Nature Cancer

Curative-intent immunochemotherapy fails in ~30% of patients with large B-cell lymphoma (LBCL), yet no validated molecular tool enables early identification of high-risk individuals to guide treatment intensification. Using shallow whole genome sequencing (sWGS) of plasma cell-free DNA from 190 LBCL patients, we developed and validated the ACT score (Aberrations, fragment Composition, Terminal motifs), a composite classifier integrating genomic and fragmentomic features from a single post-cycle-1 sample. ACT-positive patients had worse 2-year outcomes versus ACT-negative patients: time-to-progression 29% vs. 83% (HR 4.4, 95% CI 1.9 - 10.0; P = 1.5 x 10 - 4) and overall survival 47% vs. 93% (HR 8.7, 95% CI 3.0 - 25.4; P = 1.8 x 10-6). ACT score was independently prognostic of the International Prognostic Index, and their combination identified the highest-risk patients. Unlike mutation-based approaches, this assay requires neither tumor tissue, germline control nor a baseline plasma sample. Built on open-source tools and sWGS, the ACT score offers a feasible scalable strategy for early risk stratification in aggressive LBCL.

Conventional short-read sequencing cannot determine whether co-occurring variants within a cancer gene reside on the same allele (cis) or on opposing alleles (trans), a distinction with direct biological and therapeutic consequences. Trans configurations confirm biallelic tumor suppressor inactivation and inform therapy selection, while cis configurations generate compound oncogenic alleles with enhanced activity. We analyzed 768 patients with prostate, breast, or ovarian cancers in the PROBLEM cohort, using mutational signatures to nominate cryptic genomic instability cases where the causative biallelic event was not apparent from short-read sequencing. Long-read nanopore sequencing resolved 32 of 46 cryptic cases (69.6%), leveraging its unique advantages in direct methylation detection, long insertion resolution, and complex structural variant characterization, confirming trans biallelic inactivation in all resolved tumor suppressor cases. Systematic analysis of 4,496 MiOncoSeq samples identified 17,519 multi-hit gene pairs, of which 78.7% exceeded the 500 bp short-read phasing limit. Long-read phasing further revealed recurrent compound cis oncogenic alleles in NOTCH1, PIK3CA, PDGFRB, and KIT with functionally synergistic activity. Haplotype phasing resolves a systematically overlooked gap in cancer variant interpretation and warrants broader integration into precision oncology workflows. Statement of SignificanceShort-read sequencing cannot resolve whether co-occurring variants within a cancer gene are cis or trans, a distinction critical for clinical interpretation. Long-read nanopore sequencing addresses this gap through direct haplotype phasing, methylation detection, and complex structural variant resolution, confirming biallelic tumor suppressor inactivation and revealing compound cis oncogenic alleles with enhanced activity.

Neoadjuvant chemoradiotherapy (CRT) is standard for locally advanced rectal cancer (LARC), yet many patients retain residual disease. To resolve CRT-associated remodeling of the tumor microenvironment, we generated a multimodal spatial atlas from serial sections of paired pretreatment and post-treatment specimens from 24 patients using Xenium single-cell spatial transcriptomics and PhenoCycler multiplex proteomics, profiling 2.8 million cells; matched Visium HD datasets were generated on adjacent serial sections. Resistance was most strongly associated with fibroblast and myeloid programs adjacent to residual tumor. We identify a periostin (POSTN)-expressing CAF subset selectively enriched around residual tumor cells in non-responders, displaying a myofibroblastic phenotype and activating extracellular matrix remodeling, noncanonical WNT signaling, and immunosuppressive pathways. Tumor cells neighboring POSTN+ CAFs show consistent epithelial-mesenchymal transition signatures. Together, this atlas enables interrogation of CRT-induced spatial remodeling and nominates POSTN+ CAFs as key mediators and targets of CRT resistance, with direct relevance to CRT-based combination strategies.

