eBioMedicine

Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis

Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and clinical practice are urgently needed. The last decade has seen increasingly rapid advances in sequencing and biotechnological methodologies. Consequently, multiple omics technologies, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra, have been widely applied to analyze tissue- and liquid-derived samples from OC patients. The integration of multi-omics data has increased our knowledge of the disease and identified valuable OC biomarkers. In this review, we summarize the recent advances and perspectives in the use of multi-omics technologies in OC research and highlight potential applications of multi-omics for identifying novel biomarkers and improving clinical assessments.

B7-H3-mediated reversal of CAR-T cell exhaustion induces a notable antitumour response in ovarian cancer models

Functional CAR-T cell exhaustion in the immunosuppressive tumour microenvironment remains the main barrier to the success of CAR-T cell therapy for treating solid tumours. Mesothelin (MSLN) has emerged as an attractive target for CAR-T cell therapy for several solid malignancies, including ovarian cancer. In this study, we aimed to investigate the role and mechanism of lipid metabolites in anti-MSLN CAR-T cell exhaustion in ovarian cancer cells. We engineered anti-MSLN CAR-T cells targeting ovarian cancer cells with high MSLN expression as a pivotal tool for in vitro and in vivo experiments. Moreover, liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed the critical role of oxylipin 12-HETE in the exhaustion of CAR-T cells. By employing structure-based high-throughput virtual screening (HTVS), we identified the inhibitor targeting B7-H3. We demonstrated that GPR31-dependent 12-HETE accumulation in the ovarian cancer microenvironment drives CAR-T cell exhaustion via lipid peroxidation, impairing their antitumour efficacy. Genetic or pharmacological inhibition of the 12-HETE/GPR31 axis restored CAR-T cell cytotoxicity and proliferation, leading to significant tumour regression in murine models. Silencing B7-H3 relieved repression of FOXO3, leading to reduced 12-LOX expression and lower 12-HETE levels, which places B7-H3 upstream of this metabolic checkpoint. Through structure-based screening, we identified HI-TOPK-032 as a potent B7-H3 inhibitor that synergised with CAR-T cell therapy by reversing exhaustion markers (e.g., PD-1, TIM-3) and enhancing cytokine polyfunctionality. Combined HI-TOPK-032 and anti-PD-1 treatment achieved superior tumour control compared to monotherapies, particularly in B7-H3/12-LOX-high patient-derived xenografts, underscoring its precision therapeutic potential. CAR-T cell therapy combined with HI-TOPK-032 is a promising novel strategy for treating MSLN-expressing solid tumours. This study was funded by the National Natural Science Foundation of China (Grant number: 82503173), Beijing Hospitals Authority's Ascent Plan (Grant number: DFL20221201), Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support (Grant number: ZYLX202120), Beijing Natural Science Foundation (Grant number: 7162063), Capital Medical University Laboratory for Clinical Medicine and Gynecological Tumour Precise Diagnosis and Treatment Innovation Studio.

Quantifying rate-limiting genetic variation in breast and ovarian tumourigenesis

The number and type of genetic alterations required to initiate breast and ovarian cancer remain unclear. While germline BRCA1/2 carriers show markedly elevated cancer risk, it is uncertain whether point mutations or copy number alterations constitute the rate-limiting events of tumourigenesis. We developed a statistical framework extending prior incidence-mutation models to estimate the minimal number and type of driver events required for cancer initiation. Somatic mutation and copy-number data from >3000 breast and ovarian cancers in TCGA and METABRIC were compared between germline BRCA1/2 carriers and non-carriers matched on subtypes. Results were validated through analyses of evolutionary timing data, as well as single-cell whole genome sequencing (scWGS) data of genetically-engineered and patient-derived cancer/pre-cancerous cells. Deletions, rather than single-nucleotide variants (SNVs), emerged as the likely rate-limiting events. Modeling indicated that 1-3 deletions are sufficient to initiate tumourigenesis, whereas SNVs alone could not explain observed incidence ratios. BRCA1/2-driven and sporadic tumours converged on similar deletion profiles, including early recurrent deletions of chromosomes 13q and 17, though carriers accumulated them more rapidly. Deletion-associated chromosomal instability likely represents the central trigger for breast and ovarian cancer initiation. These results explain why certain somatic driver mutations detected in normal tissues may not predict malignant progression, and that early detection strategies should instead prioritize testing deletions as potential biomarkers. NIH/NCI (P30CA016042; 1U01CA214194-01), NIH NIGMS (R35GM138113, 2R35GM138113), ACS (RSG-22-115-01-DMC), CIHR Vanier Fellowship, and the Francis Crick Institute with core funding from Cancer Research UK, UK Medical Research Council, and Wellcome Trust.

Machine learning-enhanced gas sensor technology identifies ovarian and endometrial cancer of all stages through plasma volatile organic compound patterns

Ovarian cancer presents with non-specific symptoms that make early diagnosis challenging and the prognosis poor. Ovarian and endometrial cancers exhibit similar genomic mutations and biomarker profiles. Endogenous volatile organic compounds (VOCs) are products of metabolic activity. In cancer, metabolites increase due to tumour necrosis, leading to cancer-specific VOC patterns. The aim of this study was to evaluate VOC analyses in plasma as diagnostic tests for early diagnosis of ovarian and endometrial cancer. Preoperative plasma from 133 women with ovarian cancer (stages I-IV or borderline ovarian tumors) and 41 women with endometrial cancer (stages I-IV) was compared to 115 healthy controls with highly sensitive gas sensors. Data analyses were performed using feature extraction from 32 gas sensors per sample. 85 features were extracted from each signal (including statistical, time-domain, and frequency-domain features), and training and test datasets were formed. The features underwent an iterative redundancy removal process for stepwise optimization of models. Model robustness was assessed using a train/test split scheme with unique datasets, leading to a model optimized for diagnostic performance. By implementing sequential binary classification boosting-based models, it was possible to determine not only the presence or not of cancer, but also to distinguish between ovarian- and endometrial cancer, and the stage of the cancer. The VOC analysis, powered by a 5-fold cross-validated ensemble classifier, achieved exceptional diagnostic performance. It correctly identified all 133 patients with ovarian cancer and borderline ovarian tumors, all 41 cases of endometrial cancer, and all 115 healthy controls. For staging, the model accurately classified 172 out of 174 (98.9%) cancer cases as stage I vs. II-IV. On validation data, the classifier yielded an accuracy of 96.63% (95% CI: 96.56%-96.70%), sensitivity of 96.42% (95% CI: 96.29%-96.54%), and specificity of 96.88% (95% CI: 96.76%-97.01%). These metrics were robustly replicated on the independent test set, with an accuracy of 97.13% (95% CI: 96.80%-97.45%), sensitivity of 96.92% (95% CI: 96.49%-97.35%), and specificity of 97.37% (95% CI: 96.97%-97.77%). Complementing this, four additional classifiers (each with accuracy exceeding 90%) were developed and integrated into a cascaded algorithm to enable multi-class discrimination (ovarian cancer and endometrial cancer vs. healthy controls), cancer typing (ovarian vs. endometrial), and staging (stage I vs. later stages). The analysis of VOCs correctly identified 133 out of 133 patients with ovarian cancer and borderline ovarian tumour. All 41 cases of endometrial cancer were correctly identified, as were all the 115 healthy controls. In 172 out of 174 (98.9%) cancer cases the model correctly classified stage I vs. II-IV. VOC analysis emitted to gas-phase from plasma demonstrates high sensitivity and specificity for diagnosing ovarian cancer, including borderline ovarian tumors and endometrial cancers, compared to healthy controls. VOC analyses accurately differentiated between early and advanced stages of both cancer types. Future external validation needs to be performed. The Strategic Innovation Programs Swelife and MedTech4Health, a joint venture of Vinnova, Formas and the Energy Agency (grant No. 2022-03464 and grant No. 2023-03874) and within the Convergence Accelerator Program (Track L - Real-World Chemical Sensing Applications), funded by the Swedish Research Council, Vetenskapsrådet (grant No. 2023-07219), and Sweden's Innovation Agency, Vinnova (grant No. 2023-04186), in collaboration with the US National Science Foundation (NSF). The computations, data handling, and machine learning model training and testing were conducted in the MATLAB environment and enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS), partially funded by the Swedish Research Council through grant agreement no. 2022-06725. This work received funding from the European Union's Horizon Europe Research and Innovation Programme under Grant Agreement No 101214318 (DISARM). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Health and Digital Executive Agency (HaDEA). Neither the European Union nor HaDEA can be held responsible for them.

