Translational Oncology

Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive molecular complexity, profound stromal remodeling, and limited responsiveness to systemic therapies. Although gemcitabine-based regimens remain widely utilized, the molecular pathways that influence treatment-associated biological variation are incompletely understood. The TGF{beta} and JAK/STAT signaling networks are recognized regulators of tumor progression, immune modulation, and therapeutic resistance; however, their genomic architecture in clinically stratified PDAC populations remains poorly defined. Methods: We employed a conversational artificial intelligence-driven analytical framework to investigate TGF{beta} and JAK/STAT pathway alterations in a cohort of 184 PDAC patients. Clinical and molecular data were integrated to generate age- and treatment-stratified cohorts, enabling pathway-level and gene-level analyses according to gemcitabine exposure. Findings generated through AI-assisted interrogation were subsequently evaluated using conventional statistical approaches. Results: TGF{beta} pathway alterations were identified in approximately one-quarter to one-third of tumors across clinical subgroups and demonstrated relatively stable frequencies regardless of age at diagnosis or gemcitabine treatment status. Gene-level analyses revealed that pathway disruption was predominantly driven by recurrent alterations in SMAD4, with additional low-frequency events involving TGFBR1 and TGFBR2. Notably, TGFBR2 mutations were significantly more frequent among late-onset PDAC patients receiving gemcitabine compared with untreated late-onset patients (8.8% vs. 1.4%; p = 0.04), suggesting a potential treatment-associated enrichment. In contrast, JAK/STAT pathway alterations were rare throughout the cohort, with only isolated mutations observed in pathway components including JAK1, JAK2, JAK3, STAT1, STAT3, and related regulatory genes. No significant differences in JAK/STAT alteration frequencies were identified according to age or treatment exposure. Conclusions: TGF{beta} and JAK/STAT pathways exhibit distinct genomic architectures in PDAC. TGF{beta} pathway disruption represents a recurrent feature of disease biology, largely driven by SMAD4 alterations, while TGFBR2 enrichment in gemcitabine-treated late-onset tumors suggests a potential context-specific association worthy of further investigation. Conversely, genomic alterations within the JAK/STAT pathway are uncommon, indicating that pathway activity may be regulated predominantly through non-genomic mechanisms. These findings demonstrate the utility of conversational artificial intelligence agents for rapid, scalable, and clinically contextualized pathway interrogation and support future studies integrating multi-omic data to refine precision medicine strategies in PDAC.

BackgroundBreast cancer stem cells (BCSCs) contribute significantly to breast cancer (BC) mortality among women globally. It underpins tumor heterogeneity in BC by driving variations in stemness potential and altering immune microenvironment. However, how BCSCs, subpopulations of breast cancer cells from distinct molecular subtypes differentially modulate CD8 T-cell exhaustion and immune dysfunction remain unclear. MethodsWe conducted our study from patients with BC of four subtypes. MACS sorted (Lin-CD44+CD24-) BCSCs were prepared for mammosphere formation assay from mastectomies samples. Flow-cytometry was used to analyze breast cancer stem cells (BCSCs). Immunofluorescence, immunohistochemistry, Real Time and Reverse Transcriptase PCR array, Chromatin-immunoprecipitation assay, Transwell, ELISA, Western blotting, Cloning, Transfection, Knockdown, chromatin immunoprecipitation approaches were used to investigate the underlying mechanisms. ResultsHere, we report that BCSCs actively participate in tumor progression by modulating effector CD8 T-cells. Triple-negative breast cancer (TNBC), being the subtype with the most adverse outcomes, sustains the enrichment of stem cell regulating transcription factors like NANOG, OCT4 and SOX2 compared to HER2, Luminal B, and Luminal A subtypes. Tumor from TNBC patients exhibited an exhausted phenotype within CD8 T-cell infiltrates with PD1high TIM3high LAG3 high IFN{gamma}low signature. BCSCs induced increased proportion of exhausted CD8 T-cells, predominantly in the TNBC subtype. Cell-surface Notch1 expression was upregulated in BCSCs across all molecular BC subtypes, with the highest elevation observed in TNBC. Knockdown or inhibition of Notch1 downregulated stemness-associated genes and diminished CSC-mediated induction of CD8 T-cell exhaustion. Cumulatively, these findings suggest that assessment of high Notch1 and Nanog frequency within BCSCs can guide Notch1-targeted therapies and may formulate for new combinatorial treatment strategies to improve patient outcomes. Additionally, therapeutic targeting of BCSC-intrinsic NOTCH1-NANOG/NOTCH1-PD-L1 axis could represent an effective strategy to reduce stemness programs and alter BCSC-driven CD8 T-cell exhaustion, majorly in aggressive subtypes such as TNBC. ConclusionsBCSCs aggressiveness is perpetuated through Notch1-mediated axis. Targeting Notch1 would reduce stemness (majorly NANOG), survival, as well as prevent CD8 T-cell exhaustion (upregulating PD-1, TIM3, LAG3), thereby weakening tumor progression.

