Translational Oncology

Background Cancer treatment response is highly variable, even among patients with the same tumor type and treatment. Exceptional responders (ERs), who are individuals who experience unusually favorable outcomes, provide critical insights into the biological factors driving treatment success. While prior studies have highlighted the role of somatic changes, the contribution of germline rare variants remains underexplored. This study aimed to uncover the genetic underpinnings of exceptional responses by identifying rare, non-silent and predicted deleterious germline mutations enriched among ERs compared to typical cancer patients. Methods The Network of Enigmatic Exceptional Responders (NEER) project collected clinical and germline whole-genome sequencing (WGS) data from 53 ERs. After quality control procedures and ancestry background checks, 51 ERs were left for final analysis. While non-silent mutations were identified based on allele frequencies and mutation types, multiple pathogenicity predictors were applied for predicted deleterious variants. These were compared to a harmonized and comparable subset from the Pan-Cancer Analysis of Whole Genomes (PCAWG) cohort (n=414) using Fisher's exact tests. Kaplan-Meier survival analysis applied to evaluate prognostic associations in PCAWG patients. Additionally, Fisher's exact tests were conducted stratified by cancer type and treatment regimen to identify potential associations between rare germline variants and therapeutic responses. Results Variants in immune-related genes such as CCL26 and GPRC5D were prevalent, suggesting enhanced immune regulation among ERs. Fourteen genes with non-silent and eight with predicted deleterious mutations showed significantly different frequencies between NEER and PCAWG cohorts (FDR < 0.05). IRX3 emerged as a protective gene enriched in ERs, whereas OR6B2 was associated with poor survival in PCAWG lung cancer patients. Moreover, rare non-silent germline variants in drug target genes were enriched among ERs treated with cisplatin and doxorubicin, implicating altered DNA repair and drug-binding mechanisms in their remarkable outcomes. Conclusions This study reveals a distinctive germline mutation landscape in exceptional cancer responders, marked by immune-related and drug-target-associated variants that may enhance therapy response and prolong survival. The findings highlight potential novel prognostic biomarkers, such as IRX3 and OR6B2, providing a foundation for developing personalized cancer treatments informed by rare genetic variation.

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.

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.

BackgroundMesothelioma (Me) is an aggressive cancer with limited response to conventional therapies. The tumors harsh microenvironment contributes to immune escape and therapy resistance and the effects of ICIs on Me are still unclear. Adenosine, an immunosuppressive molecule produced from AMP by the enzyme CD73, accumulates in hypoxic tumor areas. Elevated CD73 and adenosine receptor A2B (A2Br) levels on Me cells are linked to worse patient outcomes, indicating their important role in disease progression and potential as targets for treatment. AimThis study characterizes the Me-ME (micro environment) and evaluates the efficacy of TT-4 (A2B inibitor) and AB680 (CD73 inibitor), alone or with aPD-1, using 3D models in vitro and in vivo. MethodsCD73 and A2B receptor levels were quantified in tumor and normal samples using qRT-PCR and IHC. Cells lines were treated with CoCl2 to mimic hypoxia, then CD73, A2Br and related markers were analyzed. MSTO-211H and REN cells were silenced for CD73, grown as spheroids and adenosine release was measured. Co-culture spheroids of MSTO-211H and Jurkat cells were treated with AMP and CD73 inhibitor, then analyzed for viability and immune markers. An orthotopic Me model was established by injecting AB1-B/c-LUC cells and monitored by in vivo imaging. Proteomic analysis of spheroids was conducted to identify proteins and pathways involved. ResultsHypoxia boosts CD73 and A2Br expression in Me cells, leading to adenosine production via CD73. In 3D co-cultures, AB680 lowered Me cell viability and enhanced activation of Jurkat T cells. In mice, combining aPD-1 therapy with A2Br or CD73 inhibitors strongly reduced tumor growth. Proteomics identified 93 proteins influenced by adenosine signaling through A2B. ConclusionTargeting the adenosine pathway alongside PD-1 blockade offers a promising new immunotherapy strategy for Me.