MELK promotes Endometrial carcinoma progression via activating mTOR signaling pathway

Endometrial carcinoma (EC) is one of the most common gynecological malignancies among women. Maternal embryonic leucine Zipper Kinase (MELK) is upregulated in a variety of human tumors, where it contributes to malignant phenotype and correlates with a poor prognosis. However, the biological function of MELK in EC progression remains largely unknown. We explored the MELK expression in EC using TCGA and GEO databases and verified it using clinical samples by IHC methods. CCK-8 assay, colony formation assay, cell cycle assay, wound healing assay and subcutaneous xenograft mouse model were generated to estimate the functions of MELK and its inhibitor OTSSP167. qRT-PCR, western blotting, co-immunoprecipitation, chromatin immunoprecipitation and luciferase reporter assay were performed to uncover the underlying mechanism concerning MELK during the progression of EC. MELK was significantly elevated in patients with EC, and high expression of MELK was associated with serous EC, high histological grade, advanced clinical stage and reduced overall survival and disease-free survival. MELK knockdown decreased the ability of cell proliferation and migration in vitro and subcutaneous tumorigenesis in vivo. In addition, high expression of MELK could be regulated by transcription factor E2F1. Moreover, we found that MELK had a direct interaction with MLST8 and then activated mTORC1 and mTORC2 signaling pathway for EC progression. Furthermore, OTSSP167, an effective inhibitor, could inhibit cell proliferation driven by MELK in vivo and vitro assays. We have explored the crucial role of the E2F1/MELK/mTORC1/2 axis in the progression of EC, which could be served as potential therapeutic targets for treatment of EC. This research was supported by National Natural Science Foundation of China (No:81672565), the Natural Science Foundation of Shanghai (Grant NO:17ZR1421400 to Dr. Zhihong Ai) and the fundamental research funds for central universities (No: 22120180595).

Impact of germline variants on breast and ovarian cancer risk in Japanese women: an original cohort study and meta-analysis

Pathogenic variants (PVs) of BRCA1 and BRCA2 predispose individuals to a higher risk of breast and ovarian cancer; however, the precise risks posed by other cancer susceptibility genes remain unclear, particularly in Asian populations. We executed a case-control study of 11 and 26 genes associated with breast and ovarian cancer susceptibility, respectively, in 7220 women with breast cancer, 2464 women with ovarian cancer, and 4032 controls from a multicentre, hospital-based registry in Japan. Furthermore, we conducted a meta-analysis of 23,193 patients with breast and/or ovarian cancer and 31,190 controls from six other hospital-based studies. Overall, 395 (5.5%) patients with breast cancer and 331 (13.4%) patients with ovarian cancer harboured PVs. Meta-analyses revealed that PVs of BRCA1, BRCA2, CHEK2, PALB2, and TP53 were associated significantly with breast cancer risk (P < 0.001), while PVs of ATM, BRCA1, BRCA2, MSH6, and RAD51D were associated significantly with ovarian cancer risk (P < 0.001). PVs in the BRCA1 DNA-binding domain were associated with a younger age at diagnosis after adjusting for cancer type and family history (β = -3.79, 95% CI = -7.16 to -0.41; P = 0.028). These results provide information about genes associated with breast and ovarian cancer risk in Asian women, as well as guidance for management of PV carriers. The study was funded by AMED (JP15ck010609, 19cm0106605h0003, 23ama221520h0001, and JP19kk0305010), by a Health Labour Sciences Research Grant (202108001B), by JSPS KAKENHI (JP18K16292, 20H03668, 23H02955, 17H06162, 20H03695, and 16H06277), and by a Grant-in-Aid for the Genome Research Project from Yamanashi Prefecture.

Tumour immune cell infiltration and survival after platinum-based chemotherapy in high-grade serous ovarian cancer subtypes: A gene expression-based computational study

Increasing evidence supports that the immune infiltration of tumours is associated with prognosis. Here, we sought to assess the relevance of the cellular composition of the immune infiltrate to survival after platinum-based chemotherapy amongst patients with high-grade serous ovarian cancer and evaluate these effects by molecular subtype. We searched publicly available databases and identified 13 studies with more than 2000 patients. We estimated the proportions of 22 immune cell subsets by using a computational approach (CIBERSORT). Then, we investigated the associations between each immune cell subset and progression-free survival (PFS) and overall survival (OS), with cellular proportions modelled as quartiles. A high fraction of M1 [hazard ratio (HR) = 0.92, 95% confidence interval (CI) = 0.86-0.99] and M0 (HR = 0.93, 95% CI = 0.87-0.99) macrophages emerged as the most closely associated with favourable OS. Neutrophils were associated with poor OS (HR = 1.06, 95% CI = 1.00-1.13) and PFS (HR = 1.10, 95% CI = 1.02-1.13). Amongst the immunoreactive tumours, the M0 macrophages and the CD8+ T cells were associated with improved OS, whereas the M2 macrophages conferred worse OS. Interestingly, PD-1 was associated with good OS (HR=0.89, 95% CI = 0.80-1.00) and PFS (HR=0.89, 95% CI = 0.79-1.01) in this subtype. Four subgroups of tumours with distinct survival patterns were identified using immune cell proportions with unsupervised clustering. Further investigations of the quantitative cellular immune infiltrations in tumours may contribute to therapeutic advances.

