Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

The impact of estrogen receptor and L1 cell adhesion molecule expression on endometrial cancer outcome correlates with clinicopathological risk group and molecular subgroup.

OBJECTIVE: To assess the risk stratification of clinicopathologically and molecularly classified endometrial cancer based on estrogen receptor (ER) and L1 cell adhesion molecule (L1CAM) expression. METHODS: This was a retrospective study of patients who underwent primary treatment at a single tertiary center. Carcinomas were classified into 5 clinicopathological risk groups, as per European guidelines. Immunohistochemistry and polymerase-ϵ sequencing were conducted for molecular classification and determination of ER and L1CAM expression. RESULTS: Data from 1044 patients were analyzed. The median follow-up was 67.5 months. In univariable analyses, ER expression correlated with improved disease-specific survival (DSS) in the "no specific molecular profile" (NSMP) (P < 0.001) and mismatch repair deficient (MMRd) (P = 0.002) subgroups. Negative L1CAM expression was associated with enhanced DSS in the NSMP subgroup alone (P < 0.001). ER (hazard ratio [HR] 0.18), but not L1CAM, exhibited prognostic significance within NSMP when controlling for parameters available at the time of diagnosis (tumor histotype, grade, age). ER and L1CAM were not independently associated with DSS within NSMP when controlling for parameters available after surgery (clinicopathological risk groups, age, adjuvant therapy). However, in high-risk-advanced-metastatic cases, both ER (HR 0.26) and L1CAM (HR 3.9) independently correlated with DSS. Similarly, within MMRd, ER was associated with improved DSS in high-risk-advanced-metastatic carcinomas (HR 0.42). CONCLUSION: The prognostic significance of ER and L1CAM varies across clinicopathological risk groups and molecular subgroups of endometrial cancer. Notably, risk assessment for high-risk-advanced-metastatic NSMP and MMRd subtype carcinomas can be refined by ER status.

Clinical and molecular risk factors for repeat interventions due to symptomatic uterine leiomyomas.

BACKGROUND: Repeat leiomyoma occurrence or even reintervention is common after myomectomy. Little is known about the factors related to repeat interventions. OBJECTIVES: This study aimed to determine the frequency of leiomyoma-related reintervention after an initial laparoscopic or abdominal myomectomy and to analyze both clinical and molecular risk factors for reinterventions. Another objective was to define the frequency of clonally related tumors from repeat operations. STUDY DESIGN: This retrospective cohort study included 234 women who had undergone laparoscopic or abdominal myomectomy in 2009-2014. Information on repeat leiomyoma-related interventions as well as on other clinical factors was collected from medical records after a median follow-up time of 11,4 years (range 7,9-13,8 years) after the index procedure. The effect of clinical risk factors on the risk of reintervention was analyzed by the Kaplan-Meier estimator and the Cox proportional hazards model. For molecular analyses, we examined the mutation profiles of 133 formalin-fixed paraffin-embedded leiomyoma samples from 33 patients with repeat operations. We screened the tumors for the three primary leiomyoma driver alterations-MED12 mutations, HMGA2 overexpression, and FH-deficiency-utilizing Sanger sequencing and immunohistochemistry. To further assess the clonal relationship of the tumors, we executed whole-exome sequencing for 52 leiomyomas from 21 patients who exhibited the same driver alteration in tumors obtained from multiple procedures. RESULTS: Reintervention rate at 11,4 years after myomectomy was 20% (46/234). Number of leiomyomas removed at the index myomectomy was a risk factor (hazard ratio 1.21; 95% confidence interval 1.09-1.34). Age at index myomectomy (hazard ratio 0.94; 95% confidence interval 0.89-0.99) and postoperative parity (hazard ratio 0.23; 95% confidence interval 0.09-0.60) were protective factors. Molecular characterization of tumors from index and non-index operations confirmed a clonal relationship of the tumors in 3/33 (9%) patients. None of the leiomyomas harboring a MED12 mutation -the most common leiomyoma driver- were confirmed clonally related. FH-deficiency was detected in repeat leiomyomas from 3/33 (9%) patients. All these patients harbored a germline FH mutation, which is distinctive for the hereditary leiomyomatosis and renal cell cancer (HLRCC) syndrome. Finally, we identified three (3/33; 9%) patients with two tumors each displaying somatic mutations in a recently identified novel leiomyoma driver gene, YEATS4. All YEATS4 mutations were different and thus the tumors were not clonally related. CONCLUSION: Our study shows that reintervention is common after surgical myomectomy. Uterine leiomyomas typically develop independently, but some share a clonal origin. Repeat leiomyoma occurrence may be due to genetic predisposition, such as a germline FH mutation. Distinct somatic YEATS4 mutations identified in multiple leiomyomas from the same patient indicate a possible role for YEATS4 in repeat leiomyomas.