Background Patients with advanced pancreatic ductal adenocarcinoma (aPDAC) often experience general health decline at diagnosis due to a high-symptom burden. The optimal management of symptoms and/or poor performance status (PS) in these patients remains an unmet medical need. Patients and Methods In this multicenter study, patients with PS[≥]2 and pathologically confirmed or imaging-suspected aPDAC were included at first oncology visit in a personalized 14-day emergency integrative supportive care program (14-EISCP) to manage pain, nutrition, diagnostics, and stenting procedures. The primary endpoint was the 14-EISCP success in feasibility of planned procedures and clinical benefit defined as post-EISCP PS[≤]1, [≥]5 points improvement in fatigue, pain, global health-related quality of life (HRQoL) scores (EORTC QLQ-C15-PAL), or chemotherapy initiation within 30 days. Results A total of 106 patients were included; 93 evaluable patients considered for primary endpoint analysis (median age: 76 years [68-80], PS3: 20.9%, metastases: 61.3%). The median overall survival was 4.1 months (IC95% 2.6-5.6). The 14-EISCP was successful in 59.1% (n=55) of patients, meeting the primary objective (clinically relevant). The 14-EISCP feasibility was achieved in 70.9% of cases. Post-EISCP clinical benefit was observed in 79.6% of patients, with PS improvement to 0/1 in 13.2%, HRQoL improvement in 23.9%, and chemotherapy initiation [≤]30 days in 73.1%. Among evaluable patients, 17.2% received mFOLFIRINOX or gemcitabine-nab-paclitaxel, 35.4% received FOLFOX, 25.3% had gemcitabine or 5-fluorouracil alone, and 22.2% received best supportive care. In patients with PS2 at baseline, the administration of doublet/triplet chemotherapy was associated with improved overall survival compared to single-agent. Discussion These results offer a promising framework for improving outcomes in aPDAC patients, bridging the gap between symptom management and systemic therapy administration. Conclusions In patients with PS[≥]2 and aPDAC, the personalized 14-EISCP was feasible and lead to meaningful clinical benefit, allowing doublet or triplet chemotherapy in half the patients.

Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in early detection and treatment, up to 39% of patients develop recurrent tumors following complete resection. Currently, no widely available models exist for reliably predicting early recurrence of LUAD, which is a significant prognostic factor of post-recurrence survival. Models leveraging deep learning (DL) techniques have demonstrated notable utility in cancer recurrence prediction, particularly when used in combination with both clinical and genomic data. We developed a DL-based model, Predicting Lung Adenocarcinoma recurrence via Selective Multimodal Attention (PLASMA), to predict early recurrence using clinical, mRNA expression, and mutation data from patients with primary stage I-III LUAD. Trained on The Cancer Genome Atlas (TCGA) dataset, PLASMA outperformed traditional machine learning models in predicting early recurrence in both the TCGA test set and an external validation set (TRACERx Lung), achieving area under the receiver operating characteristic curve (AUROC) scores of 85.0% and 76.5%, respectively. Our results support the potential of multimodal DL for early LUAD recurrence prediction and risk stratification.

Introduction. TAC/SARIFA has been introduced as a new robust and easy-to-evaluate biomarker in several cancer entities, including colorectal cancer. It is defined by direct contact between at least five tumour cells and one adipocyte and is believed to indicate metabolic reprogramming associated with adverse outcome. However, the mechanism that leads to TAC/SARIFA positivity remains unclear. To investigate whether there is an individual component, we conducted a study on double and triple cancers, establishing a within patient design. Methods. We retrospectively analysed a total of 135 cases with 276 colorectal cancers from two academic medical centres. The TAC/SARIFA status was evaluated, as were the basic histopathological factors. The median follow-up time was 120 months. Results. Cases with any TAC/SARIFA positive tumours showed significantly reduced overall survival (62 vs. 88 months; p = 0.011). Analysing the entire cohort, the rates of concordant and discordant cases followed a random distribution. However, restricting the analysis to synchronous pT3/4 cases revealed a significant deviation from a random distribution (p = 0.016). Conclusion. This study reveals significant concordance of TAC/SARIFA status in synchronous locally advanced colorectal double/triple carcinomas, supporting the concept that tumour adipocyte interaction reflects a host related microenvironmental condition linked to metabolic reprogramming rather than a purely tumour intrinsic event.

