Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Informations de copyright

Copyright © 2022 Irajizad, Wu, Vykoukal, Murage, Spencer, Dennison, Moulder, Ravenberg, Lim, Litton, Tripathym, Valero, Damodaran, Rauch, Adrada, Candelaria, White, Brewster, Arun, Long, Do, Hanash and Fahrmann.

Déclaration de conflit d'intérêts

Author SM declares honoraria from Novartis, Pfizer and research funding from Oncothyreon (Inst), Pfizer (Inst), Novartis (Inst), Genentech (Inst), Takeda (Inst), Bayer (Inst), EMD Serono (Inst), Genentech (Inst); travel, accommodations, expenses: Novartis, Pfizer. Author JLi declares consulting or advisory role: Pfizer, AstraZeneca, Medivation/Pfizer; speakers' bureau from Physician Education Resource, UpToDate, Med Learning, Group, Medscape; research funding from Novartis (Inst), Bristol-Myers Squibb (Inst), Genentech (Inst), Pfizer (Inst), EMD Serono (Inst), Jounce Therapeutics (Inst), GlaxoSmithKline (Inst), Medivation/Pfizer (Inst); patents, royalties, other intellectual property: UpToDate; travel, accommodations, expenses: Physician Education Resource, Med Learning Group, Medscape. Author DT declares consulting or advisory role: AstraZeneca, Genomic Health, Gilead Sciences Inc, GlaxoSmithKline, Novartis Pharma, OncoPep, Pfizer; research funding: Pfizer, Novartis Pharma. Author VV declares honoraria: Genentec; consulting or advisory role: Genentech; travel, accommodations, expenses: Genentech. Author SD declares honoraria: Novartis; consulting or advisory role: Tempus, Taiho Pharmaceutical, Pfizer; research funding: EMD Serono, Guardant Health; travel, accommodations; expenses: Phillips Gilmore Oncology Communications. Author BAd declares consulting or advisory role: Bright Pink, AbbVie; research funding: AbbVie (Inst), PharmaMar (Inst), AstraZeneca (Inst), InVitae (Inst); travel, accommodations, expenses: AstraZeneca. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.