Platinum resistance remains a major barrier in Ovarian cancer (OC) treatment[1]. While hyperactivation of DNA damage response (DDR) is a hallmark of chemoresistance[2], the underlying epigenetic mechanisms driving this adaptation remain poorly understood. Here, we identify a novel post-transcriptional regulatory axis involving miR-221-5p that governs two critical DDR effectors: RAD18, which mediates DNA damage tolerance through trans-lesion synthesis (TLS)[3][4], and RAD51, the central recombinase for homologous recombination (HR)[5][6]. Although the miR-221/222 cluster is traditionally categorized as oncogenic[7][8], we demonstrate that the miR-221-5p arm functions as a potent tumor suppressor in OC. Bioinformatic and luciferase reporter assays confirmed that miR-221-5p directly targets the 3'UTRs of both RAD18 and RAD51. In OC clinical specimens and cell lines, miR-221-5p downregulation inversely correlates with RAD18/RAD51 expression. Functionally, miR-221-5p restoration suppressed platinum-induced PCNA mono-ubiquitination and HR, inducing a "functional BRCAness" that sensitized both established and patient-derived primary OC cells to carboplatin and PARP inhibition. Furthermore, in vivo disseminated xenograft models demonstrated that stable miR-221-5p expression significantly reduced tumor burden. Collectively, our results delineate a novel regulatory mechanism where loss of miR-221-5p drives chemoresistance by derepressing the RAD18/RAD51 axis, identifying this axis as a promising therapeutic target.

BackgroundIn RAS-mutant tumors, ERK phosphorylates the mitochondrial fission GTPase DRP1 to promote mitochondrial fission. DRP1 activity is tumor-promoting in pancreatic and other RAS-driven cancers, but its role in therapeutic resistance is unknown. MethodsWe developed a panel of patient-derived pancreatic cancer cell lines resistant to the MEK inhibitor trametinib. We used immunofluorescence imaging, in vitro growth assays and orthotopic xenografts to determine the role of DRP1 in trametinib resistance. ResultsWe find that trametinib-resistant cells exhibit increased expression and phosphorylation of DRP1 compared to sensitive counterparts. Quantitative analysis of mitochondrial structure reveals that mitochondria in resistant cells are morphologically distinct and relatively smaller than sensitive cells treated with trametinib. Genetic and pharmacological inhibition of both c-Myc and CDK6 are sufficient to block DRP1 phosphorylation in resistant cells, suggesting that activation of a c-Myc-CDK6 signaling axis drives reactivation of mitochondrial fission in the absence of MAPK signaling. Importantly, deletion of DRP1 leads to either growth inhibition or re-sensitization to trametinib in resistant lines. ConclusionThese findings suggest DRP1 contributes to drug resistance, and that inhibition of mitochondrial fission might be a promising therapeutic strategy to combat resistance to MAPK and RAS inhibitors.

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.

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.

The RNA polymerase-associated factor 1 complex (PAF1C) is an evolutionarily conserved transcription elongation complex that regulates RNA polymerase II-mediated transcription and chromatin modification. LEO1, a core subunit of PAF1C, has been implicated in developmental gene regulation, WNT signaling, and leukemogenesis; however, its role in solid tumor progression remains poorly understood. In this study, we found that although LEO1 expression is generally elevated in colorectal cancer (CRC), its expression is reduced in stage IV tumors and is associated with poor clinical outcomes. To investigate its function, we established LEO1 -deficient HCT116 cell line and performed transcriptomic analyses. Loss of LEO1 suppressed epithelial differentiation and developmental gene programs while inducing cell cycle delay. Despite these changes, LEO1-deficient cells exhibited aggressive phenotypes, including enlarged nuclei and increased expression of migration-associated genes, which were further enhanced under glucose deprivation. Motif analysis identified FOXM1 as a key regulator of these migration-related genes. Mechanistically, LEO1 deficiency promoted accelerated transcriptional activation of GRP78, a central regulator of endoplasmic reticulum (ER) stress adaptation. GRP78 was required for survival under ER stress conditions, and its inhibition suppressed both migration and migration-associated gene expression. In addition, transcriptomic analyses revealed upregulation of cholesterol metabolism-related genes in LEO1-deficient cells. Consistently, treatment with the HMG-CoA reductase inhibitor atorvastatin selectively impaired their survival, indicating cholesterol metabolic dependency. Collectively, these findings demonstrate that LEO1 loss promotes ER stress-adapted migration and cholesterol metabolic dependency in CRC, suggesting that these pathways may represent therapeutic vulnerabilities in metastatic LEO1-low CRC.

