Molecular Cancer

Colorectal cancer (CRC) screening remains limited by patient adherence and sub-optimal sensitivity for early-stage disease. While liquid biopsy has revolutionized cancer diagnostics, cfDNA-based methods often struggle with early-stage detection due to low analyte levels. Here, we present a robust cell-free RNA (cfRNA) platform for the early detection of CRC. Using a retrospective cohort of 255 healthy controls and 250 CRC patients, we implemented an optimized workflow featuring a RUVg-based normalization strategy to remove platelet-driven transcriptomic noise. We identified differentially expressed genes enriched in key CRC-associated biological pathways, including inflammation, EMT, and metabolic dysregulation. An XGBoost classifier trained on these features achieved a mean AUC of 0.92 in cross-validation and 0.89 in a validation cohort, demonstrating 67% sensitivity at 90% specificity. Notably, our platform showed particular efficacy in identifying early stage cancer (stage I and II), achieving 73.7% sensitivity at 90% specificity. These findings suggest that cfRNA profiling offers a powerful, non-invasive orthogonal approach to CRC screening, capable of overcoming the sensitivity limitations of DNA-based assays in early-stage disease.

While recent therapeutic advances have extended the survival of patients with non-small cell lung cancer (NSCLC), overcoming metastatic progression in the CNS remains a significant challenge. Some patients with NSCLC may require concurrent management of CNS and extracranial metastases, while others develop isolated brain metastasis or leptomeningeal disease. These heterogenous clinical outcomes are difficult to predict and diagnose for early intervention with current surveillance modalities. Herein, we comprehensively analyzed gene mutations, copy number variations, and DNA methylation of NSCLC brain metastasis tissue collected at the time of craniotomy, combined with ctDNA sequencing of paired plasma and CSF liquid biopsies. We confirmed a high concordance between the molecular features of brain metastasis tissue with ctDNA from CSF which were largely distinct from ctDNA alterations in paired plasma samples. Plasma ctDNA tumor fraction and ctDNA hypermethylation were most significantly associated with extracranial metastasis and overall survival. Alternatively, we identified specific hypermethylated DNA loci in brain metastasis tissue and CSF ctDNA as significant correlates of brain metastasis progression and risk of leptomeningeal disease. Our findings support the utility of integrating ctDNA testing from CSF and plasma, while revealing distinct epigenetic features and biomarkers of brain metastasis or leptomeningeal disease.

Colorectal cancer (CRC) is highly heterogeneous at both clinical and molecular levels, and the integration of circulating biomarkers with comprehensive genomic profiling remains limited. In this study, we measured circulating urokinase-type plasminogen activator (uPA) and its receptor (uPAR) in 53 patients with colorectal neoplasms and performed whole-genome sequencing (WGS) on matched tumor-normal pairs from 51 patients to characterize somatic mutations, copy number alterations (CNAs), tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and mutational signatures. Circulating uPAR levels were significantly elevated in patients with CRC compared with healthy controls, showing a stepwise increase across tumor stages and reaching the highest levels in stage IV disease. In contrast, circulating uPA levels showed only a non-significant trend toward elevation and did not vary significantly by stage. Despite the strong association between uPAR and tumor progression, circulating uPA and uPAR levels were not significantly correlated with TMB, MSI, HRD scores, or the mutational status of major CRC driver genes, including TP53, KRAS, FBXW7, BRAF, NRAS, and PIK3CA. Genomic analysis revealed a heterogeneous mutational landscape dominated by TP53 and APC, with only a minority of tumors exhibiting high TMB or MSI. Mutational signatures were primarily clock-like (SBS1, SBS5), with minimal contribution from MMR- or HRD-related processes. Together, these findings indicate that circulating uPAR is a robust marker of CRC progression that appears to operate largely independently of established genomic instability metrics. This supports uPAR potential utility in risk stratification and biological monitoring when integrated with molecular profiling.

