Search Results (238)

Background: Endometrial carcinoma (EC) is now classified primarily by molecular subtype—POLE-ultramutated, mismatch repair–deficient (dMMR), TP53-mutant/copy-number-high (CNH), and “no specific molecular profile” (NSMP)—a framework that has reshaped prognostic counseling and adjuvant therapy decisions. Yet several practically important questions remain insufficiently addressed in real-world cohorts: whether all four mismatch repair genes confer an equivalent favorable prognosis, whether all POLE alterations carry the same survival benefit or only specific pathogenic variants, and whether molecular subtypes retain prognostic value after adjustment for histology and tumor burden. Methods: We addressed these questions in 2901 patients pooled from the MSK-IMPACT 50K Clinical Sequencing Cohort (n = 2372; discovery) and the TCGA UCEC PanCancer Atlas (n = 529; validation)—the largest dual-cohort genomic analysis of EC reported to date. We performed individual MMR gene and combined dMMR survival stratification, multivariable Cox regression adjusted for age, histology, and sample type, and a pathogenicity-aware sensitivity analysis for POLE variants, with tumor mutational burden (TMB) compared across subgroups. Results: Across both cohorts, all four MMR gene–mutant subgroups (MLH1, MSH2, MSH6, PMS2) conferred equivalently favorable overall survival (OS) (six-group log-rank p = 7.66 × 10⁻¹² in discovery; p = 6.78 × 10⁻³ in validation), confirming dMMR as a class-level prognostic designation independent of which MMR gene is altered. Multivariable Cox regression demonstrated that POLE-ultramutated status retained an independent favorable effect (HR = 0.62, p = 0.038 in MSK; HR = 0.35, p = 0.028 in TCGA) after adjustment for age, histology, and sample type, while the favorable dMMR effect was largely accounted for by histologic context. Critically, a pathogenicity-aware sensitivity analysis revealed that the exceptional survival of the POLE subgroup is confined to canonical exonuclease-domain hotspot mutations (event rate 0.9% in MSK), whereas POLE variants of uncertain significance behave indistinguishably from NSMP-like tumors. Consistent with this finding, TMB was markedly elevated in canonical pathogenic POLE cases (median 138.7 mut/Mb in MSK; 247.4 in TCGA) but not in POLE-VUS-only cases (median 29.0 and 15.0, respectively; p < 0.001 between groups in both cohorts), confirming that the ultramutator phenotype is confined to canonical pathogenic POLE variants. We additionally characterize Uterine Clear Cell Carcinoma as a distinct histologic entity (n = 73; 3.0%) and report the POLE + TP53 co-mutant group (n = 90; 3.8%). Conclusions: These findings refine the molecular classification of EC in clinically meaningful ways: they support class-level immunotherapy eligibility based on dMMR status regardless of the specific MMR gene altered, demonstrate that POLE-ultramutated classification requires variant-level pathogenicity assessment, and identify TP53-mutant/CNH patients as the population with the most urgent unmet therapeutic need. Full article

