Multiscale protein networks systematically identify aberrant protein interactions and oncogenic regulators in seven cancer types.

Global proteomic data generated by advanced mass spectrometry (MS) technologies can help bridge the gap between genome/transcriptome and functions and hold great potential in elucidating unbiased functional models of pro-tumorigenic pathways. To this end, we collected the high-throughput, whole-genome MS data and conducted integrative proteomic network analyses of 687 cases across 7 cancer types including breast carcinoma (115 tumor samples; 10,438 genes), clear cell renal carcinoma (100 tumor samples; 9,910 genes), colorectal cancer (91 tumor samples; 7,362 genes), hepatocellular carcinoma (101 tumor samples; 6,478 genes), lung adenocarcinoma (104 tumor samples; 10,967 genes), stomach adenocarcinoma (80 tumor samples; 9,268 genes), and uterine corpus endometrial carcinoma UCEC (96 tumor samples; 10,768 genes). Through the protein co-expression network analysis, we identified co-expressed protein modules enriched for differentially expressed proteins in tumor as disease-associated pathways. Comparison with the respective transcriptome network models revealed proteome-specific cancer subnetworks associated with heme metabolism, DNA repair, spliceosome, oxidative phosphorylation and several oncogenic signaling pathways. Cross-cancer comparison identified highly preserved protein modules showing robust pan-cancer interactions and identified endoplasmic reticulum-associated degradation (ERAD) and N-acetyltransferase activity as the central functional axes. We further utilized these network models to predict pan-cancer protein regulators of disease-associated pathways. The top predicted pan-cancer regulators including RSL1D1, DDX21 and SMC2, were experimentally validated in lung, colon, breast cancer and fetal kidney cells. In summary, this study has developed interpretable network models of cancer proteomes, showcasing their potential in unveiling novel oncogenic regulators, elucidating underlying mechanisms, and identifying new therapeutic targets.

Author Correction: Expression-based drug screening of neural progenitor cells from individuals with schizophrenia.

In the originally published version of this Article, the affiliation details for Eric E. Schadt and Radoslav Savic incorrectly omitted 'Sema4, a Mount Sinai venture, Stamford, Connecticut, USA'. This has been corrected in both the PDF and HTML versions of the Article.

Expression-based drug screening of neural progenitor cells from individuals with schizophrenia.

A lack of biologically relevant screening models hinders the discovery of better treatments for schizophrenia (SZ) and other neuropsychiatric disorders. Here we compare the transcriptional responses of 8 commonly used cancer cell lines (CCLs) directly with that of human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells (NPCs) from 12 individuals with SZ and 12 controls across 135 drugs, generating 4320 unique drug-response transcriptional signatures. We identify those drugs that reverse post-mortem SZ-associated transcriptomic signatures, several of which also differentially regulate neuropsychiatric disease-associated genes in a cell type (hiPSC NPC vs. CCL) and/or a diagnosis (SZ vs. control)-dependent manner. Overall, we describe a proof-of-concept application of transcriptomic drug screening to hiPSC-based models, demonstrating that the drug-induced gene expression differences observed with patient-derived hiPSC NPCs are enriched for SZ biology, thereby revealing a major advantage of incorporating cell type and patient-specific platforms in drug discovery.

Expression of an Mg2+-dependent HIV-1 RNase H construct for drug screening.

A single polypeptide of the HIV-1 reverse transcriptase that reconstituted Mg(2+)-dependent RNase H activity has been made. Using molecular modeling, the construct was designed to encode the p51 subunit joined by a linker to the thumb (T), connection (C), and RNase H (R) domains of p66. This p51-G-TCR construct was purified from the soluble fraction of an Escherichia coli strain, MIC2067(DE3), lacking endogenous RNase HI and HII. The p51-G-TCR RNase H construct displayed Mg(2+)-dependent activity using a fluorescent nonspecific assay and showed the same cleavage pattern as HIV-1 reverse transcriptase (RT) on substrates that mimic the tRNA removal required for second-strand transfer reactions. The mutant E706Q (E478Q in RT) was purified under similar conditions and was not active. The RNase H of the p51-G-TCR RNase H construct and wild type HIV-1 RT had similar K(m)s for an RNA-DNA hybrid substrate and showed similar inhibition kinetics to two known inhibitors of the HIV-1 RT RNase H.