Self-supervised deep learning for highly efficient spatial immunophenotyping

Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently needed to reveal diverse cell distribution and spatial interactions in large-scale multiplex datasets. This study proposed Self-supervised Learning for Antigen Detection (SANDI) for accurate cell phenotyping while mitigating the annotation burden. The model first learns intrinsic pairwise similarities in unlabelled cell images, followed by a classification step to map learnt features to cell labels using a small set of annotated references. We acquired four multiplex immunohistochemistry datasets and one imaging mass cytometry dataset, comprising 2825 to 15,258 single-cell images to train and test the model. With 1% annotations (18-114 cells), SANDI achieved weighted F1-scores ranging from 0.82 to 0.98 across the five datasets, which was comparable to the fully supervised classifier trained on 1828-11,459 annotated cells (-0.002 to -0.053 of averaged weighted F1-score, Wilcoxon rank-sum test, P = 0.31). Leveraging the immune checkpoint markers stained in ovarian cancer slides, SANDI-based cell identification reveals spatial expulsion between PD1-expressing T helper cells and T regulatory cells, suggesting an interplay between PD1 expression and T regulatory cell-mediated immunosuppression. By striking a fine balance between minimal expert guidance and the power of deep learning to learn similarity within abundant data, SANDI presents new opportunities for efficient, large-scale learning for histology multiplex imaging data. This study was funded by the Royal Marsden/ICR National Institute of Health Research Biomedical Research Centre.

Enhanced immune checkpoint inhibitor therapy for advanced recurrent cervical cancer: the key to treatment efficacy and maintenance of quality of life

VIPAS39 confers ferroptosis resistance in epithelial ovarian cancer through exporting ACSL4

The high mortality rate associated with epithelial ovarian cancer (EOC) is primarily due to recurrence and chemoresistance, underscoring the urgent need for innovative therapeutic approaches that leverage newly identified vulnerabilities in cancer cells. While conventional chemotherapies induce apoptosis by targeting DNA or mitotic machinery, ferroptosis represents a new distinct form of programmed cell death characterised by the accumulation of lipid peroxides. The sensitivity of different EOC cell lines to ferroptosis inducers was evaluated using cell viability assays and lipid peroxidation measurements. Live-cell imaging with the pH-sensitive CD63-pHuji reporter was performed to track the extracellular export of acyl-CoA synthetase long-chain family member 4 (ACSL4) via exosomes. The upstream regulator of ACSL4 were identified through immunoprecipitation-mass spectrometry (IP-MS) and validated using protein binding assays. Finally, cell-derived xenograft (CDX) and patient-derived xenograft (PDX) models were utilised to evaluate the therapeutic potential overcoming ferroptosis resistance. In this study, we found that interferon (IFN)-γ combined with arachidonic acid (AA), which are endogenous ferroptosis inducers, could initiate ferroptosis in most EOC cells. However, some EOC cells displayed significant resistance. Contrary to the typical increase in ACSL4 protein observed in ferroptosis-sensitive cells, resistant EOC cells exhibited surprisingly low levels of this pro-ferroptotic lipid metabolic protein. Intriguingly, this reduction is attributed to the exosomal expulsion of ACSL4 protein, revealing a distinct cellular mechanism to evade ferroptosis. We further identified VIPAS39 as a pivotal regulator in sorting ACSL4 into late endosomes, thereby facilitating their subsequent release as exosomes. Notably, targeting VIPAS39 not only overcomes the resistance to ferroptotic cell death but also markedly suppresses tumour growth. Our findings uncover the crucial role of VIPAS39 in ferroptosis evasion by facilitating the exporting of ACSL4 protein via exosomes, highlighting VIPAS39 as a promising target for ferroptosis-based anti-cancer therapy. Funded by Beijing Municipal Natural Science Foundation (Key program Z220011), National Natural Science Foundation of China (NSFC) (T2225006, T2488301, 82272948), Peking University Medicine Youth Science and Technology Innovation 'Sail Plan' Project Type B Medical Interdisciplinary Seed Fund (71006Y3171), GuangDong Basic and Applied Basic Research Foundation (2021A1515110820), and the special fund of the National Clinical Key Speciality Construction Program, P. R. China (2023).

Plasma cfDNA methylation markers for the detection and prognosis of ovarian cancer

Plasma cell-free DNA (cfDNA) methylation has shown the potential in the detection and prognostic testing in multiple cancers. Herein, we thoroughly investigate the performance of cfDNA methylation in the detection and prognosis of ovarian cancer (OC). The OC-specific differentially methylated regions (DMRs) were identified by sequencing ovarian tissue samples from OC (n = 61), benign ovarian disease (BOD, n = 49) and healthy controls (HC, n = 37). Based on 1,272 DMRs, a cfDNA OC detection model (OC-D model) was trained and validated in plasma samples from patients of OC (n = 104), BOD (n = 56) and HC (n = 56) and a prognostic testing model (OC-P model) was developed in plasma samples in patients with high-grade serous OC (HG-SOC) in the training cohort and then tested the rationality of this model with International Cancer Genome Consortium (ICGC) tissue methylation data. Mechanisms were investigated in the TCGA-OC cohort. In the validation cohort, the cfDNA OC-D model consisting of 18 DMRs achieved a sensitivity of 94.7% (95% CI: 85.4%‒98.9%) at a specificity of 88.7% (95% CI: 78.7%‒94.9%), which outperformed CA 125 (AUC: 0.967 vs 0.905, P = 0.03). Then the cfDNA OC-P model consisting of 15 DMRs was constructed and associated with a better prognosis of HG-SOC in multivariable Cox regression analysis (HR: 0.29, 95% CI, 0.11‒0.78, P = 0.01) in the training cohort, which was also observed in the ICGC cohort using tissue methylation (HR: 0.56, 95% CI, 0.32‒0.98, P = 0.04). Investigation into mechanisms revealed that the low-risk group had higher homologous recombination deficiency and immune cell infiltration (P < 0.05). Our study demonstrated the potential utility of cfDNA methylation in the detection and prognostic testing in OC. Future studies with a larger population are warranted. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Development and preclinical evaluation of KDTV001, an adenovirus 5-vectored trivalent HPV therapeutic vaccine targeting HPV16/18/52

