Cancer Research

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.

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.

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.

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.

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.

Glypican-3 (GPC3) is an oncofetal protein widely being explored as a diagnostic and therapeutic target in hepatocellular carcinoma (HCC). Given that radiotherapy in the form of external beam and radioembolization are standard-of-care treatments for HCC, we aimed to determine whether there was any relationship between GPC3 and response to radiotherapy. Here, we demonstrate that GPC3 expression confers radioresistance in liver cancer through integrated in vitro, in vivo, and patient-level clinical analyses. Stable GPC3-knockout in liver cancer cell lines (HepG2, Hep3B, Huh7) and ectopic GPC3 expression in GPC3-negative liver cancer cells (SNU449), as well as in non-hepatic A431 cells, demonstrated that GPC3-mediated radioresistance is not restricted to hepatic lineage. Following irradiation, GPC3-deficient cells exhibited reduced proliferation, impaired clonogenic survival, persistent DNA damage, prolonged G2/M arrest, and increased apoptosis. Transcriptomic profiling demonstrated enrichment of cell-cycle and DNA damage response pathways in irradiated GPC3-deficient cells compared with GPC3-positive cells, and protein analyses confirmed sustained activation of the ATM/CHK2 axis. In vivo, GPC3 deletion markedly enhanced radiation-induced tumor growth delay in both HepG2 and A431 xenograft models. Consistent with these findings, high GPC3 expression was associated with inferior clinical outcomes in patients with HCC undergoing external-beam radiotherapy or radioembolization. Together, these findings identify GPC3 as a determinant of radioresistance in liver cancer and suggest its potential utility as a biomarker to guide radiotherapeutic strategies. Significance statementRadiotherapy is an important treatment option for HCC, but biomarkers that predict tumor response remain limited. GPC3 is highly expressed in most HCCs and is being investigated as an important biomarker for diagnosis and treatment of this disease, yet its relationship, if any, on radiosensitivity has not been previously reported. Here, we identify GPC3 as a modulator of radioresistance. GPC3 loss enhances radiosensitivity and is associated with persistent unresolved DNA damage, prolonged G2/M arrest, and sustained activation of the ATM/CHK2 pathway, resulting in delayed tumor growth after irradiation. In a clinical cohort of patients treated with radiotherapy, high GPC3 expression was associated with poorer overall survival. These findings suggest that GPC3 expressing tumors may necessitate either more dose-intense radiotherapy, radiobioligically ablative and/or combined with other modalities, or alternative therapeutic modalities to adequately treat HCC.

Targeting immunosuppressive tumor-associated myeloid populations has emerged as a promising strategy to enhance anti-tumor immunity. The CCL2-CCR2 axis plays a central role in the recruitment of monocytes that differentiate into tumor-associated macrophages (TAMs), yet the therapeutic potential of CCR2 targeting remains limited. Using transgenic CCR2-DTR mice, we show that depletion of CCR2+ monocytes and TAMs reduced tumor growth across multiple models, accompanied by remodeling of the tumor microenvironment (TME). Residual CCR2-independent TAMs exhibited a pro-inflammatory and less immunosuppressive phenotype, and expressed the alternative recruitment receptor CCR3. Concomitantly, CCR2 depletion markedly enhanced anti-tumor immunity by increasing infiltration of activated CD8+ T cells. Splenocytes from tumor-bearing CCR2-DTR mice showed an increased IFN{gamma} response to a cancer-associated antigen. Furthermore, CCR2 depletion synergized with immune checkpoint blockade to enhance tumor control. Despite these effects, compensatory tumor infiltration of neutrophils following CCR2 targeting limited therapeutic benefit. These neutrophils exhibited a terminally differentiated, immunosuppressive phenotype and were associated with increased cancer cell-intrinsic expression of the neutrophil-recruiting chemokines Cxcl2 and Cxcl5. Importantly, combined depletion of CCR2+ cells and neutrophils overcame this resistance mechanism, resulting in reduced tumor growth, prolonged survival, and complete tumor clearance in 25% of the mice. Dual depletion of CCR2+ cells and neutrophils was also associated with a synergistic increase in circulating CD8+ T cells. These findings highlight the dynamic remodeling of the TME upon CCR2 depletion and suggest that combinatorial strategies addressing immunosuppressive neutrophil infiltration may improve the efficacy of CCR2 targeting therapies.