Background and AimsA major goal of personalised liver oncology is the ability to make targeted predictions about cancer-specific toxicity, however there are limited methods available. To address this, we validated the performance of our bioinformatics framework, TARGET-SL, through ex vivo drug screening. MethodsUsing TARGET-SL we predicted gain of function (GOF), loss of function (LOF) and synthetic lethal (SL) genetic events, and corresponding drug candidates. We validated drug predictions across hepatocellular carcinoma (HCC) cell lines, and a cohort of HCC and cholangiocarcinoma (CCA) patient-derived organoids (PDOs). ResultsFor HCC cells and PDOs we found 37.5% and 25% of the respective selected compounds induced unique target-specific growth inhibition based on genetic biomarkers, suggesting novel biomarker-driven drug sensitivities. ConclusionsOur analyses demonstrate TARGET-SLs potential to enhance personalized drug screening for liver cancer, by focusing on genetically informed targets. This will reduce experimental costs and accelerate the pace of therapeutic discovery. Impact and ImplicationsPrimary liver cancer (PLC) is a cancer with poor prognosis, and current therapies increase survival only for a minority of patients. Through the application of TARGET-SL we can predict, for each patient, the essential genes and corresponding small molecule inhibitors. These data support further investigation in larger patient cohorts and offer the possibility to specify new small molecule inhibitors and to repurpose current drugs for PLC treatment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/725819v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@10cb252org.highwire.dtl.DTLVardef@8f3049org.highwire.dtl.DTLVardef@ab4467org.highwire.dtl.DTLVardef@17f9d3_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITARGET-SL can predict gene and drug sensitivities for cell lines and patient-derived organoids C_LIO_LIThis may reduce drug screening costs and accelerate the pace of therapeutic discovery. C_LIO_LITARGET-SL may assist in the repurposing of current drugs and their rapid translation for primary liver cancer C_LIO_LITARGET-SL is tumour-type agnostic, and therefore may have application in other cancers with poor prognosis C_LI

BackgroundTriple-negative breast cancer (TNBC) is an aggressive subtype lacking well-defined molecular targets, leaving chemotherapy as the primary treatment despite drug resistance, systemic toxicity, and high recurrence rates. Therefore, the development of effective and less toxic therapeutic agents is essential. This study investigated the anti-cancer potential of gloriosine, a bioactive alkaloid with antiproliferative activity and low toxicity toward normal breast cells. MethodsPotential targets of gloriosine were predicted using SwissTargetPrediction, TargetNet, and PharmMapper, and overlapping genes related to TNBC and glutamine metabolism were selected. Protein-protein interaction networks, Gene Ontology, and KEGG pathway enrichment analyses were performed. Molecular docking evaluated binding affinity, followed by in vitro validation using cell viability, colony formation, and wound healing assays. ROS levels were measured by DCFDA and GSH assays, and ferroptosis was assessed by Western blot and FerroOrange staining in MDA{square}MB{square}231 cells. ResultsA total of 100 potential targets were identified, with 60 overlapping with TNBC and glutamine metabolism-related genes. Key targets included SRC, EGFR, mTOR, and HSP90AA1. Enrichment analyses indicated involvement in cancer progression, metabolic regulation, and resistance pathways, including central carbon metabolism, EGFR inhibitor resistance, and ErbB signaling. Gloriosine showed strong binding affinity toward hub targets. Experimental studies confirmed concentration-dependent inhibition of cell proliferation and migration. Mechanistically, gloriosine suppressed glutamine metabolism via GLS1 downregulation and induced ferroptosis, evidenced by increased ROS, glutathione depletion, GPX4 downregulation, and elevated intracellular iron levels. ConclusionsGloriosine exerts significant anti-cancer effects in TNBC through multi-target modulation and induction of ferroptosis, highlighting its potential as a promising therapeutic candidate. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/725321v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@ce0ebcorg.highwire.dtl.DTLVardef@29603borg.highwire.dtl.DTLVardef@6d0025org.highwire.dtl.DTLVardef@249700_HPS_FORMAT_FIGEXP M_FIG C_FIG Flow chart of the network pharmacological and in vitro study of gloriosine

