Abstract Background: Women with ovarian cancer suffer from a high rate of mortality due to the development of chemotherapy resistance. To better understand the mechanisms of chemotherapy resistance we initiated a prospective study of women with ovarian cancer, which we refer to as the Ovarian Cancer Precision Medicine Initiative (OCPMI) where we collect tumor biopsies and perform comprehensive molecular analyses. Our goal is to use the molecular data from these specimens to understand the mechanisms of chemo-resistance and use that information to improve therapeutic approaches. Methods: In this study, we report our analysis of pairs of matched tumor specimens taken from seven ovarian cancer patients enrolled in OCPMI who were treated using neoadjuvant chemotherapy (NACT). The first tumor specimen was taken at time of initial diagnostic biopsy (pre-NACT), while the matched second tumor biopsy was taken after NACT administration (post-NACT), during interval debulking surgery. All fourteen tumor biopsies were subjected to single cell RNA sequencing to generate gene expression data on 54,827 pre-NACT cells and 30,661 post-NACT cells. Bioinformatic techniques were used to compare the post-NACT tumor cells that had experienced chemotherapy to the chemo-naïve pre-NACT tumor cells. Gene/pathway enrichment tests were performed to identify genes and pathways that correlated with the chemo resistance phenotype. Results: In all matched biopsies we found that the majority of cells in the chemo-experienced post-NACT samples could be mapped to a subset of the cells in the chemo-naïve, pre-NACT samples based on gene expression patterns. We hypothesize that this subset of pre-NACT cells are the precursor cells that are able to withstand chemotherapy and could be the cause of recurrence. Analysis of the genes and signaling pathways that were upregulated in the chemo-resistant subset of pre-NACT cells identified potential novel therapeutic targets including TNFa signaling, JAK-STAT signaling, interferon signaling, TGFb signaling, and STK33 kinase activation. Conclusions: Single cell RNA sequencing combined with sequential biopsies provides an unprecedented ability to understand mechanisms of response to chemotherapy. This type of analysis can be used to identify novel therapeutic approaches targeting the chemo-resistance phenotype. Citation Format: Timothy K. Starr, Shobhana Talukdar, Zenas Chang, Jason Cepela, Christopher Tastad, Mihir Shetty, Isaac Schneider, Jun Woo, Marissa Macchietto, Christine Henzler, Ying Zhang, Joshua Baller, Constantin Aiferis, Sarah Munro, Andrew C. Nelson, Jinhua Wang, Boris J. Winterhoff. Chemotherapy resistance pathways identified in ovarian cancer patients treated with neoadjuvant chemotherapy using single cell RNA sequencing of matched tumor biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1410.