Translational Oncology

Abstract Objective Commercially available next-generation sequencing (NGS) platforms in China routinely adopt a lung cancer-derived tumor microenvironment (TME) subtyping signature from a European cohort to classify colorectal cancer (CRC), yet its diagnostic performance in Chinese CRC patients remains unvalidated. This study aimed to evaluate the subtyping efficiency of the lung cancer TME signature in a Chinese CRC cohort, screen CRC-specific immune mRNA biomarkers for TME subtyping, and explore the clinical utility of IRF1, CD8A and LAG3 for distinguishing immune-enriched (IE) and immune-desert plus fibrotic (D+F) subtypes. Methods A total of 87 FFPE CRC specimens with complete NGS and clinicopathological data were retrospectively enrolled, including 15 IE subtype and 72 D+F subtype patients. Thirty-one mRNA transcripts covering 13 immune-metabolic homeostasis genes and 18 immune checkpoint/infiltration-related genes were divided into two functional modules. Spearman correlation analysis was performed to assess co-expression patterns among candidate genes. Receiver operating characteristic (ROC) curves combined with five-fold cross-validation were used to compare the discriminatory efficacy of single-gene markers and the three-gene combined panel. Results Strong positive co-expression was observed between IRF1, CD8A and LAG3 (IRF1-CD8A: r=0.93; IRF1-LAG3: r=0.84; CD8A-LAG3: r=0.73). Nominal P-values indicated elevated expression of IRF1, CD8A and LAG3 in IE subtype, though no intergroup significance remained after Benjamini-Hochberg FDR correction, largely attributed to the limited sample size of IE cases. Single-gene ROC analysis showed AUC values of 0.763 (IRF1), 0.752 (CD8A) and 0.771 (LAG3), with LAG3 exhibiting the best individual discriminatory capacity. The three-gene combined panel yielded a cross-validated AUC of 0.717, inferior to single LAG3, due to severe collinearity that generated redundant predictive information. Conclusions The lung cancer-originated TME subtyping system cannot be directly extrapolated to Chinese CRC patients. LAG3 serves as a promising independent transcriptomic candidate marker for distinguishing CRC TME subtypes. The robust collinearity among IRF1, CD8A and LAG3 eliminates additional predictive benefits of the combined signature. Large independent multi-center Chinese CRC cohorts are required to construct population-specific immune transcriptomic biomarkers for standardized clinical NGS TME stratification.

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.

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.

Metastasis is the leading cause of mortality in breast cancer and remains largely untargeted therapeutically. Identifying molecular drivers of metastatic progression is essential for developing effective treatments. This study investigated the role of the transcription factor ELK3 in triple-negative breast cancer (TNBC) metastasis by defining the cellular and molecular processes it regulates. MDA231 cells with ELK3 overexpression (OE) or knockdown (KD) were generated by lentiviral transduction. Transcriptomic alterations induced by ELK3-KD were analyzed by microarray and validated by RT-qPCR. Ingenuity Pathway Analysis and Gene Set Enrichment Analysis identified ELK3-dependent metastasis-associated pathways, which were functionally validated using 3D microfluidic migration assays, mammosphere formation assays, and flow cytometry/ AlamarBlue proliferation assays. High ELK3 expression correlated with a mesenchymal phenotype in BC cell lines and lymph node invasion in patient tumors. ELK3-KD significantly altered 740 genes, many linked to migration and stemness. Functionally, ELK3 enhanced 3D confined migration, likely through regulation of EMT, cell adhesion and protrusion formation. ELK3 also promoted cancer stem cell traits, potentially via hypoxia-related and WNT/{beta}-catenin, JAK/STAT3, TGF-{beta}, Notch1, and NF-{kappa}B signaling pathways. Additionally, ELK3 induced cellular quiescence while suppressing proliferation under adherent conditions. Overall, ELK3 acts as a pro-metastatic regulator in TNBC by promoting migration and stemness.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and more evidence suggests that glucose metabolism plays a significant role in the development and progression with glycosylation at multiple sites potentially being a key characteristic. However, the underlying mechanisms remain insufficiently studied. Here, we first confirmed the presence of O-GlcNAc glycosylation modifications at Thr50 on PKM, which is highly expressed in PDAC and strongly correlated with poor prognosis. Further, we found that PKM expression was significantly positively correlated with CDC27 levels, and mutation of the Thr50 O-GlcNAc site in PKM abolished the upregulation of CDC27. We confirmed that O-GlcNAc-modified PKM enhances nuclear translocation of ARNT, which binds to the CDC27 promoter to upregulate its expression. Finally, we demonstrated that reduced expression of CDC27, as a key component of the APC/C complex, leads to downregulation of ubiquitination at the K11 site of PPP2CA, resulting in upregulation of PPP2CA expression, in turn, reduces AKT phosphorylation, ultimately driving PDAC regression by inhibiting aerobic glycolysis. Thus, we delineate a novel O-GlcNAcylation-dependent pathway where PKM drives PDAC progression through ARNT-mediated CDC27 transcriptional activation and AKT-mediated glycolysis.