Background and aimsTherapeutic outcomes for advanced hepatocellular carcinoma remain inadequate, despite recent advances using immunotherapy. Long-term effectiveness of systemic therapies, including second-line multi-tyrosine kinase inhibitor sorafenib, is limited by resistance mechanisms and adverse effects. Upregulated deubiquitinase UCH-L1 is frequently correlated with poor prognosis in cancers. Here, we investigated the therapeutic potential of combining pharmacological UCH-L1-inhibition with sorafenib in HCC. MethodsUCH-L1 expression was analysed in TCGA-LIHC data and patient-derived HCC tissues. Sorafenib and LDN57444 effects were evaluated in vitro in cytotoxicity and invasion assays. Gene and protein expression were examined by RT-qPCR, Western blotting and immunohistochemistry. In vivo efficacy of drug synergy was assessed in an orthotopic xenograft mouse HCC model. ResultsIn silico data-analysis revealed significantly higher UCH-L1 levels in patient HCC tumours versus non-tumour, associated with reduced overall survival. Low-dose sorafenib upregulated UCH-L1 in HCC cell line Hep3B. Paradoxically, this also promoted invasiveness and sustained MEK1/2-ERK1/2-pathway activation. Combining low-dose sorafenib with LDN57444 produced strong synergistic cytotoxicity in vitro, reverted MAPK-activation and suppressed invasion. Consistently, at low sorafenib dose co-treatment with LDN57444 completely inhibited tumour growth of Hep3B xenografts and enhanced sorafenib efficacy. ConclusionLDN57444 sensitises HCC cells to low-dose sorafenib by reverting drug-induced pro-oncogenic signalling and thereby strongly synergises with sorafenib to enhance anti-tumour efficacy in a HCC mouse model. This presents UCH-L1 as a player in treatment-induced adaptive response and supports further exploring UCH-L1-targeting in combination with sorafenib as therapeutic avenue for advanced HCC. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/725527v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@176dc91org.highwire.dtl.DTLVardef@8acae8org.highwire.dtl.DTLVardef@f71bborg.highwire.dtl.DTLVardef@1f3c5aa_HPS_FORMAT_FIGEXP M_FIG C_FIG Lay summaryThis study explores a new treatment approach for hepatocellular carcinoma (HCC) by combining two drugs: LDN57444, which blocks the enzyme UCH-L1, and sorafenib, a FDA-approved multi-tyrosine kinase inhibitor. We evaluated the effect of this drug combination in vitro using a HCC cell line and in an mouse HCC-model. The drug combination displayed strong, synergy in lowering HCC cell viability, and greatly reduced invasiveness and in vivo tumour growth. LDN57444 sensitised HCC cells to low doses of sorafenib by preventing UCH-L1-mediated activation of pro-oncogenic signalling. These findings highlight the potential of this new drug combination for treating advanced HCC thereby potentially reducing side-effects and countering drug resistance. Impact and implicationsOur preclinical research introduces a novel combination strategy against advanced HCC that holds potential to improve existing therapies, particularly the second-line multi-tyrosine kinase inhibitor sorafenib. The proposed combination of sorafenib with an inhibitor of the deubiquitinase UCH-L1 not only enhances sorafenib efficacy but present promise to also counter resistance mechanisms. Moreover, because effective responses are achieved at lower drug doses, this may in addition reduce therapy-associated adverse effects further increasing potential impact. While sorafenib is FDA-approved, the UCH-L1 inhibitor LDN57444 needs further (clinical) development to bring our promising findings to full translational potential for HCC patients and physicians.

