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Ovarian cancer comprises a broad range of histologically and genetically different tumours. In this Opinion article, Karnezis et al . explore the different origins of ovarian cancers and how these contribute to our understanding of genetic and environmental risk to better prevent and treat these tumours. Ovarian cancer is the fifth cause of cancer-related death in women and comprises a histologically and genetically broad range of tumours, including those of epithelial, sex cord-stromal and germ cell origin. Recent evidence indicates that high-grade serous ovarian carcinoma, clear cell carcinoma and endometrioid carcinoma primarily arise from tissues that are not normally present in the ovary. These histogenetic pathways are informing risk-reduction strategies for the prevention of ovarian and ovary-associated cancers and have highlighted the importance of the seemingly unique ovarian microenvironment.

Endometrioid ovarian carcinoma (EnOC) demonstrates substantial clinical and molecular heterogeneity. Here, we report whole exome sequencing of 112 EnOC cases following rigorous pathological assessment. We detect a high frequency of mutation in CTNNB1 (43%), PIK3CA (43%), ARID1A (36%), PTEN (29%),  KRAS  (26%), TP53 (26%) and SOX8 (19%), a recurrently-mutated gene previously unreported in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy is constructed, identifying clinically distinct EnOC subtypes: cases with TP53 mutation demonstrate greater genomic complexity, are commonly FIGO stage III/IV at diagnosis (48%), are frequently incompletely debulked (44%) and demonstrate inferior survival; conversely, cases with CTNNB1 mutation, which is mutually exclusive with TP53 mutation, demonstrate low genomic complexity and excellent clinical outcome, and are predominantly stage I/II at diagnosis (89%) and completely resected (87%). Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC. The molecular classification of endometroid ovarian carcinomas (EnOC) has not been established, preventing the development of stratified therapeutic approaches. Here the authors characterise the molecular landscape of EnOC by whole exome sequencing, identifying clinically distinct disease subtypes.

The use of primary patient-derived organoids for drug sensitivity and resistance testing could play an important role in precision cancer medicine. We developed expandable ovarian cancer organoids in < 3 weeks; these organoids captured the characteristics of histological cancer subtypes and replicated the mutational landscape of the primary tumours. Seven pairs of organoids (3 high-grade serous, 1 clear cell, 3 endometrioid) and original tumours shared 59.5% (36.1–73.1%) of the variants identified. Copy number variations were also similar among organoids and primary tumours. The organoid that harboured the BRCA1 pathogenic variant (p.L63*) showed a higher sensitivity to PARP inhibitor, olaparib, as well as to platinum drugs compared to the other organoids, whereas an organoid derived from clear cell ovarian cancer was resistant to conventional drugs for ovarian cancer, namely platinum drugs, paclitaxel, and olaparib. The overall success rate of primary organoid culture, including those of various histological subtypes, was 80% (28/35). Our data show that patient-derived organoids are suitable physiological ex vivo cancer models that can be used to screen effective personalised ovarian cancer drugs.

Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for an accurate diagnosis are lacking in developing countries. Artificial intelligence (AI) has been recently used in computer-aided diagnosis showing remarkable promise. In this study, we developed and validated deep learning models to automatically classify cervical neoplasms on colposcopic photographs. Pre-trained convolutional neural networks were fine-tuned for two grading systems: the cervical intraepithelial neoplasia (CIN) system and the lower anogenital squamous terminology (LAST) system. The multi-class classification accuracies of the networks for the CIN system in the test dataset were 48.6 ± 1.3% by Inception-Resnet-v2 and 51.7 ± 5.2% by Resnet-152. The accuracies for the LAST system were 71.8 ± 1.8% and 74.7 ± 1.8%, respectively. The area under the curve (AUC) for discriminating high-risk lesions from low-risk lesions by Resnet-152 was 0.781 ± 0.020 for the CIN system and 0.708 ± 0.024 for the LAST system. The lesions requiring biopsy were also detected efficiently (AUC, 0.947 ± 0.030 by Resnet-152), and presented meaningfully on attention maps. These results may indicate the potential of the application of AI for automated reading of colposcopic photographs.

The goal of this work was to investigate the tumor mutational burden (TMB) in Chinese patients with gynecologic cancer. In total, 117 patients with gynecologic cancers were included in this study. Both tumor DNA and paired blood cell genomic DNA were isolated from formalin-fixed paraffin-embedded (FFPE) specimens and blood samples, and next-generation sequencing was performed to identify somatic mutations. TP53 , PTEN , ARID1A , and PIK3CA alterations were significantly different in various types of gynecologic cancers (p = 0.001, 1.15E-07, 0.004, and 0.009, respectively). The median TMB of all 117 gynecologic tumor specimens was 0.37 mutations/Mb, with a range of 0–41.45 mutations/Mb. Despite the lack of significant difference, endometrial cancer cases had a higher median TMB than cervical and ovarian cancer cases. Younger gynecologic cancer patients (age <40 years) had a significantly lower TMB than older patients (age ≥40 years) (p = 0.04). In addition, TMB was significantly increased with increasing clinical stage of disease (p = 0.001). PTEN alterations were commonly observed in patients with a moderate to high TMB (n = 8, 38.10%, p = 9.95E-04). Although limited by sample size, all of the patients with TSC2 (n = 3, p = 3.83E-11) or POLE (n = 2, p = 0.005) mutations had a moderate to high TMB. Further large-scale, prospective studies are needed to validate our findings.

