07 Aug Ovarian Cancer: Proteomics Study Allows Identification of Subtype Resistant to Chemotherapy

MedicalResearch.com Interview with:
Pei Wang, PhD
Professor, Department of Genetics and Genomic Sciences
Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
Michael J. Birrer MD PhD
Director, Winthrop P. Rockefeller Cancer Institute
University of Arkansas for Medical Sciences
Little Rock, AR 72205
Amanda G. Paulovich MD PhD
Translational Science and Therapeutics Division
Fred Hutchinson Cancer Center
Seattle WA 98109

MedicalResearch.com: What is the background for this study? How common is serous ovarian cancer?

Response: Epithelial ovarian cancer accounts for >185,000 deaths/year worldwide. The most common subtype, high-grade serous ovarian cancer (HGSOC), accounts for 60% of deaths. Despite improvements in surgical and chemotherapeutic approaches, HGSOC mortality has not changed in decades. Five-year survival remains ~30% for the majority of patients.

Standard of care involves surgical debulking combined with adjuvant or neoadjuvant chemotherapy with carbo- or cisplatin in combination with a taxane. At diagnosis, HGSOC is among the most chemo-sensitive of all epithelial malignancies, with initial response rates of ~85%, presumably related to DNA repair defects. Platinum is thought primarily to drive the response rate, due to the lower single-agent response rate for taxanes.

Unfortunately, 10-20% of HGSOC patients have treatment-refractory disease at diagnosis, fail to respond to initial chemotherapy, and have a dismal prognosis. The poor response to subsequent therapy and median overall survival of ~12 months for these patients has not changed in 40 years.

Despite >30 years of literature studying platinum resistance in cancer, there currently is no way to distinguish refractory from sensitive HGSOCs prior to therapy. Consequently, patients with refractory disease experience the toxicity of platinum-based chemotherapy without benefit. Due to their rapid progression, they are commonly excluded from participating in clinical trials. Consequently, there is no ongoing clinical research that could identify effective therapeutic agents for these patients or provide insights into molecular mechanisms of refractory disease.  “Right now, we can’t identify drug-resistant ovarian cancer patients up front,” said co-senior author Michael Birrer, MD, PhD, who directs UAMS’ Winthrop J. Rockefeller Cancer Institute. “We find them by default: They get sick and pass away so quickly that they can’t even be put on new clinical trials.”

To address this unmet clinical need, we performed proteogenomic analysis of treatment-naïve HGSOCs (chemo-sensitive and chemo-refractory) to identify molecular signatures of refractory HGSOC and to identify potential treatment targets.

MedicalResearch.com: Briefly describe how your study was conducted.

Response:       We characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts and two biospecimen types (formalin-fixed paraffin-embedded and frozen tumor biopsies). Using machine learning models, we identified a 64-protein signature that predicts with high specificity a subset of high-grade serous ovarian cancers refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We also detected a significant association between lack of Ch17 loss-of-heterozygosity and refractory disease. Based on pathway protein expression, we identified five novel clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models.

MedicalResearch.com: What are the main findings?

Response:  We identified a 64-protein signature that predicts with high specificity a subset of high-grade serous ovarian cancers refractory to initial platinum-based therapy and is validated in two independent patient cohorts. “Importantly, instead of looking at individual genes or proteins, we have taken into account mechanisms at the pathway level and meticulously modeled the interactions among proteins within the same pathway,” said Pei Wang, Ph.D. at the Icahn School of Medicine at Mount Sinai, who led the development of the computational prediction model.

We detected a significant association between lack of Ch17 loss-of-heterozygosity and chemo-refractoriness. Based on pathway protein expression, we identified five novel clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

If clinically validated, the predictor of chemo-refractoriness could enable a precision oncology approach by providing a means upfront to identify patients whose tumors will not respond to standard therapy, so that they can be offered alternative treatment options.

MedicalResearch.com: Can you describe in simple terms how your study is novel?

1. This is the first proteogenomic analysis of platinum refractoriness in HGSOC.
2. Using a novel approach leveraging multiple data sources and machine learning tools, we identify a novel 64-protein signature that replicates in 2 independent patient cohorts and detects a subset of refractory cases upfront, at high specificity.
3. We identify a novel association between ch17 LOH and platinum response and show that a novel combined proteogenomic predictor of platinum response is superior to genomic and clinical predictors alone.
4. We identify 5 novel subtypes of HGSOC based on protein pathway expression, possibly reflecting different mechanisms of platinum refractoriness and implicating subtype-specific treatment approaches (e.g., immune therapies, TGFbeta inhibitors, metabolic inhibitors).

MedicalResearch.com: What should readers take away from your report?

1. Protein markers contain useful information beyond genomic markers for distinguishing chemo-refractory vs -sensitive HGSOC.
2. Refractoriness of HGSOC is driven by heterogeneous mechanisms, and different treatment strategies might be needed for different subtypes of refractory tumors (i.e., personalized oncology).
3. For FFPE samples, for which genomics profiling could sometimes be challenging, proteomic profiling can be performed with high quality.

MedicalResearch.com: What recommendations do you have for future research as a results of this study?

1. Adding proteomics info to genomics might be indispensable for understanding complicated clinical phenotypes.
2. Employing pathway and network-based models may reveal more robust biological signals then modeling individual genes/proteins.
3. “To achieve personalized oncology, Nextgen diagnostics must move beyond single gene and single protein biomarkers. Predicting complex clinical phenotypes will likely require multi-analyte molecular panels coupled with clinical and demographic data in algorithmic-driven patient care,” said Amanda Paulovich, MD, Ph.D., Fred Hutch oncologist, proteomics expert, and Aven Foundation Endowed Chair holder.

MedicalResearch.com: Is there anything else you would like to add? Any disclosures?

Response:       The findings from this study suggest potential protein signatures to:
1. pPredict chemo refractoriness and
2. Identify molecular subtypes among HGSOC.

These tools, once validated, can be used by clinicians to design/employ customized alternative treatments to help patients with chemo-refractory tumors.

Citation:

Chowdhury S, Kennedy JJ, Ivey RG, et al. Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer. Cell. Published online August 3, 2023. doi:10.1016/j.cell.2023.07.004

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Last Updated on August 7, 2023 by Marie Benz