NF1-depleted ER breast cancers are differentially sensitive to CDK4/6 inhibitors.

Neurofibromin/NF1 is a RAS (rat sarcoma virus) GTPase-activating protein and estrogen receptor (ER) transcriptional corepressor. NF1 status, identified by copy number loss or low mRNA/protein expression, is associated with endocrine therapy resistance in ~20% of ER/HER2 (human epidermal growth factor receptor 2) early-stage breast cancers. The identification of targeted treatments for NF1 ER/HER2 breast cancer is therefore a priority.

Proteogenomic characterization unveils biomarkers associated with chemoresistance in muscle-invasive bladder cancer.

To explore potential chemoresistance mechanisms and identify therapeutic opportunities in muscle-invasive bladder cancer (MIBC), we conduct comprehensive proteogenomic characterization of 46 pre- and 14 post-treatment MIBC tumors incorporating genomics, transcriptomics, proteomics, and phosphoproteomics. Multi-omics clustering not only recapitulated established molecular subtypes but also revealed subtypes associated with chemotherapy sensitivity. Protein isoform level analysis identifies protein abundance of a short isoform of ATAD1 and RAF family proteins as biomarkers of chemosensitivity.

Integrative analysis of lung adenocarcinoma across diverse ethnicities and exposures.

Lung adenocarcinomas (LUAD) are a pressing global health problem with enduring lethality and rapidly shifting epidemiology. Proteogenomic studies integrating proteomics and post-translational modifications with genomics can identify clinical strata and oncogenic mechanisms, but have been underpowered to examine effects of ethnicity, smoking and environmental exposures, or sex on this heterogeneous disease. This comprehensive proteogenomic analysis of LUAD tumors and matched normal adjacent tissues from 406 patients across diverse geographic and demographic backgrounds explores the impact of understudied driver mutations, prognostic role of chromosomal instability, patterns of immune signaling, differential and sex-specific effects of endogenous mutagens and environmental carcinogens, and pathobiology of early-stage tumors with "late-like" characteristics.

Proteogenomic analysis of the CALGB 40601 (Alliance) HER2+ breast cancer neoadjuvant trial reveals resistance biomarkers.

Proteogenomic analysis is applied to samples from the CALGB 40601 (Alliance) randomized neoadjuvant trial of trastuzumab, lapatinib, or the combination to identify biomarkers associated with pathological response status. Absence of ERBB2 gene amplification and human epidermal growth factor receptor 2 (HER2) protein overexpression by proteogenomics is associated with non-pathological compete response (pCR) (p < 0.05), highlighting potential false positives from standard diagnostics.

Comprehensive evaluation of phosphoproteomic-based kinase activity inference.

Kinases regulate cellular processes and are essential for understanding cellular function and disease. To investigate the regulatory state of a kinase, numerous methods have been developed to infer kinase activities from phosphoproteomics data using kinase-substrate libraries. However, few phosphorylation sites can be attributed to an upstream kinase in these libraries, limiting the scope of kinase activity inference.

ZP4: A novel target for CAR-T cell therapy in triple negative breast cancer.

Triple-negative breast cancer (TNBC) remains one of the most challenging subtypes of breast cancer to treat due to a lack of effective targeted therapies. Chimeric antigen receptor (CAR)-T cells hold promise, but their efficacy in solid tumors is often limited by on-target/off-tumor toxicities. Through comprehensive bioinformatic analysis of public RNA and proteomic data, we identified zona pellucida glycoprotein 4 (ZP4) as a novel target for TNBC.

Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses.

Combination chemotherapy remains essential for clinical management of triple-negative breast cancer (TNBC). Consequently, responses to multiple single agents cannot be delineated at the single patient level, even though some patients might not require all drugs in the combination. Herein, we conduct multi-omic analyses of orthotopic TNBC patient-derived xenografts (PDXs) treated with single agent carboplatin, docetaxel, or the combination.

Pan-cancer proteogenomics expands the landscape of therapeutic targets.

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation.

PKMYT1 Is a Marker of Treatment Response and a Therapeutic Target for CDK4/6 Inhibitor-Resistance in ER+ Breast Cancer.