Objective: Tumor protein D52 (TPD52) is aberrantly expressed in various malignancies; however, its systematic expression profile, prognostic significance, tumor microenvironment associations, and functional mechanisms in breast cancer remain poorly defined. Methods: GEO and TCGA breast cancer expression datasets were integrated to identify differentially expressed genes (DEGs). We evaluated the diagnostic performance of TPD52 via protein-protein interaction (PPI) network analysis, GO/KEGG enrichment analysis and eleven machine learning algorithms. Immunohistochemistry verified TPD52 protein expression in clinical specimens, and Kaplan-Meier analysis assessed its prognostic significance. Analysis of single-cell transcriptomic data (GSE176078) revealed the cell-type-specific distribution of TPD52 and its intercellular communication network in the breast cancer microenvironment. Weighted gene co-expression network analysis (WGCNA) explored relationships between TPD52 and tumor microbiome, hypoxia signatures as well as microsatellite instability. Moreover, TPD52 was knocked down by siRNA in MCF7 cells, and its impacts on cell migration, invasion, proliferation and the MAPK/ERK signaling pathway were examined through wound healing, Transwell, CCK-8 and Western blot assays. Results: TPD52 was significantly overexpressed in breast cancer tissues at both the mRNA and protein levels. A random forest-based diagnostic model demonstrated high accuracy across multiple datasets. Kaplan-Meier analysis revealed that elevated TPD52 expression was associated with longer overall survival in specific subgroups, including the basal-like subtype, invasive lobular carcinoma, and N0/N1 stages. Single-cell analysis showed that TPD52 was predominantly expressed in tumor epithelial cells, which occupied a central position within the intercellular communication network. WGCNA further identified a positive correlation between TPD52 and a hypoxia-associated microbial module, as well as a negative correlation with a microsatellite instability module. In vitro functional assays confirmed that TPD52 knockdown significantly suppressed the migration, invasion, and proliferation of MCF7 cells, and led to reduced p-ERK1/2 protein levels. Conclusion: TPD52 promotes the malignant phenotypes of breast cancer cells through activation of the MAPK/ERK signaling pathway, yet its prognostic significance is subtype- and microenvironment-dependent. These findings establish TPD52 as both a diagnostically valuable biomarker and a mechanistically defined potential therapeutic target.

Non-small cell lung cancer (NSCLC) is the most common form of lung cancer accounting for most cancer-related deaths worldwide. Despite substantial recent advances in targeted therapies and immunotherapy, the prognosis for advanced-stage disease remains comparably poor, which is why the identification of novel molecular biomarkers as well as therapeutic targets influencing tumor development, progression, and metastasis remain important. This study focusses on SERPINB13, a serine-protease inhibitor expressed in selected tissues that is dysregulated in several tumor entities. However, its role in NSCLC still remains largely unclear. We analyzed SERPINB13 transcription in a cohort of non-small cell lung cancer (NSCLC) cases including both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) by transcriptome profiling. Epigenetic modifications were assessed via Methylation BeadChips. Additionally, SERPINB13 protein expression was assessed by immunohistochemistry (IHC) in an independent cohort of NSCLC comprising 126 LUSC patients. Correlation analyses were performed to associate SERPINB13 expression with key clinico-pathological parameters, including overall survival and extent of tumor-infiltrating immune cells. To functionally investigate the regulatory influence of peripheral blood mononuclear cells (PBMCs) on SERPINB13 expression in LUSC tumor cells in vitro, we utilized the SERPINB13-expressing LUSC cell line LUDLU-1. Here, gene transcription was analyzed by quantitative real-time PCR (RT-qPCR), confirmed by Western blot on the protein level. Transcriptome analysis revealed a significant upregulation of SERPINB13 in lung squamous cell carcinoma (LUSC) compared to lung adenocarcinoma (LUAD), highlighting a subtype-specific expression pattern. This differential expression was further associated with a distinct epigenetic DNA methylation signature at the SERPINB13 loci in LUSC, suggesting transcriptional regulation via hypomethylation. IHC analysis demonstrated that high SERPINB13 protein expression is significantly associated with prolonged overall survival in LUSC. Notably, SERPINB13 expression was enriched in immune-inflamed ("hot") tumors, characterized by elevated infiltrating lymphocytes and immune activation. Mechanistically, co-culture experiments with PBMCs induced SERPINB13 expression in a LUSC cell line in a dose- and time-dependent manner in the absence of direct cell contact. This suggests that soluble factors secreted by immune cells might play a key role in regulating SERPINB13 expression in the tumor microenvironment. Taken together, SERPINB13 is a novel prognostic indicator in LUSC that is modulated by Immune cells. Further studies are necessary to decipher the crosstalk of Immune cells on the Serpin B13 expressing tumor cells in depth, with regard to a possible interventional strategy. immunomodulatory potential strategies and personalized therapeutic approaches in NSCLC.