Background: Human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) generally has a more favorable prognosis compared to HPV-negative cases. Overexpression of p16^INK4a is widely used as a surrogate marker for HPV-induced carcinogenesis, and it also represents an important tumor suppressor gene, the second most frequently altered after TP53. In turn, mutations in TP53 are characteristic of tumors linked to smoking and alcohol consumption and p53 expression is consistently associated with worse clinical outcomes. Aims: Investigate the impact of p53 immunohistochemical expression on prognosis of OPSCC. Methods: This retrospective study included 155 OPSCC patients with longitudinal follow-up exceeding 10 years. Immunohistochemistry was used to evaluate p53 protein expression. Clinicopathological associations were performed to evaluate the prognostic impact of p53 protein expression in OPSCC HPV-positive and HPV-negative tumors. Results: Among the 155 OPSCC cases, 90 (58.1%) were classified as HPV-positive and 65 (41.9%) as HPV-negative. HPV status was inversely associated with p53 positivity, with HPV-negative tumors showing a higher frequency of p53 expression (p < 0.0001). Patients with HPV-positive tumors experienced better clinical outcomes than those with HPV-negative disease, including cancer-specific survival (CSS; HR: 3.47, 95% CI 1.16–10.4, p = 0.02) and disease-free survival (DFS; HR: 3.73, 95% CI 1.29–10.7, p = 0.01), whereas p53 positivity alone was not independently associated with survival. Notably, individuals with HPV-negative and p53-positive tumors exhibited the poorest outcomes, in contrast to patients with HPV-positive OPSCC, regardless of p53 expression. Conclusions: Patients with HPV-negative and p53-positive OPSCC showed inferior clinical outcomes compared with their HPV-positive counterparts, independent of p53 status. These findings underscore the prognostic relevance of jointly evaluating HPV status and p53 expression in OPSCC and support more refined risk stratification and personalized therapeutic strategies. Full article

Background: Gliomas are characterized by a high degree of molecular heterogeneity, which impairs the reproducibility of predictive biomarkers derived from bulk-based molecular profiling due to immune/stromal contamination of tumors and the high prevalence of the IDH mutation signature. Methods: In this study, we used MOFA+ to derive intrinsic molecular signatures from transcriptional, methylation, and genomic profiles of a cohort of 667 diffuse gliomas in the Cancer Genome Atlas database. Thereafter, factor scores were derived for two separate Chinese Glioma Genome Atlas batches (Batch 1, n = 325; Batch 2, n = 693) without any retraining on the model. The prognostic independence of identified molecular signatures was assessed using multivariable Cox regression adjusted for IDH mutation status and tumor purity; purity-residualized survival analyses; IDH-stratified Cox regression in each cohort; validation by concordance index against established molecular signatures; and survival extreme profiling. To characterize the biological significance of factor signatures, we projected gene set signatures corresponding to each factor signature onto a single-cell RNA-seq dataset of GBM (GSE131928). Results: MOFA+ identified 12 latent factors, of which a vascular–extracellular matrix (ECM) remodeling axis (Factor 1) explained the highest multi-omics variance (24.9%) and was the strongest independent prognostic factor. In multivariable Cox regression adjusting for IDH status and tumor purity, Factor 1 remained independently prognostic (HR = 1.67, 95% CI 1.27–2.20, p = 0.0002); in a fully-adjusted model additionally including age, WHO grade, MGMT methylation, and 1p/19q codeletion (plus radiotherapy and chemotherapy status in the CGGA cohorts), Factor 1 remained prognostic in both CGGA cohorts (CGGA1: HR = 1.50, p = 3.8 × 10⁻⁵; CGGA2: HR = 1.18, p = 0.003) but lost significance in TCGA (HR = 1.04, p = 0.83), consistent with the cohort-dependent magnitude reported in the IDH-stratified and meta-regression analyses below. Purity-residualized survival analysis showed negligible attenuation of the Factor 1 signal (raw HR = 3.57 vs. residualized HR = 3.72; concordance 96.5%). Within IDH-wildtype gliomas, Factor 1 was significant in both external validation cohorts (CGGA1: HR = 1.64, FDR = 4.6 × 10⁻⁶; CGGA2: HR = 1.20, FDR = 0.02), though the TCGA IDH-wildtype subgroup showed a trend that did not survive FDR correction (FDR = 0.060). All validation was performed without model retraining. Within IDH-mutant gliomas, Factor 1 was strongly prognostic in both CGGA cohorts but was not significant in TCGA (HR = 1.17, FDR = 0.33). These findings should therefore be interpreted as consistent in directionality across cohorts but not uniformly replicated at the FDR-adjusted significance threshold in the TCGA discovery dataset. Concordance index benchmarking on a matched subset (n = 503) showed Factor 1 achieved discrimination comparable to the Mesenchymal signature (C = 0.797 vs. 0.801; ΔC = −0.004) while outperforming four other established classifiers. Factor 1 consistently separated patients with extreme survival phenotypes (OS < 6 vs. >15 months) across all three cohorts (all log-rank p < 0.001). Projection onto a single-cell GBM atlas (GSE131928), supported by inferCNV-based malignant-cell classification, localized the Vascular–ECM program to malignant cells and the Immune–ECM axis to myeloid compartments. Conclusions: The Vascular–ECM axis is a consistent, prognostic program robust to purity adjustment for diffuse gliomas that remains relevant across IDH-defined subgroups in three independent datasets comprising 1685 patients. The Vascular–ECM axis is a reproducible, purity-robust prognostic program in diffuse glioma, with directionally consistent adverse effects across TCGA, CGGA Batch 1, and CGGA Batch 2 (pooled n = 1685). Given the strong co-loading of endothelial, ECM, and myeloid genes observed in the single-cell projection, Factor 1 is best interpreted as a vascular/ECM-associated tumor–microenvironment ecosystem program rather than a malignant-cell-autonomous signature. Its FDR-adjusted significance within IDH-stratified subgroups is cohort-dependent and robust in both CGGA cohorts but attenuated in the TCGA IDH-wildtype (FDR = 0.060) and TCGA IDH-mutant (FDR = 0.33) strata. The pooled signal should therefore be interpreted as evidence of a generalizable biological program rather than a uniformly replicated subgroup-specific biomarker. It is possible to calculate factor scores based on RNA sequencing alone using fixed loadings (Z = XWᵀ), which may have implications for future translational applications. All findings are correlative; a causal role for the Vascular–ECM program in glioma progression, invasion, or therapy resistance remains to be established through functional perturbation experiments. Full article