T-cell receptor (TCR) repertoires encode the organization of adaptive immunity and its reshaping by cancer and therapy, but disentangling treatment-associated structure from V(D)J recombination constraints remains challenging. We present CRAFT (Cancer Repertoire Anomaly Finding Transformer), a conditional sequence-to-sequence transformer that learns a nucleotide-level generative grammar of productive TCR-beta CDR3 sequences from healthy-donor repertoires, conditioned on germline V(D)J assignments. A dual-head decoder mirrors the independence of V-D and D-J recombination, and curriculum training yields embeddings that serve as a reference coordinate system for quantifying structured deviations in cancer-associated repertoires. In proof-of-concept analyses of a checkpoint blockade cohort (n=18) and a two-patient single-cell study of oncolytic immunotherapy, CRAFT-derived geometric metrics capture response-associated immune remodeling, including longitudinal shifts in repertoire organization. In antigen-labeled benchmarks, CRAFT yields coherent organization across specificity classes while highlighting settings where CDR3-beta alone provides partial signal.

Breast cancer is a highly heterogeneous disease shaped by dynamic interactions between malignant cells, immune infiltrates, stromal compartments, and the extracellular matrix. Among the molecular regulators of these interactions, cysteine cathepsins and legumain have emerged as important proteases involved in tissue remodeling, immune regulation, and tumor progression, yet their distribution and functional status across human breast cancer ecosystems remain insufficiently defined. Here, we performed an integrated protease-centric analysis of breast cancer specimens from 66 patients using high-dimensional single-cell mass cytometry of matched peripheral blood and tumor samples, imaging mass cytometry of intact tissues, and activity-based TOF probes for in situ detection of active proteases. Systemic immune profiling identified two patient clusters associated primarily with neoadjuvant therapy and tumor grade, accompanied by distinct cytokine and circulating protease patterns. In tumors, single-cell analysis revealed pronounced interpatient heterogeneity in tissue architecture and immune infiltration, while protease profiling uncovered reproducible cell type-associated modules, including cathepsin B/L-cystatin C and legumain-cystatin E/M axes. Cathepsins B and L were prominent in tumor-infiltrating immune cells and variably expressed in epithelial cells, whereas cathepsin D showed broader tumor distribution and cathepsin S remained more restricted. In epithelial cells, HER2 expression did not consistently coincide with high cathepsin B or L abundance, enabling identification of a limited subgroup of patients with combined HER2-high/protease-high states relevant to protease-cleavable antibody-drug conjugates. Spatial imaging further localized cathepsins B and D to tumor-stroma interfaces and macrophage-rich niches, and activity-based IMC confirmed the presence of catalytically active cathepsin B in human breast tumor tissue. Together, these findings define cysteine cathepsins as spatially and cellularly organized components of breast tumor ecosystems and provide a framework for protease-informed patient stratification and biomarker-protease pairing in targeted therapy.

Brain metastasis (BM) in renal cell carcinoma (RCC) remains poorly understood and often resistant to immune checkpoint inhibitors. We generated a large single-nucleus RNA-seq data of RCC BM, profiling 14 BM samples alongside matched extracranial metastases and primary tumors. Tumor cells in BM displayed neuronal infiltration, neural-like adaptation, and marked remodeling of the microenvironment, including expansion of immunosuppressive myeloid cells and depletion of antigen-presenting dendritic cells. Tumor, immune, and stromal cells exhibited metabolic rewiring characterized by fatty-acid metabolism, oxidative phosphorylation, and MYC-driven programs. CD8 T cells showed terminal exhaustion and impaired proliferative capacity, and tertiary lymphoid structures were absent. Spatial profiling of 12 BM samples (13,128 cells) validated key cellular interactions, while ligand-receptor analysis revealed immunoregulatory circuits between tumor, stromal, and immune cells. These findings define BM-specific adaptations that promote immune evasion and resistance, revealing therapeutic vulnerabilities in RCC BM. SIGNIFICANCESingle-nucleus RNA-sequencing profiling reveals tumor, immune, and metabolic adaptations in renal cell carcinoma (RCC) brain metastases, including neuroglial remodelling and immunosuppressive niche formation. These findings identify immune evasion mechanisms that could contribute to therapeutic resistance, providing new avenues for site-specific therapeutic interventions to improve treatment efficacy and outcomes in patients with RCC BM.