Persistent high-risk HPV infections (e.g., HPV16/18/52) are directly linked to cervical cancer development, thus necessitating the development of effective multi-target therapeutic vaccines. We developed KDTV001, a non-replicating adenovirus 5-vectored trivalent vaccine encoding engineered E6/E7 oncoproteins from HPV16/18/52. Its immunogenicity was evaluated in C57BL/6, CD1, HLA-transgenic mice, SD rats, and a human DC-T cell co-culture system. Assessments included IFN-γ ELISpot, flow cytometry, tumour challenge/rechallenge, single-cell RNA/TCR sequencing (scRNA/TCR-seq) of lymphocytes, and immune cell depletion. KDTV001 demonstrated robust preclinical efficacy across multiple models, eliciting potent immune and cross-reactive responses in immunocompetent and HLA-transgenic mice. scRNA/TCR-seq revealed KDTV001 remodelled the tumour microenvironment, increasing cytotoxic CD8 KDTV001, the adenovirus 5-vectored trivalent therapeutic vaccine targeting HPV16/18/52, demonstrates potent immunogenicity, significant antitumour efficacy, and long-term protective immunity across diverse preclinical models, paving the way for clinical translation in treating HPV-associated malignancies. This study was funded by the Noncommunicable Chronic Diseases-National Science and Technology Major Project of China (Nos.2025ZD0544101), the Hubei Provincial Science and Technology Major Project of China (Nos.2023BCA004), and the National Clinical Research Center for Gynaecological Diseases Special Fund of China (Nos.2025LCPT01).

10 Years of GWAS discovery in endometrial cancer: Aetiology, function and translation

Endometrial cancer is a common gynaecological cancer with increasing incidence and mortality. In the last decade, endometrial cancer genome-wide association studies (GWAS) have provided a resource to explore aetiology and for functional interpretation of heritable risk variation, informing endometrial cancer biology. Indeed, GWAS data have been used to assess relationships with other traits through correlation and Mendelian randomisation analyses, establishing genetic relationships and potential risk factors. Cross-trait GWAS analyses have increased statistical power and identified novel endometrial cancer risk variation related to other traits. Functional analysis of risk loci has helped prioritise candidate susceptibility genes, revealing molecular mechanisms and networks. Lastly, risk scores generated using endometrial cancer GWAS data may allow for clinical translation through identification of patients at high risk of disease. In the next decade, this knowledge base should enable substantial progress in our understanding of endometrial cancer and, potentially, new approaches for its screening and treatment.

Serum metabolic fingerprints encode functional biomarkers for ovarian cancer diagnosis: a large-scale cohort study

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).

Estimating the ovarian cancer CA-125 preclinical detectable phase, in-vivo tumour doubling time, and window for detection in early stage: an exploratory analysis of UKCTOCS

The ovarian cancer (OC) preclinical detectable phase (PCDP), defined as the interval during which cancer is detectable prior to clinical diagnosis, remains poorly characterised. We report exploratory analyses from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). In UKCTOCS between Apr-2001 and Sep-2005, 101,314 postmenopausal women were randomised to no screening (NS) and 50,625 to annual multimodal screening (MMS) (until Dec-2011) using serum CA-125 interpreted by the Risk of Ovarian Cancer Algorithm (ROCA). All provided a baseline blood sample. Women with invasive epithelial OC diagnosed between randomisation and trial censorship (Dec-2014) in the MMS and NS arms with two or more CA-125 measurements, including one within two years of diagnosis were included. OC-free women (2:1 to cases) from the MMS arm provided information on baseline CA-125 distribution. CA-125 measurements were obtained from MMS results, secondary analysis of baseline samples, and medical records. PCDP duration and in-vivo tumour doubling time were estimated using the change-point model underlying ROCA. Early-stage (Stage I and II) PCDP was estimated from a Bayesian model for the probability of early stage given a CA-125 measurement. Of 541 women (2371 CA-125 measurements) with high-grade serous cancer (HGSC), 93% (504/541) secreted CA-125 into the circulation. Median CA-125 PCDP duration for clinically-diagnosed HGSC was 15.2 (IQR 13.1-16.9, 95% IPR 9.6-21.8) months, of which 11.9 (IQR 10.5-13.1, 95% IPR 7.5-16.5) months was in early stage. The median HGSC in-vivo tumour doubling time for cancers secreting CA-125 was 2.9 (IQR 2.3-3.7, 95% IPR 1.5-7.6) months. We report a comprehensive characterisation of the OC CA-125 PCDP. The 12-month window for early-stage detection and short tumour doubling time of HGSC provide a benchmark for researchers evaluating novel screening approaches including need to reduce diagnostic workup interval. Equally the findings provide urgent impetus for clinicians to reduce intervals from presentation to treatment onset. NCI Early Detection Research Network, Concord (MA) Detect Ovarian Cancer Early Fund, MRC Clinical Trials Unit at UCL Core Funding.

Single-nucleus RNA sequencing reveals heterogenous microenvironments and specific drug response between cervical squamous cell carcinoma and adenocarcinoma

Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAde) are two major pathological types of cervical cancer (CC), but their high-resolution heterogeneity of tumor and immune microenvironment remains elusive. Here, we performed single-nucleus RNA sequencing (snRNA-seq) from five CSCC and three CAde samples, and systematically outlined their specific transcriptome atlas. We found CD8 Our study described the immune heterogeneity and specific cellular interactions between CSCC and CAde, which could provide insights for uncovering pathogenesis and designing personalized treatment. National Key R&D Program of China (2021YFC2701201), National Natural Science Foundation of China (82072895, 82141106, 82103134, 81903114).

Identification of cervical cancer stem cells using single-cell transcriptomes of normal cervix, cervical premalignant lesions, and cervical cancer

Cervical cancer is the fourth leading cause of mortality among gynecological malignancies. However, the identification of cervical cancer stem cells remains unclear. We performed single-cell mRNA sequencing on ∼122,400 cells from 20 cervical biopsies, including 5 healthy controls, 4 high-grade intraepithelial neoplasias, 5 microinvasive carcinomas of the cervix, and 6 invasive cervical squamous carcinomas. Bioinformatic results were validated by multiplex immunohistochemistry (mIHC) in cervical cancer tissue microarrays (TMA) (n = 85). We identified cervical cancer stem cells and highlighted the functional changes in cervical stem cells during malignant transformation. The original non-malignant stem cell properties (characterized by high proliferation) gradually diminished, whereas the tumor stem cell properties (characterized by epithelial-mesenchymal transformation and invasion) were enhanced. The mIHC results of our TMA cohort confirmed the existence of stem-like cells and indicated that cluster correlated with neoplastic recurrence. Subsequently, we investigated malignant and immune cell heterogeneity in the cervical multicellular ecosystem across different disease stages. We observed global upregulation of interferon responses in the cervical microenvironment during lesion progression. Our results provide more insights into cervical premalignant and malignant lesion microenvironments. This research was supported by the Guangdong Provincial Natural Science Foundation of China (2023A1515010382), Grant 2021YFC2700603 from the National Key Research & Development Program of China and the Hubei Provincial Natural Science Foundation of China (2022CFB174 and 2022CFB893).

