FASEB J. 2025 Aug 31;39(16):e70978. doi: 10.1096/fj.202500722RR.

ABSTRACT

Ribophorin 1 (RPN1), a key component of the oligosaccharyltransferase complex, is implicated in tumor progression through glycosylation-mediated pathways, yet its pan-cancer roles remain unexplored. This study presents a comprehensive multi-omics analysis of RPN1 across 33 cancers such as sarcoma (SARC), integrating genomic, transcriptomic, and proteomic data from TCGA, GTEx, and CPTAC. RPN1 was significantly overexpressed in 14 malignancies and correlated with advanced tumor stages and poor prognosis in glioblastoma (GBM), lower-grade glioma, SARC and hepatocellular carcinoma, validated in an independent glioma cohort (n = 151). Genomically, RPN1 amplification linked to homologous recombination deficiency and elevated tumor mutational burden, suggesting a role in genomic instability. Critically, multiplex immunofluorescence demonstrates RPN1 overexpression colocalizes with CD206⁺ M2 macrophages in tumor microenvironments, while in vitro coculture experiments confirm RPN1-dependent microglial recruitment and M2 polarization. RPN1 expression negatively correlates with CD8⁺ T cell infiltration and predicts resistance to chemotherapy (GBM, ovarian cancer) and immunotherapy (GBM, esophageal carcinoma), though it associates with PD-1 inhibitor sensitivity in bladder cancer. Functional validation shows RPN1 knockdown suppresses proliferation, migration, and invasion in GBM cells. Pathway enrichment connects RPN1 to endoplasmic reticulum stress, glycosylation, DNA repair, and immune checkpoint regulation. These findings position RPN1 as a multimodal oncogenic driver promoting genomic instability, immunosuppressive microenvironment remodeling, and context-dependent therapeutic vulnerabilities across cancers.

PMID:40857034 | DOI:10.1096/fj.202500722RR

Cell Oncol (Dordr). 2025 Aug 26. doi: 10.1007/s13402-025-01103-3. Online ahead of print.

ABSTRACT

Lung cancer remains the leading cause of cancer-related mortality worldwide, with limited treatment efficacy and frequent resistance to conventional therapies. Recent advances have uncovered the critical influence of the human microbiota-complex communities of bacteria, viruses, fungi, and other microorganisms-on lung cancer pathogenesis and therapeutic responses. This review synthesizes current knowledge on the compositional and functional roles of microbiota across multiple body sites, including the gut, lung, tumor microenvironment, circulation, and oral cavity, highlighting their contributions to tumor initiation, progression, metastasis, and immune regulation. We emphasize the bidirectional communication between microbial metabolites and host immune pathways, particularly the gut-lung axis, which modulates systemic and local antitumor immunity. Importantly, microbiota composition has been linked to differential responses and toxicities in chemotherapy, radiotherapy, targeted therapy, and immune checkpoint blockade. Microbiota-targeted interventions, such as probiotics, fecal microbiota transplantation, and selective antibiotics, show promising potential to enhance treatment efficacy and mitigate adverse effects. However, challenges remain in clinical translation due to interindividual microbiome variability, mechanistic complexities, and limited longitudinal data. Future research integrating multi-omics, microbial functional profiling, and controlled clinical trials is essential to harness the microbiome as a precision medicine tool in lung cancer management. This review provides a comprehensive overview of the emerging role of microbiota in lung cancer development and therapy, offering new perspectives for innovative therapeutic strategies.

