TY - JOUR
T1 - Molecular response to neoadjuvant chemotherapy in high-grade serous ovarian carcinoma
AU - Arend, Rebecca C.
AU - Londoño, Angelina I.
AU - Montgomery, Allison M.
AU - Smith, Haller J.
AU - Dobbin, Zachary C.
AU - Katre, Ashwini A.
AU - Martinez, Alba
AU - Yang, Eddy S.
AU - Alvarez, Ronald D.
AU - Huh, Warner K.
AU - Bevis, Kerri S.
AU - Michael Straughn, J.
AU - Estes, Jacob M.
AU - Novak, Lea
AU - Crossman, David K.
AU - Cooper, Sara J.
AU - Landen, Charles N.
AU - Leath, Charles A.
N1 - Publisher Copyright:
© 2018 American Association for Cancer Research.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - While high-grade serous ovarian carcinoma (HGSOC) is the most common histologic subtype of ovarian cancer, significant tumor heterogeneity exists. In addition, chemotherapy induces changes in gene expression and alters the mutational profile. To evaluate the notion that patients with HGSOC could be better classified for optimal treatment based on gene expression, we compared genetic variants [by DNA next-generation sequencing (NGS) using a 50 gene Ion Torrent panel] and gene expression (using the NanoString PanCancer 770 gene Panel) in the tumor from 20 patients with HGSOC before and after neoadjuvant chemotherapy (NACT). NGS was performed on plasma cell free DNA (cfDNA) on a select group of patients (n ¼ 14) to assess the utility of using cfDNA to monitor these changes. A total of 86 genes had significant changes in RNA expression after NACT. Thirty-eight genetic variants (including SNPs) from 6 genes were identified in tumors pre-NACT, while 59 variants from 19 genes were detected in the cfDNA. The number of DNA variants were similar after NACT. Of the 59 variants in the plasma pre-NACT, only 6 persisted, whereas 33 of 38 specific variants in the tumor DNA remained unchanged. Pathway analysis showed the most significant alterations in the cell cycle and DNA damage pathways. Implications: Gene expression profiles at the time of interval debulking provide additional genetic information that could help impact treatment decisions after NACT; although, continued collection and analysis of matched tumor and cfDNA from multiple time points are needed to determine the role of cfDNA in the management of HGSOC.
AB - While high-grade serous ovarian carcinoma (HGSOC) is the most common histologic subtype of ovarian cancer, significant tumor heterogeneity exists. In addition, chemotherapy induces changes in gene expression and alters the mutational profile. To evaluate the notion that patients with HGSOC could be better classified for optimal treatment based on gene expression, we compared genetic variants [by DNA next-generation sequencing (NGS) using a 50 gene Ion Torrent panel] and gene expression (using the NanoString PanCancer 770 gene Panel) in the tumor from 20 patients with HGSOC before and after neoadjuvant chemotherapy (NACT). NGS was performed on plasma cell free DNA (cfDNA) on a select group of patients (n ¼ 14) to assess the utility of using cfDNA to monitor these changes. A total of 86 genes had significant changes in RNA expression after NACT. Thirty-eight genetic variants (including SNPs) from 6 genes were identified in tumors pre-NACT, while 59 variants from 19 genes were detected in the cfDNA. The number of DNA variants were similar after NACT. Of the 59 variants in the plasma pre-NACT, only 6 persisted, whereas 33 of 38 specific variants in the tumor DNA remained unchanged. Pathway analysis showed the most significant alterations in the cell cycle and DNA damage pathways. Implications: Gene expression profiles at the time of interval debulking provide additional genetic information that could help impact treatment decisions after NACT; although, continued collection and analysis of matched tumor and cfDNA from multiple time points are needed to determine the role of cfDNA in the management of HGSOC.
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U2 - 10.1158/1541-7786.MCR-17-0594
DO - 10.1158/1541-7786.MCR-17-0594
M3 - Article
C2 - 29523763
AN - SCOPUS:85047728475
SN - 1541-7786
VL - 16
SP - 813
EP - 824
JO - Molecular Cancer Research
JF - Molecular Cancer Research
IS - 5
ER -