RNAGAN (version 2.0, https://github.com/ZhaozhengHou-HKU/RNAGAN-2.0.git) is a published foundation model that analyzes single-cell and bulk-level RNA sequencing samples and enables multiple applications that enhance medical insights. Here we applied this model to Nasopharyngeal Carcinoma (NPC) as in-context few-short format (i.e., the model was never trained with any NPC data). We conducted all four supported functions, which include sample stratification, vectorization, pseudo data generation, and marker identification. The results were then used for identifying metastatic NPC and to investigate mechanisms associated with NPC metastasis. Examination with stratification showed that the accuracy of RNAGAN results for evaluating the metastasis risk in NPC patients are comparable to or outcompeted recently published risk estimation linear prediction model. Vectorization results present consistency across multiple cohorts and RNAGAN model versions. In the task of identifying markers and mechanisms related to NPC metastasis, incorporating pseudo data substantially enhanced the representativeness of single-cohort-based differential expression (DE) analysis. Moreover, RNAGAN identified metastasis-related marker genes based on single cohort, were concordant with the ground truth obtained across multiple cohorts (p=1.05e-9). Regarding biomedical mechanisms, RNAGAN enabled second-order feature extraction, unveiling a remarkable domination of the protective function of adaptive immune responses (as indicated by IL21R levels) over the hazardous function of chronic, non-resolving innate inflammation (as indicated by S100A8 levels) against NPC metastasis after first-line treatment. This association demonstrates a high degree of consistency with the external cohort. This study demonstrates the utility of the foundation model RNAGAN in uncovering therapeutic insights for novel cancer types without extra training. We reveal a critical spatial mechanism preventing distant metastasis via humoral anti-tumor immunity in NPC. High S100A8 expression by innate antigen-presenting cells (APCs) triggers an inflammatory cascade promoting epithelial-mesenchymal transition (EMT) and metastasis. However, when germinal center IL21R+ B cells simultaneously colocalize with these innate signals, they override this suppressive tissue stress. Spatial analysis shows that a high S100A8/IL21R intersection within tumor regions strictly distinguishes treatment responders, whereas non-responders display spatial mismatch or S100A8+ hyper-infiltration. This coordinated innate-adaptive cross-talk sustains functional tertiary lymphoid structures (TLS) that mature IgG-secreting plasma cells, which opsonize and eliminate emerging EMT tumor cells before systemic escape. Consequently, while S100A8 alone is an unreliable prognosticator, its spatial colocalization with IL21R is a robust protective indicator overlooked by conventional bulk analysis methods.

Peripheral whole-blood gene expression profiling offers a minimally invasive route to lung cancer detection, but high-dimensional transcriptomic data are prone to optimistic bias when preprocessing and model selection are not properly separated from performance evaluation. We applied L1-penalised (LASSO) logistic regression to 303 peripheral whole-blood microarray profiles (123 lung cancer cases and 180 healthy controls; Gene Expression Omnibus accession GSE252168; Illumina HumanHT-12 v4) within a leakage-free nested cross-validation framework (5 outer and 3 inner folds), in which all data-dependent steps (imputation, univariate feature screening by ANOVA F-test with k = 500, and standardisation) were confined strictly to training partitions. Statistical significance was assessed by permutation testing (B = 100), and feature selection stability was quantified across outer folds. LASSO was compared with ridge logistic regression, linear support vector machines, and random forest under the same framework. The LASSO model identified a sparse 29-probe signature with a pooled out-of-fold area under the ROC curve (AUC) of 0.990 (nested estimate 0.989 +/- 0.015), accuracy 97.4%, sensitivity 94.3%, and specificity 99.4% at a 0.50 threshold; permutation testing confirmed significance (p = 0.0099). Six probes, including CDC42, U2AF1, and RPS15A, were selected in all five outer folds, forming a stable core, and all classifiers exceeded AUC 0.987, indicating a strong, algorithm-independent signal. A leakage-free nested cross-validation framework enables unbiased performance estimation and reproducible feature selection in blood-based lung cancer classification. The 29-probe panel is an internally validated candidate requiring prospective, multicentre external validation before clinical use.

Lung cancer is a highly heterogeneous disease and remains the leading cause of cancer-related mortality worldwide. While mouse models and patient-derived organoids have advanced our understanding of lung cancer, key interactions within the tumor microenvironment (TME) remain poorly characterized. We developed microtumor models from lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) using mouse and patient samples, including surgical resections and rapid autopsy specimens. Microtumors preserve structural, cellular, and molecular features of the native TME, enabling mechanistic studies of tumor progression ex vivo. Multi-omics analyses of LUAD microtumors revealed progression-associated changes, including increased epithelial-to-mesenchymal transition (EMT) and metabolic reprogramming toward fatty acid synthesis. Pharmacologic inhibition of fatty acid synthesis through ACC1/2 reduced proliferation in patient-derived microtumors, identifying a targetable vulnerability. This platform provides a robust system for studying tumor progression, therapeutic response, and resistance mechanisms in lung cancer, including culturing postmortem specimens that are not accessible in current models.

