Mol Med Rep. 2026 Jan;33(1):6. doi: 10.3892/mmr.2025.13716. Epub 2025 Oct 17.

ABSTRACT

R‑loops, three‑stranded nucleic acid structures composed of an RNA:DNA hybrid and displaced single‑stranded DNA, have emerged as important regulators of gene expression and genome maintenance. Although physiological R‑loops participate in normal cellular processes, their dysregulation can threaten genomic integrity by inducing DNA damage and replication stress. The present review explores the role of R‑loops in hepatocellular carcinoma (HCC), a malignancy characterized by marked genomic instability. In the present review, the formation mechanisms of R‑loops, their dual functions in transcriptional regulation and DNA damage, and their specific implications for HCC pathophysiology were discussed. HCC cells exhibit altered R‑loop homeostasis with aberrant accumulation linked to hepatitis B virus infection, inflammatory signaling and oncogene activation. The present review highlighted how HCC cells exploit or manage R‑loops to promote tumor progression, particularly through the epigenetic silencing of differentiation genes and modulation of replication stress responses. Furthermore, emerging therapeutic strategies targeting R‑loop biology were examined, including small molecules that induce synthetic lethality, gene‑based interventions and combination approaches that exploit R‑loop vulnerabilities. Challenges in targeting R‑loops and future directions, including multi‑omics profiling and biomarker development, were also addressed. Understanding the complex interplay between R‑loops and HCC offers promising avenues for novel diagnostic and therapeutic approaches for this malignancy.

PMID:41104860 | DOI:10.3892/mmr.2025.13716

J Proteome Res. 2025 Sep 1. doi: 10.1021/acs.jproteome.5c00424. Online ahead of print.

ABSTRACT

Glioma is an aggressive brain tumor that requires challenging treatments. Tumor Treating Fields (TTFields), an FDA-approved therapy for glioblastoma (GBM), pleural mesothelioma, and platinum-refractory metastatic nonsmall cell lung cancer (in combination with PD-1/PD-L1 inhibitors or docetaxel), employs specific frequency electric fields to disrupt cell division and enhance treatment efficacy. However, their molecular mechanisms remain unclear. This study aimed to elucidate these mechanisms and optimize the therapeutic potential of TTFields through quantitative proteomics, phosphoproteomics, and glycoproteomics. Pathway analysis of the proteomics revealed that TTFields impact the cell cycle, DNA repair, autophagy, and DNA replication. Phosphoproteomic studies further demonstrated a marked decline in the activity of key kinases ABL1 and PDK1, while glycoproteomics highlighted disruptions in cell adhesion and ECM-receptor interactions. Notably, proteomic analysis identified an upregulation of PARP1 and BRD4 protein levels, suggesting a previously unrecognized resistance mechanism. Consistently, combining TTFields with inhibitors targeting these proteins significantly enhanced the treatment efficacy in U87 cells. Thus, this study uncovers comprehensive molecular mechanisms underlying TTFields' effects on GBM cells and supports the development of concomitant therapies to enhance treatment efficacy.

PMID:40889189 | DOI:10.1021/acs.jproteome.5c00424

Cell. 2025 Aug 22:S0092-8674(25)00922-5. doi: 10.1016/j.cell.2025.08.008. Online ahead of print.

ABSTRACT

Performing total RNA profiling on formalin-fixed, paraffin-embedded (FFPE) samples, the predominant sample conservation method in clinical practice, remains challenging for current spatial transcriptomics techniques. Here, we introduce Stereo-seq V2, which employs random primers to capture and sequence RNAs in situ on FFPE sections and provides single-cell resolution. The random-priming-based strategy offers unbiased transcript capturing and uniform gene body coverage, which increase the sensitivity to marker genes, the efficiency of non-polyadenylation (poly(A)) RNA profiling, and immune repertoire coverage. We demonstrated the robust performance of Stereo-seq V2 on clinical FFPE samples using triple-negative breast cancer (TNBC) sections and identified tumor-specific alternative splicing events. In a Mycobacterium tuberculosis (Mtb)-infected mouse model, we monitored gene expression dynamics of host and pathogen transcriptomes simultaneously by utilizing Stereo-seq V2. We also assembled immune repertoires and identified Mtb-specific BCR clones, which could also be observed in human tuberculous lung samples. These results highlight Stereo-seq V2's potential in biomedical research and personalized medicine.

PMID:40882628 | DOI:10.1016/j.cell.2025.08.008

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

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

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 Proteome Res. 2025 Aug 2. doi: 10.1021/acs.jproteome.5c00385. Online ahead of print.