Breast cancer has emerged as the preeminent global health crisis in oncology, currently standing as the most frequently diagnosed malignancy among women worldwide. Establishing novel predictive biomarkers is paramount to truly personalize treatment approaches, minimize unnecessary toxicity, and significantly improve long-term outcomes for patients with breast cancer. Breast cancer transcriptomic datasets were retrieved from the Gene Expression Omnibus and processed through standardized normalization procedures. Mutation-driven regulation of SYTL4 expression, treatment response to trastuzumab, cancer hallmark enrichment, and survival associations were evaluated using established bioinformatic tools and enrichment analysis based on integrated cancer hallmark gene sets. Additionally, DNA methylation profiles were analyzed. Herein, it is shown that SYTL4 mRNA expression is significantly (p = 2.01 × 10⁻⁴) diminished in breast cancer bearing BRCA1 mutations, suggesting a mechanistic interplay between BRCA1-driven genomic instability and SYTL4-regulated signaling cascades. Kaplan–Meier survival analysis demonstrated that elevated SYTL4 mRNA expression is significantly associated with improved overall survival in HER2-positive breast cancer patients (HR = 0.72; p = 0.034). Consistently, SYTL4 expression was significantly higher in patients who responded to trastuzumab therapy, supporting its potential as a biomarker of therapeutic response. Epigenetic analysis further revealed significant differential DNA methylation of SYTL4 between tumor and unaffected control tissues (p < 2.2 × 10⁻¹⁶), with region-specific hypomethylation in tumor regulatory regions. KEGG pathway and cancer hallmark enrichment analyses indicated that genes with prominent methylation changes are involved in cytokine signaling, growth factor pathways, and extracellular matrix remodeling, with the strongest associations observed for hallmarks related to genome instability, replicative immortality, resisting cell death, and metabolic reprogramming. In summary, we present that the gene SYTL4 is a prospective biomarker for survival and trastuzumab treatment responsiveness. Our observations posit that SYTL4 expression may signify a biological milieu conducive to sustained HER2 reliance and amplified therapeutic vulnerability. Full article