Gastric cancer patients frequently experience skeletal muscle loss during the perioperative and adjuvant treatment period, which has been associated with poorer treatment tolerance and adverse clinical outcomes. Early identification of patients at high risk of skeletal muscle loss may allow timely supportive intervention, but repeated computed tomography assessment is not always practical in routine care. This study aimed to develop an interpretable machine learning model based on routinely available clinical data for early prediction of significant skeletal muscle loss in patients with gastric cancer. This single-center retrospective study screened 362 patients who underwent radical gastrectomy followed by adjuvant chemotherapy, of whom 292 were finally included. Significant skeletal muscle loss was defined as a decrease of at least 5% in skeletal muscle index between the baseline scan performed before surgery and the follow-up scan obtained 3 months after initiation of adjuvant chemotherapy. Candidate predictors included demographic, clinicopathological, laboratory, tumor marker, and inflammatory or nutritional variables, together with their early postoperative dynamic changes. Six machine learning models were developed and compared. Among the evaluated models, the multilayer perception showed the best overall performance in the validation set, with an area under the receiver operating characteristic curve of 0.757 and an area under the precision-recall curve of 0.745. At the selected decision threshold of 0.45, this model achieved an accuracy of 0.693, a recall of 0.833, and a specificity of 0.525. Compared with the model using baseline variables alone, the model incorporating longitudinal dynamic features showed better overall performance. Model interpretation suggested that prediction of skeletal muscle loss was mainly related to nutritional reserve, operation-related burden, and inflammatory or metabolic status. These findings indicate that routinely available preoperative and early postoperative clinical data can support early prediction of subsequent skeletal muscle loss in gastric cancer. This approach may help identify high-risk patients earlier and facilitate individualized nutritional support and supportive care during treatment.

Lung adenocarcinomas frequently harbour actionable oncogenic mutations that are vulnerable to treatment with targeted therapies. While responses to targeted therapies are often initially dramatic, relapse is almost inevitable and prevents durable responses in advanced-stage patients. Relapse is, in part, caused by drug tolerant persister cells (DTPs) which are able to survive treatment by entering a reversible, dormant state. Although long non-coding RNAs (lncRNAs) regulate processes thought to allow DTPs to survive and become stably resistant, the potential roles of lncRNAs in DTPs are largely unknown. In this study, we sought to investigate the expression of lncRNAs in in vitro DTP models of lung adenocarcinoma. We found that the lncRNAs Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1) and Nuclear Paraspeckle Assembly Transcript 1 (NEAT1) were enriched in DTPs and that knocking down MALAT1 enhanced the effect of targeted therapies in both EGFR- and KRAS-mutant DTP models. To better understand pathways that MALAT1 might regulate in DTPs, bulk RNA-sequencing was performed and several pathways that may contribute to the actions of MALAT1 in DTPs were identified. Overall, our work describes a role for the lncRNA MALAT1 in DTPs in NSCLC and suggests that MALAT1 may be a novel target for the prevention of drug tolerance and subsequent resistance to targeted therapy in NSCLC.

Triple Negative Breast Cancer (TNBC) is the deadliest and most aggressive subtype of breast cancer, with poor prognosis and high rates of metastasis. Despite knowledge of metabolic rewiring in TNBC, the systems-level coordination of these adaptive pathways remains unmapped. This integrative systems-level analysis reveals key metabolic hub genes and identifies ATP1A2 as a significant prognostic marker. Analysis identified 764 differentially expressed genes, with 89 enriched biological processes predominantly involving metabolic pathways. Co-expression network analysis of 261 genes identified metabolic hub genes including LEP, ADIPOQ, and ATP1A2. To evaluate the prognostic framework, survival analysis of the top 10 hubs was performed on synthetic survival data, revealing ATP1A2 as a significant marker (p = 0.03) under Cox regression, with elevated expression associating with altered survival outcomes. By systematically mapping metabolic rewiring in TNBC, this work identifies ATP1A2 as an actionable therapeutic target and establishes a systems-level framework for rational drug discovery and patient stratification in this aggressive malignancy.