ADNP (Activity Dependent Neuroprotector Homeobox): A novel oncogene driving poor prognosis in high-grade serous carcinoma

Endometrial cancer: improving management among increasing incidence rates

DNA methylation mediates the immunosuppressive tumour microenvironment in metastatic endometrial clear cell carcinoma

Endometrial clear cell carcinoma (ECCC) is a rare and highly aggressive histological subtype of endometrial cancer with marked metastatic potential. The molecular characteristics and underlying mechanisms governing its metastatic behaviour remain poorly understood. This study aimed to delineate molecular distinctions between metastatic (Pm) and non-metastatic (Pn) primary ECCC tumours, elucidate DNA methylation-mediated regulatory mechanisms driving metastasis, and identify potential epigenetic biomarkers and therapeutic targets. This multicentre study involved 51 individuals diagnosed with ECCC, leading to the establishment of two independent cohorts: a sequencing cohort (n = 35) for integrated whole-genome methylation and transcriptomic analysis, and a tissue microarray (TMA) cohort (n = 16) to validate key findings. Tumours exhibiting metastasis were found to possess a profoundly immunosuppressive tumour microenvironment (TME), evidenced by reduced density of tumour-infiltrating lymphocytes (TILs), especially within subsets of anti-tumour immune cells. Further analysis highlighted differential hypermethylation events in Pm tumours that acted as crucial epigenetic switches regulating immune responses. Specifically, methylation at ETS1-binding sites influenced ETS1 regulon activity, thus broadly regulating immune response processes. Epigenetic silencing of key genes in the T cell receptor (TCR) signalling pathway, such as LCK, CD3E, and ZAP70, impaired T cell activation and inhibited the activity of interacting immune pathways. Additionally, we developed a Lasso-derived metastatic risk score model, incorporating TME features (TIL density) and epigenetic predictors (LCK methylation), which demonstrated strong predictive performance (area under the curve [AUC] = 0.859). This study illuminated the "epigenetic-immune axis" as a central regulatory mechanism driving ECCC metastasis. DNA methylation systematically silenced immune response genes by targeting ETS1-binding sites and TCR signalling components, thus reconstructing the immunosuppressive TME to facilitate metastasis. The development of the metastatic risk score model and identification of LCK as a potential therapeutic target provide valuable strategies for precision treatment decisions and advancing targeted epigenetic-immune therapies in ECCC. This work was supported by the National Natural Science Foundation of China, Joint Foundation Programme, Qingdao Municipal Science and Technology Bureau Municipal Science, Shenzhen Science and Technology Programme, and the Affiliated Hospital of Qingdao University Young Investigator Fund.

Overcoming resistance to PARP inhibitor in epithelial ovarian cancer, are we ready?

GWAS meta-analysis identifies five susceptibility loci for endometrial cancer

Endometrial cancer is the most common gynaecological cancer in high-income countries. In addition to environmental risk factors, genetic predisposition contributes towards endometrial cancer development but is still incompletely defined. Building on genome-wide association studies (GWASs) by the Endometrial Cancer Association Consortium, we conducted a GWAS meta-analysis of 17,278 endometrial cancer cases and 289,180 controls, incorporating biobank samples from the UK, Finland, Estonia and Japan. GWAS analysis identified five additional risk loci (3p25.2, 3q25.2, 6q22.31, 12q21.2, and 17q24.2). Corresponding gene-based analyses supported findings for three of the five loci, at NAV3 (12q21.2), PPARG (3p25.2), and BPTF (17q24.2), as well as two additional candidate risk regions at ATF7IP2 (16p13.2-p13.13) and RPP21 (6p22.1). Validation genotyping in further independent case-control series replicated the most significant locus at 12q21.2 and corroborated risk variants located intronic to NAV3, the gene for Neuron Navigator 3. Downregulation of NAV3 in endometrial cell lines accelerated cell division and wound healing capacity whereas NAV3 overexpression reduced cell survival and increased cell death, indicating that NAV3 acts as a tumour suppressor in endometrial cells. Our large study extends the number of genome-wide significant risk loci identified for endometrial carcinoma by about one-third and proposes a role of NAV3 as a tumour suppressor in this common cancer. This study was mainly supported by funding from the Wilhelm Sander Foundation, Germany, and the National Health and Medical Research Council (NHMRC) of Australia. A complete list of funding organisations is provided in the acknowledgements.

Circadian rhythm disruption by PARP inhibitors correlates with treatment toxicity in patients with ovarian cancer and is a predictor of side effects

Ovarian cancer is among the most lethal malignancies in women. The advent of PARP inhibitors (PARPi) has improved outcomes. However, treatment-related toxicity remains a critical challenge, impacting patient quality of life and treatment adherence. In a circadian sub-study of the MAMOC trial-a double-blind, phase III study-42 patients (FIGO stage IIIA-IV) were randomised in a 2:1 ratio to receive rucaparib or placebo. In a subset of these patients, we performed differential gene expression and rhythmicity analysis on up to 800 genes, including clock and clock-controlled genes. Machine learning algorithms and mathematical modelling were employed to simulate patient-specific toxicity profiles and to explore correlations between gene expression patterns and treatment-related side effects. Our analysis revealed significant disruptions in circadian rhythms, specifically in the expression of the core clock genes BMAL1 and PER2, following treatment. These disruptions strongly correlated with the severity and frequency of side effects, including nausea and fatigue, displaying opposite trends between the placebo and rucaparib-treated groups. K-means clustering successfully distinguished rucaparib-treated patients from those receiving placebo based on BMAL1 phase and gene expression profiles. In addition, rucaparib therapy also altered the expression of several clock-controlled genes, including SIRT1, BRCA1, BRCA2, and TP53. Notably, our data suggest that individual differences in circadian rhythms may lead to distinct 24-h toxicity profiles among patients. These findings suggest that circadian rhythm dysregulation may contribute to the toxicity of PARPi therapy. Aligning treatment timing with circadian rhythms could mitigate these adverse effects, and improve patient outcomes. This study was funded by the Dr. Rolf Schwiete Stiftung and the MSH Medical School Hamburg, Germany. The MAMOC trial (ClinicalTrials.gov: NCT04227522) was funded by Clovis Oncology, United States.

