Clinical trial NCT02288676: DOvEEgene/WISE Genomics: Diagnosing Ovarian and Endometrial Cancer Early Using Genomics
Official title: DOvEEgene/WISE Genomics: Diagnosing Ovarian and Endometrial Cancer Early Using Genomics
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Ovarian Neoplasms
Endometrial Neoplasms
Endometrial Cancer
Ovarian Cancer
Screening
Safety
Reduced Mortality
Reduced Morbidity
Early Diagnosis
Keywords: genomics
somatic mutations
genetic mutations
high-grade serous cancer
ovarian cancer
endometrial cancer
DNA tagging
Lead sponsor: McGill University
Sponsor class: OTHER
Collaborators: name: McGill University Health Centre/Research Institute of the McGill University Health Centre
First posted: 2014-11-11
Enrollment: 1200
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The participating hospitals run multiple weekly routine gynecology and gynecologic oncology clinics. The cases include women scheduled to undergo surgery for tumor removal, for either proven or suspected upper genital tract cancer. The controls include women scheduled to have a hysterectomy, bilateral salpingectomy (removal of the fallopian tubes) with/without bilateral oophorectomy (removal of the ovaries) to treat benign conditions.

Brief summary: This study aims to develop and validate a test for detecting ovarian and endometrial cancers early. It relies on detecting somatic mutations that are associated with these cancers from a uterine pap test. A saliva sample is also collected that acts as an internal control and has the ability to detect deleterious germline mutations associated with common hereditary cancers (such as breast, ovarian, endometrial, colon, and pancreatic cancers). A machine learning classifier is then used to discriminate between cancer and benign disease.

Detailed description: For women in high-income countries, ovarian/fallopian tube and endometrial cancers are within the top four cancers in terms of incidence, death and healthcare expenditure. The deaths associated with these cancers are largely caused by Stage III/IV disease, for which cure rates have not changed in three decades, despite escalating costs of treatment. Attempts at early detection have been ineffective in reducing mortality, because the high-grade subtypes, which account for the majority of deaths, metastasize while the primary cancer is still small, has not caused symptoms, and is undetectable by imaging or blood tumour markers.

In recent years, the recognition that somatic mutations are early steps in carcinogenesis has led to a shift from tests such as imaging and non-specific blood tumour markers to technology that detects cancer-associated mutations in cervical, uterine, or blood samples. Several DNA-tagging technologies have been shown to be capable of identifying small amount of cancer DNA among thousands of normal cells, the proverbial needle in a haystack.

This investigation aims to develop and validate a high-sensitivity capture using a panel of genes involved in ovarian and endometrial carcinogenesis, low-pass whole genome sequencing, coupled with a machine-learning derived classifier for discriminating cancer from benign gynecologic disease prevalent in peri/post-menopausal women.

Eligibility criteria: Case Inclusion:

* Subjects should have suspected or confirmed cancer of the upper genital tract.
* Participant will undergo surgery for tumour removal.

Control inclusion:

• Subjects should be scheduled to have a hysterectomy, bilateral salpingectomy, with or without bilateral oophorectomy, for presumed benign disease.

Primary outcomes:
measure: Detection of cancer-related mutations
timeFrame: 3 years
Secondary outcomes:
measure: Patient related outcomes including pain and acceptability
timeFrame: 3 years
measure: Risks associated with the DOvEEgene test
timeFrame: 3 years
Other outcomes:
Locations:
city: Montreal
country: Canada
facility: Royal Victoria Hospital (Glen Site)
state: Quebec
Study officials:
affiliation: McGill Genome Center
name: Dr Ioannis Ragoussis, PhD
role: STUDY_DIRECTOR
References:
citation: Gilbert L, Basso O, Sampalis J, Karp I, Martins C, Feng J, Piedimonte S, Quintal L, Ramanakumar AV, Takefman J, Grigorie MS, Artho G, Krishnamurthy S; DOvE Study Group. Assessment of symptomatic women for early diagnosis of ovarian cancer: results from the prospective DOvE pilot project. Lancet Oncol. 2012 Mar;13(3):285-91. doi: 10.1016/S1470-2045(11)70333-3. Epub 2012 Jan 17.
citation: Kinde I, Bettegowda C, Wang Y, Wu J, Agrawal N, Shih IeM, Kurman R, Dao F, Levine DA, Giuntoli R, Roden R, Eshleman JR, Carvalho JP, Marie SK, Papadopoulos N, Kinzler KW, Vogelstein B, Diaz LA Jr. Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers. Sci Transl Med. 2013 Jan 9;5(167):167ra4. doi: 10.1126/scitranslmed.3004952.
citation: Gilbert L, Revil T, Meunier C, Jardon K, Zeng X, Martins C, Arseneau J, Fu L, North K, Schiavi A, Ehrensperger E, Artho G, Lee T, Morris D, Ragoussis J. The empress of subterfuge: cancer of the fallopian tube presenting with malapropism. Lancet. 2017 Sep 2;390(10098):1003-1004. doi: 10.1016/S0140-6736(17)31586-6. No abstract available.
citation: Wang Y, Li L, Douville C, Cohen JD, Yen TT, Kinde I, Sundfelt K, Kjaer SK, Hruban RH, Shih IM, Wang TL, Kurman RJ, Springer S, Ptak J, Popoli M, Schaefer J, Silliman N, Dobbyn L, Tanner EJ, Angarita A, Lycke M, Jochumsen K, Afsari B, Danilova L, Levine DA, Jardon K, Zeng X, Arseneau J, Fu L, Diaz LA Jr, Karchin R, Tomasetti C, Kinzler KW, Vogelstein B, Fader AN, Gilbert L, Papadopoulos N. Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers. Sci Transl Med. 2018 Mar 21;10(433):eaap8793. doi: 10.1126/scitranslmed.aap8793.