Reactive oxygen species (ROS) are central signaling molecules in many biological processes by inducing oxidative modifications of protein cysteine residues, including S-glutathionylation. Increasing evidence supports that ROS contribute to cancer progression via promoting cancer cell migration, invasion, and metastasis. Nevertheless, the protein targets of S-glutathionylation that regulate cancer cell motility remain ill-defined. In this study, we report on the redox regulation of ARHGEF7, a guanine nucleotide exchange factor highly expressed in metastatic cancer cells, that plays a major role in regulating cell migration. Our data demonstrates that ARHGEF7 is selectively glutathionylated at the highly conserved C312 residue in its PH domain, which is implicated in regulating its enzymatic activity. Breast cancer cell lines showed increased cell migration and invasion upon glutathionylation of ARHGEF7 at C312 in response to both oxidative stress and epidermal growth factor (EGF). Mechanistically, upon C312 glutathionylation, ARHGEF7 exhibited significantly enhanced binding to Rac1 and increased Rac1 recruitment to the cell membrane and lamellipodia. ARHGEF7 S-glutathionylation also increased its enzymatic rate of GDP-GTP nucleotide exchange, resulting in Rac1 activation. Consequently, ARHGEF7 C312 S-glutathionylation induced Rac1-PAK1 activation and their downstream pathways, including LIMK1 and MEK1, thereby enhancing migration and invasion. Our data reveal a new redox player in cell migration, with its potential implications for ROS-induced cancer progression.

Background: Immune checkpoint inhibitors have transformed cancer treatment, yet a large number of patients fail to respond. Identifying molecular characteristics that predict response before treatment initiation remains an unmet need. Towards that end, this study presents a large-scale integrative analysis of existing single-cell and bulk tissue datasets, aimed at identifying predictive features while providing insights into their cellular origin and potential function within the tumor microenvironment. Methods: A stepwise analysis was performed using single-cell RNA-sequencing data from 60 melanoma patients at baseline, separated into discovery (n=41) and validation (n=19) sets. An integrated bulk transcriptomics dataset (n=128) from melanoma patients and a bladder cancer dataset (n=298) were used for further validation. Results: Integrative analysis of melanoma single-cell datasets revealed that responders exhibit distinct molecular profiles across multiple cell types compared to non-responders. Notably, these included downregulation of the TNFR superfamily and other immunosuppressive genes (TNFRSF18, TNFRSF9, TNFRSF4, LGALS1, BATF, IL12RB2, LINGO1, DUSP4, SDC4, VCAM1) in T-cells. By investigating the findings from the immune cell populations in the bulk tumor context, 13 transcripts were found to be consistently associated with response across all cohorts. These were differentially expressed in T-cells (SELL, EPB41, CD96, UHFR2, LINGO1, LGALS1), B-cells (ALDH5A1), NK cells (PLEC, PDGFRB) and Monocytes (TLR10, ST6GAL1, IKZF1, MPRIP). A predictive model based on these features effectively discriminated responders from non-responders in melanoma (AUC=0.73). The model maintained significant predictive power in an independent bladder cancer dataset (IMvigor210; AUC=0.64). Of high clinical relevance, it demonstrated enhanced performance in identifying responders among patients with low tumor mutational burden (AUC=0.75). Conclusion: Our study reveals pre-treatment molecular features related to immune-cancer crosstalk that are associated with response to immunotherapy. A 13-gene model demonstrates potential added clinical value in stratifying responders, particularly in patients with low tumor mutational burden, meriting further validation.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is the paradigmatic immunotherapy-refractory cancer, with a 5-year survival of approximately 12% and minimal benefit from immune checkpoint blockade (ICB). The dominant mechanistic explanation classifies PDAC as a T cell-excluded "cold" tumor, implying that no functional anti-tumor T cells are available for checkpoint release. Whether this Block-strategy view is correct has not been re-examined under integrated evasion-framework analysis. MethodsWe applied a previously developed 16-module immune evasion framework to TCGA-PAAD (n=183), integrated with hub-cytokine analysis (IL-10/TGF-{beta}), Kv1.3-immune channelome data, and clinical trial mapping (12,007 trials). Single-cell validation used two independent PDAC cohorts retrieved through TISCH2: PAAD_CRA001160 (Peng 2019, 35 samples [24 PDAC + 11 adjacent normal], 57,443 cells) and PAAD_GSE154778 (Lin 2020, 16 samples, 14,953 cells), examined for CD8A, TOX, PRF1, KCNA3, and FAP expression by cell type. ResultsPDAC scored highest in CAF Wall (z=0.768) and Platelet Cloak (z=0.663) modules; strategy classification yielded Brake -- not Block -- driven by a positive KCNA3-survival relationship (HR=0.649, 95% CI 0.43-0.97, p=0.037). Single-cell qualitative analysis of TISCH2 violin plots showed that CD8 exhausted T cells (CD8Tex) carried (i) high CD8A, (ii) the highest TOX expression among annotated cell types, (iii) preserved PRF1, and (iv) high KCNA3 expression. FAP was strongly localized to fibroblasts (peak [~]3.0 vs. <0.5 elsewhere). The pattern was reproduced in the second cohort. The optimal three-module attack (MHC restoration + CAF disruption + VEGF blockade) suppressed 10 of 16 evasion modules in silico (62.5%); zero of 370 PDAC immunotherapy trials test this combination. ConclusionsPDAC may not be T cell-cold but T cell-trapped: CD8 T cells with intact Kv1.3 channels appear immobilized behind a FAP-positive cancer-associated fibroblast wall. ICB monotherapy is mechanistically insufficient because the brake is engaged on T cells that cannot reach the tumor. The framework predicts that triple-targeted intervention -- checkpoint release + CAF wall disruption + vascular normalization -- is the minimum effective strategy. This is a hypothesis-generating computational analysis; prospective experimental and clinical validation are required.