ABSTRACT

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have transformed lung adenocarcinoma (LUAD) treatment in EGFR-mutant (MT) patients, but strategies targeting wild-type (WT) EGFR tumors remain necessary. This study analyzed a diverse LUAD patient cohort with EGFR mutation statuses and wild-type profiles for ALK and KRAS to identify stage-specific biomarkers. Using quantitative proteomics and multiomics, we discovered 21 dysregulated proteins in early-stage EGFR-WT LUAD, identifying myeloid-derived growth factor (MYDGF) as a key candidate biomarker. Elevated MYDGF levels in tissue (n = 117) and serum (n = 196) correlated significantly with cancer stage in EGFR-WT patients but not EGFR-MT cases. Notably, a higher tumor-to-normal MYDGF ratio predicted a favorable prognosis in early-stage EGFR-WT LUAD. Functional studies demonstrated that MYDGF exerts distinct roles in cell viability and migration depending on its cellular localization and the invasive potential of cancer cells. Specifically, secreted MYDGF promoted a protumorigenic phenotype, whereas excess intracellular MYDGF appeared to suppress the oncogenic capacity of aggressive cancer cells. MYDGF knockdown and subsequent proteomic analysis provided further insights into these context-dependent functions. These findings highlight EGFR status- and stage-specific proteomic profiles in LUAD, emphasizing the importance of context-dependent biomarker assessment for personalized treatment strategies.

PMID:40752010 | DOI:10.1021/acs.jproteome.5c00385

World J Clin Oncol. 2025 Jul 24;16(7):106981. doi: 10.5306/wjco.v16.i7.106981.

ABSTRACT

Cancer remains a major global health concern, with escalating incidence and mortality rates underscoring the urgent need for novel diagnostic and therapeutic strategies. Increasing evidence has identified the oral microbiota as a critical contributor to tumorigenesis, thereby expanding the understanding of cancer pathogenesis beyond conventional risk factors such as tobacco use and genetic predisposition. This review summarizes recent progress in elucidating the complex relationship between the oral microbiota and various malignancies, particularly oral squamous cell carcinoma, esophageal adenocarcinoma, and pancreatic ductal adenocarcinoma. Pathogenic bacteria, including Porphyromonas gingivalis and Fusobacterium nucleatum, have been implicated in promoting tumor progression through mechanisms involving chronic inflammation, the production of metabolic toxins, and immune evasion. The dysbiosis of the oral microbiota, often driven by lifestyle factors such as poor diet, tobacco use, and alcohol consumption, further exacerbates these carcinogenic processes. Emerging therapeutic approaches including probiotics, oral microbiota transplantation, and CRISPR-based bacterial editing are under investigation for their potential to restore microbial homeostasis and suppress pathogenic species. Additionally, saliva-based microbial biomarkers have shown promise for non-invasive cancer screening. The integration of multi-omics technologies and artificial intelligence-driven platforms is further advancing the development of precision oncology. This review aims to consolidate fragmented findings concerning the oral microbiota-cancer axis and address existing gaps in mechanistic understanding. The review's significance lies in the translational potential of microbial research to clinical applications, offering opportunities to reduce the global cancer burden through early detection and microbiota-targeted therapies.

PMID:40741186 | PMC:PMC12304933 | DOI:10.5306/wjco.v16.i7.106981

Int J Surg. 2025 Jul 22. doi: 10.1097/JS9.0000000000002999. Online ahead of print.

ABSTRACT

BACKGROUND: Breast cancer remains the most prevalent malignancy among women, and patients presenting with both breast and lung cancer pose significant challenges in clinical diagnosis and treatment. Currently, comprehensive multi-omics analyses for such multiple malignancies are lacking.

METHODS: An integrated multi-omics analysis was performed, incorporating quantitative proteomics and radiomics data from patients with single primary breast cancer as well as those with multiple primary tumors (breast and lung cancer).

RESULTS: Quantitative proteomics analysis revealed four distinct molecular signatures (Types I-IV). Patients with single breast cancer exhibited driving pathways primarily linked to cell proliferation (e.g., HER2), whereas those with multiple breast cancers showed enrichment in ER-related and proliferative pathways. In contrast, patients with multiple lung cancers displayed pathways associated with immune response and immune escape. Additionally, immune subtyping identified three distinct immune landscapes (Types I-III). Radiomic analysis demonstrated strong correlations between these molecular/immune subtypes and imaging findings. Patients with high imaging information scores exhibited pronounced tumor heterogeneity and reduced immune infiltration.

CONCLUSIONS: This study provides new insights into the molecular pathogenesis of multiple primary malignancies, particularly breast and lung cancer.

PMID:40694032 | DOI:10.1097/JS9.0000000000002999