Oncogenic KRAS mutations promote tumorigenesis by constitutive activation of multiple, well-characterised signalling pathways. However, there is significant heterogeneity across mutant KRAS tumours in terms of mutation present, mutant allele abundance and downstream signalling strength. It is unclear whether these variations can impact responses to specific therapies. Here, we demonstrate that [~]20% of lung adenocarcinomas (LUAD) show an increase in mutant KRAS dosage (KRASmutant allele fraction > KRASwild-type). Furthermore, we show that KRAS mutant dosage can directly influence clinical outcome and therapeutic susceptibilities in lung cancer. Our findings show that mutant KRAS copy gains specifically affect platinum lung cancer response, promoting resistance to this standard-of-care therapy. Importantly, increases in KRAS mutant dosage are also associated with an increased vulnerability to pS6K inhibition, due to the unique metabolic rewiring of these cells. Together, we show that mutant KRAS dosage contributes to the phenotypic heterogeneity of mutant KRAS NSCLC and that assessment of mutant KRAS content or signalling strength can help optimise treatments strategies for these patients.

Predictive assays for precision oncology increasingly rely on multi-scale biomarkers that manifest as morphologic signatures in routine whole-slide images (WSIs). However, most computational pathology models treat biomarker profiling and outcome prediction (i.e., prognostic stratification and therapeutic response) as independent tasks, and lack the interactive and trustworthy capabilities required for clinical translation. Here, we present TEAM, an interactive trustworthy AI pathology copilot that improves biomarker-driven outcome prediction. Pretrained on 55,648 pan-cancer WSIs and 1,750,648 regions of interest (ROIs), comprising 360 million patches, TEAM learns risk-aware embeddings by conditioning on clinical metadata and aligning with relative risk prior. For trustworthy assessment, TEAM quantifies patch-level data (aleatoric) and model (epistemic) uncertainty, then propagates these estimates to patient-level predictions. In outcome prediction, profiled biomarkers serve as intermediate features to contextualize prognostic and therapeutic estimates. Beyond passive prediction, TEAM integrates vision-language models with agentic orchestration for clinical reasoning, and provides a web-based clinician-in-the-loop interface for interactive prediction refinement. Evaluated across 48 multi-institutional cohorts encompassing 85 benchmarks, TEAM consistently outperforms existing methods across biomarker profiling, prognostic stratification, and therapeutic response prediction, supporting trustworthy AI-assisted decision-making in computational pathology.

Ductal carcinoma in situ (DCIS) exhibits substantial heterogeneity in its risk of progression to invasive breast cancer, yet the cellular and molecular determinants of high-risk lesions remain incompletely defined. Using spatially resolved single-cell transcriptomic and epigenomic profiling of 43 patient-derived DCIS and DCIS/invasive ductal carcinoma (IDC) samples, we delineate cellular programs, spatial organization, and epigenetic regulatory mechanisms associated with invasive potential. We identify an epithelial population with stemness features within luminal hormone-responsive (LumHR) cells that progressively expands from benign tissue to DCIS and IDC, and is strongly associated with invasive progression and recurrence-linked transcriptional programs. Spatial mapping reveals discrete DCIS niches enriched for stem-like LumHR cells, characterized by elevated CEACAM6 expression and enhanced ligand-receptor interactions, including CEACAM6-EGFR signaling between epithelial and stromal compartments, including cancer-associated fibroblasts, macrophages (APOC1-positive) and perivascular cells. These niches define a microenvironmental context that supports stemness and invasive potential. Epigenomic analyses implicate FOXA1 as a key regulator of these stem-like transcriptional states. Pharmacologic disruption of FOXA1-regulatory network using LSD1 inhibition suppresses stemness-associated transcriptional programs in vitro and significantly restrains tumor growth in vivo. Collectively, these findings define high-risk DCIS as a stemness-driven disease embedded within specialized microenvironments, and identify associated regulatory networks as candidate biomarkers and therapeutic vulnerabilities.