Background: African Americans (AA) experience disproportionate burden of colorectal cancer (CRC). Dysregulation of the Wingless-related integration site (WNT) pathways contributes to tumor progression, yet their prognostic roles in FOLFOX-treated CRC among AA patients remain understudied. Methods: We analyzed 2,562 CRC cases stratified by ancestry, age at onset, and FOLFOX treatment using Fisher's exact, chi-square, and Kaplan-Meier analyses from AACR Project GENIE and cBioPortal databases. To enhance data integration and interpretation, we applied AI-HOPE and AI-HOPE-WNT, conversational artificial intelligence (AI) platforms designed to integrate clinical, genomic, and treatment data through natural language-driven queries. Results: Overall survival analyses showed that early-onset CRC (EOCRC) AA patients treated with FOLFOX who had WNT pathway alterations experienced significantly better survival (p = 0.035). WNT pathway alterations were less frequent in late-onset AA patients treated with FOLFOX compared to those not treated (80% vs. 92%; p = 0.05). Conclusions: Chemotherapy exposure may influence pathway-specific mutation frequencies across ancestry and disease stage. AI-enabled integrative analyses highlight the potential of conversational AI platforms to accelerate biomarker discovery and reveal ancestry- and treatment-specific vulnerabilities in CRC.

BackgroundFor pancreatic cancer, practical blood-based tests for early detection and postoperative surveillance remain elusive. We sought to develop a qPCR-measurable serum microRNA (miRNA) panel that robustly discriminates pancreatic cancer from non-cancer controls and other malignancies. MethodsWe profiled 255 serum miRNAs in batch 1 (n=72) and selected 27 candidates. Candidates were refined in batch 2 (n=552) and cross-batch evaluation was performed with batch 3 (n=391) to derive a miRNA model. Independent validation used batch 4 (n=616). Clinical relevance was assessed in an independent clinical cohort of resection patients with samples obtained preoperatively and at 1 and 12 months postoperatively. ResultsThe miRNA model trained on batches 2 and 3 achieved an area under the curve (AUC) of 0.91 and 0.83 for pancreatic cancer versus non-cancer controls and non-cancer plus other cancers, respectively, when independently validated in batch 4. Stage-wise AUCs in batch 4 were 0.91 (I), 0.94 (II), 0.86 (III) and 0.90 (IV). In the clinical batch, the score decreased postoperatively (preoperative vs month 1; p<0.01) and was higher in recurrence than non-recurrence (p<0.001). ConclusionsThe developed compact miRNA qPCR assay discriminated pancreatic cancer across independent assay batches and showed clinical relevance for postoperative surveillance. Clinical Trial RegistrationNot applicable.

IntroductionMTAP emerges as potential predictive biomarker for MTA-cooperative PRMT5-inhibitors. Although MTAP attracts increasing attention in non-small cell lung cancer, its role in pulmonary neuroendocrine neoplasms (NENs) remains largely unexplored. MethodsHere, we assessed the prevalence of MTAP deficiency in 209 pulmonary NENs using immunohistochemistry (IHC). Additionally, we performed fluorescence in situ hybridization (FISH), whole exome sequencing (WES), deep proteomic profiling, transcriptomic, and methylation analyses of selected MTAP deficient and proficient carcinoids to further elucidate the underlying mechanisms of MTAP expression pattern. ResultsMTAP deficiency by IHC was detected in all neuroendocrine precursor lesions (n=17), 92% of typical carcinoids (n=51), 86% of atypical carcinoids (n=21), and 10% of large cell neuroendocrine carcinomas (LCNEC) (n=30). In contrast, all small cell lung cancers (SCLC) were MTAP proficient (n=90). In MTAP deficient carcinoids, FISH and WES did not detect homozygous 9p21 deletions, and methylation analysis showed no evidence of MTAP promoter hypermethylation. Comparing MTAP deficient and MTAP proficient carcinoids, proteomic data showed a clear separation between the two groups. Further, there was an inverse correlation between the expression of MTAP and OTP (orthopedia homeobox protein), which is known as a strong prognostic marker in pulmonary carcinoids. DiscussionMTAP deficiency is a novel hallmark of neuroendocrine precursors and most pulmonary carcinoids, clearly distinguishing the latter from SCLC and most LCNEC. It is neither caused by 9p21 deletion, nor by MTAP promoter hypermethylation. MTAP deficiency is a group-defining feature of carcinoids that might pave the way for new therapeutic approaches.

