Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

A proteogenomic portrait of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Avant-garde: an automated data-driven DIA data curation tool.

Several challenges remain in data-independent acquisition (DIA) data analysis, such as to confidently identify peptides, define integration boundaries, remove interferences, and control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. We present Avant-garde as a tool to refine DIA (and parallel reaction monitoring) data. Avant-garde uses a novel data-driven scoring strategy: signals are refined by learning from the dataset itself, using all measurements in all samples to achieve the best optimization. We evaluate the performance of Avant-garde using benchmark DIA datasets and show that it can determine the quantitative suitability of a peptide peak, and reach the same levels of selectivity, accuracy, and reproducibility as manual validation. Avant-garde is complementary to existing DIA analysis engines and aims to establish a strong foundation for subsequent analysis of quantitative mass spectrometry data.

Biochemical and structural characterization of HDAC8 mutants associated with Cornelia de Lange syndrome spectrum disorders.

Cornelia de Lange Syndrome (CdLS) spectrum disorders are characterized by multiple organ system congenital anomalies that result from mutations in genes encoding core cohesin proteins SMC1A, SMC3, and RAD21, or proteins that regulate cohesin function such as NIPBL and HDAC8. HDAC8 is the Zn(2+)-dependent SMC3 deacetylase required for cohesin recycling during the cell cycle, and 17 different HDAC8 mutants have been identified to date in children diagnosed with CdLS. As part of our continuing studies focusing on aberrant HDAC8 function in CdLS, we now report the preparation and biophysical evaluation of five human HDAC8 mutants: P91L, G117E, H180R, D233G, and G304R. Additionally, the double mutants D233G-Y306F and P91L-Y306F were prepared to enable cocrystallization of intact enzyme-substrate complexes. X-ray crystal structures of G117E, P91L-Y306F, and D233G-Y306F HDAC8 mutants reveal that each CdLS mutation causes structural changes that compromise catalysis and/or thermostability. For example, the D233G mutation disrupts the D233-K202-S276 hydrogen bond network, which stabilizes key tertiary structure interactions, thereby significantly compromising thermostability. Molecular dynamics simulations of H180R and G304R HDAC8 mutants suggest that the bulky arginine side chain of each mutant protrudes into the substrate binding site and also causes active site residue Y306 to fluctuate away from the position required for substrate activation and catalysis. Significantly, the catalytic activities of most mutants can be partially or fully rescued by the activator N-(phenylcarbamothioyl)-benzamide, suggesting that HDAC8 activators may serve as possible leads in the therapeutic management of CdLS.

Causal interactions from proteomic profiles: Molecular data meet pathway knowledge.

We present a computational method to infer causal mechanisms in cell biology by analyzing changes in high-throughput proteomic profiles on the background of prior knowledge captured in biochemical reaction knowledge bases. The method mimics a biologist's traditional approach of explaining changes in data using prior knowledge but does this at the scale of hundreds of thousands of reactions. This is a specific example of how to automate scientific reasoning processes and illustrates the power of mapping from experimental data to prior knowledge via logic programming. The identified mechanisms can explain how experimental and physiological perturbations, propagating in a network of reactions, affect cellular responses and their phenotypic consequences. Causal pathway analysis is a powerful and flexible discovery tool for a wide range of cellular profiling data types and biological questions. The automated causation inference tool, as well as the source code, are freely available at http://causalpath.org.

Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds.

While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics .

Compromised structure and function of HDAC8 mutants identified in Cornelia de Lange Syndrome spectrum disorders.

Cornelia de Lange Syndrome (CdLS) is a multiple congenital anomaly disorder resulting from mutations in genes that encode the core components of the cohesin complex, SMC1A, SMC3, and RAD21, or two of its regulatory proteins, NIPBL and HDAC8. HDAC8 is the human SMC3 lysine deacetylase required for cohesin recycling in the cell cycle. To date, 16 different missense mutations in HDAC8 have recently been identified in children diagnosed with CdLS. To understand the molecular effects of these mutations in causing CdLS and overlapping phenotypes, we have fully characterized the structure and function of five HDAC8 mutants: C153F, A188T, I243N, T311M, and H334R. X-ray crystal structures reveal that each mutation causes local structural changes that compromise catalysis and/or thermostability. For example, the C153F mutation triggers conformational changes that block acetate product release channels, resulting in only 2% residual catalytic activity. In contrast, the H334R mutation causes structural changes in a polypeptide loop distant from the active site and results in 91% residual activity, but the thermostability of this mutant is significantly compromised. Strikingly, the catalytic activity of these mutants can be partially or fully rescued in vitro by the HDAC8 activator N-(phenylcarbamothioyl)benzamide. These results suggest that HDAC8 activators might be useful leads in the search for new therapeutic strategies in managing CdLS.