Glioma prognosis is shaped by molecular markers such as IDH mutation, WHO grade, and MGMT methylation, yet heterogeneity persists within defined subgroups. Sidekick Cell Adhesion Molecule 1 (SDK1), an immunoglobulin superfamily member mediating homophilic adhesion, has been documented in glioma tissue but lacks systematic prognostic evaluation. I assessed SDK1’s prognostic value using the Chinese Glioma Genome Atlas (CGGA, N = 503) and The Cancer Genome Atlas (TCGA, N = 572) through multivariate Cox regression, subgroup analyses, differential gene expression, pathway enrichment, ssGSEA-based immune profiling, and molecular subtype association. High SDK1 expression was independently associated with poor overall survival in both cohorts (CGGA: adjusted HR = 1.48, 95% CI 1.16–1.89, p = 0.002; TCGA: HR = 1.76, 95% CI 1.19–2.61, p = 0.005; pooled HR = 1.55, I² = 0%). Effect estimates varied across subgroups, with significant associations in WHO grade IV and IDH-wildtype strata but not in grade II or older patients. Cross-validated differentially expressed genes were enriched in extracellular matrix organization and focal adhesion pathways. Notably, SDK1 expression showed weak but statistically significant correlations with COL1A1-associated mesenchymal program scores (CGGA: R = 0.12, p = 0.008; TCGA: R = 0.15, p < 0.001) and oncostream-related gene signatures (CGGA: R = 0.16, p < 0.001; TCGA: R = 0.086, p = 0.039), suggesting a modest association with mesenchymal invasion programs. SDK1-high tumors showed elevated M2 macrophage and Treg signatures with upregulated immune checkpoints, though cohort-dependent differences were observed. Multivariate Cox analysis demonstrated that the prognostic significance of SDK1 is independent of tumor mutational burden (TMB), with no significant correlation or interaction observed between them (p > 0.05). SDK1 is a candidate prognostic biomarker in glioma co-occurring with ECM remodeling and immunosuppressive features, warranting experimental validation for clinical translation. Full article

Objective: Gastric cancer (GC) exhibits profound heterogeneity, yet the contribution of lactate metabolism reprogramming to this diversity and its cellular basis remain incompletely understood. This study aimed to dissect GC heterogeneity through lactate metabolism-related genes (LMRGs), with a focus on the cellular origins and context-specific functions of key genes. Methods: We performed consensus clustering of TCGA GC samples (n = 375) using a curated set of 49 LMRGs. A multi-step screening strategy was employed to identify hub genes. Single-cell RNA-seq data were integrated to map the cellular sources of key genes. Subtype-specific analyses of mutation, expression, and prognosis were conducted. A prognostic model was constructed, but its cross-platform generalizability was critically evaluated to explore the functional heterogeneity of its constituent genes. Results: We identified two distinct GC subtypes: G1, a glycolytic and immunosuppressive subtype associated with poor prognosis, and G2, an immune-activated subtype with better prognosis. Crucially, single-cell analysis revealed that the hub gene HK2 is enriched in NK cells and pDCs, while FABP4 exhibits a dual cellular origin, being expressed in both proliferative CD8+ T cells and fibroblasts. This dual origin provides a mechanistic basis for the gene’s context-dependent behavior: while FABP4 appeared protective in overall models, it acted as a significant risk factor within the G2 subtype (HR = 1.71, p = 0.017) and in an external validation cohort (HR = 2.64). A derived prognostic model failed external cross-platform validation, a phenomenon driven by the reversal of risk effects for FABP4 and other genes across different populations. Conclusions: This study uncovers two distinct metabolic-immune subtypes of GC and demonstrates that the prognostic effect of FABP4 is not fixed but is highly dependent on its cellular source and the tumor microenvironmental context. Our findings generate a testable hypothesis regarding FABP4’s role in balancing anti-tumor immunity and stromal promotion. More broadly, the failure of our cross-platform model serves as a cautionary tale on the limitations of single-cohort-derived signatures and underscores the necessity of integrating single-cell resolution to unravel the biological complexity underlying prognostic biomarkers. Full article