Phase 2 study of the antitumour activity and safety of simlukafusp alfa (FAP-IL2v) combined with atezolizumab in patients with recurrent and/or metastatic cervical squamous cell carcinoma

Simlukafusp alfa (FAP-IL2v) is an immune cytokine engineered to selectively promote immune responses in the tumour microenvironment. We evaluated the antitumour activity and safety of FAP-IL2v plus atezolizumab in recurrent and/or metastatic cervical squamous cell carcinoma (SCC) in a phase 2 basket study (NCT03386721). Patients with confirmed metastatic, persistent or recurrent cervical SCC who had progressed on ≥1 anti-cancer therapy and had measurable disease were enrolled. FAP-IL2v 10 mg was administered once every 3 weeks (Q3W) or once weekly (QW) for 4 weeks then once every 2 weeks (Q2W) with the corresponding Q3W or Q2W atezolizumab regimens. The primary endpoint was objective response rate by investigator assessment. Forty-eight patients were enrolled (Q3W: n = 47; QW/Q2W: n = 1). Among 45 response evaluable patients, objective responses occurred in 12 patients (27%; CI 16.0-41.0), including 3 complete and 9 partial responses. Responses occurred in 6/19 PD-L1 positive patients (32%; 95% CI 15.4-54.0) and 5/24 PD-L1 negative patients (21%; 95% CI 9.2-35.6). Median duration of response was 13.3 months (95% CI 7.6-NE). Median progression-free survival was 3.7 months (95% CI 3.3-9.0). Adverse events (AEs) were consistent with the known safety profile of each drug. AEs leading to withdrawal of either agent occurred in 6 patients (13%). Pronounced expansion and activation of natural killer and CD8 T cells in peripheral blood and increased tumour infiltration and inflammation were observed. FAP-IL2v plus atezolizumab is clinically active and has manageable safety in patients with recurrent and/or metastatic cervical SCC. F. Hoffmann-La Roche Ltd.

Impact of insomnia on ovarian cancer risk and survival: a Mendelian randomization study

Insomnia is the most common sleep disorder in patients with epithelial ovarian cancer (EOC). We investigated the causal association between genetically predicted insomnia and EOC risk and survival through a two-sample Mendelian randomization (MR) study. Insomnia was proxied using genetic variants identified in a genome-wide association study (GWAS) meta-analysis of UK Biobank and 23andMe. Using genetic associations with EOC risk and overall survival from the Ovarian Cancer Association Consortium (OCAC) GWAS in 66,450 women (over 11,000 cases with clinical follow-up), we performed Iterative Mendelian Randomization and Pleiotropy (IMRP) analysis followed by a set of sensitivity analyses. Genetic associations with survival and response to treatment in ovarian cancer study of The Cancer Genome Atlas (TCGA) were estimated controlling for chemotherapy and clinical factors. Insomnia was associated with higher risk of endometrioid EOC (OR = 1.60, 95% CI 1.05-2.45) and lower risk of high-grade serous EOC (HGSOC) and clear cell EOC (OR = 0.79 and 0.48, 95% CI 0.63-1.00 and 0.27-0.86, respectively). In survival analysis, insomnia was associated with shorter survival of invasive EOC (OR = 1.45, 95% CI 1.13-1.87) and HGSOC (OR = 1.4, 95% CI 1.04-1.89), which was attenuated after adjustment for body mass index and reproductive age. Insomnia was associated with reduced survival in TCGA HGSOC cases who received standard chemotherapy (OR = 2.48, 95% CI 1.13-5.42), but was attenuated after adjustment for clinical factors. This study supports the impact of insomnia on EOC risk and survival, suggesting treatments targeting insomnia could be pivotal for prevention and improving patient survival. National Institutes of Health, National Cancer Institute. Full funding details are provided in acknowledgments.

Mathematical modeling of the early modeled CA-125 longitudinal kinetics (KELIM-PARP) as a pragmatic indicator of rucaparib efficacy in patients with recurrent ovarian carcinoma in ARIEL2 &amp; STUDY 10

PARP inhibitors (PARPi) have revolutionized the management of advanced ovarian carcinoma, and were investigated as forefront treatment in recurrent disease. The objective was to explore if mathematical modeling of the early longitudinal CA-125 kinetics could be used as a pragmatic indicator of the subsequent rucaparib efficacy, like it is for platinum-based chemotherapy. The datasets of ARIEL2 and Study 10 involving recurrent HGOC patients treated with rucaparib were retrospectively investigated. The same strategy as those successfully developed for platinum chemotherapy, based on CA-125 ELIMination rate constant K (KELIM™), was implemented. Individual values of rucaparib-adjusted KELIM (KELIM-PARP) were estimated based on the longitudinal CA-125 kinetics during the first 100 treatment days, and then scored as favorable (KELIM-PARP ≥1.0) or unfavorable (KELIM-PARP <1.0). The prognostic value of KELIM-PARP regarding treatment efficacy (radiological response, and progression-free survival (PFS)) was assessed using univariable/multivariable analyses, with respect to platinum-sensitivity and homologous recombination deficiency (HRD) status. The data from 476 patients were assessed. The CA-125 longitudinal kinetics during the first 100-treatment days could be accurately assessed using the KELIM-PARP model. In patients with platinum-sensitive diseases, BRCA mutational status KELIM-PARP score and were associated with subsequent complete/partial radiological responses (KELIM-PARP: odds-ratio = 2.81, 95% CI 1.86-4.52), and PFS (KELIM-PARP: hazard-ratio = 0.67, 95% CI 0.50-0.91). The patients with BRCA-wild type cancer and favorable KELIM-PARP experienced long PFS with rucaparib regardless of HRD. In platinum-resistant disease patients, KELIM-PARP was associated with subsequent radiological response (odds-ratio = 2.80, 95% CI 1.82-4.72). This proof-of-concept study confirms the early CA-125 longitudinal kinetics during rucaparib in recurrent HGOC patients are assessable by mathematical modeling, to generate individual a KELIM-PARP score associated with the subsequent efficacy. This pragmatic strategy might be useful for selecting the patients for PARPi-based combination regimens, when identifying efficacy biomarker is challenging. Further assessment of this hypothesis is warranted. The present study was supported by Clovis Oncology with a grant to academic research association.

Comparison of HPV-positive triage strategies combining extended genotyping with cytology or p16/ki67 dual staining in the Italian NTCC2 study

Each high-risk HPV genotype has different oncogenic potential, and the risk of CIN3+ varies according to genotype. We evaluated the performance of different strategies of HPV-positivity triage combining cytology, p16/ki67 dual staining (DS), and extended genotyping. Samples from 3180 consecutive women from the NTCC2 study (NCT01837693) positive for HPV DNA at primary screening, were retrospectively analyzed by the BD Onclarity HPV Assay, which allows extended genotyping. Genotypes were divided into three groups based on the risk of CIN3+. HPV DNA-positive women were followed up for 24 months or to clearance. Combining the three groups of genotypes with cytology or DS results we identify a group of women who need immediate colposcopy (PPV for CIN3+ from 7.8 to 20.1%), a group that can be referred to 1-year HPV retesting (PPV in those HPV-positive at retesting from 2.2 to 3.8), and a group with a very low 24-month CIN3+ risk, i.e. 0.4%, composed by women cytology or DS negative and positive for HPV 56/59/66 or 35/39/68 or negative with the Onclarity test, who can be referred to 3-year retesting. Among the baseline HPV DNA positive/cytology or DS negative women, the extended genotyping allows to stratify for risk of CIN3+, and to identify a group of women with a risk of CIN3+ so low in the next 24 months that they could be referred to a new screening round after 3 years. Italian Ministry of Health (grant number RF-2009-1536040). Hologic-Genprobe, Roche Diagnostics, and Becton & Dickinson provided financial and non-financial support.