Stage distribution and prognostic accuracy of the 2023 FIGO (the International Federation of Gynecology & Obstetrics) staging system for endometrial cancer: A retrospective cohort study.

OBJECTIVE: To assess the stage distribution and stage-related disease-specific survival rates for endometrial cancer using the FIGO (the International Federation of Gynecology & Obstetrics) 2009 and 2023 staging systems. Further, we sought to evaluate the prognostic utility of additional covariates beyond the FIGO 2023 stage. METHODS: Endometrial carcinomas were molecularly classified by the Proactive Molecular Risk Classifier for Endometrial Cancer and staged according to FIGO 2009 and 2023 criteria. Disease-specific survival was calculated as the time from surgery to death from endometrial cancer. RESULTS: Data from 604 patients were analyzed. Median follow-up time was 81 months. A total of 118 stage shifts (19.5%) occurred between the FIGO 2009 and FIGO 2023 systems, with upshifts accounting for 107 (90.7%) of these changes. Within the FIGO 2023 system, molecular classification resulted in restaging of 69 patients (11.4%). Shifts that could alter adjuvant therapy decisions were identified in 23 patients (3.8%). The FIGO 2023 system effectively categorized endometrial cancers into prognostic subgroups. The FIGO 2023 stage, tumor size, positive peritoneal cytology, and mismatch repair deficiency were associated with disease-specific survival in a multivariable analysis, whereas age and adjuvant therapy were not. CONCLUSION: The FIGO 2023 staging system for endometrial cancer appears highly prognostic. Prognostic assessment of the patients can be further enhanced by readily accessible covariates. A stage shift between the FIGO 2009 and 2023 systems occurs in about one-fifth of patients. The implementation of molecular classification within the FIGO 2023 system bears implications for decisions regarding adjuvant therapy.

Asparaginase-like protein 1 as a prognostic tissue biomarker in clinicopathologically and molecularly characterized endometrial cancer.

OBJECTIVE: Prognostic stratification of endometrial cancer involves the assessment of stage, uterine risk factors, and molecular classification. This process can be further refined through annotation of prognostic biomarkers, notably L1 cell adhesion molecule (L1CAM) and hormonal receptors. Loss of asparaginase-like protein 1 (ASRGL1) has been shown to correlate with poor outcome in endometrial cancer. Our objective was to assess prognostication of endometrial cancer by ASRGL1 in conjunction with other available methodologies. STUDY DESIGN: This was a retrospective study of patients who underwent primary treatment at a single tertiary center. Tumors were molecularly classified by the Proactive Molecular Risk Classifier for Endometrial Cancer. Expression of ASRGL1, L1CAM, estrogen receptor, and progesterone receptor was determined by immunohistochemistry. ASRGL1 expression intensity was scored into four classes. RESULTS: In a cohort of 775 patients, monitored for a median time of 81 months, ASRGL1 expression intensity was related to improved disease-specific survival in a dose-dependent manner (P < 0.001). Low expression levels were associated with stage II-IV disease and presence of uterine factors, i.e. high grade, lymphovascular space invasion, and deep myometrial invasion (P < 0.001 for all). Among the molecular subgroups, low expression was most prevalent in p53 abnormal carcinomas (P < 0.001). Low ASRGL1 was associated with positive L1CAM expression and negative estrogen and progesterone receptor expression (P < 0.001 for all). After adjustment for stage and uterine factors, strong ASRGL1 staining intensity was associated with a lower risk for cancer-related deaths (hazard ratio 0.56, 95 % confidence interval 0.32-0.97; P = 0.038). ASRGL1 was not associated with the outcome when adjusted for stage, molecular subgroups, L1CAM, and hormonal receptors. When analyzed separately within the different molecular subgroups, ASRGL1 showed an association with disease-specific survival specifically in "no specific molecular profile" subtype carcinomas (P < 0.001). However, this association became nonsignificant upon controlling for confounders. CONCLUSIONS: Low ASRGL1 expression intensity correlates with poor survival in endometrial cancer. ASRGL1 contributes to more accurate prognostication when controlled for stage and uterine factors. However, when adjusted for stage and other biomarkers, including molecular subgroups, ASRGL1 does not improve prognostic stratification.