Understanding the molecular mechanisms that drive treatment response is central to personalized cancer care, but assays such as spatial transcriptomics are not yet scalable in routine clinical practice. A critical question, then, is whether this deeper molecular insight can be extracted directly from routine histology. Here, we introduce SPARC, a framework that infers spatially resolved activity maps for 40 gene expression programs directly from H&E slides. Integrating predicted program maps with morphological features improves survival prediction in 17 of 18 cancer types across 8,383 patients and matches a multi-omic method requiring paired RNA sequencing. SPARC also stratifies bevacizumab response in ovarian cancer (odds ratio = 8.08) and trastuzumab response in breast cancer (odds ratio = 3.44), while H&E image-only baselines yield non-significant separation between responders and non-responders. Unsupervised anal-ysis of predicted maps reveals canonical tumor microenvironment compartments and spatial interaction patterns directly from tissue morphology, linking predictive perfor-mance of clinical outcomes to underlying biological mechanisms.

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy associated with poor prognosis despite recent therapeutic advances. We hypothesized that a comprehensive understanding of the spatial heterogeneity and organization of the tumor microenvironment (TME) can substantially improve risk stratification and prediction of treatment response in HNSC. As spatial transcriptomics (ST) remains labor-intensive and costly, we developed HEiST (H&E-Inferred Spatial Transcriptomics), a deep learning framework that predicts spatially resolved gene expression profiles directly from routine hematoxylin and eosin (H&E)-stained histology slides. After rigorous validation across two independent external ST cohorts, we applied HEiST to infer spatial transcriptomes across 1,500 HNSC patient tumors spanning two publicly available datasets and two newly generated cohorts, one treated with concurrent chemoradiotherapy (CCRT) and one with immunotherapy. This large-scale analysis uncovered reproducible spatial clusters characterizing the HNSC TME, defining two distinct prognostic Spatiotypes, Immune-Exhausted and Immune-Activated, with significantly distinct survival outcomes. Critically, spatial cluster composition accurately predicts HPV status and yields treatment response predictors for both CCRT/radiotherapy and immunotherapy that outperform costly gene-expression and direct image-based approaches. Notably, the ST cluster-based predictor of immunotherapy response markedly surpasses the performance of commonly used FDA-approved biomarkers, including CPS, TPS, and their combination. To the best of our knowledge, this represents the first virtual spatial profiling effort and the most comprehensive large-scale spatial TME analysis in HNSC to date. HEiST thus introduces a scalable, low-cost, and spatially grounded biomarker discovery for precision oncology in HNSC.

BRCA-deficient high-grade serous ovarian cancer is characterized by profound genomic instability and elevated replication-associated DNA damage, rendering these tumors initially sensitive to platinum-based chemotherapy and PARP inhibition. However, despite this vulnerability, most patients ultimately develop resistance, underscoring the need for therapeutic strategies that extend beyond DNA repair-targeted mechanisms. Here, we introduce the MTDH-SND1 complex as a complementary therapeutic target that may expose additional stress vulnerabilities in ovarian cancer cells. We show that pharmacological disruption of the MTDH-SND1 interaction using C26-A6 increases susceptibility to ferroptosis-associated stress, an iron-dependent form of regulated cell death and that BRCA-deficient models are particularly more sensitive to this perturbation. Notably, when combined with PARP inhibition, MTDH-SND1 disruption is associated with increased MHC class I expression in tumor cells, suggesting enhanced tumor visibility to the immune system. Together, these findings support a combination strategy that couples DNA repair disruption with metabolic and immunogenic remodeling in BRCA-deficient ovarian cancer.

Drug-response measurements across pre-clinical pharmacogenomic studies remain poorly correlated, which limits biomarker discovery, precision oncology, and predictive modelling. The drivers of this inconsistency have been debated but not yet resolved. By integrating 15 pharmacogenomic studies encompassing 760 small-molecule compounds, 1,111 cell models, and 9.8 million dose-response measurements, we demonstrate that dose-response metric is the strongest driver of inconsistency, followed by experimental factors, such as treatment duration, plate format, and viability readout; in contrast, cell line molecular features contribute only minimally to reproducibility. Among drug classes, hormone therapies and PARP inhibitors show the highest concordance, whereas antimetabolites, topoisomerase inhibitors, and mitotic inhibitors exhibit substantial response variability across studies. To improve consistency, we developed a Drug Response Score (DRS), a proximity-weighted measure that emphasize pharmacologically informative concentrations near IC50, and we demonstrate in systematic benchmarking how DRS markedly improved cross-dataset concordance. Applications to patient-derived neuroblastoma organoids and leukemia patients primary cells demonstrate that DRS improves replicate-level consistency in patients drug-response profiles. To improve reproducible pharmacogenomic studies, we make openly available an integrated Drug Response Resource (iDRR, https://aittokallio.group/iDRR/), a standardized 15-dataset portal that supports robust biomarker discovery and cross-study benchmarking.

