Background: Discovery of oncogenic mutations as targets for cancer therapy revolutionized treatment of GIST and other cancers. However, nearly all patients ultimately progress, which emphasizes the need for development of new tools to assess cancer prognosis and factors associated with benefit of cancer therapies. Altered metabolism is a hallmark of cancer, enabling tumors to proliferate, survive and metastasize. By measuring the complete set of metabolites in an individual (metabolome) it is possible to identify biomarkers that correlate with disease status, prognosis, and therapeutic response. Methods: We performed untargeted NMR and MS-based machine learning metabolomic analysis (Olaris, Waltham, MA) of serial plasma samples collected at baseline and during experimental systemic therapies in 39 patients with advanced/metastatic GIST. Results were compared to clinical outcomes. Results: In serial plasma samples from 39 patients with advanced/metastatic GIST using untargeted NMR and MS-based machine learning (ML) metabolomic analysis, we identified metabolic signatures to build Biomarker-of-Response (BoR) ML models that could accurately differentiate patients with response, intrinsic and adaptive resistance to experimental systemic therapies. The BoR ML model also correlated with tumor growth or tumor reduction in patients with response, intrinsic and adaptive resistance. Finally, we identified metabolic pathways associated with response and resistance. Conclusions: Comprehensive metabolomic profiling of serially collected plasma is feasible and detects metabolic signatures associated with therapeutic response in advanced GIST. Citation Format: Chandrashekhar Honrao, Srihari Raghavendra Rao, Nathalie Teissier, S. Greg Call, Elizabeth M. ODay, Filip Janku. Plasma based metabolic profiling in metastatic gastrointestinal stromal tumors (GIST) [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 LB031.
Background: CDK4/6 inhibitors (CDK4/6i) palbociclib (palbo) and abemaciclib (abema) have significantly improved outcomes in patients with hormonal receptor positive (HR+)/human epidermal growth factor receptor negative (HER2-) breast cancer. Yet almost 20% of patients never respond to treatment and all patients eventually develop acquired resistance. In vitro palbo and abema have different affinities for CDK4/6 and other cellular kinases, and in vivo they have different toxicity profiles. At present there are no clinically validated biomarkers to determine CDK4/6i sensitivity or resistance. Further it is not clear if and how to choose between the CDK4/6i for optimal outcomes. In this study, using 13C-isotopically enriched glucose we sought to identify metabolic changes associated with palbo and abema treatment in sensitive and resistant cell lines. Methods: MCF-7 cells (wild-type), palbociclib resistant cells (PDR) and abemaciclib resistant cells (ABR) treated with DMSO, palbo or abema were incubated for 24hrs in DMEM supplemented with 13C-glucose. After the incubation, cells were harvested, metabolites were extracted and analyzed via 1D and 2D NMR spectroscopy. Biological triplicates were prepared for each condition. Results: In wild-type MCF-7 cells treated with palbo or abema significant metabolite changes were observed compared to DMSO. In both palbo and abema treatment a marked decrease in nucleotide metabolites was observed, which is consistent with the ability of CDK4/6i to prevent cell cycle progression. In abema treated cells there was also significant decrease in metabolites involved in the serine-glycine pathway, which was not observed in the palbo treated cells. Palbo and abema treated cells were easily distinguishable via hierarchical clustering. PDR and ABR also had distinct metabolic profiles when they were maintained with palbo and abema, respectively or if the drugs were removed. Notably the serine-glycine pathway was increased in ABR cells but decreased in PDR cells. In PDR cells we observed an increase in glucose-1-phosphate and shift towards galactose/glycogen metabolism. Conclusions: Using cell line models we were able to demonstrate that glucose metabolism is altered in palbo and abema treatment and that resistance to each drug may activate different metabolic pathways. To the best of our knowledge this is the first direct evidence of palbo-specific and abema-specific metabolite signatures. We are assessing whether the results of these in vitro studies translate to clinical samples. If so, the altered metabolites could lead to biomarkers that correlate with response and resistance for specific CDK4/6i. Further, we are exploring if by targeting the pathways associated with resistance, we can restore CDK4/6i sensitivity. This could lead to novel therapeutic targets or treatment regimens that improve patient outcomes. Citation Format: Chandrashekhar Honrao, Kanchan Sonkar, Cristina Guarducci, Agostina Nardone, Wen Ma, Srihari Raghavendra Rao, Chen Dong, Leo Rodrigues, Rinath Jeselsohn, Elizabeth O'Day. Isotopic tracing reveals distinct metabolic changes with palbociclib or abemaciclib treatment & resistance in breast cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5802.
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