Endocrine therapies (ET) with cyclin-dependent kinase 4/6 (CDK4/6) inhibition are the standard treatment for estrogen receptor-α-positive (ER+) breast cancer, however drug resistance is common. In this study, proteogenomic analyses of patient-derived xenografts (PDXs) from patients with 22 ER+ breast cancer demonstrated that protein kinase, membrane-associated tyrosine/threonine one (PKMYT1), a WEE1 homolog, is estradiol (E2) regulated in E2-dependent PDXs and constitutively expressed when growth is E2-independent. In clinical samples, high PKMYT1 mRNA levels associated with resistance to both ET and CDK4/6 inhibition.

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics.

ClinicalOmicsDB: exploring molecular associations of oncology drug responses in clinical trials.

Matching patients to optimal treatment is challenging, in part due to the limited availability of real-world clinical datasets for predictive biomarker identification. The growing integration of omics profiling into clinical trials presents a new opportunity to tackle this challenge. Here, we introduce ClinicalOmicsDB, a web application for exploring molecular associations of oncology drug responses in clinical trials.

A proteogenomics data-driven knowledge base of human cancer.

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages.

Kinase Inhibitor Pulldown Assay Identifies a Chemotherapy Response Signature in Triple-negative Breast Cancer Based on Purine-binding Proteins.

Unlabelled: Triple-negative breast cancer (TNBC) constitutes 10%-15% of all breast tumors. The current standard of care is multiagent chemotherapy, which is effective in only a subset of patients. The original objective of this study was to deploy a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) to identify kinases elevated in non-pCR (pathologic complete response) cases for therapeutic targeting.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity.

Proteogenomic Approaches for the Identification of NF1/Neurofibromin-depleted Estrogen Receptor-positive Breast Cancers for Targeted Treatment.

Unlabelled: NF1 is a key tumor suppressor that represses both RAS and estrogen receptor-α (ER) signaling in breast cancer. Blocking both pathways by fulvestrant (F), a selective ER degrader, together with binimetinib (B), a MEK inhibitor, promotes tumor regression in NF1-depleted ER models. We aimed to establish approaches to determine how NF1 protein levels impact B+F treatment response to improve our ability to identify B+F sensitive tumors.

Molecular portraits of cell cycle checkpoint kinases in cancer evolution, progression, and treatment responsiveness.

Cell cycle dysregulation is prerequisite for cancer formation. However, it is unknown whether the mode of dysregulation affects disease characteristics. Here, we conduct comprehensive analyses of cell cycle checkpoint dysregulation using patient data and experimental investigations.

The Breast Cancer Proteome and Precision Oncology.

The goal of precision oncology is to translate the molecular features of cancer into predictive and prognostic tests that can be used to individualize treatment leading to improved outcomes and decreased toxicity. Success for this strategy in breast cancer is exemplified by efficacy of trastuzumab in tumors overexpressing ERBB2 and endocrine therapy for tumors that are estrogen receptor positive. However, other effective treatments, including chemotherapy, immune checkpoint inhibitors, and CDK4/6 inhibitors are not associated with strong predictive biomarkers.

Kinome Reprogramming Is a Targetable Vulnerability in ESR1 Fusion-Driven Breast Cancer.

Unlabelled: Transcriptionally active ESR1 fusions (ESR1-TAF) are a potent cause of breast cancer endocrine therapy (ET) resistance. ESR1-TAFs are not directly druggable because the C-terminal estrogen/anti-estrogen-binding domain is replaced with translocated in-frame partner gene sequences that confer constitutive transactivation. To discover alternative treatments, a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) was deployed to identify druggable kinases that are upregulated by diverse ESR1-TAFs.

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach.

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response.

Elevated NRAS expression during DCIS is a potential driver for progression to basal-like properties and local invasiveness.

Background: Ductal carcinoma in situ (DCIS) is the most common type of in situ premalignant breast cancers. What drives DCIS to invasive breast cancer is unclear. Basal-like invasive breast cancers are aggressive.