Oncogenic KRAS mutations exhibit a striking tissue-restricted tropism, occurring with high frequency in pancreatic, colorectal, and lung adenocarcinomas while remaining rare in other lineages. The molecular basis for why these specific tissues are uniquely permissive to KRAS transformation, and how this context shapes therapeutic vulnerabilities, remains poorly defined. Here, we utilized CRISPR-mediated genome engineering to generate endogenous, conditional KRAS-mutant isogenic cell line models across three primary permissive lineages (lung, colon, and pancreas) and the non-permissive breast lineage. Integrated genome-wide CRISPR fitness screens and comparative transcriptome analyses revealed that KRAS-driven synthetic lethal (SL) dependencies are profoundly shaped by their tissue of origin. Strikingly, we observed minimal overlap in SL hits across lineages, with only three genes shared among the permissive lines, suggesting that the KRAS oncogene operates through divergent, context-specific genetic networks. Mechanistically, we show that KRAS activation induces a universal MYC-driven metabolic signature, but the specific machinery required to sustain this state is lineage-restricted. We identified a dependency on the diphthamide synthesis pathway to maintain translational fidelity amidst a KRAS-induced hyper-translational state. These findings demonstrate that even when driven by the same oncogene, tumors exhibit distinct regulatory landscapes and unique genetic vulnerabilities. Our results provide a framework for developing lineage-aware therapeutic strategies, moving beyond universal KRAS inhibition toward targeted interventions tailored to a tumors specific tissue context. SIGNIFICANCE STATEMENTWhile KRAS mutations drive a significant portion of human malignancies, their prevalence is strikingly restricted to specific lineages, namely pancreatic, colorectal, and lung tissues. This tissue-restricted tropism suggests that oncogenic KRAS does not operate in a vacuum but requires a permissive, tissue-specific molecular landscape to sustain tumorigenesis. By integrating comparative transcriptome analyses with functional genomics across four isogenic lineages, we demonstrate that KRAS synthetic lethal dependencies are not universal but are hardwired to the cell of origin. This work establishes a framework for tissue lineage-aware oncology, shifting treatment paradigms from targeting the KRAS mutation alone to targeting the specific genetic networks, defined by the tissue of origin, that sustain KRAS-driven growth.

Platinum resistance remains a major barrier in Ovarian cancer (OC) treatment[1]. While hyperactivation of DNA damage response (DDR) is a hallmark of chemoresistance[2], the underlying epigenetic mechanisms driving this adaptation remain poorly understood. Here, we identify a novel post-transcriptional regulatory axis involving miR-221-5p that governs two critical DDR effectors: RAD18, which mediates DNA damage tolerance through trans-lesion synthesis (TLS)[3][4], and RAD51, the central recombinase for homologous recombination (HR)[5][6]. Although the miR-221/222 cluster is traditionally categorized as oncogenic[7][8], we demonstrate that the miR-221-5p arm functions as a potent tumor suppressor in OC. Bioinformatic and luciferase reporter assays confirmed that miR-221-5p directly targets the 3'UTRs of both RAD18 and RAD51. In OC clinical specimens and cell lines, miR-221-5p downregulation inversely correlates with RAD18/RAD51 expression. Functionally, miR-221-5p restoration suppressed platinum-induced PCNA mono-ubiquitination and HR, inducing a "functional BRCAness" that sensitized both established and patient-derived primary OC cells to carboplatin and PARP inhibition. Furthermore, in vivo disseminated xenograft models demonstrated that stable miR-221-5p expression significantly reduced tumor burden. Collectively, our results delineate a novel regulatory mechanism where loss of miR-221-5p drives chemoresistance by derepressing the RAD18/RAD51 axis, identifying this axis as a promising therapeutic target.