PMID:40856929 | DOI:10.1007/s13402-025-01103-3

Cell Rep. 2025 Aug 21;44(9):116191. doi: 10.1016/j.celrep.2025.116191. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease, and new therapeutic strategies are urgently needed. Here, we conduct an integrative, genome-scale examination of genetic dependencies and cell surface targets using CRISPR-Cas screening and multi-omic data, including single-nucleus and spatial transcriptomic data from patient tumors. We systematically identify clinically tractable and biomarker-linked PDAC dependencies, including CDS2 as a synthetic lethal target in cancer cells expressing signatures of epithelial-to-mesenchymal transition. We examine biomarkers and co-dependencies of the KRAS oncogene, defining gene expression signatures of sensitivity and resistance associated with response to pharmacological inhibition of KRAS. mRNA and protein profiling reveal cell surface protein-encoding genes with robust expression in patient tumors and minimal expression in non-malignant tissues. Furthermore, we define intratumoral and interpatient heterogeneity of target gene expression and identify orthogonal targets that suggest combinatorial strategies. Collectively, this work identifies multiple targets that may inform therapeutic strategies for patients with PDAC.

PMID:40848256 | DOI:10.1016/j.celrep.2025.116191

Nat Commun. 2025 Aug 22;16(1):7827. doi: 10.1038/s41467-025-63146-2.

ABSTRACT

While dysregulation of polyamine metabolism is frequently observed in cancer, it is unknown how polyamines alter the tumor microenvironment (TME) and contribute to therapeutic resistance. Analysis of polyamines in the plasma of pancreatic cancer patients reveals that spermine levels are significantly elevated and correlate with poor prognosis. Using a multi-omics approach, we identify Serpinb9 as a vulnerability in spermine metabolism in pancreatic cancer. Serpinb9, a serine protease inhibitor, directly interacts with spermine synthase (SMS), impeding its lysosome-mediated degradation and thereby augmenting spermine production and secretion. Mechanistically, the accumulation of spermine in the TME alters the metabolic landscape of immune cells, promoting CD8⁺ T cell dysfunction and pro-tumor polarization of macrophages, thus creating an immunosuppressive microenvironment. Small peptides that disrupt the Serpinb9-SMS interaction significantly enhance the efficacy of immune checkpoint blockade therapy. Together, our findings suggest that targeting spermine metabolism is a promising strategy to improve pancreatic cancer immunotherapy.

PMID:40846845 | PMC:PMC12373741 | DOI:10.1038/s41467-025-63146-2

Ann Rheum Dis. 2025 Aug 20:S0003-4967(25)04249-9. doi: 10.1016/j.ard.2025.07.016. Online ahead of print.

ABSTRACT

OBJECTIVES: Catastrophic antiphospholipid syndrome (CAPS) is a complement-driven thrombotic disorder, characterised by widespread thrombosis and multiorgan failure. We identified rare germline variants including complement receptor 1 (CR1) in 50% of patients with CAPS. Here, we define CR1 dysregulation mechanisms (genetic/epigenetic) underlying complement-mediated thrombosis in CAPS and support C5 inhibition as a potential therapy.

METHODS: We quantified CR1 expression by flow cytometry across haematopoietic cell types. CRISPR/Cas9 genome editing of TF-1 (erythroleukaemia) cells was performed to generate CR1 'knock-out' and 'knock-in' lines with patient-specific CR1 variants. Multiomics analysis was performed to investigate the role of methylation in patients with reduced CR1 expression. Functional impact of low CR1 was assessed by complement-mediated cell killing using modified Ham assay, cell-bound complement degradation products through flow cytometry, and circulatory immune complexes in serum samples through ELISA.

RESULTS: CR1 expression in erythrocytes was markedly reduced on CAPS erythrocytes (n = 9, 21.80%) compared to healthy controls (HCs; n = 35, 84.04%), with promoter hypermethylation emerging as a plausible epigenetic mechanism for CR1 downregulation. Novel germline variant (CR1-V2125L; rs202148801) mitigated CR1 expression and increased complement-mediated cell death of knock-in cell lines. Erythrocytes from the patient with the CR1-V2125L variant had low CR1 expression. Levels of circulating immune complexes, which are bound and cleared by CR1 on erythrocytes, were higher in acute CAPS (n = 3, 25.55 µg Eq/mL) than HCs (n = 3, 7.445 µg Eq/mL). Five patients were treated with C5 inhibition which mitigated thrombosis.