Background: Serum proteomic signatures may reflect tumor- and host-related biology and serve as prognostic biomarkers in patients receiving immune checkpoint inhibitors (ICIs). We evaluated the association of the VeriStrat serum proteomic classification with survival outcomes and immune-related adverse events (irAEs) in patients with non-small cell lung cancer (NSCLC) treated with ICIs. Methods: We retrospectively reviewed patients with NSCLC who received ICI-containing therapy and underwent VeriStrat testing at Northwestern Memorial Hospital from October 2015 through June 2023. Patients were classified as proteomic signature Good (PS-Good) or Poor (PS-Poor). Progression-free survival (PFS) and overall survival (OS) were assessed among patients receiving palliative-intent ICI therapy. First any-grade and grade 3 or higher irAEs were evaluated in all ICI-treated patients using cumulative incidence functions and Fine-Gray competing-risk regression. Results: Among 162 ICI-treated patients included in the toxicity analysis, 129 received palliative-intent therapy and were included in the survival analysis; 91 (71%) were PS-Good and 38 (29%) were PS-Poor. PS-Good status was associated with longer PFS (median, 6 vs 3 months; hazard ratio [HR], 0.50; 95% CI, 0.33-0.77; P<0.01) and OS (median, 20 vs 8 months; HR, 0.59; 95% CI, 0.39-0.91; P=0.02). These associations remained significant after multivariable adjustment for PFS (adjusted HR, 0.46; 95% CI, 0.26-0.82; P<0.01) and OS (adjusted HR, 0.50; 95% CI, 0.28-0.87; P=0.01). Any-grade irAEs showed a nonsignificant trend toward a higher cumulative incidence in PS-Good patients. At 12 months, the cumulative incidence was 32.6% for PS-Good versus 22.5% for PS-Poor (subdistribution HR, 1.53; 95% CI, 0.77-3.02; P=0.23). The cumulative incidence of grade 3 or higher irAEs was similar between groups (16.3% vs 15.0%; subdistribution HR, 1.12; 95% CI, 0.48-2.62; P=0.79). Conclusions: PS-Good classification was independently associated with improved survival in patients with NSCLC receiving ICI-containing therapy. Although any-grade irAEs were numerically more frequent among PS-Good patients, proteomic classification was not significantly associated with any-grade or high-grade irAE risk. Prospective validation is warranted.

Purpose Modified FOLFIRINOX (FFX) and gemcitabine plus nab-paclitaxel (GNP) are standard first-line treatments for metastatic pancreatic ductal adenocarcinoma (PDAC), but no validated biomarker guides treatment selection. We developed MULTIPL, a multimodal machine learning system, and established the PASS-01 Challenge to benchmark prognostic and predictive biomarkers. Patients and Methods MULTIPL was trained in the COMPASS study (N=268), integrating clinical, digitized histopathology, whole-genome, and RNA-seq data. MULTIPL, PurIST, hENT1 expression, and HRDetect were evaluated in the PASS-01 trial, a randomized phase II trial of FFX versus GNP (N=160), within the Challenge. The primary endpoint was differential treatment benefit measured by concordance-for-benefit for progression-free survival. Results MULTIPL had the highest concordance index for OS among individually evaluated biomarkers (0.595; 95% confidence interval [CI], 0.55-0.65) and separated high- versus low-risk patients (hazard ratio, 1.62; 95% CI, 1.13-2.33; P=0.009). Patients recommended for GNP by MULTIPL had significantly longer OS with GNP than with FFX (hazard ratio, 0.47; 95% CI, 0.28-0.82; P=0.007), whereas patients recommended for FFX had similar OS between treatments. Interpretability analysis of MULTIPL in COMPASS identified KDM6A alterations and SSTR1 expression as prognostic biomarkers, which were validated in PASS-01. However, none of the tested biomarkers significantly predicted differential treatment benefit in the PASS-01 Challenge. Conclusion MULTIPL demonstrated robust prognostic performance in external validation, identified a subgroup enriched for benefit from GNP, and enabled discovery and validation of prognostic biomarkers in metastatic PDAC. However, no biomarker met the primary endpoint for differential treatment benefit, underscoring the value of the PASS-01 Challenge.

