Serous ovarian cancers (SOCs) are unusual among epithelial cancers in that some (10-15%) are curable by chemotherapy in stages 3 and 4. SOCs are complex entities in which a pathologically symbiotic interplay occurs between cancer cells and immune, inflammatory, vascular and stromal cells. We propose to study proteomic profiles of SOCs at the single-cell level in many malignant and normal cell types, including tumor-initiating cell populations that can re-establish a complete tumor cell hierarchy post treatment. Multi-dimensional (>40 parameters per cell) mass cytometry affords unprecedented opportunities to measure these responses simultaneously in the multiple cell types that comprise the tumor and, in so doing, to identify pathways and mechanisms associated with ex vivo drug sensitivity and resistance. Thus, we will assess both basal and drug-evoked proteomic signatures for carboplatin (PT), paclitaxel (TX) and selective pathway inhibitors. A major challenge in SOC is to enhance cure by initial PT and TX. Our goals are to identify predictive therapeutic biomarkers for PT, TX, and novel combinations with PT/TX.
The aims are: (1) Utilize mass cytometry to identify proteomic profiles that designate the relative responsiveness of SOC drug-sensitive and resistant cell models to PT, TX, and two potential sensitizing pathways: IAPs and CCL2/CCR2.
This aim will utilize 12 drug-resistant cell models derived from 6 parental lines. In our preliminary data, IAP and CCL2 inhibition enhances the efficacy of PT and TX. Combinations of inhibitors will be evaluated with PT and TX for their ability to promote cell death in the cell models and tumor regression in xenografts. (2) Validate these proteomic profiles and therapeutic targets in SOC clinical specimens. We have an existing viably frozen SOC tumor bank of more than 50 specimens and plan to study a total of 90 during this project. Xenografts from selected clinical specimens will be utilized to assess drug responsiveness in vivo, with harvesting of tumors for mass cytometric assays. (3) Perform genomic studies using mutation analyses and expression profiles of the SOC cell models and clinical specimens. These will be analyzed in conjunction with the TCGA and Tothill databases, applying novel computational tools for combining mass cytometry analysis with transcriptomic, epigenetic and exomic databases. The genomic analyses will facility the identification of new candidate therapeutic biomarkers for mass cytometry, as well as additional therapeutic targets for PT/TX combinations. The scientific benefits of this project will be new insights into SOC curability via determinants of drug responsiveness at the functional proteomic and molecular level. The expected benefits to patients are the ability to identify responders at diagnosis, new drug combinations leading to new clinical trials, and tailoring therapies prospectively for individual patients.
The public health relevance of this project is new knowledge about why some ovarian cancers are cured while others are not, as well as identifying how curability of ovarian cancers can be increased by adding targeted therapies to current treatments. The project will use novel technologies recently developed at Stanford and uniquely applicable to ovarian cancers in this project. These include (1) the ability to measure many proteins simultaneously in individual cells and subpopulations of cells in a cancer (mass cytometry), developed by Drs. Nolan and Fantl; (2) the analysis of the resulting millions of data points (SPADE and other software from Dr. Plevritis); (3) new cellular models of ovarian cancer drug resistance in concert with ovarian cancer specimens from patients (from Dr. Sikic); and integrated methods for analyzing associated genomic and proteomic data (by Dr. Gevaert).
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