Uterine Lavage Identifies Cancer Mutations and Increased TP53 Somatic Mutation Burden in Individuals with Ovarian Cancer

Current screening methods for ovarian cancer have failed to demonstrate a significant reduction in mortality. Uterine lavage combined with TP53 ultradeep sequencing for the detection of disseminated ovarian cancer cells has emerged as a promising tool, but this approach has not been tested for early-stage disease or non-serous histologies. In addition, lavages carry multiple background mutations, the significance of which is poorly understood. Uterine lavage was collected preoperatively in 34 patients undergoing surgery for suspected ovarian malignancy including 14 patients with benign disease and 20 patients with ovarian cancer [6 non-serous and 14 high-grade serous-like (serous)]. Ultradeep duplex sequencing (∼3,000×) with a panel of common ovarian cancer genes identified the tumor mutation in 33% of non-serous (all early stage) and 79% of serous cancers (including four early stage). In addition, all lavages carried multiple somatic mutations (average of 25 mutations per lavage), more than half of which corresponded to common cancer driver mutations. Driver mutations in KRAS, PIK3CA, PTEN, PPP2R1A, and ARID1A presented as larger clones than non-driver mutations and with similar frequency in lavages from patients with and without ovarian cancer, indicating prevalent somatic evolution in all patients. Driver TP53 mutations, however, presented as significantly larger clones and with higher frequency in lavages from individuals with ovarian cancer, suggesting that TP53-specific clonal expansions are linked to ovarian cancer development. Our results demonstrate that lavages capture cancer cells, even from early-stage cancers, as well as other clonal expansions and support further exploration of TP53 mutation burden as a potential ovarian cancer risk factor. Significance: Cancer driver mutations are found in uterine lavage DNA in all individuals, but driver TP53 mutations presented as significantly larger clones and with higher frequency in lavages from individuals with ovarian cancer. This suggests that TP53-specific clonal expansion plays a role in tumorigenesis and presents opportunities for early detection.

[1]  R. Verhaak,et al.  Spatiotemporal dynamics of clonal selection and diversification in normal endometrial epithelium , 2022, Nature communications.

[2]  Brendan F. Kohrn,et al.  Colorectal cancer is associated with the presence of cancer driver mutations in normal colon , 2021, medRxiv.

[3]  S. Ogawa,et al.  Clonal expansion in non-cancer tissues , 2021, Nature Reviews Cancer.

[4]  A. Jemal,et al.  Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries , 2021, CA: a cancer journal for clinicians.

[5]  Rochelle L. Garcia,et al.  Characterizing TP53 mutations in ovarian carcinomas with and without concurrent BRCA1 or BRCA2 mutations. , 2020, Gynecologic oncology.

[6]  I. Shih,et al.  The Origin of Ovarian Cancer Species and Precancerous Landscape. , 2020, The American journal of pathology.

[7]  A. Jemal,et al.  Cancer statistics, 2020 , 2020, CA: a cancer journal for clinicians.

[8]  Kathryn T. Baker,et al.  Characterization of TP53 mutations in Pap test DNA of women with and without serous ovarian carcinoma. , 2019, Gynecologic oncology.

[9]  Scott R. Kennedy,et al.  Cancer-Associated Mutations but No Cancer: Insights into the Early Steps of Carcinogenesis and Implications for Early Cancer Detection. , 2019, Trends in cancer.

[10]  Kathryn T. Baker,et al.  Ultra-Sensitive TP53 Sequencing for Cancer Detection Reveals Progressive Clonal Selection in Normal Tissue over a Century of Human Lifespan. , 2019, Cell reports.

[11]  I. Martincorena.  Somatic mutation and clonal expansions in human tissues , 2019, Genome Medicine.

[12]  M. Nucci,et al.  The fallopian tube, "precursor escape" and narrowing the knowledge gap to the origins of high-grade serous carcinoma. , 2019, Gynecologic oncology.

