Importance: Since the discovery of BRCA1 and BRCA2, multiple high- and moderate-penetrance genes have been reported as risk factors for hereditary breast cancer, ovarian cancer, or both; however, it is unclear whether these findings represent the complete genetic landscape of these cancers. Systematic investigation of the genetic contributions to breast and ovarian cancers is needed to confirm these findings and explore potentially new associations.
Objective: To confirm reported and identify additional predisposition genes for breast or ovarian cancer.
Design, Setting, And Participants: In this sample of 11 416 patients with clinical features of breast cancer, ovarian cancer, or both who were referred for genetic testing from 1200 hospitals and clinics across the United States and of 3988 controls who were referred for genetic testing for noncancer conditions between 2014 and 2015, whole-exome sequencing was conducted and gene-phenotype associations were examined. Case-control analyses using the Genome Aggregation Database as a set of reference controls were also conducted.
Main Outcomes And Measures: Breast cancer risk associated with pathogenic variants among 625 cancer predisposition genes; association of identified predisposition breast or ovarian cancer genes with the breast cancer subtypes invasive ductal, invasive lobular, hormone receptor-positive, hormone receptor-negative, and male, and with early-onset disease.
Results: Of 9639 patients with breast cancer, 3960 (41.1%) were early-onset cases (≤45 years at diagnosis) and 123 (1.3%) were male, with men having an older age at diagnosis than women (mean [SD] age, 61.8 [12.8] vs 48.6 [11.4] years). Of 2051 women with ovarian cancer, 445 (21.7%) received a diagnosis at 45 years or younger. Enrichment of pathogenic variants were identified in 4 non-BRCA genes associated with breast cancer risk: ATM (odds ratio [OR], 2.97; 95% CI, 1.67-5.68), CHEK2 (OR, 2.19; 95% CI, 1.40-3.56), PALB2 (OR, 5.53; 95% CI, 2.24-17.65), and MSH6 (OR, 2.59; 95% CI, 1.35-5.44). Increased risk for ovarian cancer was associated with 4 genes: MSH6 (OR, 4.16; 95% CI, 1.95-9.47), RAD51C (OR, not estimable; false-discovery rate-corrected P = .004), TP53 (OR, 18.50; 95% CI, 2.56-808.10), and ATM (OR, 2.85; 95% CI, 1.30-6.32). Neither the MRN complex genes nor CDKN2A was associated with increased breast or ovarian cancer risk. The findings also do not support previously reported breast cancer associations with the ovarian cancer susceptibility genes BRIP1, RAD51C, and RAD51D, or mismatch repair genes MSH2 and PMS2.
Conclusions And Relevance: The results of this large-scale exome sequencing of patients and controls shed light on both well-established and controversial non-BRCA predisposition gene associations with breast or ovarian cancer reported to date and may implicate additional breast or ovarian cancer susceptibility gene candidates involved in DNA repair and genomic maintenance.
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http://dx.doi.org/10.1001/jamaoncol.2018.2956 | DOI Listing |
Clin Cancer Res
January 2025
University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Purpose: Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that is essential for the survival and immune sequestration of cancer cells. We conducted a phase 1 study of TTI‑101, a first-in-class, selective small-molecule inhibitor of STAT3, in patients with advanced metastatic cancer.
Patients And Methods: Patients were treated with TTI-101 orally twice daily in 28-day cycles at 4 dose levels (DLs): 3.
Cancer Chemother Pharmacol
January 2025
Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China.
Purpose: Ovarian clear cell carcinoma is a highly malignant gynecological tumor characterized by a high rate of chemotherapy resistance and poor prognosis. The PI3K/AKT/mTOR pathway is well-known to be closely related to the progression of various malignancies, and recent studies have indicated that this pathway may play a critical role in the progression and worsening of OCCC.
Methods: In this study, we investigated the combined effects of WX390, a dual inhibitor of PI3K/mTOR, and cisplatin on OCCC through both in vitro and in vivo experiments to further elucidate their therapeutic effects.
Cells
December 2024
State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, School of Marine Sciences, Ningbo University, Ningbo 315211, China.
Ubiquitin-conjugating enzyme E2 T (UBE2T) is a crucial E2 enzyme in the ubiquitin-proteasome system (UPS), playing a significant role in the ubiquitination of proteins and influencing a wide range of cellular processes, including proliferation, differentiation, apoptosis, invasion, and metabolism. Its overexpression has been implicated in various malignancies, such as lung adenocarcinoma, gastric cancer, pancreatic cancer, liver cancer, and ovarian cancer, where it correlates strongly with disease progression. UBE2T facilitates tumorigenesis and malignant behaviors by mediating essential functions such as DNA repair, apoptosis, cell cycle regulation, and the activation of oncogenic signaling pathways.
View Article and Find Full Text PDFJ Gynecol Oncol
December 2025
Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China.
Objective: To explore the characteristics and survival outcomes of ovarian squamous cell carcinoma (SCC) and the treatment effectiveness of immune checkpoint inhibitors (ICIs).
Methods: Patients diagnosed with ovarian SCC at Peking Union Medical College Hospital between January 2000 and September 2023 were included. Overall survival (OS) and progression-free survival (PFS) were analyzed using the Kaplan-Meier method.
J Gynecol Oncol
December 2024
Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric and Gynecologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Objective: Our study was aimed to construct a predictive model to advance ovarian cancer diagnosis by machine learning.
Methods: A retrospective analysis of patients with pelvic/adnexal/ovarian mass was performed. Potential features related to ovarian cancer were obtained as many as possible.
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