Ovarian cancer (OC) ranks as the most lethal gynaecological malignancy worldwide, with early diagnosis being crucial yet challenging. Current diagnostic methods like transvaginal ultrasound and blood biomarkers show limited sensitivity/specificity. This study aimed to identify and validate serum metabolic biomarkers for OC diagnosis using the largest cohort reported to date. We constructed a large-scale OC-associated cohort of 1432 subjects, including 662 OC, 563 benign ovarian disease, and 207 healthy control subjects, across retrospective (n = 1073) and set-aside validation (n = 359) cohorts. Serum metabolic fingerprints (SMFs) were recorded using nanoparticle-enhanced laser desorption/ionization mass spectrometry (NELDI-MS). A diagnostic panel was developed through machine learning of SMFs in the discovery cohort and validated in independent verification and set-aside validation cohorts. The identified metabolic biomarkers were further validated using liquid chromatography MS and their biological functions were assessed in OC cell lines. We identified a metabolic biomarker panel including glucose, histidine, pyrrole-2-carboxylic acid, and dihydrothymine. This panel achieved consistent areas under the curve (AUCs) of 0.87-0.89 for distinguishing between malignant and benign ovarian masses across all cohorts, and improved to AUCs of 0.95-0.99 when combined with risk of ovarian malignancy algorithm (ROMA). In vitro validation provided initial biological context for the metabolic alterations observed in our diagnostic panel. Our study established a reliable serum metabolic biomarker panel for OC diagnosis with potential clinical translations. The NELDI-MS based approach offers advantages of fast analytical speed (∼30 s/sample) and low cost (∼2-3 dollars/sample), making it suitable for large-scale clinical applications. MOST (2021YFA0910100), NSFC (82421001, 823B2050, 824B2059, and 82173077), Medical-Engineering Joint Funds of Shanghai Jiao Tong University (YG2021GD02, YG2024ZD07, and YG2023ZD08), Shanghai Science and Technology Committee Project (23JC1403000), Shanghai Institutions of Higher Learning (2021-01-07-00-02-E00083), Shanghai Jiao Tong University Inner Mongolia Research Institute (2022XYJG0001-01-16), Sichuan Provincial Department of Science and Technology (2024YFHZ0176), Innovation Research Plan by the Shanghai Municipal Education Commission (ZXWF082101), Innovative Research Team of High-Level Local Universities in Shanghai (SHSMU-ZDCX20210700), Basic-Clinical Collaborative Innovation Project from Shanghai Immune Therapy Institute, Guangdong Basic and Applied Basic Research Foundation (2024A1515013255).

Ovarian cancer is characterized by aberrant activation of the mitogen-activated protein kinase (MAPK), highlighting the importance of targeting the MAPK pathway as an attractive therapeutic strategy. However, the clinical efficacy of MEK inhibitors is limited by intrinsic or acquired drug resistance. Here, we established patient-derived ovarian cancer models resistant to MEK inhibitors and demonstrated that resistance to the clinically approved MEK inhibitor trametinib was associated with enhancer reprogramming. We also showed that enhancer decommissioning induced the downregulation of negative regulators of the MAPK pathway, leading to constitutive ERK activation and acquired resistance to trametinib. Epigenetic compound screening uncovered that HDAC inhibitors could alter the enhancer reprogramming and upregulate the expression of MAPK negative regulators, resulting in sustained MAPK inhibition and reversal of trametinib resistance. Consequently, a combination of HDAC inhibitor and trametinib demonstrated a synergistic antitumor effect in vitro and in vivo, including patient-derived xenograft mouse models. These findings demonstrated that enhancer reprogramming of the MAPK regulatory pathway might serve as a potential mechanism underlying MAPK inhibitor resistance and concurrent targeting of epigenetic pathways and MAPK signaling might provide an effective treatment strategy for advanced ovarian cancer.

Cervical cancer (CCa) patients with lymph node (LN) metastasis face poor prognoses and have limited treatment options. Aberrant N6-methyladenosine (m⁶A) modification of RNAs are known to promote tumor metastasis, but their role in CCa remains unclear. Our study reveals that HNRNPC, an alternative splicing (AS) factor and m⁶A reader, increases tumor-related variants through m⁶A-dependent manner, thereby promoting lymphatic metastasis in CCa. We found that HNRNPC overexpression correlates with lymphatic metastasis and poorer prognoses in CCa patients. Functionally, knocking down HNRNPC markedly inhibited the migration and invasion of several CCa cell lines, while supplementing HNRNPC restored the malignant phenotypes of these cells. Mechanistically, HNRNPC regulates exon skipping of FOXM1 by binding to its m6A-modified motif. Mutating the m⁶A site on FOXM1 weakened the interaction between HNRNPC and FOXM1 pre-RNA, leading to a reduction in the metastasis-related FOXM1-S variant. In conclusion, our findings demonstrate that m⁶A-dependent alternative splicing mediated by HNRNPC is essential for lymphatic metastasis in CCa, potentially providing novel clinical markers and therapeutic strategies for patients with advanced CCa.

Breast cancer and gynecological tumors seriously endanger women’s physical and mental health, fertility, and quality of life. Due to standardized surgical treatment, chemotherapy, and radiotherapy, the prognosis and overall survival of cancer patients have improved compared to earlier, but the management of advanced disease still faces great challenges. Recently, poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis) have been clinically approved for breast and gynecological cancer patients, significantly improving their quality of life, especially of patients with BRCA1/2 mutations. However, drug resistance faced by PARPi therapy has hindered its clinical promotion. Therefore, developing new drug strategies to resensitize cancers affecting women to PARPi therapy is the direction of our future research. Currently, the effects of PARPi in combination with other drugs to overcome drug resistance are being studied. In this article, we review the mechanisms of PARPi resistance and summarize the current combination of clinical trials that can improve its resistance, with a view to identify the best clinical treatment to save the lives of patients.

Cervical cancer (CC), a leading cause of cancer-related deaths among women worldwide, is primarily driven by high-risk human papillomavirus (HPV) infections and comprises two major histological subtypes: adenocarcinoma (AC) and squamous cell carcinoma (SCC). Despite advances in prevention and treatment, the molecular and cellular heterogeneity of these subtypes poses significant challenges to achieving optimal clinical outcomes. Here, we integrate single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to dissect the cellular and spatial heterogeneity of AC and SCC, uncovering distinct tumor microenvironment (TME) dynamics that underlie their divergent clinical behaviors. Our scRNA-seq analysis reveals that AC is enriched in epithelial cells, while SCC exhibits a more immunogenic TME with elevated plasma cells and NK/T cells. Spatial transcriptomics further highlights robust interactions between CD8 + T cells and epithelial subtypes in SCC, contrasting with the stromal-rich, immune-cold phenotype of AC. We identify subtype-specific immune and stromal features, including ICOS+ Tregs, IDO1+ cancer-associated fibroblasts (CAFs), and PLVAP+ endothelial cells, which may drive immune evasion, angiogenesis, and metastasis. These findings provide a comprehensive framework for understanding CC heterogeneity and offer actionable insights for developing subtype-specific therapeutic strategies, such as combining immune checkpoint inhibitors with stromal-targeting agents. This study underscores the potential of spatial multi-omics technologies to advance precision oncology and improve outcomes for cervical cancer patients.