ContextImmunotherapy based on immune checkpoint inhibitors (ICI) revolutionized the treatment of triple-negative (TN) breast carcinomas (BC), but remains more challenging in HR+/HER2- BCs. Because invasive lobular carcinomas (ILC) generally exhibit low immune infiltration, ICIs were largely overlooked in this pathological type. The only clinical trial of ICIs dedicated to ILCs showed disappointing results, notably in HR+/HER2- cases. The immune landscape of HR+/HER2- ILCs has been poorly described. High level of tumor-infiltrating lymphocytes (TIL) was associated with worse prognosis in HR+/HER2- ILCs. A better characterization of the immune landscape of HR+/HER2- ILCs could clarify the poor efficiency of ICIs and the negative prognostic value of TILs, and reveal complementary targets able to increase immunotherapy efficiency. MethodWe comprehensively characterized the immune landscape of HR+/HER2- ILCs, comparatively to HR+/HER2- invasive ductal carcinomas (IDC), by applying multi-omics and multi-scale analysis (gene expression at the bulk and single-cell levels, and protein-based spatial analysis) to clinical samples. ResultsWhile the overall level of immune infiltration was comparable between both pathological types, the quality of immune infiltrate differed markedly. Comparatively to HR+/HER2- IDCs, HR+/HER2- ILCs were enriched in immune cells and tertiary lymphoid structures with anti-tumor potential, presented more spatial proximity between cancer cells and CD8+ cytotoxic T cells, and stronger theorical vulnerability to ICIs. However, in HR+/HER2- ILCs, anti-tumor response was defective; CD8+ cytotoxic T cells failed to fully unleash their cytotoxic function and CD4+ helper T cells evidenced a pro-tumoral and naive phenotype. Furthermore, antigen-presenting compartment was defective, altogether embedded in a stronger immunosuppressive environment, enriched in immunoregulatory cancer-associated fibroblasts (iCAF). ConclusionThis study contributes to explain the lesser efficiency of PD-1/PD-L1-based ICIs in HR+/HER2-ILCs by comparison with HR+/HER2- IDCs, by shedding light on a complex ecosystem where tumor cells shape a distinctive stroma that contribute to prevent anti-tumor immune response activation. Altogether, our findings further support the rationale for combining iCAF-targeting strategy with an ad hoc immunotherapy (such as an anti-VTCN1/B7-H4 antibody-drug conjugates for example). Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/728418v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c62294org.highwire.dtl.DTLVardef@86392org.highwire.dtl.DTLVardef@c10748org.highwire.dtl.DTLVardef@c543da_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_ST_ABSWHAT IS ALREADY KNOWN ON THIS TOPICC_ST_ABSO_LIImmune cells infiltrate both HR+/HER2- IDC and HR+/HER2- ILC tumors, but current ICIs are less effective in HR+/HER2- ILCs than HR+/HER2- IDCs. C_LI WHAT THIS STUDY ADDSO_LIThe anti-tumor immune response is mobilized but not effective in HR+/HER2- ILCs. C_LIO_LIA complex ecosystem - composed of immunoregulatory cancer-associated fibroblasts, high levels of TGFa, prostaglandin, acidosis, and a lack of antigen-presenting cells - prevents anti-tumor CD8+ cytotoxic T cell activation in HR+/HER2- ILCs. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE, OR POLICYO_LITargeting the PD-1/PD-L1 axis is not the appropriate therapeutic strategy for HR+/HER2- ILCs. A more complex approach should be considered, notably those combining other immune-based strategies and iCAF targeting, which may offer a better chance to eradicate HR+/HER2- ILC tumor cells. C_LI