Background: The development of personalised mRNA cancer vaccines holds considerable promise for oncology, yet a significant translational gap persists between neoantigen identification and the selection of therapeutically impactful targets. Current approaches predominantly prioritise human leukocyte antigen (HLA) binding affinity and immunogenicity, often overlooking the systems-level biological context of the target. This can inadvertently favour immunogenic but biologically peripheral peptides that exert limited influence on tumour signalling networks, thereby constraining vaccine efficacy. Furthermore, mRNA therapeutics must satisfy additional design requirements, including favourable codon usage and favourable secondary-structure stability, which directly affect in vivo translation and half-life. A unified computational framework that integrates neoantigen discovery with network biology is therefore critically needed. Results: Here, we present PimRNA, a Priority index (Pi)-centric computational medicine framework that bridges this gap by unifying neoantigen identification, mRNA sequence optimisation, and gene interaction network analysis. First, high-confidence tumour-specific HLA class I and II neoantigenic peptides are identified from paired tumour-normal genomic and tumour transcriptomic data using NeoDisc. Second, the coding sequences of these peptides are optimised for stability and translational efficiency with LinearDesign, yielding a core set of neoantigen-encoding mRNAs. Third, a random walk with restart algorithm is applied to a knowledgebase of gene interactions to identify peripheral genes exhibiting significant network connectivity to core genes, generating a gene-predictor matrix in which each gene is assigned an affinity score reflecting its network proximity to immunogenic neoantigens. These scores are consolidated into a single, unified priority rating (0-5) for each gene, followed by subnetwork analysis that reveals therapeutically relevant gene modules. Application of PimRNA to breast cancer and melanoma datasets demonstrates that it successfully selects high-confidence immunogenic neoantigen candidates embedded within biologically meaningful tumour-specific networks. Conclusion: PimRNA provides a systems biology foundation for mRNA vaccine design, moving beyond isolated immunogenicity to prioritise targets that are both highly presented and central to tumour-relevant biological networks. This framework offers a generalisable strategy for the rational discovery and prioritisation of mRNA therapeutics, significantly advancing the field of computational medicine towards personalised cancer vaccines.