Plasma-derived cell-free small non-coding RNAs are promising non-invasive biomarkers for cancer detection and monitoring. However, variability in sequencing output limits standardization, and cross-platform performance for plasma small RNA profiling has not been systematically evaluated. Illumina short-read sequencing is the current standard, whereas the newcomer, Ultima-Genomics platform, has been less extensively studied for circulating small RNA in plasma. To directly compare platform performance, we sequenced plasma cell-free RNA from 39 patients with pancreatic cancer and 39 matched controls on both platforms. After filtering, Ultima-Genomics retained more mature microRNA reads, whereas Illumina achieved slightly higher enrichment efficiency and mapping rates. Despite these technical differences, both platforms produced concordant expression profiles, with strong cross-platform correlations for shared microRNAs and clear separation of cases and controls within each dataset. Differential expression analysis identified 14 significant microRNAs on both platforms with concordant directions of change, most of which are supported by pancreatic cancer databases. Pathway enrichment analysis highlighted signaling pathways implicated in pancreatic cancer, supporting the biological relevance of both shared and platform-specific signatures. These findings indicate that both Illumina and Ultima Genomics platforms are suitable for plasma small RNA profiling and capture biologically relevant signals in pancreatic cancer.

BackgroundSingle-cell atlases have described diverse stem cell states in colorectal cancer (CRC), however, the overarching trajectories of those states and the underlying functional mechanisms, including their relevance for drug sensitivity, need better understanding. MethodsWe established 64 patient-derived organoids from microsatellite-stable colorectal cancers, characterized their transcriptomes and genomes, and performed drug screening with 62-140 clinically approved substances. We analyzed additional published transcriptome data from patient-derived organoids (72 patients from three independent datasets), TCGA-CRC data (466 patients), and single-cell transcriptomes of tumor biopsies (123,000 cells from six independent cohorts) to establish a functional and molecular landscape of CRC stem cells. We performed mechanistic follow-up analyses by mass-spectrometry-based proteomics, large-scale kinase inhibition assays and immunofluorescence analyses. ResultsWe find a continuous landscape of CRC stem cells that is characterized by distinct developmental programs: adult stem cell-to fetal-like regenerative states and transition between differentiation programs. By large-scale drug perturbations and multi-omics modeling, we identify a regenerative/fetal-like stem cell trajectory characterized by PI3K/mTOR dependency. We find the identified developmental axes conserved in organoid, clinical, as well as single-cell data, and the fetal-like PI3K/mTOR-dependent state to be associated with poor clinical prognosis. Mechanistically, PI3K/mTOR vulnerability is linked to a lack of adaptive capability due to suppressed mRNA translation and associated with an upregulated SRC signaling network. ConclusionsOur work moves beyond a molecular CRC landscape by combined functional perturbation analyses in organoids. This enables mechanistic modeling of stem cell state regulation and identifies an SRC/mTOR-dependent regenerative state in CRC, which might allow improved therapeutic targeting in the future.

Glioblastoma (GBM) is a highly lethal brain cancer with limited therapeutic durability, where the majority of patients develop recurrent or persistent disease after standard chemoradiotherapy. Meanwhile, tRNA-derived fragments (tRFs) have become increasingly relevant to cancer biology; however, their clinical relevance in GBM remains undefined. Here, we report that a specific family of tRFs, 5-tRNA halves (tiR5s) dominates the small RNA landscape of GBM patient tumors and associates with worse overall survival, post-therapeutic disease persistence, and pro-invasive proteogenomic pathways across two independent GBM patient cohorts. This association between elevated tiR5 levels and therapeutic resistance re-emerges in radiation-resistant GBM xenograft models. Our findings reveal that tiR5s are an underappreciated molecular feature of highly aggressive GBM tumors, supporting further investigation into their biological roles and prognostic utility in GBM. HighlightsO_LItiR5s are the predominant tRF family in primary GBM patient tumors C_LIO_LIElevated tiR5 expression distinguishes primary GBM tumors that develop persistent disease after first-line therapy C_LIO_LIRadiation-resistant GBM PDX models show elevated tiR5 expression C_LIO_LIElevated tiR5 expression associates with poor overall patient survival and pro-invasive molecular programs in GBM patient tumors C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/738483v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@184ddc1org.highwire.dtl.DTLVardef@1faadc2org.highwire.dtl.DTLVardef@a5ae02org.highwire.dtl.DTLVardef@1431506_HPS_FORMAT_FIGEXP M_FIG C_FIG