BackgroundBevacizumab resistance severely limits long-term efficacy in metastatic colorectal cancer (CRC). This study aimed to develop and validate a bevacizumab resistance-associated gene signature for prognosis prediction and immune microenvironment characterization in CRC. MethodsTwo GEO datasets (GSE19862, GSE86582) with bevacizumab response data and TCGA-COAD/READ RNA-seq data were analyzed. Overlapping differentially expressed genes (DEGs) linked to both CRC progression and bevacizumab resistance were identified. An 8-gene signature (AXIN2, PSORS1C1, KRT74, SLC2A3, STIL, IL33, GALNT6, HSD11B2) was constructed via univariate Cox and LASSO-Cox regression. ResultsIn the TCGA cohort, high-risk patients had shorter overall survival (OS; log-rank P < 0.0001). Time-dependent ROC yielded 1-year AUC = 0.638, 3-year AUC = 0.657, and 5-year AUC = 0.757. Multivariate Cox regression confirmed the risk score as an independent prognostic factor. External validation in GSE39582 (optimal cutoff = -1.49) replicated these findings: high-risk patients had inferior OS (P = 0.0016) with acceptable 1/3/5-year AUCs and retained independent prognostic value (HR = 1.634, P = 0.00415). CIBERSORT and ESTIMATE analyses showed that the high-risk group was characterized by increased M2 macrophages and neutrophils, higher immune and stromal scores, and reduced activated memory CD4+ T cells, monocytes, and activated dendritic cells (all P < 0.05). GSEA highlighted enrichment of TNF-/NF-{kappa}B, IL-6/JAK/STAT3, and immune checkpoint pathways in the high-risk group. AXIN2 (HR = 0.829, P = 0.032) was an independent protective factor, while PSORS1C1 (HR = 1.356, P = 0.048) was an independent risk factor. ConclusionThe 8-gene bevacizumab resistance signature robustly predicts prognosis and reflects an immunosuppressive microenvironment closely linked to bevacizumab failure in CRC. These findings provide novel insights into immune-mediated resistance and support clinical risk stratification.

Objective: To identify Dickkopf-1 (DKK1) as a prognostically relevant candidate in head and neck squamous cell carcinoma and to evaluate whether DKK1 and cytoskeleton-associated protein 4 (CKAP4) expression is associated with cervical lymph node metastasis in tongue squamous cell carcinoma (TSCC). Methods: DKK1 was screened using the Human Protein Atlas Pathology Atlas. Immunohistochemical expression of DKK1 and CKAP4 was examined in 54 patients with primary TSCC (cT1-4N0) treated surgically between 2015 and 2020. Nine cases were excluded because of insufficient tissue blocks or inadequate staining quality, leaving 45 evaluable cases. Associations with delayed cervical lymph node metastasis were assessed together with conventional clinicopathological factors, including infiltrative growth pattern (INF) and pathological depth of invasion (pDOI). Results: In public database analysis, high DKK1 expression was associated with poorer overall survival in head and neck squamous cell carcinoma. In the TSCC cohort, pDOI [&ge;]5 mm and INF pattern c were significantly associated with cervical lymph node metastasis. Positive DKK1 and CKAP4 expression were also significantly associated with cervical lymph node metastasis. Furthermore, combined DKK1/CKAP4 positivity, when incorporated with INF and pDOI, provided additional risk stratification, and cases with all 3 factors showed a markedly increased likelihood of cervical lymph node metastasis. Conclusions: Expression of DKK1 and CKAP4 was associated with cervical lymph node metastasis in TSCC. Combined assessment of DKK1/CKAP4 expression with INF and pDOI may improve pathological risk stratification and may help identify patients who require closer neck evaluation and postoperative management.

P2Y12 receptor (P2RY12), mainly expressed on platelets, is known for its central role in hemostasis. P2RY12 activation is also involved in cancer development through platelet adhesion to cancer cells supporting immune-evasion, promoting tumor angiogenesis and metastasis, among others. P2RY12 is known as an actionable target, and P2RY12 antagonists are in clinical use for cardiovascular diseases. However, very little data are available regarding the protein expression of P2RY12 in lung carcinomas. We performed immunohistochemical staining for P2RY12 in a cohort of non-small cell lung cancer (NSCLC) samples comprising 320 adenocarcinomas (LUAD) and 158 squamous cell carcinomas (LUSC). Results were evaluated using a dual approach combining microscopic assessment and digital image analysis (QuPath). Results were correlated with clinical-pathological data. We found significantly higher P2RY12 protein expression in LUSC compared to LUAD (p<0.001) via eyeballing (absent/low expression in 21.7% (34/158) and moderate/high expression in 78.3% (124/158) of LUSC cases versus absent/low expression in 98.4% (315/320) and moderate/high expression in 1.6% (5/320) of LUAD cases). Digital analysis yielded similar results. High P2RY12 expression was associated with a significantly better 5-year overall survival rate for the entire cohort (p=0.0048) as well as for the LUAD (p=0.015) and LUSC (p=0.05) subgroups. Furthermore, P2RY12 showed excellent discriminatory performance for classifying carcinomas as LUAD or LUSC, with an AUC of 0.916 in ROC-analysis. High P2RY12 expression is linked to a better prognosis and might serve as a promising novel prognostic biomarker for NSCLC. Its assessment could be implemented in future routine diagnostic workup. At the same time, the data suggest that P2RY12 could also serve as a diagnostic marker for LUSC.