Importance: While gut dysbiosis is known to impair response to immune checkpoint inhibitors (ICIs), the relative clinical impact of antibiotic timing (pre- vs. post-ICI initiation) remains unclear. Objective: To evaluate whether antibiotic timing differentially influences overall survival (OS) in a large, multi-institutional pan-cancer cohort. Design, Setting, and Participants: This retrospective cohort study utilized deidentified electronic health record data from six academic medical centers within the University of California Health system. We included 21,108 adults with any malignancy who received PD-1, PD-L1, or CTLA-4 inhibitors between January 2014 and December 2024. Exposures: Antibiotic exposure windows were categorized as pre-only (-60 to -1 days), post-only (+1 to +60 days), both windows, or none. Main Outcomes and Measures: The primary outcome was overall survival (OS) calculated from the first ICI dose. Multivariable Cox proportional hazards models adjusted for demographics, tumor type, line of therapy, and baseline health indicators (albumin, NLR, and recent hospitalization). Results: Among 21,108 patients, 17.3% had pre-only exposure, 13.3% had post-only exposure, and 60.6% had no exposure. In the multivariable model, post-only exposure (HR, 1.27; 95% CI, 1.20-1.35) and combined pre- and post- exposure (HR, 1.31; 95% CI, 1.23-1.40) were significantly associated with higher mortality. Pre-only exposure was not significantly associated with OS (HR, 1.04; 95% CI, 0.99-1.10). Subgroup analyses by tumor type showed consistent trends across major malignancies, including head and neck (Post HR, 1.46) and renal cell carcinoma (Post HR, 1.26). Conclusions and Relevance: In contrast to some smaller studies, this large-scale analysis indicates that antibiotic exposure after ICI initiation carries a greater risk than exposure prior to treatment. These findings highlight the need for rigorous antibiotic stewardship strategies specifically during the early phases of immunotherapy treatment.

BackgroundRecent evidence suggests that cancer can exhibit splicing alterations that give rise to tumour-specific isoforms. One example is NUMB, which produces four isoforms (p72, p71, p66, and p65) through alternative splicing of exons 3 and 9. Traditionally considered a tumour suppressor, it also has been considered an oncogene. We propose that this duality is due to isoform-specific expression. ResultsUsing public databases, we identified a tumour-associated switch in NUMB isoform expression: p72/p71 are upregulated in tumours, whereas p66/p65 are more expressed in non-tumour tissues. These isoforms correlate differently with cellular processes. NUMBL, a NUMB homolog, behaves similarly to p65. We identified two transcriptional clusters: one characterized by high expression of p72/p71, and another by p66/p65/NUMBL. Each group was associated differently with the Notch, WNT/{beta}-catenin, Hedgehog, and Hippo signalling pathways, suggesting isoform-specific regulatory roles. Analysis of breast cancer cell lines (CCLE) led to a NUMB score based on isoform expression, which classified cell lines into biologically distinct groups. The p72/p71-enriched group showed distinct signatures, pathway activity, and drug sensitivity. Applying this score to TCGA-BRCA samples revealed a significant link between high NUMB-score and poor survival, confirmed by Kaplan-Meier analysis. ConclusionsNUMB emerges as a potential oncogenic contributor and biomarker in splicing-based personalised medicine, highlighting isoform-specific expression as a clinically relevant determinant of tumour behaviour, pathway activity, and therapeutic response.