CONCLUSIONS: Genetic or epigenetic-mediated CR1 deficiency is a potential hallmark of CAPS and predicts response to C5 inhibition.

PMID:40841298 | DOI:10.1016/j.ard.2025.07.016

Expert Rev Anticancer Ther. 2025 Aug 18. doi: 10.1080/14737140.2025.2549538. Online ahead of print.

ABSTRACT

INTRODUCTION: In the era of precision medicine, molecular biomarker testing is increasingly becoming standard of care for Non-Small Cell Lung Cancer (NSCLC) patients. Tissue and liquid biopsy-based Next-Generation Sequencing (NGS) is now highly recommended.

AREAS COVERED: Different NGS platforms emerged as a cost-effective strategy to perform a massive and parallel sequencing performing higher technical sensitivity than old generation technologies in detecting low abundant alterations in challenging diagnostic samples. NGS systems can detect single nucleotide variants (SNV), small insertions and deletions (indels), copy number alterations (CNAs) and structural variants (SVs) or gene fusions across selected druggable genes optimizing clinical administration of NSCLC patients. The diagnostic implementation of the most adequate NGS panel depending on several factors that could impact on the clinical utility of testing assay.

EXPERT OPINION: Promising advanced technologies are emerging as potentially integrative tools in personalized medicine. In this context, multi-omic evaluation including genomic, transcriptomic, fragmentomic and epigenomic signatures are under investigation to significantly modify clinical algorithm of NSCLC patients. On this basis, sequencing strategies may play a pivotal role in the implementation of a new predictive model for cancer diagnosis and prognosis.

PMID:40823981 | DOI:10.1080/14737140.2025.2549538

Transl Lung Cancer Res. 2025 Jul 31;14(7):2369-2373. doi: 10.21037/tlcr-2025-523. Epub 2025 Jul 17.

NO ABSTRACT

PMID:40799451 | PMC:PMC12337028 | DOI:10.21037/tlcr-2025-523

Cell Cycle. 2025 Aug 13:1-22. doi: 10.1080/15384101.2025.2539645. Online ahead of print.

ABSTRACT

Epithelial carcinoma cells require penetration of the basement membrane (BM) to metastasize. The BM is a thin layer of extracellular matrix beneath epithelial and endothelial tissues. It acts as a structural barrier, preventing cancer cells from invading and undergoing endocytosis and exocytosis. Thus, understanding the relationship between the BM and tumor immunity can lead to new strategies for halting cancer progression and metastasis. Gene expression data of 33 cancers were obtained from the Cancer Genome Atlas database. The study analyzed the correlation between BM regulatory genes, copy number variations, immune-related genes, and tumor immune dysfunction rejection (TIDE). Immunohistochemical methods were used to analyze the expression of regulatory genes. And the BM score was calculated using single-sample gene set enrichment analysis. Single-cell transcriptional sequencing determined the activation status of the BM in the tumor microenvironment. The expression of BM-related genes (BMGs) exhibited significant heterogeneity across different cancer types. Most genes were up-regulated in tumor tissues. Major single nucleotide polymorphisms of BMGs included missense mutations, while major copy number variations were heterozygous deletion and heterozygous amplification. Additionally, the expressions of immune checkpoint molecules CD276, NRP1, and C10orf54 showed positive correlations with BMS. Numerous tumors displayed a significant positive correlation between BMS and TIDE scores. We demonstrate that BM regulatory genes undergo alterations specific to different cancer types, which are associated with the expression of immune checkpoints and immune dysfunction. This indicates that BM remodeling plays an active role in modulating immune resistance, rather than being a passive structural alteration.

PMID:40799172 | DOI:10.1080/15384101.2025.2539645

Biomark Res. 2025 Aug 11;13(1):101. doi: 10.1186/s40364-025-00812-z.