Invasive lobular breast carcinoma (ILC) is the most common special histological subtype of breast cancer, which accounts for 10-15% of all cases. To study the phenotype characteristics, metastatic growth kinetic and immune microenvironment of ILC, we developed an orthotopically transplantable cell line model from the spontaneous mammary fat pad tumor of CDH1-PTEN dual knockout C57BL/6 mouse with Cre-loxP system, designated CPT6. CPT6 recapitulates single-file growth pattern of human ILC, with pleomorphic features and a high mitotic index. RNA sequencing together with whole exome sequencing reveals a luminal A subtype with targetable driver mutations such as Kras G12C. As a novel orthotopically transplantable ILC model in immune competent mice, CPT6 shows robust in vivo growth and metastatic rate, and has moderate immunogenicity which appears to be T-cell independent. We also profiled the immune microenvironment of CPT6, revealing a myeloid-rich environment with dominant M2-macrophage population, which is concordant with human ILC. In summary, this model recapitulates human ILC phenotype and represents a valuable preclinical platform for evaluating immunotherapy and other therapeutic strategies for invasive lobular breast carcinoma.

AbstractAutophagy and Toll-like receptor (TLR) signaling are both implicated in cancer progression, but whether they act as tumor suppressors or promoters remains unclear. To explore this relationship, we investigated the role of autophagy downstream of therapeutic TLR activation in oral squamous cell carcinoma (OSCC). Using the FDA- approved TLR agonists Bacillus Calmette-Guerin (TLR2/4) and imiquimod (TLR7), we assessed their effects in vitro on SCC-4 cells and in vivo in a chemically induced OSCC hamster model. Both agents, alone or in combination with each other or with Monophosphoryl Lipid-A induced robust autophagy, as measured by LC3B staining in vitro and flow cytometry in vivo. Autophagy induction correlated with reduced tumor volume and prolonged survival, with outcomes comparable to cisplatin, the current standard chemotherapeutic, but with less treatment-associated morbidity and mortality. Autophagy was also associated with cisplatin antitumor effects. Notably, imiquimod produced the most pronounced and sustained autophagic and antitumor effects. To our knowledge, this is the first study to directly link the therapeutic efficacy of TLR agonists in OSCC to autophagy modulation, providing both mechanistic and translational insights into their potential as immunotherapeutic agents.

Background and PurposePARP inhibitors have been evaluated in clinical trials for several cancers and Olaparib is FDA approved for treating BRCA deficient ovarian cancer. Numerous reports have suggested Poly(ADP-ribose) polymerase1(PARP1) overexpression in a variety of cancers including breast carcinomas and proposed the role of PARP1 in metastasis. However, the mechanism of PARP1 in regulating metastatic process in BRCA proficient and deficient TNBC is not studied thoroughly. In this study, we propose that PARP1 mediated breast carcinoma progression is gene transcription mediated, where it regulates several steps of pro-metastasis. Experimental ApproachPARP inhibitors effect on metastasis was monitored by migration and invasion assay, modulation in protein expression was assessed by proteomic analysis and further confirmed by immunoblotting. Chromatin immunoprecipitation was performed to study the transcriptional role of PARP1. Ectopic expression and siRhoGDI, and immunofluorescence assessed the cytoskeleton changes. PARP inhibitor was administered in xenograft mice to study metastasis. Immunohistochemical analysis was done on patient and mice tissues. Key resultsBreast cancer cells exhibited reduced migration and invasion due to PARP1 inhibition. PARP1 regulates expression of vimentin and RhoGDI and hence cytoskeletal rearrangement causing a change in migrating potential of a cell. Metastasis in mice was reduced upon PARP inhibition. PARP1 was identified to be a novel transcriptional regulator of RhoGDI. Furthermore, RhoGDI ectopic expression substantiated the PARP inhibitor effects, suggesting the PARP inhibitor downstream signaling to be mediated through RhoGDI. Conclusions and ImplicationsWe identified a novel aspect of PARP1 as promoter of metastasis via transcriptional regulation of RhoGDI. Assessing RhoGDI levels in TNBC patients might be useful to predict sensitivity to PARP inhibitors.

