ breast cancers with low RUNX1 expression displayed elevated immune signatures and poorer patient survival. Together, our results identify RUNX1-loss as a driver of an immune-active subtype of ER+ breast cancer.

Tumour heterogeneity presents a major challenge for precision oncology, as genetically and phenotypically distinct tumour clones may respond differently to therapy. To address this, we introduce scClone2DR, a probabilistic multi-modal framework that predicts drug responses at the level of individual tumour clones by integrating single-cell DNA and RNA sequencing with ex-vivo drug-screening data. In simulations, scClone2DR substantially outperforms alternatives in recovering true drug-effects and clonal sensitivities. Applied to 60 melanoma and 21 acute myeloid leukaemia patient samples, the method identifies heterogeneous clonal responses, yields biologically meaningful feature rankings, highlights clones that may be resistant to treatment, and improves the prediction of clinical outcomes compared to models ignoring clonal structure. These results demonstrate that modelling tumour evolution and clonal diversity is crucial for accurate drug-response prediction and provides a foundation for more effective, clone-aware precision oncology.