The role of cancer-associated fibroblasts (CAFs) in glioblastoma remains unclear, as their existence in the brain tumor microenvironment is still debated, given that the normal brain parenchyma is devoid of fibroblasts. It is unclear whether cells described as CAFs represent a distinct stromal population or a transcriptional state of perivascular cells such as pericytes. The aim of this study was to determine the identity, origin, and functional relevance of CAFs in glioblastoma. We analyzed 54 single-cell RNA sequencing datasets together with 88 bulk RNA sequencing samples. We identified a continuous transcriptional spectrum linking endothelial cells, pericytes, and CAFs, supporting pericytes as the most likely source of CAFs in glioblastoma. We further derived and validated robust CAF- and pericyte-specific gene signatures, enabling clear separation of these populations across cohorts. Reproducible CAF-associated ligand-receptor interactions were enriched in angiogenesis and immune modulation pathways. In bulk RNA-seq data, both CAF signature scoring and deconvolution consistently demonstrated increased CAF abundance in IDH-wildtype gliomas and further enrichment after chemoradiotherapy, while selective CYP1B1 expression in CAFs suggested a potential association with therapy-induced tumor adaptation. Overall, CAFs represent a distinct, pericyte-related stromal population in glioblastoma with conserved transcriptional and signaling programs. High CAF signature scores were associated with poorer overall and progression-free survival and were enriched in IDH-wildtype and post-chemoradiotherapy gliomas, suggesting a role for CAFs in therapy-associated remodeling of the tumor microenvironment in aggressive disease.

Primary tumor biopsy in retinoblastoma carries an unacceptable risk of extraocular dissemination. As a result, children treated with eye-sparing approaches currently lack access to tumor-derived genomic information at diagnosis, limiting accurate risk stratification, preventing subtype-guided therapy, and obscuring insight into tumor evolution during conservative treatment. Aqueous humor (AH) liquid biopsy has emerged as a promising window into circulating tumor DNA (ctDNA) from eyes managed conservatively, yet its ability to comprehensively capture the genomic and epigenomic landscape of retinoblastoma and to deliver clinically actionable molecular stratification has not been rigorously evaluated. We analyzed 18 matched AH-tumor pairs using genome-wide methylation profiling, copy-number analysis, and targeted sequencing. AH samples consistently contained high ctDNA fractions (median 0.65), enabling robust detection of single-nucleotide variants, canonical copy-number alterations, and methylation signatures defining established retinoblastoma subtypes. Importantly, promoter methylation patterns associated with RB1 inactivation and optic nerve invasion were confidently detected in AH, highlighting that liquid biopsy enables functional interrogation of disease-relevant genes and pathways. To enable biopsy-independent molecular classification, we developed a methylation-based machine learning classifier trained on combined AH and tumor datasets (n=114). The classifier demonstrated exceptional performance, with AUCs of 0.96-1.00 in cross-validation and 0.97-1.00 in independent validation across 63 additional retinoblastoma cases. Together, these findings position AH liquid biopsy as powerful, minimally invasive platform for comprehensive molecular profiling in retinoblastoma. This work establishes the first clinically viable non-invasive molecular stratification tool for the disease, enabling pretreatment risk assessment and paving the way for next-generation precision diagnostics in eye-preserving care.