Classic Hodgkin lymphoma (cHL) is a distinctive B-cell malignancy defined by the presence of scarce but pathobiologically dominant Hodgkin Reed-Sternberg (HRS) cells within an inflammatory tumor microenvironment (TME). Although representing less than 10% of total tumor cellularity, HRS cells shape the TME by recruiting and functionally polarizing immune and stromal elements through cytokine- and chemokine-mediated signaling. Morphologically, HRS cells are large, atypical, often binucleated or multinucleated cells with prominent eosinophilic nucleoli and abundant cytoplasm, giving rise to the classic “owl’s eye” appearance. Distinct morphological variants—including lacunar, mummified, mononuclear, and anaplastic forms—contribute to the histopathologic diversity across cHL subtypes such as nodular sclerosis, mixed cellularity, lymphocyte-rich, and lymphocyte-depleted disease. The immunophenotype of HRS cells is equally characteristic, with strong and uniform CD30 expression, frequent CD15 positivity, reduced expression of B-cell markers (CD20, CD79A/B), and partial retention of PAX5, reflecting profound lineage dysregulation. Aberrant expression of activation markers and immune-evasion molecules, including PD-L1 driven by recurrent 9p24.1 amplification, underscores their capacity for immune escape. Genetically, HRS cells display alterations affecting NF-κB, JAK/STAT, and PI3K/AKT pathways, facilitated by somatic mutations, chromosomal gains, and epigenetic remodeling that silence B-cell-defining genes. Despite reprogramming, clonality and somatic hypermutation patterns confirm their origin from germinal center B-cells, even in EBV-associated cases. Collectively, the morphology, phenotype, and genotype of HRS cells reveal a complex pathogenic network in which intrinsic oncogenic pathways and extrinsic TME interactions co-operate to sustain malignant transformation. Understanding these integrated mechanisms provides a biological foundation for current therapeutic strategies. Full article

Uridine diphosphate glucuronosyltransferases (UGTs) are critical phase II detoxification enzymes; however, their mutational landscape and protective roles against chemical carcinogenesis in hepatocellular carcinoma (HCC) remain poorly defined. Here, targeted sequencing of ten liver-enriched UGT genes in 38 paired tissues from a Chinese HCC cohort revealed striking mutation frequencies in UGT2B15 (44.74%), UGT2B10 (36.84%), and UGT2B17 (26.32%). This genomic instability was accompanied by a profound downregulation of UGT2B15 mRNA (9.02-fold decrease, p < 0.001) and protein levels (Z-score = 2.32, p = 0.0093) in tumors, with higher UGT2B15 expression correlating with improved overall survival in TCGA cohorts (HR = 1.724, p = 0.012). Mechanistically, we identified the androgen receptor (AR) as a direct transcriptional regulator of UGT2B15 and UGT2B17, with dihydrotestosterone (DHT) inducing dose-dependent increases in their expression, thereby linking endocrine signaling to hepatic detoxification. Transcriptomic profiling following UGT2B15 knockdown in HCC cells revealed a significant enrichment in chemical carcinogenesis-related pathways. Crucially, UGT2B15 deficiency severely exacerbated carbon tetrachloride (CCl₄)- and ethanol-induced hepatotoxicity both in vitro and in vivo. Our study uncovers a profound impairment of UGT-mediated detoxification in HCC and establishes the AR–UGT2B15 axis as a critical barrier against chemical-induced liver injury, highlighting its potential as a chemopreventive target in carcinogen-exposed populations. Full article