Background & AimsHepatocellular carcinoma (HCC) frequently exhibits resistance to immune checkpoint inhibitors (ICIs), particularly in {beta} -catenin-driven tumors characterized by immune exclusion. While the Unfolded Protein Response (UPR) and the Integrated Stress Responses (ISR) enable tumor adaptation to metabolic stress their role in shaping tumor immunogenicity remains incompletely understood. We investigated whether ATF4, a central effector of the integrated stress response, couples metabolic reprogramming to suppression of anti-tumor immunity in HCC. MethodsWe combined transcriptomic analyses across three independent human HCC cohorts with mechanistic studies using an immunotherapy-resistant MYC/{beta}-catenin-driven murine HCC model. We integrated CRISPR/Cas9-mediated deletion of Atf4 with RNA-sequencing and targeted metabolomics. The impact of tumor-derived metabolites on macrophage differentiation and polarization was evaluated using primary bone marrow-derived cells. Therapeutic responses were evaluated in orthotopic and subcutaneous models treated with anti-PD-1 and anti-VEGFA. ResultsATF4 and XBP1 transcriptional signatures are selectively enriched in human HCC and associate with poor prognosis, vascular invasion, and an immunosuppressive myeloid-enriched tumor microenvironment. Genetic ablation of Atf4 markedly suppressed tumor growth in immunocompetent but not immunodeficient hosts, establishing a requirement for immune-mediated tumor control. Mechanistically, Atf4 loss downregulated Aldh18a1 and disrupted proline biosynthesis, resulting in extracellular proline depletion. This proline-deficient environment abrogated monocyte-to-macrophage differentiation and decreased M2 polarization, thereby reshaping the tumor microenvironment toward enhanced T cell infiltration and activation. Functionally, Atf4-deficient tumors exhibited restored sensitivity to anti-PD-1 monotherapy and showed pronounced responses to combined anti-PD-1/anti-VEGFA treatment in aggressive orthotopic models. ConclusionATF4 programs a proline-dependent metabolic axis that sustains macrophage-mediated immunosuppression and immune evasion in {beta}-catenin-driven HCC. Disruption of this pathway converts immune-excluded tumors into T cell-inflamed states and restores responsiveness to immunotherapy. By governing proline homeostasis and macrophage-mediated immunosuppression, ATF4 is a key metabolic checkpoint for immune evasion, linking stress adaptation to immune escape and a candidate therapeutic target in HCC. Impact and implicationsWe identify ATF4 as a crucial metabolic-immune orchestrator that sustains myeloid-driven immune evasion in {beta}-catenin-dependent HCC through proline-dependent circuitry. Disrupting the ATF4-proline axis converts immune-desert tumors into T cell-inflamed lesions by blocking macrophage differentiation, thereby sensitizing tumors to immune checkpoint therapy. This work positions ATF4 as a tractable therapeutic target to overcome immunotherapy resistance in HCC. Graphical abstract Highlights- ATF4 orchestrates an immunosuppressive tumor microenvironment in HCC by coupling metabolic stress adaptation to immune evasion. - Ablation of ATF4 disrupts proline biosynthesis, leading to a marked depletion of extracellular proline. - Cancer cell-derived proline availability contributes to macrophage differentiation and M2 polarization; its loss restores T cell-mediated anti-tumor surveillance and sensitizes beta-catenin-driven HCC to immune checkpoint blockade.

Background: Immune-oncology has revolutionized cancer treatment, but some patients fail to benefit due to primary resistance and tumour-immune evasion. Extracellular vesicles (EVs) are secreted by both tumour and immune cells and mediate communication between cancer cells and the immune system. Our study used proteomic profiling of circulating EVs collected from NSCLC patients treated with immune checkpoint inhibitors (ICI) to identify predictive biomarkers of response as well as immune evasion mechanisms related to treatment resistance. Methods: EVs were isolated from plasma collected prior to ICI treatment using peptide-affinity purification and high-throughput proteomics was performed using Proximal Extension Assay. Differentially expressed EV proteins between durable (DR) and non-durable responders (NDR) were identified and evaluated using Cox proportional hazards regression, survival analysis, sex-stratified analysis, as well as pathway and network analysis. Results: Proteomics analysis identified 116 differentially expressed EV proteins between DR and NDR. NDR was characterized by enrichment of inflammatory, angiogenic, and immune-suppressive EV proteins, such as IL1RL1, TFRC, IL6ST, galectins, TNF superfamily death receptors, chemokines, and PCSK9. Pathway analysis revealed enrichment of angiogenesis, chemotaxis, ECM remodeling, and neutrophil degranulation associated with poor progression-free survival (PFS). In contrast, DR to ICI treatment was associated with EV proteins related to T- and B-cell activation and adaptive immunity. Sex-related differences in abundance and association with PFS was observed for certain EV proteins, including IL1RL1 and TFRC. A six protein EV model (IL1RL1, TFRC, ERI1, CCN5, IGFBPL1, and TNFRSF13C) demonstrated good prognostic performance for identifying NDR (AUC = 0.907) and stratified patients into three discrete risk groups. Conclusions: High-plex EV proteomics revealed biologically coherent tumour-immune signaling programs that are associated with ICI treatment resistance. Profiling circulating EVs may improve our understanding of EV-mediated immune evasion mechanisms and identify protein signatures that reflect the tumour immune microenvironment and predict response to immune checkpoint blockade.