Genome-wide association study identifies genetic regulation of oestrone concentrations and association with endometrial cancer risk in postmenopausal women

Oestrone, predominantly made in fat, is the main circulating oestrogen and important for target tissue oestradiol production in women after menopause. The present study was undertaken to determine the genetic regulation of blood oestrone, measured with precision, in postmenopausal women and to explore associations between the identified genetic loci and endometrial cancer in a large, independent cohort. A genome-wide association study (GWAS) was undertaken in women aged at least 70 years to identify genetic associations with blood oestrone concentrations measured by liquid chromatography and tandem mass spectrometry. The GWAS included participants from the Sex Hormones in Older Women (SHOW) study, a sub-study of the longitudinal ASPREE (ASPirin in Reducing Events in the Elderly) randomised trial. Of the 6358 women providing a biobank sample at enrolment, 4951 unrelated women of European ancestry, not taking sex hormones, anti-oestrogens, anti-androgens or systemic glucocorticoids were included in the GWAS. Single nucleotide polymorphisms (SNPs) from loci identified below the genome-wide significance threshold were then tested in an independent cohort (the UK Biobank) for association with endometrial cancer risk, using logistic regression and adjusting for age, body mass index (BMI) and the top 10 genetic principal components. The median age of the 4951 women included in the GWAS was 75.9 years (range 70-94.8 years). The GWAS identified four independent SNPs associated with oestrone concentrations (p < 5 × 10 We have shown genetic regulation of oestrone concentrations in postmenopausal women, and that SNPs associated with oestrone were also associated with endometrial cancer risk, independent of BMI, parity and diabetes mellitus. Although the apparent contribution was modest, the biological influence of oestrone concentrations may be greater through conversion to oestradiol in endometrial tissue. The ASPREE trial was supported by the National Institute on Aging and the National Cancer Institute at the National Institutes of Health (Grant U01AG029824); the National Health and Medical Research Council (NHMRC) of Australia (Grant 34047, 1127060); Monash University (Australia); and the Victorian Cancer Agency (Australia). The ASPREE Healthy Ageing Biobank was funded by the CSIRO (Flagship Grant), the National Cancer Institute (Grant U01 AG029824) and Monash University. This analysis of sex hormones was funded by an NHMRC of Australia Project Grant (No. 1105305). SRD holds an NHMRC Investigator Grant (2016627). PL is supported by a National Heart Foundation Future Leader Fellowship (102604).

Genetic markers and phosphoprotein forms of beta-catenin pβ-Cat552 and pβ-Cat675 are prognostic biomarkers of cervical cancer

Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality world wide and constitutes the third most common malignancy in women. The RAIDs consortium (http://www.raids-fp7.eu/) conducted a prospective European study [BioRAIDs (NCT02428842)] with the objective to stratify CC patients for innovative treatments. A "metagene" of genomic markers in the PI3K pathway and epigenetic regulators had been previously associated with poor outcome [2]. To detect new, more specific, targets for treatment of patients who resist standard chemo-radiation, a high-dimensional Cox model was applied to define dominant molecular variants, copy number variations, and reverse phase protein arrays (RPPA). Survival analysis on 89 patients with all omics data available, suggested loss-of-function (LOF) or activating molecular alterations in nine genes to be candidate biomarkers for worse prognosis in patients treated by chemo-radiation while LOF of ATRX, MED13 as well as CASP8 were associated with better prognosis. When protein expression data by RPPA were factored in, the supposedly low molecular weight and nuclear form, of beta-catenin, phosphorylated in Ser552 (pβ-Cat552), ranked highest for good prognosis, while pβ-Cat675 was associated with worse prognosis. These findings call for molecularly targeted treatments involving p53, Wnt pathway, PI3K pathway, and epigenetic regulator genes. Pβ-Cat552 and pβ-Cat675 may be useful biomarkers to predict outcome to chemo-radiation, which targets the DNA repair axis. European Union's Seventh Program for research, technological development and demonstration (agreement N°304,810), the Fondation ARC pour la recherche contre le cancer.

CD24-targeted intraoperative fluorescence image-guided surgery leads to improved cytoreduction of ovarian cancer in a preclinical orthotopic surgical model

The completeness of resection is a key prognostic indicator in patients with ovarian cancer, and the application of tumour-targeted fluorescence image-guided surgery (FIGS) has led to improved detection of peritoneal metastases during cytoreductive surgery. CD24 is highly expressed in ovarian cancer and has been shown to be a suitable biomarker for tumour-targeted imaging. CD24 expression was investigated in cell lines and heterogenous patient-derived xenograft (PDX) tumour samples of high-grade serous ovarian carcinoma (HGSOC). After conjugation of the monoclonal antibody CD24 to the NIR dye Alexa Fluor 750 and the evaluation of the optimal pharmacological parameters (OV-90, n = 21), orthotopic HGSOC metastatic xenografts (OV-90, n = 16) underwent cytoreductive surgery with real-time feedback. The impact of intraoperative CD24-targeted fluorescence guidance was compared to white light and palpation alone, and the recurrence of disease was monitored post-operatively (OV-90, n = 12). CD24-AF750 was further evaluated in four clinically annotated orthotopic PDX models of metastatic HGSOC, to validate the translational potential for intraoperative guidance. CD24-targeted intraoperative NIR FIGS significantly (47•3%) improved tumour detection and resection, and reduced the post-operative tumour burden compared to standard white-light surgery in orthotopic HGSOC xenografts. CD24-AF750 allowed identification of minuscule tumour lesions which were undetectable with the naked eye in four HGSOC PDX. CD24-targeted FIGS has translational potential as an aid to improve debulking surgery of ovarian cancer. This study was supported by the H2020 program MSCA-ITN [675743], Helse Vest RHF, and Helse Bergen HF [911809, 911852, 912171, 240222, 911974, HV1269], as well as by The Norwegian Cancer Society [182735], and The Research Council of Norway through its Centres of excellence funding scheme [223250, 262652].