Background/Objectives: Genetic testing in Human Epidermal Growth Factor Receptor 2-negative (HER2−) metastatic breast cancer (mBC) is necessary to enable optimal treatment choices including poly(ADP-ribose)polymerase inhibitors (PARPis). The present study evaluated the implementation of genetic testing in a real-world setting to reveal and subsequently allow targeting of potential inadequacies and risk factors for low testing frequency. Methods: We performed a retrospective analysis including HER2− mBC patients treated at a single academic center starting from 10 April 2019 (date of European Medicines Agency (EMA) approval of Olaparib for germline breast cancer gene mutant (gBRCAm) HER2− mBC) to 7 September 2021. The primary objective of the study was to evaluate the rate of HER2− mBC patients that were recommended to undergo genetic testing by the multidisciplinary tumor board (MTB). The secondary objective was to identify factors that were associated with a higher likelihood of having undergone genetic testing. Results: In total, 47.6% (109 of 229) of HER2− mBC patients had been recommended to undergo genetic testing by the MTB. Of these informed patients, 89.0% (97 of 109) underwent genetic testing, of which 11.6% (11 of 95) had a germline BRCA mutation (gBRCAmut) and were eligible for PARPi treatment. In multivariate analysis, younger age (p-value: 0.0007), hormone receptor positive (HR+)/HER2− subtype (p-value < 0.0001) and positive family history for breast and ovarian cancer (p-value: 0.0001) were significantly associated with the performance of genetic counseling. Conclusions: The present study demonstrated low genetic counseling rates of HER2− mBC patients, especially in individuals without specific risk factors for hereditary breast cancer. Informed patients showed a high willingness to undergo genetic testing. Genetic testing revealed targetable mutations in over 10% of tested patients. Full article

Fucosylation, the enzymatic addition of fucose residues to glycans, modulates receptor signalling and cellular identity in the intestinal epithelium. Its role as an integrative determinant of cancer cell fate in colorectal cancer (CRC) remains undefined. Transcriptomic and clinicopathological data from 976 CRC patients across three independent cohorts (TCGA-CRC, CPTAC2-CRC, Sidra-LUMC) were analysed. A curated fucosylation gene set was used to calculate tumour fucosylation scores. Associations with histogenetic status, genomic features, microenvironmental phenotypes, drug resistance programmes, and survival were evaluated using gene set enrichment analysis, multivariable Cox regression, and integrated molecular subtyping. High-fucosylation tumours exhibited elevated epithelial differentiation, MSI-H/BRAF-mutant enrichment, oxidative phosphorylation dominance, the complete absence of EMT and invasion programmes, and favourable prognosis (HR = 0.633, 95% CI: 0.470–0.853, p = 0.003). Low-fucosylation tumours demonstrated mesenchymal phenotypes, TP53 mutations, chromosomal instability, comprehensive multi-family RTK signalling, immune-excluded microenvironments, and poor outcomes. Distinct multidrug resistance programmes emerged: drug efflux in low-fucosylation tumours versus xenobiotic sensing, target bypass, and drug sequestration in high-fucosylation tumours. Tumour fucosylation status defines two fundamentally distinct CRC cell states with mutually exclusive engagement of invasion programmes, metabolic pathways, immune phenotypes, and resistance mechanisms. Fucosylation represents an independent prognostic biomarker and integrative determinant of cancer cell fate, with significant implications for risk stratification and personalised therapeutic strategies. Full article