MotivationThe tumor microenvironment (TME) dictates cancer progression and therapeutic response, yet translating TME subtypes into robust clinical biomarkers remains a significant challenge. Existing classification models typically rely on static gene signatures and cohort-dependent normalization, making them ill-suited for application to the small, unbalanced datasets common in early-phase clinical trials. To better guide drug development, methods are required that offer the flexibility to target specific biological contexts and bridge the gap between the discovery of tumor archetypes and their robust translation to individual patient samples. ResultsWe developed TumorArchetypeR, a modular R package that unifies unsupervised subtype discovery with the generation of rank-based, single-sample classifiers. By leveraging a systematic parameter grid search, the framework identifies stable, data-driven subtypes rather than relying on arbitrary defaults. Crucially, to ensure clinical translatability, the package includes a module to train a robust classifier using binary gene-pair rules, enabling prediction without cohort-level preprocessing. Applying TumorArchetypeR to colorectal cancer, we resolved the heterogeneity of fibrotic tumors, distinguishing an immunosuppressive "Immune-enriched/Fibrotic" state from an immune-excluded "Fibrotic/Myeloid" phenotype. Furthermore, we identified a distinct "Th/B-cell enriched" archetype associated with superior survival, a group largely obscured by existing pan-cancer models. With our rank-based classifier demonstrating robust performance on previously unseen samples, these findings highlight TumorArchetypeR as a scalable, end-to-end solution for refining patient stratification and optimizing precision oncology strategies. The TumorArchetypeR package and documentation are openly available on GitHub at https://github.com/lutgem/TumorArchetypeR.

Tumor-associated macrophages (TAM) exert essential functions during the immune response to cancer. However, investigations of TAM within a native human tumor microenvironment (TME) have been impeded by a lack of appropriate model systems. Here, patient-derived organoids (PDO) from air-liquid interface (ALI)-grown tumor fragments, containing a human TME that encompassed stroma and immune subsets, robustly preserved TAM that were maintained by endogenous CSF-1 and appropriately responded to polarization signals. Antibody blockade of the CD47 regulatory checkpoint in organoids stimulated phagocytosis and remodeled TAM cytokine secretion profiles that were confirmed in anti-CD47 phase I trial patients. Amongst PDO histologies screened, anti-CD47 tumor killing was notable in clear cell renal cell carcinoma (ccRCC) which was associated with increased TAM infiltration. PDO contained diverse previously described TAM subsets; however, anti-CD47 reprogrammed organoid TAM toward an immunosuppressive SPP1+ phenotype, highlighting a negative feedback mechanism. Our findings uncover a resistance circuit engaged by macrophage checkpoint blockade and position ALI PDO as a robust translational platform for dissecting human macrophage biology and informing precision immunotherapy.

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.

The DNA damage response (DDR) is critical for pancreatic ductal adenocarcinoma (PDAC) development and therapeutic responses, including to genotoxic agents. While epigenetic modulators have been shown to contribute to the DDR, how chromatin regulation dictates responses to DNA damage in PDAC remains incompletely understood. Here, we identify Class I histone deacetylases (HDACs) as critical regulators of the DDR. HDAC1/2 directs the genomic distribution of H3K27ac, ensuring sufficient BRD4 and RNA polymerase II (Pol II) occupancy at DDR gene promoters. HDAC inhibition by entinostat shifts the balance of H3K27 acetylation preferentially towards intergenic regions, diverting BRD4 and Pol II from promoters, thereby suppressing DDR gene expression. In line with this, HDAC inhibition heightens DNA damage and sensitizes PDAC to diverse DNA-damaging and DDR-targeting agents. Since the clinical development of HDAC inhibitors has been limited by systemic toxicity, we developed bottlebrush prodrug (BPD) nanoparticles for tumor-selective entinostat delivery. Entinostat-BPD achieved tumor-specific HDAC inhibition while displaying potent efficacy and reduced systemic toxicity. These findings reveal an HDAC-dependent DDR vulnerability and offer combinational and precision targeting strategies to facilitate clinical translation and improve PDAC patient outcomes. SIGNIFICANCE STATEMENTThe ability of tumor cells to tolerate DNA damage limits the efficacy of many anticancer therapies. Our study reveals that pancreatic cancer cells enforce this resistance by sustaining expression of DNA damage response (DDR) genes through Class I histone deacetylases (HDACs). HDACs maintain genome-wide acetylation patterns required for efficient recruitment of the transcriptional machinery to DDR genes. Pharmacological HDAC inhibition disrupts this process and sensitizes pancreatic cancer cells to diverse DNA-damaging agents. To overcome systemic toxicity that limits translational potential, we further establish a bottlebrush prodrug nanoparticle platform that enables tumor-selective HDAC inhibition. Given the central role of the DDR in cancer, targeting HDAC-mediated DDR regulation through drug combinations and precision delivery may have broad therapeutic relevance across cancer types.