BackgroundOpportunistic nutrient uptake is a hallmark of cancer metabolism. Cancer cells upregulate macropinocytosis to acquire extracellular nutrients to support growth and stress adaptation. We previously showed that extracellular ATP (eATP) is internalized by macropinocytosis and promotes multiple cancer phenotypes. Here, we tested whether eATP uptake is prevalent across cancers and whether eATP also induces senescence through purinergic receptor (PR) signaling. MethodsIntracellular ATP (iATP) levels were measured following eATP exposure across multiple cancer cell lines. eATP internalization was visualized in vitro and in vivo using a non-hydrolyzable fluorescent ATP analog together with high-molecular-weight dextran as a macropinocytosis marker. Senescence was quantified using three SA-{beta}-galactosidase assays and flow cytometry. Pharmacologic inhibitors of macropinocytosis and purinergic receptors were used to define pathway dependence. Combination treatments with the glucose transporter inhibitor DRB18 and the senolytic navitoclax were evaluated for antiproliferative effects. ResultseATP produced dose- and time-dependent increases in iATP across diverse cancer cell types. Imaging demonstrated widespread macropinocytic internalization of ATP in vitro and in tumor xenografts. eATP induced senescence in NSCLC cells, confirmed by multiple {beta}-gal assays and flow cytometry. PR inhibition significantly reduced senescence, whereas macropinocytosis inhibition had minimal effect on senescence induction. ConclusionseATP acts through dual pathways in cancer cells: macropinocytic internalization that elevates iATP and PR signaling that drives senescence. Targeting metabolic uptake together with senolytic therapy may offer a novel anticancer strategy.

Colorectal cancer (CRC) poses a severe global health threat with high incidence, mortality, and poor 5-year survival rates for advanced cases despite existing treatments. This study aims to explore the role of STRIP2 in CRC progression and its underlying mechanisms. Impact of STRIP2 on CRC in vitro was investigated via CRC cell proliferation, migration, invasion, and apoptosis. The in vivo impact was investigated via nude mice models. The role of STRIP2 in CRC was investigated via transcriptomic analysis, Western blot, Co-immunoprecipitation assays and ferroptosis validations. STRIP2 is overexpressed in CRC, driving malignant phenotypes in vitro and in vivo. Mechanically, STRIP2 stabilizes the IL17 downstream effector LCN2 by blocking its K48-linked ubiquitination and degradation, enhances anti-ferroptosis of CRC cells. Oe-STRIP2 suppresses ferroptosis, boosting proliferation and reducing oxidative stress; while si-STRIP2 induces the opposite effect. This study suggests STRIP2-mediated stabilization of LCN2 and enhances CRC cells ferroptosis resistance, thus promoting CRC cell survival and mediates malignant progression in CRC, which provides a novel link between STRIP2 and ferroptosis regulation in CRC. HighlightO_LISTRIP2 is overexpressed in CRC tissues and cells C_LIO_LISTRIP2 blocks LCN2 Ubiquitination and stabilizes LCN2 C_LIO_LISTRIP2 suppresses CRC ferroptosis C_LIO_LISTRIP2 drives CRC malignant phenotypes both in vitro & in vivo C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/725308v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@1baf7baorg.highwire.dtl.DTLVardef@1de15d9org.highwire.dtl.DTLVardef@16c8078org.highwire.dtl.DTLVardef@667840_HPS_FORMAT_FIGEXP M_FIG C_FIG

