Precision oncology can use the unique genetic landscape of your cancer cells and specific protein expression profiles to inform on which therapy is best to treat your cancer. This approach is primarily useful for difficult-to-treat cancers that are resistant to first-line chemotherapies prior to initial treatment. The integrative use of genetic, RNA, and protein profiles to hone the therapeutic plan for chemo-refractory high grade serious ovarian cancer (HGSOC) was employed by Dr. Amanda Paulovich, Aven Foundation Endowed Chair and Professor in the Translational Sciences and Therapeutics Division at Fred Hutchinson Cancer Center, her lab, and colleagues including co-corresponding authors Drs. Pei Wang and Michael Birrer from Icahn School of Medicine at Mount Sinai and Winthrop P. Rockefeller Cancer Institute, respectively. This work was published recently in Cell.
The challenges of ineffective therapies and poor outcomes for patients diagnosed with chemo-refractory HGSOC have not changed in 40 years. A primary barrier to treating these cancers is that 10-20% of patients fail to respond to first line platinum-based chemotherapies. “Without a way to distinguish refractory from sensitive HGSOC before treatment, many patients face chemotherapy's toxicity with no benefit,” explained Dr. Paulovich. “Rapid disease progression excludes them from clinical trials, hindering research on effective therapies.” These issues call for a new approach to classify subtypes of HGSOC specifically based on tumor sensitivity or resistance to first line chemotherapies.
With their combined expertise, this team of researchers sought to answer if combined genetic and protein expression profiles of tumors could shed light on 1) the chemo-responsiveness of HGSOC to first line platinum-based chemotherapy and 2) identify potential therapeutic targets for these formidable tumors. Excitingly, their efforts yield profound results. Using their proteomic data, the team identified a 64-protein signature encompassing metabolic, hypoxia, and NF-κB pathways that together were associated with refractory tumors (tumors that do not respond to chemotherapy).
Next, they trained an ensemble prediction model on this 64-protein signature of refractory tumors using machine learning algorithms and validated the model in independent patient cohorts. They were able to detect a subset of 35-40% refractory high-grade serous ovarian cancers with 98% specificity. The team also identified five sub-clusters of ovarian cancers resistant to chemotherapy based on these analyses, and these associations were replicated in two independent patient cohorts as well as in patient-derived xenograft models of ovarian cancer. Their integrative approach that highlighted several cellular processes related to refractory tumors (e.g., metabolism, immune infiltration, TGF-beta, cell cycle, and translation) provides insight into which processes should be targeted with therapeutic interventions. Yet, “there’s no single mechanism that all cancer cells use to become resistant to platinum,” shared Dr. Paulovich. “We believe these clusters represent different mechanisms of chemo-refractoriness and may implicate different therapeutic vulnerabilities for the molecular subtypes of ovarian cancer.” Binning HGSOC tumors into the five subtypes discovered by these researchers will guide the use of precision oncology approaches to target tumor-specific vulnerabilities for each patient.
Instead of finding a single protein or pathway, the researchers discovered that the chemo-resistance phenotypes of these cancers have a complex landscape. Dr. Paulovich shared that two clinical-grade assays for HGSOC are currently under development and may help address these complexities. One assay will predict the likelihood of resistance to chemotherapy, and another will subtype the patient’s tumor based on its molecular characteristics. These new tools to better characterize each patient’s tumor will lead to improved outcomes by identifying new treatment approaches and performing better matching of patients with therapies. These studies highlight the importance of studying combined genome, RNA, and protein landscapes of cells to inform on complex phenotypes in cancer and their implementation in precision oncology treatment-based approaches.
The spotlighted research was funded by the National Cancer Institute and the Aven Foundation.
Fred Hutch/University of Washington/Seattle Children's Cancer Consortium member Amanda Paulovich contributed to this work.
Chowdhury S, Kennedy JJ, Ivey RG, Murillo OD, Hosseini N, Song X, Petralia F, Calinawan A, Savage SR, Berry AB, Reva B, Ozbek U, Krek A, Ma W, da Veiga Leprevost F, Ji J, Yoo S, Lin C, Voytovich UJ, Huang Y, Lee SH, Bergan L, Lorentzen TD, Mesri M, Rodriguez H, Hoofnagle AN, Herbert ZT, Nesvizhskii AI, Zhang B, Whiteaker JR, Fenyo D, McKerrow W, Wang J, Schürer SC, Stathias V, Chen XS, Barcellos-Hoff MH, Starr TK, Winterhoff BJ, Nelson AC, Mok SC, Kaufmann SH, Drescher C, Cieslik M, Wang P, Birrer MJ, Paulovich AG. 2023. Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer. Cell. 186(16):3476-3498.e35.