Background/Objectives: Immune aging has been associated with survival outcomes in patients with lung adenocarcinoma (LUAD), but its relevance within the tumor microenvironment (TME) remains unclear. Methods: Clinical, RNA-sequencing, and somatic mutation data from the TCGA LUAD cohort were analyzed. Immune aging score within the TME was quantified using a predefined blood-driven 121-gene immune aging signature (IAS-121), and patients were categorized into the lowest versus the highest IAS-121 tertiles. Immune cell composition in the TME was inferred using xCell. Overall survival (OS) was evaluated using Kaplan–Meier analysis, Cox proportional hazards models adjusted for age, sex, tumor stage, smoking status, and EGFR mutation status, and restricted cubic spline analysis to examine the dose–response relationship between IAS-121 and mortality risk. Sensitivity analyses comparing the highest versus lowest quartiles or higher than median versus lower than median of IAS-121 were performed. Two independent LUAD cohorts (GSE68465 and GSE50081) were employed for validation. Results: A total of 518 patients with LUAD from the TCGA cohort were analyzed. Restricted cubic spline analysis showed a linear association between IAS-121 and OS. Patients in the highest IAS-121 tertile showed significantly better survival than those in the lowest tertile in both the TCGA cohort (p < 0.001) and the external validation cohorts (p = 0.003). In multivariable-adjusted Cox models, the lowest IAS-121 tertile was associated with worse survival in TCGA (adjusted HR 1.87, 95% CI 1.20–2.92) and in the pooled external cohorts (adjusted HR 1.57, 95% CI 1.02–2.43). Subgroup analyses showed generally consistent associations across clinical strata. Tumors with higher IAS-121 exhibited lower CD8⁺ and CD4⁺ naïve T-cell enrichment but higher neutrophil infiltration. Conclusions: Immune aging within TME is associated with poorer survival in LUAD. Given this study is hypothesis-generating, further investigations integrating tissue- and blood-based measures of immune aging are warranted to clarify its clinical and biological implications. Full article

The bone marrow tumor microenvironment (TME) is critical for acute myeloid leukemia (AML) progression, immune evasion, and treatment resistance. SRC, a non-receptor tyrosine kinase involved in multiple oncogenic pathways, has not been systematically characterized in AML in relation to prognosis and immune regulation. We integrated bulk transcriptomic and single-cell RNA-sequencing datasets from TCGA, BeatAML, and GEO. Immune-related targets were identified using xCell-based immune scoring and weighted gene co-expression network analysis (WGCNA), followed by protein–protein interaction analysis and multi-algorithm machine-learning screening. We then evaluated SRC expression patterns, prognostic associations, immune microenvironment features, predicted drug sensitivity, single-cell differentiation dynamics, intercellular communication, and in silico virtual knockout perturbation (scTenifoldKnk). SRC emerged as the most robust hub gene after integration of WGCNA, PPI analysis, machine-learning feature selection, and survival screening. SRC was significantly upregulated in AML compared with normal controls and was independently associated with poor overall survival (HR = 1.231, p = 0.037). High SRC expression was linked to adverse ELN/FAB features, increased immune checkpoint expression, enrichment of inflammatory and immunoregulatory pathways, and a higher proportion of primitive leukemia-associated cell states. Single-cell analyses further suggested that SRC was enriched in CD34⁺ progenitor compartments, associated with altered cell–cell communication, and accompanied by distinct mutation and pathway profiles. Drug-response prediction and in silico network perturbation analysis further supported the potential biological and translational relevance of SRC-centered programs. SRC is a prognostically relevant and immune-associated hub linked to AML microenvironment remodeling, and may serve as a candidate biomarker and potential therapeutic target that warrants further experimental validation. Full article