Glioblastoma (GBM) is the most aggressive primary brain malignancy, characterized by hypoxia-driven proliferation, therapeutic resistance, and poor prognosis. While hypoxia-induced transcriptional changes are well documented, the temporal regulation of cell cycle genes under sustained hypoxia remains unclear. This study profiled transcriptomic alterations in U87MG cells cultured under normoxia and graded hypoxia for one to three days. Differentially expressed genes (DEGs) were identified and analyzed using STRING, Cytoscape, MCODE, and CytoHubba to construct protein-protein interaction (PPI) networks and extract hub genes. Functional enrichment was assessed through DAVID, ClueGO, and KEGG, while prognostic relevance was evaluated using GlioVis and ONCOMINE datasets. qRT-PCR validated expression of selected hub genes. A total of 294 DEGs were identified, forming two main functional modules enriched in cell cycle regulation and chemokine signaling pathways. Eighteen hub genes (KIF20A, CCNB1, AURKA, EGR1, CDCA3, CENPF, CDCA2, ASPM, KIF11, CCL2, CCNA2, DLGAP5, RACGAP1, TPX2, PTGS2, CTGF, and KIFC1) were significantly associated with mitotic processes and GBM progression. Survival analysis demonstrated that 17 of these genes correlated with poor overall survival (p < 0.05). qRT-PCR confirmed that hub gene expression peaked during early hypoxia and declined with prolonged exposure, indicating dynamic regulatory adaptation. These findings identify key hypoxia-responsive genes governing cell cycle progression and highlight their prognostic and therapeutic potential in glioblastoma.

CD47 is a "dont eat me" signal that suppresses macrophage-mediated phagocytosis. Its upregulation in lung and other cancers facilitates tumour immune escape, making CD47 a promising immunotherapeutic target. Studies have demonstrated anti-tumour efficacy of CD47 blockade in preclinical lung cancer models, but monoclonal antibodies targeting CD47 have had limited efficacy as monotherapy in solid tumour patients to date. This discrepancy may in part reflect the use of human tumour xenografts in mice that do not have fully-functioning immune systems in preclinical efficacy studies. Thus, understanding tumour responses to CD47 inhibition using immune competent lung cancer models is needed to inform strategies to harness its therapeutic potential. Here, we characterized the effects of CD47 knockout (KO) on tumour growth and immune responses in two syngeneic, orthotopic murine lung cancer models, LLC-Luc (LLC) and CMT167 (CMT). As expected, CD47 KO impaired the fitness of LLC and CMT cells in vivo. Mice with CD47-deficient tumours exhibited prolonged survival and increased infiltration of anti-tumour leukocytes. However, although CD47 KO impaired lung tumour growth in syngeneic mice, KO tumours were ultimately lethal. Immunophenotyping revealed an increased prevalence of PD-L1+ cells in CD47-deficient tumours, nominating PD-L1-mediated suppression of tumour immunity as an acquired mechanism of resistance to CD47 blockade. Concordantly, dual inhibition of CD47 and PD-L1 extended the survival of CMT tumour-bearing mice compared to inhibition of either alone. These findings suggest that PD-L1 blockade could be leveraged to overcome resistance and potentiate the efficacy of CD47-targeted immunotherapy in lung cancer.

MicroRNAs (miRNAs) have been widely implicated in cancer initiation and progression, yet examination of the effects of global miRNA disruption on these processes has been limited. We developed novel genetically engineered mouse models of Kras-driven pulmonary adenocarcinoma (LUAD) with cell-type-specific disruption of miRNA biosynthesis via Dicer1 allele deletion, which exhibit significant differences in tumor progression rates and expected survival. Dicer1 is an RNase III enzyme that is required for the biogenesis of mature, functional miRNAs. Lung tumor progression was accelerated, and expected survival was decreased only when we initiated tumors and deleted one allele of Dicer1 in club cells and mutated Dicer1 in alveolar type 2 (AT2) cells. Reversing the cell types by inducing tumorigenesis, deleting one Dicer1 allele in AT2 cells, and mutating Dicer1 in club cells modestly accelerated tumor progression and had no effect on expected survival. Collectively, our results demonstrate that Dicer1 disruption accelerates lung cancer progression in a cell-type-dependent and non-cell-autonomous manner, and our mice represent tools for investigating the roles of miRNAs and miRNA-mediated intercellular communication in tumor progression. SummaryKras-driven mouse models show that Dicer1 mutations accelerate lung adenocarcinoma (LUAD) progression in a cell-type-dependent manner and suggest that the influence of miRNA-mediated intercellular communication is unidirectional and non-cell-autonomous.