Astrocytoma recurrence is shaped by genetic, epigenetic and transcriptional evolution, but how DNA remodeling is propagated into full-length RNA isoforms and coding consequences remains poorly resolved. Here we applied paired PacBio HiFi whole-genome sequencing and Kinnex full-length RNA sequencing to matched primary and recurrent astrocytoma from six patients, with matched blood controls. Recurrent tumors preserved core glioma driver identity while acquiring patient-specific remodeling across somatic variants, copy number, structural variation, loss of heterozygosity, haplotype imbalance and DNA methylation. Long-read transcriptomics revealed extensive recurrence-associated gene-expression, isoform-usage, differential transcript-usage and predicted ORF/protein-fate remodeling beyond gene-level expression. A denominator-aware integration framework showed that copy-number changes provide broad RNA-dosage links, whereas expressed somatic variants, allele/haplotype-specific transcript usage, methylation-linked isoform remodeling and structural variants generate more focused DNA-RNA-ORF chains. These findings establish longitudinal long-read multi-omics as a framework for prioritizing patient-specific remodeling trajectories and identifying targets for precision medicine in recurrent astrocytoma.

Background: Early detection of pancreatic ductal adenocarcinoma (PDAC) is critical. While faecal elastase-1 (FE-1) is a standard clinical marker for pancreatic function, its diagnostic accuracy for malignancy is limited. We sought to identify plasma metabolites that enhance FE-1 performance in symptomatic "at-risk" patients. Methods: Using the DEPEND cohort (CRUK C45617/A29908), plasma metabolomics was performed on patients with resectable PDAC (n=23) and healthy volunteers (n=24). Predictive modelling included feature selection and cross-validation, with further validation in an independent external cohort. Results: Citrulline was identified as significantly depleted in PDAC patients across discovery and validation cohorts. In isolation, Citrulline achieved an AUC of 0.86 (internal) and 0.88 (external validation). Standalone FE-1 demonstrated an AUC of 0.67. However, combining Citrulline and FE-1 significantly improved diagnostic performance, achieving a combined AUC of 0.96. Stratification revealed distinct metabolomic signatures associated with poorly differentiated tumours, suggesting a link to histological grade. Conclusions: Integrating Citrulline with FE-1 testing substantially improves PDAC detection in symptomatic patients. This non-invasive panel offers high diagnostic potential, though prospective validation is required to establish clinical cut-offs for routine practice.

Fibroblast heterogeneity shapes tumor progression, yet the transitional states linking normal-associated fibroblasts to cancer-associated fibroblasts (CAFs) remain poorly defined. Here, we integrated single-cell transcriptomic profiles of more than 90,000 stromal cells from 281 samples across nine cancer types to construct a pan-cancer atlas of fibroblast diversity. We identified a distinct CAF-like population positioned between normal-activated fibroblasts and established CAF subsets along the inferred fibroblast activation trajectory. Integration with single-nucleus chromatin accessibility data identified FOXF1 and FOXF2 as candidate regulators of this CAF-like state. Functionally, CAF-like fibroblasts were characterized by non-canonical WNT signaling, WNT5A-associated stromal communication, and a candidate GZMA-F2R/PAR immune-stromal signaling axis supported by spatial transcriptomic analysis. Clinically, the CAF-like signature demonstrated context-dependent prognostic relevance, with high expression associated with poorer survival in the tumor compartment of TCGA stomach adenocarcinoma. Together, this study identifies a FOXF1/FOXF2-associated transitional CAF-like fibroblast state and links it to stromal signaling, immune-stromal communication, and cancer type-specific clinical relevance.