CD24-targeted fluorescence imaging in patient-derived xenograft models of high-grade serous ovarian carcinoma

The survival rate of patients with advanced high-grade serous ovarian carcinoma (HGSOC) remains disappointing. Clinically translatable orthotopic cell line xenograft models and patient-derived xenografts (PDXs) may aid the implementation of more personalised treatment approaches. Although orthotopic PDX reflecting heterogeneous molecular subtypes are considered the most relevant preclinical models, their use in therapeutic development is limited by lack of appropriate imaging modalities. We developed novel orthotopic xenograft and PDX models for HGSOC, and applied a near-infrared fluorescently labelled monoclonal antibody targeting the cell surface antigen CD24 for non-invasive molecular imaging of epithelial ovarian cancer. CD24-Alexa Fluor 680 fluorescence imaging was compared to bioluminescence imaging in three orthotopic cell line xenograft models of ovarian cancer (OV-90 Application of the near-infrared probe, CD24-AF680, enabled both spatio-temporal visualisation of tumour development, and longitudinal therapy monitoring of orthotopic xenografts. Notably, CD24-AF680 facilitated imaging of multiple PDX models representing different histological subtypes of the disease. The combined implementation of CD24-AF680 and orthotopic PDX models creates a state-of-the-art preclinical platform which will impact the identification and validation of new targeted therapies, fluorescence image-guided surgery, and ultimately the outcome for HGSOC patients. This study was supported by the H2020 program MSCA-ITN [675743], Helse Vest RHF, and Helse Bergen HF [911809, 911852, 912171, 240222, HV1269], as well as by The Norwegian Cancer Society [182735], and The Research Council of Norway through its Centers of excellence funding scheme [223250, 262652].

ZNF711 down-regulation promotes CISPLATIN resistance in epithelial ovarian cancer via interacting with JHDM2A and suppressing SLC31A1 expression

Resistance to platinum-based chemotherapy is a major cause of therapeutic failure during the treatment of epithelial ovarian cancer (EOC) patients. Our study aims to elucidate the molecular mechanisms by which ZNF711 down regulation promotes CISPLATIN resistance in EOC. ZNF711 expression in 150 EOC specimens was examined using immunohistochemistry. ZNF711 expression and the survival of EOC patients were assessed with a Kaplan-Meier analysis. The effects of ZNF711 expression on CDDP resistance were studied by IC50, Annexin V, and colony formation in vitro, and in an in vivo intra-peritoneal tumor model. The molecular mechanism was determined using a luciferase reporter assay, ChIP assay, CAPTURE approach, and co-IP assay. ZNF711 down-regulation exerts a great impact on CDDP resistance for EOC patients by suppressing SLC31A1 and inhibiting CDDP influx. ZNF711 down-regulation promoted, while ZNF711 overexpression drastically inhibited CDDP resistance, both in vivo and in vitro. Mechanistically, the histone demethylase JHDM2A was recruited to the SLC31A1 promoter by ZNF711 and decreased the H3K9me2 level, resulting in the activation of SLC31A1 transcription and enhancement of CDDP uptake. Importantly, co-treatment with the histone methylation inhibitor, BIX-01294, increased the therapeutic efficacy of CDDP treatment in ZNF711-suppressed EOC cells. These findings both verified the clinical importance of ZNF711 in CDDP resistance and provide novel therapeutic regimens for EOC treatment. This work was supported by the Natural Science Foundation of China; Guangzhou Science and Technology Plan Projects; Natural Science Foundation of Guangdong Province; The Fundamental Research Funds for the Central Universities; and China Postdoctoral Science Foundation.

Laser-assisted rapid evaporative ionisation mass spectrometry (LA-REIMS) as a metabolomics platform in cervical cancer screening

The introduction of high-risk human papillomavirus (hrHPV) testing as part of primary cervical screening is anticipated to improve sensitivity, but also the number of women who will screen positive. Reflex cytology is the preferred triage test in most settings but has limitations including moderate diagnostic accuracy, lack of automation, inter-observer variability and the need for clinician-collected sample. Novel, objective and cost-effective approaches are needed. In this study, we assessed the potential use of an automated metabolomic robotic platform, employing the principle of laser-assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) in cervical cancer screening. In a population of 130 women, LA-REIMS achieved 94% sensitivity and 83% specificity (AUC: 91.6%) in distinguishing women testing positive (n = 65) or negative (n = 65) for hrHPV. We performed further analysis according to disease severity with LA-REIMS achieving sensitivity and specificity of 91% and 73% respectively (AUC: 86.7%) in discriminating normal from high-grade pre-invasive disease. This automated high-throughput technology holds promise as a low-cost and rapid test for cervical cancer screening and triage. The use of platforms like LA-REIMS has the potential to further improve the accuracy and efficiency of the current national screening programme. Work was funded by the MRC Imperial Confidence in Concept Scheme, Imperial College Healthcare Charity, British Society for Colposcopy and Cervical Pathology, National Research Development and Innovation Office of Hungary, Waters corporation and NIHR BRC.

Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumour heterogeneity

Emerging biomarkers from medical imaging or molecular characterization of tumour biopsies open up for combining the two and exploiting their synergy in treatment planning of cancer patients. We generated a paired data set of imaging- and gene-based hypoxia biomarkers in cervical cancer, appraised the influence of intratumour heterogeneity in patient classification, and investigated the benefit of combining the methodologies in prediction of chemoradiotherapy failure. Hypoxic fraction from dynamic contrast enhanced (DCE)-MR images and an expression signature of six hypoxia-responsive genes were assessed as imaging- and gene-based biomarker, respectively in 118 patients. Dichotomous biomarker cutoff to yield similar hypoxia status by imaging and genes was defined in 41 patients, and the association was validated in the remaining 77 patients. The two biomarkers classified 75% of 118 patients with the same hypoxia status, and inconsistent classification was not related to imaging-defined intratumour heterogeneity in hypoxia. Gene-based hypoxia was independent on tumour cell fraction in the biopsies and showed minor heterogeneity across multiple samples in 9 tumours. Combining imaging- and gene-based classification gave a significantly better prediction of PFS than one biomarker alone. A combined dichotomous biomarker optimized in 77 patients showed a large separation in PFS between more and less hypoxic tumours, and separated the remaining 41 patients with different PFS. The combined biomarker showed prognostic value together with tumour stage in multivariate analysis. Combining imaging- and gene-based biomarkers may enable more precise and informative assessment of hypoxia-related chemoradiotherapy resistance in cervical cancer. Norwegian Cancer Society, South-Eastern Norway Regional Health Authority, and Norwegian Research Council.

Exendin-4 — A potential therapeutic for type 2 diabetes-linked cervical cancer?

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery

The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. Cancer Research UK, Blood Cancer UK, National Institute for Health Research.