The aim of this study was to validate the performance of the Ovarian-Adnexal Reporting and Data Systems (O-RADS) series models proposed by the American College of Radiology (ACR) in the preoperative diagnosis of adnexal masses (AMs). Two experienced sonologists examined 218 patients with AMs and gave the assessment results after the examination. Pathological findings were used as a reference standard. Of the 218 lesions, 166 were benign and 52 were malignant. Based on the receiver operating characteristic (ROC) curve, we defined a malignant lesion as O-RADS > 3 (i.e., lesions in O-RADS categories 4 and 5 were malignant). The area under the curve (AUC) of O-RADS (v2022) was 0.970 (95% CI 0.938–0.988), which wasn’t statistically significantly different from the O-RADS (v1) combined Simple Rules Risk (SRR) assessment model with the largest AUC of 0.976 (95% CI 0.946–0.992) ( p  = 0.1534), but was significantly higher than the O-RADS (v1) (AUC = 0.959, p  = 0.0133) and subjective assessment (AUC = 0.918, p  = 0.0255). The O-RADS series models have good diagnostic performance for AMs. Where, O-RADS (v2022) has higher accuracy and specificity than O-RADS (v1). The accuracy and specificity of O-RADS (v1), however, can be further improved when combined with SRR assessment.

Liquid biopsies of circulating tumor DNA (ctDNA) have recently been used as a non-invasive diagnostic tool for detecting tumor-specific mutations. We present a study of ctDNA liquid biopsies in gynecological cancer using an ultrasensitive next-generation sequencing-based method for ctDNA detection named CAncer Personalized Profiling by deep Sequencing (CAPP-Seq). We performed CAPP-Seq with plasma-ctDNA obtained from 16 patients with gynecological cancer. In all cases, at least one non-synonymous somatic mutation was detected in the ctDNA. In the pre-treatment ctDNA, 4 of 16, 4/16, 5/16, 2/16, 2/16, and 2/16 patients had TP53 , KRAS , APC , PIK3CA , BRCA1 , and EGFR mutations, respectively. MET gene copy-number gains were detected in the ctDNA of 2 of 16 patients, and FISH analysis of the paired tumor samples confirmed these results. In 2 neoadjuvant chemotherapy-treated ovarian cancer patients, the changes in gene mutation patterns were associated with the treatment response. These findings suggest that CAPP-Seq-based liquid biopsies can be used for the genetic characterization of independent gynecological cancers with high frequency, and might be clinically useful for non-invasive tumor genotyping and therapeutic response monitoring.

Laboratory-markers of the systemic inflammatory-response, such as neutrophil/lymphocyte-ratio (NLR) have been studied as prognostic factors in several tumors but in OC-patients their role is still controversial and no data about the possible correlation with the BRCA-status has been ever reported. We consecutively enrolled a series of 397 newly diagnosed high-grade serous-advanced OC-patients. All patients were tested for BRCA-mutational-status and blood-parameters have been collected 48 h before staging-surgery. A significant correlation of NLR with disease distribution (p < 0.005) was found and patients with NLR < 4 underwent primary-debulking-surgery more frequently (p-value 0.001), with a lower surgical-complexity-score (p-value 0.002). Regarding survival-data, patients with NLR < 4 had a significant 7-month increase in mPFS (26 vs 19 months, p = 0.009); focusing on the BRCA-status, among both BRCA-mutated and BRCA-wild type patients, those with lower NLR had a significantly prolonged mPFS compared to patients with NLR > 4 (BRCA-mutated: 35 vs 23 months, p = 0.03; BRCA-wt: 19 vs 16 months, p = 0.05). At multivariate-analysis, independent factors of prolonged PFS were BRCA mutational status, having received complete cytoreduction and NLR < 4. Also, the strongest predictors of longer OS were BRCA-mutational status, having received complete cytoreductive surgery, NLR < 4 and age. NLR is confirmed to be a prognostic marker in OC-patients and it seems unrelated with BRCA-mutational status.

Endometrial cancer accounts for ~76,000 deaths among women each year worldwide. Disease mortality and the increasing number of new diagnoses make endometrial cancer an important consideration in women’s health, particularly in industrialized countries, where the incidence of this tumour type is highest. Most endometrial cancers are carcinomas, with the remainder being sarcomas. Endometrial carcinomas can be classified into several histological subtypes, including endometrioid, serous and clear cell carcinomas. Histological subtyping is currently used routinely to guide prognosis and treatment decisions for endometrial cancer patients, while ongoing studies are evaluating the potential clinical utility of molecular subtyping. In this Review, we summarize the overarching molecular features of endometrial cancers and highlight recent studies assessing the potential clinical utility of specific molecular features for early detection, disease risk stratification and directing targeted therapies.

Replication stress is a major cause of genomic instability and a crucial vulnerability of cancer cells. This vulnerability can be therapeutically targeted by inhibiting kinases that coordinate the DNA damage response with cell cycle control, including ATR, CHK1, WEE1 and MYT1 checkpoint kinases. In addition, inhibiting the DNA damage response releases DNA fragments into the cytoplasm, eliciting an innate immune response. Therefore, several ATR, CHK1, WEE1 and MYT1 inhibitors are undergoing clinical evaluation as monotherapies or in combination with chemotherapy, poly[ADP-ribose]polymerase (PARP) inhibitors, or immune checkpoint inhibitors to capitalize on high replication stress, overcome therapeutic resistance and promote effective antitumour immunity. Here, we review current and emerging approaches for targeting replication stress in cancer, from preclinical and biomarker development to clinical trial evaluation.Replication stress is a cause of genome instability in cancer cells. This Review discusses strategies to increase replicative stress by inhibiting the checkpoint kinases that coordinate DNA damage response and cell cycle, as well as combination strategies with other targeted therapies.