TAOK3 is a lesser-studied MAPK family serine/threonine kinase our group has shown to be targeted by HPV integration, suggesting a potential role in driving invasive cervical cancer (ICC). Here, we profiled TAOK3 expression in patient tumors, metastases, and cervical cancer models and localized TAOK3 within a tumor epithelial subpopulation by integrating two single-cell RNA-seq datasets. Functional consequences of TAOK3 loss were assessed with siRNA and CRISPRi in cell lines and 3D spheroids. In vivo effects were evaluated in intracervical xenografts with species-specific RNA-seq to resolve tumor versus microenvironmental responses. TAOK3 mRNA/protein were elevated in primary and metastatic ICC and primarily localized to a keratin-positive epithelial subset (T3epi) enriched for cadherin/S100 binding, vesicle/endocytic pathways, and leading-edge programs. TAOK3 silencing reprogrammed transcriptomes and proteomes toward reduced WNT/cell-cycle and motility signaling, altered endocytosis and cytoskeleton organization, and reshaped phospho-networks linked to chromatin remodeling and ERBB2-ERBB3/cytoskeletal kinase activity. Functionally, TAOK3 inhibition prolonged G2/M, suppressed invasion, and enhanced sensitivity to low dose paclitaxel. Prolonged inactivation induced methuosis-like cell death with extracellular ATP release. In xenografts, TAOK3 knockdown reduced tumor burden, downregulated KRT14--a leader cell marker--within the human tumor compartment, and enriched microenvironmental pathways for immune activation, with a specific decrease in CD206+ M2 macrophages. TAOK3 delineates an invasion-competent epithelial state in ICC and coordinates cell-cycle control, cytoskeleton-membrane dynamics, and tumor-immune crosstalk. Genetic or pharmacologic TAOK3 inhibition constrains tumor growth, potentiates paclitaxel, and remodels the microenvironment toward anti-tumor immunity, supporting TAOK3 as a potential therapeutic target and biomarker in ICC. Statement of SignificanceTAOK3 marks an invasion-competent epithelial subpopulation in cervical cancer. TAOK3 inhibition slows tumor growth, enhances chemoresponse, and reduces M2 macrophages, revealing TAOK3 as a potential therapeutic target and biomarker for patient stratification.

Clinical-grade RAS inhibitors raise an unresolved question as to whether KRAS-alleles impose constraints on adaptive resistance that can be exploited therapeutically. Using daraxonrasib (RMC-6236), a multi-selective RAS(ON) inhibitor, we compared resistance mechanisms between KRASG12D and KRASG12R, alleles with fundamentally different RAS network dynamics. Daraxonrasib inhibited KRASMUT primarily through steric occlusion of effector binding, while engaging RASWT only modestly ([~]20%). KRASG12R is marked by its inability to transactivate RASWT, and it was observed that daraxonrasib resistant KRASG12R PDAC cells utilize EGFR/RASWT-GTP signaling as the dominant adaptive route. In contrast, KRASG12D resistance arose through retained KRASG12D-GTP signaling, with a decrease of cyclophilin A (CypA) protein, the binding partner required for daraxonrasib activity. The shift from KRASG12R dependence to the EGFR/RASWT conferred sensitivity to trametinib. We confirmed this clinically: a KRASG12R PDAC patient who progressed after 10 months on daraxonrasib showed intratumoral EGFR/RASWT activation, and rapid 3D-bioprinted patient-derived toroid modeling predicted sensitivity to trametinib-based combination therapy. Given the aggressive disease trajectory and lack of response to the two immediately preceding lines of therapy, sixth-line trametinib-based combination therapy achieved approximately 5 months of disease control. This patient ultimately achieved 40 months of overall survival, far exceeding the 8-12 month median for metastatic PDAC. Collectively, these data establish a framework in which allele-specific RAS network topology dictates the adaptive resistance landscape, enabling rational selection of targeted therapies with meaningful clinical benefit in metastatic PDAC. STATEMENT OF SIGNIFICANCEDaraxonrasib resistance mechanisms have allele-specific routes: CypA becomes downregulated in KRASG12D and reliance on EGFR/RASWT in KRASG12R. Rapid patient-derived toroids identified sixth-line targeted therapy strategies with an overall survival of 40 months.

Oral squamous cell carcinoma (OSCC) is an aggressive head and neck malignancy characterized by high morbidity, therapeutic resistance and intratumoral heterogeneity driven by plastic cell states. Given that metabolic inputs can shape cell identities via epigenetic mechanisms, we investigated how metabolism of a non-essential amino acid, serine, affects histone modifications with key roles in cell plasticity: H3K27me3, which represses differentiation genes, and H3K4me3 which activates stemness and epithelial-to-mesenchymal transition (EMT) genes. Using a panel of human OSCC patient-derived cell lines and an orthotopic murine isograft model, we show that OSCC cells depend on exogenous serine for proliferation. Dietary serine deprivation induced de novo serine synthesis with a concomitant increase in a-ketoglutarate (aKG), a cofactor for KDM6B and KDM5A/B demethylases of H3K27me3 and H3K4me3, respectively. RNA-seq-derived serine deprivation gene signatures revealed activation of keratinization program and suppression of EMT and proliferation genes and tracked with good OSCC patient outcomes in TCGA. Furthermore, CUT & RUN profiling showed site-specific losses of H3K27me3 at differentiation genes and reduction of H3K4me3 at stemness, EMT and cell cycle genes. However, inhibition of aKG with 2-hydroxyglutarate was not sufficient to rescue cell proliferation. Instead, genome-wide analysis revealed widespread H3K27me3-H3K4me3 bivalency, with extensive transcriptional repression of proliferation and oncogenic programs. Functionally, serine deprivation impaired orthotopic tumor growth and improved the immune landscape in syngeneic mice. Our studies identify a metabolic serine-aKG-KDM-H3K27me3/H3K4me3 bivalency axis that globally reprograms OSCC chromatin as a potential therapeutic strategy to impede tumor plasticity and evolution to advanced disease.