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.

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.

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.

The metastatic progression of breast cancer involves complex interactions between tumor cells and immune cells, including T cells that exert cytotoxic pressure to limit metastasis. Tumor cells reprogram their metabolism to evade immune surveillance, a critical step to achieving metastatic outgrowth. Using an unbiased CRISPR screen targeting metabolism-related genes and a clinically relevant spontaneous metastasis mouse model, we identified CPT1A, the rate-limiting enzyme in fatty acid {beta}-oxidation, as a suppressor of immune-dependent metastasis. Loss of CPT1A enhances lung metastasis in immunocompetent mice, but not Rag1 KO mice that lack mature lymphocytes. Loss of CPT1A triggers cytosolic mitochondrial DNA (mtDNA) release via the mPTP pore. Cytosolic mtDNA release triggers a STING-dependent inflammatory response, creating an environment that impairs CD8+ T cell function, promoting metastatic outgrowth. Among breast cancer patients, low CPT1A expression correlates with poor survival when CD8+ T cell infiltration is high. These findings reveal an extrinsic role for CPT1A in immune-tumor dynamics and suggest therapeutic opportunities targeting inflammation in metastatic breast cancer.

Multiple myeloma (MM) orchestrates immune evasion by subverting natural killer (NK) cell function. CD48, one of the most abundant NK-ligands on MM cells, paradoxically enhances NK-cell activation yet is associated with high-risk cytogenetics and poor patient survival. We integrated multi-omics (bulk and single-cell RNA-seq, ATAC-seq), genome-wide CRISPR-KO/a screens, and machine learning to dissect CD48 regulation and function. In human MM and V{kappa}*MYC mice scRNA-seq datasets, NK cells exhibit stepwise increases in inflammatory and exhaustion signatures and loss of cytotoxic potential as disease progresses. In vitro co-culture assays show CD48 overexpression on MM enhances initial NK-cell cytotoxicity and cytokine secretion, whereas chronic exposure leads to ex vivo NK dysfunction. In vivo, CD48-overexpressing V{kappa}*MYC tumors progress more slowly and extend host survival, while NK-cell depletion accelerates disease. These findings support a context-dependent role for CD48, potentiating acute NK responses while coexisting with chronic NK exhaustion, and suggest strategies to modulate CD48 for therapeutic benefit.

Cancer cachexia is a wasting syndrome that remodels the anatomy of the patient. How this remodeling unfolds across tissues, whether it defines distinct disease states, and how these states relate to underlying biology remain unknown. We used longitudinal computed tomography imaging from 4,516 patients to quantify evolution of muscle, adipose, and organs during cachexia. Across two independent institutional cohorts, unsupervised analysis identified three reproducible anatomical subtypes of cachexia, including an inflammatory Type A marked by progressive hepatosplenic enlargement and inferior survival, a Type B dominated by visceral organ atrophy, and a mild Type C. These anatomical subtypes were associated with distinct serological signatures and reflected in molecular phenotypes in tumors and non-cancerous liver tissue, establishing cachexia as discrete anatomical disease states that link whole-body remodeling to systemic and tissue-level biology. This anatomy-first framework for cachexia classification provides a foundation for future patient stratification and development of subtype-specific anti-cachexia therapies.

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.