ABSTRACT

BACKGROUND: Early identification of high-risk individuals is crucial for optimizing cancer screening, particularly when considering expensive and invasive methods such as multi-omics technologies and endoscopic procedures. However, developing a robust, practical multi-cancer risk prediction model that integrates diverse, multi-scale data and with proper validation remains a significant challenge.

METHODS: We initialized the FuSion study by recruiting 42,666 participants from Taizhou, China, with a discovery cohort (n = 16,340) and an independent validation cohort (n = 26,308) after exclusion criteria. We integrated multi-scale data from 54 blood-derived biomarkers and 26 epidemiological exposures to develop a risk prediction model for five common cancers, including lung, esophageal, liver, gastric, and colorectal cancer. Employing five supervised machine learning approaches, we used a LASSO-based feature selection strategy to identify the most informative predictors. The model was trained and internally validated in the discovery cohort, externally applied in the validation cohort, and further evaluated through a prospective clinical follow-up to assess cancer events via clinical examinations.

RESULTS: The final model comprising four key biomarkers along with age, sex, and smoking intensity, achieving an AUROC of 0.767 (95% CI: 0.723-0.814) for five-year risk prediction. High-risk individuals (17.19% of the cohort) accounted for 50.42% of incident cancer cases, with a 15.19-fold increased risk compared to the low-risk group. During follow-up of 2,863 high-risk subjects, 9.64% were newly diagnosed with cancer or precancerous lesions. Notably, cancer detection in the high-risk group was 5.02 times higher than in the low-risk group and 1.74 times higher than in the intermediate-risk group. In particular, the incidence of esophageal cancers in the high-risk group was 16.84 times that of the low-risk group.

CONCLUSIONS: This is the first population-based prospective study in a large Chinese cohort that leverage multi-scale data including biomarkers for multi-cancer risk prediction. Our effective risk stratification model not only enhances early cancer detection but also lays the foundation for the targeted application of advanced screening methods, including but not limited to multi-omics technologies and endoscopy. These findings support precision prevention strategies and the optimal allocation of healthcare resources.

PMID:40790537 | PMC:PMC12341305 | DOI:10.1186/s40364-025-00812-z

J Transl Med. 2025 Aug 7;23(1):877. doi: 10.1186/s12967-025-06725-7.

ABSTRACT

BACKGROUND: Gastric cancer (GC) is characterized by significant intertumoral heterogeneity, which often leads to the development of resistance to platinum-based chemotherapy. Combining platinum drugs with other therapeutic strategies may improve treatment efficacy; however, the mechanisms underlying platinum resistance in GC remain unclear.

METHODS: Key genes related to platinum resistance in GC were selected from the platinum resistance gene database and GC resistance datasets. The Similarity Network Fusion (SNF) algorithm was employed, along with prognosis-related methylation data and somatic mutation data, to classify the molecular subtypes of GC based on GC platinum resistance genes. Gene expression profiles, prognosis, immune cell infiltration, chemotherapy sensitivity, and immunotherapy responsiveness were comprehensively evaluated for each subtype. Localization and functional evaluation were conducted at the single-cell and spatial transcriptomics levels, and predictive models were developed using machine learning techniques. These functional differences in platinum resistance gene models were further explored in GC. Moreover, experimental validation was conducted to elucidate the mechanisms of key genes involved in platinum resistance in GC.

RESULTS: Stomach adenocarcinoma (STAD) patients were classified into three subtypes using the SNF algorithm and multiomics data. Patients with subtype CS2 exhibited a significantly poorer prognosis than those with subtypes CS1 and CS3 (p < 0.05). Subtype CS1 was characterized as immune-deprived, CS2 as stroma-enriched, and CS3 as immune-enriched. Patients with subtype CS2 also exhibited the most adverse therapeutic responses to docetaxel, cisplatin, and gemcitabine. Single-cell analysis revealed high enrichment of M1 module cells with elevated expression of resistance genes, including the transcription factor KLF9. Spatial transcriptomic analysis further confirmed the independent spatial distribution of malignant cells with high expression of drug resistance genes (DRGs). Predictive models based on machine learning demonstrated excellent prognostic performance. Patients in the high DRG group also exhibited poorer responses to immunotherapy. Cellular experiments revealed that KLF9 overexpression significantly inhibited the proliferation of AGS cells (p < 0.05), reduced their resistance to platinum-based drugs, and markedly decreased the levels of inflammatory cytokines in them.