[13]  M. Stratton,et al.  The mutational landscape of normal human endometrial epithelium , 2018, bioRxiv.

[14]  E. Obermayr,et al.  Uterine and Tubal Lavage for Earlier Cancer Detection Using an Innovative Catheter , 2018, International Journal of Gynecologic Cancer.

[15]  K. Yoshihara,et al.  Clonal Expansion and Diversification of Cancer-Associated Mutations in Endometriosis and Normal Endometrium. , 2018, Cell reports.

[16]  Ludmila V. Danilova,et al.  Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers , 2018, Science Translational Medicine.

[17]  Scott R. Kennedy,et al.  Aging and the rise of somatic cancer-associated mutations in normal tissues , 2018, PLoS genetics.

[18]  Jillian T Henderson,et al.  Screening for Ovarian Cancer: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force , 2018, JAMA.

[19]  W. Chung,et al.  Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers , 2017, JAMA.

[20]  B. Reva,et al.  Genomic Analysis of Uterine Lavage Fluid Detects Early Endometrial Cancers and Reveals a Prevalent Landscape of Driver Mutations in Women without Histopathologic Evidence of Cancer: A Prospective Cross-Sectional Study , 2016, PLoS medicine.

[21]  Scott R. Kennedy,et al.  Ultra-deep sequencing detects ovarian cancer cells in peritoneal fluid and reveals somatic TP53 mutations in noncancerous tissues , 2016, Proceedings of the National Academy of Sciences.

[22]  I. Shih,et al.  The Dualistic Model of Ovarian Carcinogenesis: Revisited, Revised, and Expanded. , 2016, The American journal of pathology.

[23]  D. Oram,et al.  Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): a randomised controlled trial , 2016, The Lancet.

[24]  K. Kinzler,et al.  Lavage of the Uterine Cavity for Molecular Detection of Müllerian Duct Carcinomas: A Proof-of-Concept Study , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[25]  M. Stratton,et al.  Clock-like mutational processes in human somatic cells , 2015, Nature Genetics.

[26]  Lawrence D True,et al.  Sequencing small genomic targets with high efficiency and extreme accuracy , 2015, Nature Methods.

[27]  Brendan F. Kohrn,et al.  Detecting ultralow-frequency mutations by Duplex Sequencing , 2014, Nature Protocols.

[28]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[29]  Sheena M. Scroggins,et al.  Germline and Somatic Mutations in Homologous Recombination Genes Predict Platinum Response and Survival in Ovarian, Fallopian Tube, and Peritoneal Carcinomas , 2013, Clinical Cancer Research.

[30]  K. Kinzler,et al.  Evaluation of DNA from the Papanicolaou Test to Detect Ovarian and Endometrial Cancers , 2013, Science Translational Medicine.

[31]  Jesse J. Salk,et al.  Detection of ultra-rare mutations by next-generation sequencing , 2012, Proceedings of the National Academy of Sciences.

[32]  Rochelle L. Garcia,et al.  Mutations in 12 genes for inherited ovarian, fallopian tube, and peritoneal carcinoma identified by massively parallel sequencing , 2011, Proceedings of the National Academy of Sciences.

[33]  C. Cole,et al.  COSMIC: the catalogue of somatic mutations in cancer , 2011, Genome Biology.

[34]  J. Gohagan,et al.  Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Randomized Controlled Trial. , 2011, JAMA.

[35]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[36]  Rochelle L. Garcia,et al.  The molecular pathogenesis of hereditary ovarian carcinoma , 2010, Cancer.

[37]  Carlos Caldas,et al.  Driver mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary , 2010, The Journal of pathology.

[38]  I. Shih,et al.  Assessment of TP53 mutation using purified tissue samples of ovarian serous carcinomas reveals a higher mutation rate than previously reported and does not correlate with drug resistance , 2007, International Journal of Gynecologic Cancer.