Background: For patients with metastatic gastrointestinal cancers, chemotherapy resistance is a common phenomenon that, if known in advance, would allow for individualized treatment decisions. This study aimed to test the feasibility of developing a deep learning computer vision system that uses laparoscopy images depicting peritoneal surface metastases (i.e., capturing the in-vivo optical appearance of metastases as a summary of their molecular makeup) to predict whether a patient is resistant to standard chemotherapy. Methods: The retrospective observational feasibility study included 35 adult patients who underwent staging laparoscopy for non-colon gastrointestinal adenocarcinoma with biopsy-confirmed peritoneal surface metastases and who underwent chemotherapy as their only treatment modality. Chemotherapy resistance was determined based on each patient's observed cancer-specific survival after controlling for confounders. Results: Of 35 patients, 17 were assigned to the chemotherapy sensitive group and 18 to the chemotherapy resistant group. The study cohort provided 1010 laparoscopy image patches of 101 biopsy-confirmed metastases. A densely connected convolutional neural network with cross-validation provided the best results for correctly predicting chemotherapy resistance at the patient level (accuracy 0.80 (95%CI 0.63-0.92), sensitivity 0.72, specificity 0.88, AUC-ROC 0.78). Saliency maps demonstrated the system's trustworthiness. Conclusion: In this study, a prototype surgical computer vision system designed to determine chemotherapy resistance from operative images of peritoneal surface metastases demonstrated its technical feasibility. Further development and validation in a multi-institutional clinical study are pending.

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.

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.

CD47 is a ubiquitously expressed transmembrane protein that functions as a negative immune checkpoint, marking host cells as "self" by delivering an inhibitory "dont-eat-me" signal to phagocytes. Cancer cells co-opt this mechanism, upregulating CD47 to evade immunosurveillance and phagocytosis by innate immune cells, a pattern observed across solid tumours and haematological malignancies. CD47 overexpression correlates with poor prognosis across most cancer types, including therapy-resistant disease. Despite extensive efforts to develop CD47-targeted therapies, the downstream biological consequences of aberrant CD47 expression within tumour cells remain poorly characterised beyond its established anti-phagocytic role. This study investigated non-immunological, pro-tumorigenic functions of CD47 to define the cellular effects, beyond immune evasion, that CD47-targeted therapy might disrupt. We found that CD47 exerts cancer type-specific effects: in DLBCL, CD47 loss impaired mitochondrial metabolism and sensitised cells to R-CHOP standard-of-care chemoimmunotherapy, whereas in triple-negative breast cancer (TNBC), CD47 knockdown delayed cell cycle progression, enhanced migration, and conferred resistance to specific chemotherapeutic agents. These findings indicate that CD47 has multifaceted, context-dependent roles in tumour biology that extend beyond immune checkpoint signalling. Clinically, this suggests CD47-targeted therapies may produce cancer type-specific off-target effects on tumour metabolism, proliferation, and drug sensitivity, which are considerations that should inform their rational combination with existing targeted therapies.

BackgroundMetabolic reprogramming is a common occurrence in tumor cells, where enhanced glycolysis promotes cell growth, invasion and migration. NF1 is tumor suppressor gene that downregulates the encoded neurofibromin protein. However, the effects of NF1 on energy metabolism and epithelial-mesenchymal transition (EMT) in glioblastoma multiforme (GBM), as well as the underlying molecular mechanisms, remain unclear. MethodsCRISPR/Cas9 gene editing technology was employed to construct GBM cell lines with NF1 gene mutations. Metabolomics was utilized to examine the impact of NF1 on metabolic remodeling in GBM. The Seahorse XF24 extracellular flux analyzer was used to detect the effect of NF1 knockdown on glycolysis and mitochondrial oxidative phosphorylation in GBM cells. Wound healing assay and Transwell chamber assay were utilized to detect the effect of NF1 on GBM cell invasion. Orthotopic tumor model in nude mice was established to explore the role of NF1 in vivo. In addition, Co-IP, western blotting, and immunofluorescence were used to explore the changes of key enzymes in glycolysis and mitochondrial oxidative phosphorylation and the relationship between NF1 and MFN1. ResultsThe expression of NF1 is decreased in glioma tissues and is significantly correlated with patient prognosis. NF1 knockdown may promote the invasion, migration, and EMT of GBM cells. At the same time, the activation of the AKT/mTOR signaling pathway promotes aerobic glycolysis in GBM cells, promotes mitochondrial division through targeted regulation of MFN1, and inhibits mitochondrial oxidative phosphorylation. NF1 deficiency promotes EMT in GBM cells by enhancing aerobic glycolysis and mitochondrial division. ConclusionNF1 deficiency promotes GBM glycolysis by activating the AKT/mTOR signaling pathway and inhibits the mitochondrial oxidative phosphorylation by regulating MFN1; NF1 deletion promotes GBM EMT by remodeling the pattern of energy metabolism.

