Abstract
BackgroundProteomic characterization of cancers is essential for a comprehensive understanding of key molecular aberrations. However, proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches.MethodsWe present a proteomic landscape of 16 major types of human cancer, based on the analysis of 126 treatment-naïve primary tumor tissues, 94 tumor-matched normal adjacent tissues, and 12 normal tissues, using mass spectrometry-based data-independent acquisition approach.ResultsIn our study, a total of 8527 proteins were mapped to brain, head and neck, breast, lung (both small cell and non-small cell lung cancers), esophagus, stomach, pancreas, liver, colon, kidney, bladder, prostate, uterus and ovary cancers, including 2458 tissue-enriched proteins. Our DIA-based proteomic approach has characterized major human cancers and identified universally expressed proteins as well as tissue-type-specific and cancer-type-specific proteins. In addition, 1139 therapeutic targetable proteins and 21 cancer/testis (CT) antigens were observed.ConclusionsOur discoveries not only advance our understanding of human cancers, but also have implications for the design of future large-scale cancer proteomic studies to assist the development of diagnostic and/or therapeutic targets in multiple cancers.
Highlights
Great efforts have been made to construct a comprehensive genomic landscape of human cancers using largescale genomic data [1, 2]
To perform the quantitative proteomic analysis, data-independent acquisition (DIA) raw files of all the samples were searched against a customized spectral library constructed using DIA data of individual samples combined with dependent acquisition (DDA) data from the Human Proteome Map and quantified via Spectronaut
Besides DEAD-box helicase 27 (DDX27) and PLOD2, we found members of minichromosomal maintenance (MCM) superfamily, MCM2, MCM4 and MCM6, were up-regulated across diverse cancer types (Additional file 1: Figure S5) suggesting possible dysregulation in DNA replication and proliferation of cancer cells [43], which might contribute to the development of tumors in these cancer types
Summary
Great efforts have been made to construct a comprehensive genomic landscape of human cancers using largescale genomic data [1, 2]. These studies, the Cancer Genome Atlas (TCGA) project, focus on the discovery of the cellular origin and oncogenic processes of cancers [3,4,5,6]. Proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call