Young-onset lung cancer is enriched for never-smoking and oncogene-driven tumors, yet its inherited genetic basis remains poorly defined. We performed germline whole-genome sequencing in 251 young-onset lung cancer cases (median age 37), which we jointly analyzed with never-smoking cases (n=196; median age 68) and cancer-free controls (n=1,883). We identified enrichments of rare deleterious coding variants across 55 cancer-related gene sets, including EGFR/ERBB2 signaling and genes implicated by prior lung cancer GWAS. Exome-wide analyses of rare coding variants affirmed TP53 as a penetrant lung cancer predisposition gene (odds ratio [OR]=36.1, p=1.02x10-7) and discovered two novel exome-wide significant tumor subtype-dependent associations: IREB2 in cases with fusion-driven tumors (p=1.39x10-6) and SMAD6 in fusion-negative tumors (p=2.05x10-6). Structural variants contributed distinct risk, with enrichment in constrained, lung-expressed genes (OR=5.79, p=5.8x10-5) and very large germline deletions being markedly enriched in cases with fusion-driven tumors. Polygenic risk scores for lung cancer were inversely correlated with rare variant burden, consistent with additive risk from rare and common variants. Collectively, these findings delineate a complex germline architecture underlying susceptibility and molecular subtype in young-onset lung cancer.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense, desmoplastic microenvironment that drives disease progression, yet conventional models fail to capture this complex tumor-stroma coevolution. Here, we utilize the chick chorioallantoic membrane (CAM) platform to investigate tumor-stroma interactions using murine PDAC cell lines and patient-derived organoids (PDOs). Integrating single-cell RNA sequencing and spatial transcriptomics, we show that the CAM microenvironment supports the emergence of complex tumor ecosystems while preserving patient-specific characteristics. Within five days, in ovo tumors faithfully recapitulated the structural and molecular features of parental tumors. Histological analysis revealed the rapid recruitment and spatial organization of heterogeneous host cancer-associated fibroblast (CAF) populations, showcasing distinct myofibroblastic and inflammatory stromal states. Crucially, the model preserved intrinsic tumor heterogeneity and permitted functional interrogation of subtype-specific extracellular matrix remodeling and metastatic dissemination. Together, our findings demonstrate that the CAM provides a highly permissive niche for tumor-stroma coevolution. As a rapid, scalable, and biologically relevant platform, this in ovo model offers a powerful approach for studying stromal composition, metastatic progression, and patient-specific tumor biology in pancreatic cancer.

Scaffold integrity is essential for the activity of proteins that function through protein-protein interactions rather than catalytic output. RAF1 exemplifies this duality: although it is a bona fide kinase and a core component of the MAPK cascade, its tumor-promoting role is largely kinase-independent, relying instead on scaffold-mediated suppression of apoptosis. Genetic Raf1 ablation in KRAS-driven lung adenocarcinoma mouse models induces tumor regression without systemic toxicity, making it an attractive candidate for targeted protein degradation. Chemogenetic systems like the dTAG platform are widely used for preclinical target validation. Here, we generated a dTAG-RAF1 mouse model and showed that pharmacological degradation is efficient and systemically well tolerated, but fails to reproduce the tumor regression observed upon genetic Raf1 ablation. Mechanistically, the N-terminal FKBP12F36V tag (dTAG) perturbs the RAF1 interactome, including scaffold associations with apoptotic regulators, thereby blunting the phenotypic consequences of its degradation. These results establish scaffold integrity as a determinant of chemogenetic system fidelity and argue that degradation tools must be validated at the functional level, not only for target elimination, before assessing their therapeutic relevance.