Background: Gastric carcinoma remains a major cause of cancer related mortality worldwide, with tumor progression increasingly recognized as a consequence of complex interactions within the tumor microenvironment. Hypoxia induced signaling, cancer associated fibroblast (CAF) heterogeneity, and immune checkpoint activation play critical roles in tumor progression and immune evasion. However, their integrated relationship in gastric carcinoma remains insufficiently characterized. Objectives: To evaluate the expression of Hypoxia inducible factor 1 alpha and its association with cancer-associated fibroblast subtypes and Programmed death-ligand 1 expression in gastric carcinoma. Methods: This cross sectional analytical study included 100 histologically confirmed gastric carcinoma cases from Satkhira Medical College. Immunohistochemistry was performed for HIF 1 alpha, smooth muscle actin (SMA), fibroblast activation protein (FAP), and PD L1. CAFs were subclassified into myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs). Associations between biomarkers and clinicopathological variables were analyzed using chi square test, Spearman correlation, and multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was used to assess model performance. Result: High HIF 1 alpha expression was observed in 55% of cases and demonstrated significant association with poor differentiation (p = 0.001), advanced tumor stage (p = 0.002), and lymph node metastasis (p = 0.001). iCAF predominance was significantly associated with poor differentiation (p = 0.003), advanced stage (p = 0.004), and nodal metastasis (p = 0.004). High PD L1 expression was significantly associated with poor differentiation (p = 0.03), advanced stage (p = 0.001), and lymph node metastasis (p = 0.002). Multivariate logistic regression identified high HIF 1 alpha expression (OR = 3.8, p = 0.001), iCAF dominance (OR = 4.5, p < 0.001), and advanced tumor stage (OR = 2.9, p = 0.004) as independent predictors of high PD L1 expression. Combined high HIF 1 alpha expression and CAF activation demonstrated the highest rate of PD L1 positivity (76.7%, p < 0.001). ROC curve analysis demonstrated good predictive performance of the model with an area under the curve of 0.81. Conclusion: The present study demonstrates a significant interaction between hypoxia, stromal remodeling, and immune checkpoint activation in gastric carcinoma. High HIF 1 alpha expression and inflammatory CAF predominance are strongly associated with aggressive clinicopathological features and increased PD L1 expression, supporting the existence of a coordinated hypoxia stroma immune axis in gastric carcinoma progression. These findings may have potential implications for prognostic stratification and combined targeted therapeutic strategies.

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.

Hepatocellular carcinoma (HCC) is particularly aggressive and difficult to treat. Due to the lack of early clinical diagnosis and the unsatisfactory clinical treatment effect, it is particularly important to identify novel markers that can predict tumor behavior in HCC. biogenesis of ribosomes BRX1 (BRIX1) is abundant in various tissues of the human body. However, the regulatory mechanisms and its role in various tissues are not fully understood. Here, we analyzed the expression pattern of BRIX1 in HCC from public gene expression databases and tissue samples from clinical HCC. We confirmed that BRIX1 was upregulated in both HCC cell lines and HCC paraffin section samples. BRIX1 depletion significantly dicreased the capacity of cells to grow and migrate in vitro, and knockdown BRIX1 suppressed tumor growth in xenograft tumor model. Mechanistically, BRIX1 depletion suppressed the MAPK/ERK pathway, as reflected by reduced phosphorylated ERK (p-ERK) levels. In summary, we provide a rational clue for the further investigation of BRIX1 as an invaluable biological marker for diagnosing and predicting prognosis of patients with HCC.