CONCLUSION: KLF9 was identified as a promising therapeutic target for overcoming platinum resistance in GC, warranting further investigation into its role and potential clinical applications.

PMID:40775648 | PMC:PMC12330134 | DOI:10.1186/s12967-025-06725-7

Future Sci OA. 2025 Dec;11(1):2527598. doi: 10.1080/20565623.2025.2527598. Epub 2025 Aug 7.

ABSTRACT

AIM: This study aims to present a comprehensive international analysis of the existing techniques used in liquid biopsies and their use in isolating tumor markers to detect, predict, and monitor the results of cancer treatment.

MATERIALS AND METHODS: We conducted a narrative review using a scoping review model based on three databases, including PubMed/Medline, Scopus, and Cochrane. The search criteria included all articles on liquid biopsy of the last five years (June 30th, 2023-Oct 30, 2024) ((liquid Biopsy) AND (("2023/06/30"[Date - Publication]: "2024/10/30"[Date - Publication]))). We also approached gray literature on this topic. We focused on review articles as an eligibility criterion for this narrative review, but we also carried out a United States registered clinical trials review targeting immunotherapy and liquid biopsy with the limitation "recruiting" and/or "not yet recruiting" (updated on March 31, 2025).

RESULTS: We screened 2645 articles from PubMed/Medline, Scopus, and Cochrane and 45 articles from the gray literature. We retrieved the full text for 325 articles. Liquid biopsies involve the extraction of tumor-derived components such as circulating tumor cells, circulating tumor DNA, and tumor extracellular vesicles from the bodily fluids of cancer patients. We found 25 United States registered governmental clinical trials targeting immunotherapy and liquid biopsy, of which 20 trials are recruiting and five trials are not yet recruiting.

DISCUSSION: Developments in medicine have led to a more comprehensive understanding of tumor features, including tumor load, tumor staging, heterogeneity, gene mutations, and clonal evolution. The utilization of liquid biopsies from cancer patients has provided novel opportunities for detection and ongoing monitoring, precision medicine-based therapy, and identification of markers for therapeutic resistance.

PMID:40772765 | PMC:PMC12333414 | DOI:10.1080/20565623.2025.2527598

Nat Commun. 2025 Aug 5;16(1):7178. doi: 10.1038/s41467-025-62593-1.

ABSTRACT

Spatial transcriptomics links gene expression with tissue morphology, however, current tools often prioritize genomic analysis, lacking integrated image interpretation. To address this, we present Thor, a comprehensive platform for cell-level analysis of spatial transcriptomics and histological images. Thor employs an anti-shrinking Markov diffusion method to infer single-cell spatial transcriptome from spot-level data, effectively combining gene expression and cell morphology. The platform includes 10 modular tools for genomic and image-based analysis, and is paired with Mjolnir, a web-based interface for interactive exploration of gigapixel images. Thor is validated on simulated data and multiple spatial platforms (ISH, MERFISH, Xenium, Stereo-seq). Thor characterizes regenerative signatures in heart failure, screens breast cancer hallmarks, resolves fine layers in mouse olfactory bulb, and annotates fibrotic heart tissue. In high-resolution Visium HD data, it enhances spatial gene patterns aligned with histology. By bridging transcriptomic and histological analysis, Thor enables holistic tissue interpretation in spatial biology.

PMID:40764306 | PMC:PMC12325965 | DOI:10.1038/s41467-025-62593-1