The epidemiological surge of early-onset colorectal cancer (EOCRC) is characterized by accelerated biological kinetics and disproportionately high rates of systemic relapse following curative-intent surgery. Because standard anatomical staging (TNM) lacks the resolution to accurately capture the intrinsic regenerative capacity of microscopic residual disease, we investigated the transcriptomic architecture of post-surgical failure in a strictly defined, curative-intent clinical pan-cohort. Unbiased transcriptomic profiling of the localized (M0) discovery sub-cohort identified IGF2 as the most significantly upregulated correlate of metachronous relapse. High-resolution isoform analysis revealed that this transcriptional output is predominantly driven by the embryonic (P4) and placental (P5) promoters. Systematic allele-specific expression (ASE) analysis supported widespread biallelic IGF2 expression consistent with relaxation of imprinting-domain control. This signal was not restricted to relapsing tumors, suggesting a recurrence-independent oncofetal baseline across the EOCRC spectrum. Because this foundational epigenetic unlocking is functionally insufficient on its own to execute systemic metastasis, we distilled the additional transcriptional plasticity required for dissemination into an internally derived and bootstrap-stabilized 5-gene recurrence-risk module Multivariable analysis across the combined pan-cohort supported an independent association between the high-risk module and systemic relapse (p < 0.001), capturing prognostic dimensions completely unresolved by classical pathological covariates and baseline staging. Ultimately, our findings reframe EOCRC aggressiveness as the product of a dual-hit architecture. This framework resolves the clinical paradox of widespread IGF2 LOI co-existing with heterogeneous outcomes, offering a biologically grounded basis for molecular risk stratification beyond anatomical boundaries.

Metastatic castration-resistant prostate cancer (mCRPC) remains lethal as adaptive resistance to standard-of-care therapy develops, often driven by AR splice variants alongside transcriptional and translational reprogramming. To identify strategies capable of overcoming these mechanisms, we performed an unbiased high-throughput screen of 2,480 mechanistically annotated compounds across advanced prostate cancer models. Exportin-1 (XPO1)-mediated nuclear export emerged as a critical dependency, and matrix-based combination screening uncovered robust synergy between inhibitors of XPO1 and the translation initiation factor EIF4A1. Dual inhibition induced coordinated disruption of oncogenic protein networks, including AR/AR-V7, triggering apoptosis and suppressing cell-cycle and metabolic programs. These effects extended to genetically diverse patient-derived organoids and in vivo xenografts at low doses, approximately 8-fold (Eltanexor) and 12-fold (Zotatifin) below established human single-agent regimens. Together, these findings reveal concurrent control of nuclear export and protein translation as a therapeutic vulnerability in mCRPC, providing a strong rationale for clinical evaluation of XPO1-EIF4A1 co-inhibition to overcome AR-driven resistance. STATEMENT OF SIGNIFICANCEUnbiased combinatorial screening reveals co-inhibition of nuclear export and translation initiation as a vulnerability in metastatic castration-resistant prostate cancer. Dual targeting of XPO1 and EIF4A1 drives synergistic collapse of oncogenic protein networks, including AR/AR-V7 signaling, to overcome key resistance mechanisms and induce potent antitumor responses across heterogeneous models. Notably, these effects are achieved at substantially reduced doses using clinically tractable agents, defining a mechanistically grounded therapeutic strategy poised for rapid clinical translation.

Black women are at risk for breast cancer nearly a decade before women of other racial groups for unclear reasons. Because immune responses influence cancer initiation and progression, we performed single-cell RNA sequencing of peripheral blood mononuclear cells from non-Hispanic Black (NHB) and non-Hispanic White (NHW) women with high-risk breast lesions, ductal carcinoma in-situ, and invasive breast cancer. Race-associated transcriptional differences were observed across all disease states and were most pronounced in invasive disease. Computational analyses, supported by flow cytometric protein analysis, revealed enrichment of chronic inflammation, immune regulatory programs, and immune aging pathways in NHB cancer patients, particularly in monocytes, dendritic cells, CD4+ T cells, and B cells. From these data, we derived a population-level immune signature (IMM-POP) comprising genes differentially enriched in this subset of immune cells from NHB breast cancer patients. IMM-POP correlates with an immunosuppressive signature in external breast cancer datasets. We thus provide a single-cell peripheral immune atlas integrating race and breast disease state. SignificanceThis study revealed race-specific peripheral immunity features in precancerous and invasive breast cancers: Black patients exhibited features of chronic inflammation and immune aging compared with White patients, suggesting immune weathering and providing insights for studying early onset of breast cancer in Black patients.