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer associated with substantial morbidity and mortality in advanced stages. Despite its well-described stepwise progression from actinic keratosis to invasive disease, robust molecular markers for stage discrimination and clinical decision-making remain limited. We sought to define the transcriptional continuum underlying cSCC progression, identify stage-associated biomarkers, and assess the broader relevance of these programs across human malignancies. Bulk RNA sequencing (HTG EdgeSeq) and spatial transcriptomics (GeoMx) were performed on biopsies from eight patients, each presenting multiple disease stages (healthy skin, premalignant lesion, tumor core, and invasive front) within the same lesion field, enabling within-patient analysis of progression. Spatial transcriptomic analyses identified more than 2,000 differentially expressed genes whose expression varied across disease stages. These genes were organized into 18 coordinated expression programs reflecting progressive biological rewiring during tumor evolution. Proliferation, extracellular matrix remodeling, inflammation, and stress-response pathways were progressively upregulated, whereas epithelial differentiation and metabolic processes, including lipid and amino acid metabolism, were downregulated. Macrophages exhibited distinct metabolic reprogramming, with increased purine metabolism, glycolysis, and pyruvate metabolism across progression. To evaluate the broader clinical relevance of these progression-associated programs, we developed a reproducible Snakemake pipeline to systematically screen 32 solid and hematologic malignancies from The Cancer Genome Atlas (TCGA). A combined cSCC-progression signature was significantly associated with poor overall survival (P < 0.05) in 10 additional cancer types. Finally, we identified 12 stage-informative biomarkers, whose spatially restricted expression patterns were validated using Visium HD. This study provides a spatially resolved and stage-aware transcriptomic map of cSCC progression, identifies coordinated gene programs underlying disease evolution, and defines progression-associated signatures with prognostic relevance across multiple cancers, highlighting their potential translational value.

BRAF-targeted therapy (BRAFi/MEKi) and immune checkpoint blockade (anti-PD-1/anti-CTLA-4) have transformed the treatment of BRAF-mutant metastatic melanoma. While most patients who respond to targeted therapy eventually progress, a subset derives durable benefit, and biomarkers to identify this subset would inform optimal treatment selection. In this study, we analyzed pre-treatment tumor samples from a clinically annotated cohort of 155 patients with BRAF-mutant metastatic melanoma treated with first-line BRAFi/MEKi and followed for up to five years. We stratified patients into durable responders (PFS [&ge;] 24 months) and rapid progressors (PFS < 6 months with progression) and found that a global metric of tumor genomic heterogeneity, rather than individual gene alterations, distinguished these groups. Combining genomic heterogeneity with baseline tumor burden (e.g., lactate dehydrogenase (LDH) or radiographic lesion dimensions), we developed a parsimonious model that predicted durable responders with high precision and specificity. Notably, the analogous population of patients treated instead with immunotherapy were not durable responders, suggesting that the selected predictors of durable responders are targeted therapy specific. Spatial profiling of a subset of pre-treatment biopsies (n = 47) demonstrated that high intratumoral, but not peritumoral, CD8+ T-cell infiltration correlated with prolonged survival on BRAF-targeted therapy and served as an independent predictive factor when considered with genomic heterogeneity and features of clinical tumor burden. Together, these findings highlight the distinct baseline intrinsic and extrinsic features underlying durable response to BRAF-targeted therapy and support their potential implication in guiding treatment selection for patients with BRAF-mutant metastatic melanoma. One-Sentence SummaryIntegrated clinical, tumor genomic, and immune microenvironmental features predict durable responses to BRAF-targeted therapy.

Diffuse midline gliomas (DMGs) are driven by the H3K27M oncohistone--a challenging therapeutic target. However, conventional therapeutic modalities are never curative. Against this backdrop, we address an important unresolved question--are there H3K27M-induced oncogenic vulnerabilities that can be exploited for therapeutic benefit. We show that H3K27M induces hypertranscription, thus identifying hypertranscription as a new molecular feature of H3K27M-driven DMGs. We demonstrate this finding in genetic mouse models, human DMG cells, and primary tumor specimens. We further demonstrate that H3K27M-induced hypertranscription perturbs replication, heightens basal replication stress, and enhances sensitivity to ATR inhibition. In exploring therapeutic implications of these findings, we document brain penetrance, target engagement, and therapeutic efficacy of a clinical-stage ATR inhibitor (alnodesertib) in vitro and in intracranial DMG xenografts. We further demonstrate synergistic activity of alnodesertib with radiotherapy--the current standard of care for DMGs. These findings provide the mechanistic underpinning and preclinical rationale for including alnodesertib as monotherapy and in combination with radiation in clinical trials for children with H3K27M DMGs. The broad implications of our studies highlight ATR inhibition as a therapy for aggressive human cancers displaying hypertranscription.