Chondrosarcoma (ChS) is a rare bone malignancy with heterogeneous behavior, the molecular and immunological background of which remains unknown. No effective systemic treatment for advanced ChS patients is available. The aim of this study was to develop an immune–mutational classification of ChS and to search for novel prognostic factors and molecular targets. We performed an immunological–molecular profiling of 99 patients diagnosed with primary ChS G1–G3 and dedifferentiated ChS. An expression of 20 immune response markers was assessed by IHC and targeted the next-generation sequencing of 409 genes was performed. Immunological and mutational profiles were correlated with overall survival using a multivariate LASSO-penalized Cox model. Three immunophenotypes were described—“cold” (IMP1), “hot” (IMP2), and “intermediate” (IMP3). IMP1 was the most prevalent in G1 cases, while IMP2 was the most prevalent in dedifferentiated cases. IDH1/2 or TP53 mutations were associated with high-grade ChS (FDR < 0.05). IMP2 was characterized by a higher number of immune infiltrates in the central region of the tumor (HR: 3.3; CI: 1.13–9.8; p < 0.05). IDH1 mutations were present most often in IMP2 cases (HR: 3.8; CI: 1.75–8.1; p < 0.001). Tumor size, dedifferentiated subtype, IDH1 mutation and the presence of IMP2 were identified as independent negative prognostic survival factors in ChS. An immune–mutational classification system for ChS patients was proposed, which may be used to identify those potentially suited for immunotherapy combined with IDH-mutant inhibitors in future research. Full article

The coatomer complex has been implicated in cancer progression; however, a comprehensive pan-cancer analysis is lacking. Therefore, it is essential to identify the critical roles and essentiality of coatomer genes across pan-cancer. We systematically profiled the genetic alterations, expression patterns, prognostic relevance, and functional dependencies of all coatomer subunits across multiple cancers using more than 10,000 tumor samples from The Cancer Genome Atlas, complemented by functional perturbation data from CRISPR (n = 1178) and RNAi (n = 707) screens in DepMap. Functional validation was also performed to identify the essentiality of selectively essential coatomer genes in hepatocellular carcinoma (HCC). Gene amplification, most notably of COPB2, was the most frequent alteration and was associated with poor survival in bladder and esophageal cancers. Mutations in COPA and SEC31A also demonstrated prognostic significance in endometrial carcinoma. Expression analyses revealed broad upregulation of coatomer genes across cancer types, with COPG1 and COPB1 emerging as strong risk-associated genes (HR > 2). Integrative functional dependency analyses identified COPG1 as selectively essential in multiple cancers, and its loss was associated with increased drug sensitivity. Functional validation in hepatocellular carcinoma revealed that COPG1 knockdown impaired malignant phenotypes and reduced tumorigenicity in vivo. Mechanistically, COPG1 depletion induced Golgi disruption and ER stress, increased ROS production, and suppressed PI3K–AKT signaling, thereby sensitizing cells to sorafenib and doxorubicin. Collectively, this pan-cancer analysis reveals the context-dependent roles of coatomer subunits and identifies COPG1 as a novel oncogenic driver and potential therapeutic target in HCC, mediating chemoresistance through redox modulation and PI3K–AKT pathway inhibition. Full article

Background: Mantle Cell Lymphoma (MCL) is an aggressive malignancy with variable clinical behavior, largely reflecting the underlying molecular heterogeneity. The genomic landscape of MCL encompasses gene mutations with strong prognostic implications and secondary genetic events, which are also implicated in the pathogenesis and prognosis of the disease. Methods: We evaluated the diagnostic samples of 73 patients with relapsed/refractory MCL that were enrolled in the Fondazione Italiana Linfomi Mantle First-BIO study. All patients had available data for correlating CNVs with the presence of TP53 mutation. Time to first relapse or progression of disease (POD) was used as the primary outcome measure. Results: We identified CNVs associated with MCL, with Del 9p21.3 (CDKN2A) being the strongest predictor of shorter time to POD (p = 0.01), independently of TP53 mutation in multivariable analysis. Unsupervised clustering identified molecularly defined clusters that were associated with significantly different times to POD (p = 0.01). Pairwise log-rank tests confirmed TP53 mutated vs. wild-type (WT) as the strongest prognostic factor, with cluster assessment improving the prognostic predictivity among patients: clusters TP53-mut vs. TP53-WT, p = 0.001, HR = 3.92; and p = 0.014, HR = 2.23, respectively. In conclusion, CNV-based molecular clusters might represent a novel approach to identify patients at higher risk of treatment failure, further contributing to the prognostic predictivity of TP53 mutation. Full article