Abstract 2325: NUWA-ms: A network-based method to infer quantification of missing proteins using multi-cohort proteomics profiles

Abstract Although mass spectrometry is powerful for proteomic quantification, the inherent issue of missing values remains a significant challenge. We found a prevalent lack of quantification of valuable proteins (e.g., immune cell markers and drug targets) in published datasets, limiting the functional utilities of quantitative proteomic profiles. This was exemplified by the substantial lack of quantification of immune cell marker, which impede the dissection of tissue-infiltrating immune cells by deconvolution analysis of cancer proteomic profiles. Thus, we introduce a network-based method NUWA-ms for robust abundance inference of missing proteins using multi-cohort proteomic profiles. By evaluating 561 tumors with paired proteomic and transcriptomic profiles, a significant improvement of deconvolution performance was shown with the aid of NUWA-ms. This was further validated by the comparison between scRNA-seq and proteomic analyses of a same gastric cancer tumor tissue. NUWA-ms applications to cancer proteomic profiles facilitated the inference of CD8+ T cell markers and effector proteins, enabling the associations of CD8+ T cell infiltration with MSI status in colorectal cancer and anti-PD-1 therapy response in melanoma. These findings demonstrated the utilities of NUWA-ms in depicting infiltrating lymphocytes in the tumor microenvironment using proteomic profiles. Furthermore, based on the proteomic profiles of six patient-derived tumor organoids (PDOs), NUWA-ms application helped identifying PDOs sensitive to a targeted therapeutic agent including the ones neglected by the raw MS quantification, and aided in revealing the resistant mechanism. Together, NUWA-ms could enable a robust inference of protein abundance, to help identifying protein biomarkers and therapeutic targets for cancer and other complex diseases. Citation Format: Lihua Cao, Yuhao Xie, Jiale Chen, Man Wang, Tingting Zhao, Heli Yang, Yang Du, Yang Yang, Zhaode Bu, Jiafu Ji, Jianmin Wu. NUWA-ms: A network-based method to infer quantification of missing proteins using multi-cohort proteomics profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2325.