Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis

Juli Unternaehrer; Evgeny Chirshev; Nozomi Hojo; Antonella Bertucci; Linda Sanderman; Anthony Nguyen; Hanmin Wang; Tise Suzuki; Emmanuel Brito; Shannalee Martine; Christine Castañón; Saied Mirshahidi; Marcelo Vazquez; Kerby C. Oberg; Yevgeniya J. Ioffe

doi:10.1158/1538-7445.AM2020-1682

Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis

Juli Unternaehrer, Evgeny Chirshev, Nozomi Hojo, Antonella Bertucci, Linda Sanderman, Anthony Nguyen, Hanmin Wang, Tise Suzuki, Emmanuel Brito, Shannalee Martine, Christine Castañón, Saied Mirshahidi, Marcelo Vazquez, Kerby C. Oberg, Yevgeniya J. Ioffe

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	Cancer Research
Volume	80
DOIs	https://doi.org/10.1158/1538-7445.AM2020-1682
State	Published - Aug 15 2020

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Biology
Oncology

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Unternaehrer, J., Chirshev, E., Hojo, N., Bertucci, A., Sanderman, L., Nguyen, A., Wang, H., Suzuki, T., Brito, E., Martine, S., Castañón, C., Mirshahidi, S., Vazquez, M., Oberg, K. C., & Ioffe, Y. J. (2020). Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis. Cancer Research, 80. https://doi.org/10.1158/1538-7445.AM2020-1682

Unternaehrer, J, Chirshev, E, Hojo, N, Bertucci, A, Sanderman, L, Nguyen, A, Wang, H, Suzuki, T, Brito, E, Martine, S, Castañón, C, Mirshahidi, S, Vazquez, M, Oberg, KC & Ioffe, YJ 2020, 'Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis', Cancer Research, vol. 80. https://doi.org/10.1158/1538-7445.AM2020-1682

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title = "Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis",

author = "Juli Unternaehrer and Evgeny Chirshev and Nozomi Hojo and Antonella Bertucci and Linda Sanderman and Anthony Nguyen and Hanmin Wang and Tise Suzuki and Emmanuel Brito and Shannalee Martine and Christine Casta{\~n}{\'o}n and Saied Mirshahidi and Marcelo Vazquez and Oberg, {Kerby C.} and Ioffe, {Yevgeniya J.}",

note = "Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA Objective: Patient-derived samples present an advantage over current cell line models of high grade serous ovarian cancer (HGSOC), which are flawed in terms of being reliable and phenotypically faithful models of in vivo HGSOC.",

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doi = "10.1158/1538-7445.AM2020-1682",

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T1 - Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis

AU - Unternaehrer, Juli

AU - Chirshev, Evgeny

AU - Hojo, Nozomi

AU - Bertucci, Antonella

AU - Sanderman, Linda

AU - Nguyen, Anthony

AU - Wang, Hanmin

AU - Suzuki, Tise

AU - Brito, Emmanuel

AU - Martine, Shannalee

AU - Castañón, Christine

AU - Mirshahidi, Saied

AU - Vazquez, Marcelo

AU - Oberg, Kerby C.

AU - Ioffe, Yevgeniya J.

N1 - Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA Objective: Patient-derived samples present an advantage over current cell line models of high grade serous ovarian cancer (HGSOC), which are flawed in terms of being reliable and phenotypically faithful models of in vivo HGSOC.

PY - 2020/8/15

Y1 - 2020/8/15

UR - https://cancerres.aacrjournals.org/content/80/16_Supplement/1682

U2 - 10.1158/1538-7445.AM2020-1682

DO - 10.1158/1538-7445.AM2020-1682

M3 - Article

VL - 80

JO - Cancer Research

JF - Cancer Research

ER -

Abstract 1682: Epithelial-mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with let-7 levels and predicts tumor growth and metastasis

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