Unknown

Dataset Information

0

Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies.


ABSTRACT: Current screening methods for ovarian cancer can only detect advanced disease. Earlier detection has proved difficult because the molecular precursors involved in the natural history of the disease are unknown. To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points over three years from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). The functional and clinical significance of the identified mutations was examined using a combination of population-based whole genome sequencing, targeted deep sequencing, multi-center analysis of protein expression, loss of function experiments in an in-vivo reporter assay and mammalian models, and gain of function experiments in primary cultured fallopian tube epithelial (FTE) cells. We identified frequent mutations involving a 40kb distal repressor region for the key stem cell differentiation gene SOX2. In the apparently normal FTE, the region was also mutated. This was associated with a profound increase in SOX2 expression (p<2(-16)), which was not found in patients without cancer (n=108). Importantly, we show that SOX2 overexpression in FTE is nearly ubiquitous in patients with HGSOCs (n=100), and common in BRCA1-BRCA2 mutation carriers (n=71) who underwent prophylactic salpingo-oophorectomy. We propose that the finding of SOX2 overexpression in FTE could be exploited to develop biomarkers for detecting disease at a premalignant stage, which would reduce mortality from this devastating disease.

SUBMITTER: Hellner K 

PROVIDER: S-EPMC5006641 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies.

Hellner Karin K   Miranda Fabrizio F   Fotso Chedom Donatien D   Herrero-Gonzalez Sandra S   Hayden Daniel M DM   Tearle Rick R   Artibani Mara M   Carrami Eli M EM   Williams Ruth R   Gaitskell Kezia K   Elorbany Samar S   Xu Ruoyan R   Laios Alex A   Buiga Petronela P   Ahmed Karim K   Dhar Sunanda S   Zhang Rebecca Yu RY   Campo Leticia L   Myers Kevin A KA   Lozano María M   Ruiz-Miró María M   Gatius Sónia S   Mota Alba A   Moreno-Bueno Gema G   Matias-Guiu Xavier X   Benítez Javier J   Witty Lorna L   McVean Gil G   Leedham Simon S   Tomlinson Ian I   Drmanac Radoje R   Cazier Jean-Baptiste JB   Klein Robert R   Dunne Kevin K   Bast Robert C RC   Kennedy Stephen H SH   Hassan Bassim B   Lise Stefano S   Garcia María José MJ   Peters Brock A BA   Yau Christopher C   Sauka-Spengler Tatjana T   Ahmed Ahmed Ashour AA  

EBioMedicine 20160702


Current screening methods for ovarian cancer can only detect advanced disease. Earlier detection has proved difficult because the molecular precursors involved in the natural history of the disease are unknown. To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points over three years from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). The fu  ...[more]

Similar Datasets

| EGAS00001001909 | EGA
| S-EPMC9738935 | biostudies-literature
2019-10-18 | GSE137238 | GEO
| S-EPMC6333974 | biostudies-literature
2020-01-10 | GSE132149 | GEO
| S-EPMC4437752 | biostudies-literature
| S-EPMC3489778 | biostudies-literature
2020-01-10 | GSE139079 | GEO
| S-EPMC4410038 | biostudies-literature
| S-EPMC7227807 | biostudies-literature