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.

Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets.

Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein-expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium across 11 tumor types, we validate PROTsi's effectiveness in accurately quantifying stem-like features.

Precision proteogenomics reveals pan-cancer impact of germline variants.

We investigate the impact of germline variants on cancer patients' proteomes, encompassing 1,064 individuals across 10 cancer types. We introduced an approach, "precision peptidomics," mapping 337,469 coding germline variants onto peptides from patients' mass spectrometry data, revealing their potential impact on post-translational modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases. We identified rare pathogenic and common germline variants in cancer genes potentially affecting proteomic features, including variants altering protein abundance and structure and variants in kinases (ERBB2 and MAP2K2) impacting phosphorylation.

Proteogenomic characterization of non-functional pancreatic neuroendocrine tumors unravels clinically relevant subgroups.

The majority of neuroendocrine neoplasms in pancreas are non-functional pancreatic neuroendocrine tumors (NF-PanNETs), which exhibit a high occurrence of distant metastases with limited therapeutic options. Here, we perform a comprehensive molecular characterization of 108 NF-PanNETs through integrative analysis of genomic, transcriptomic, proteomic, and phosphoproteomic profiles. Proteogenomic analysis provides functional insights into the genomic driver alterations of NF-PanNETs, revealing a potential mediator of MEN1 alterations using Men1-conditional knockout mice.

Integrated multi-omics analyses of oral squamous cell carcinoma reveal precision patient stratification and personalized treatment strategies.

Oral cavity squamous cell carcinoma (OSCC), a leading subtype of head and neck cancer, exhibits high global incidence and mortality rates. Despite advancements in surgery and radiochemotherapy, approximately one-third of patients experience relapse. To improve current targeted and immunotherapy strategies for recurrent OSCC, we conducted multi-omics analyses on pretreatment OSCC samples (cohorts 1 and 2, n = 137) and identified A3A and EGFR, both at the RNA and protein levels, as inversely expressed markers for patient stratification and response prediction.

A proteogenomic analysis of cervical cancer reveals therapeutic and biological insights.

Although the incidence of cervical cancer (CC) has been reduced in high-income countries due to human papillomavirus (HPV) vaccination and screening strategies, it remains a significant public health issue that poses a threat to women's health in low-income countries. Here, we perform a comprehensive proteogenomic profiling of CC tumors obtained from 139 Chinese women. Integrated proteogenomic analysis links genetic aberrations to downstream pathogenesis-related pathways and reveals the landscape of HPV-associated multi-omic changes.

Urinary Metabolite Diagnostic and Prognostic Liquid Biopsy Biomarkers of Lung Cancer in Nonsmokers and Tobacco Smokers.

Purpose: Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT).

Experimental Design: Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort).

Comprehensive proteogenomic characterization of rare kidney tumors.

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes.

Acidovorax temperans skews neutrophil maturation and polarizes Th17 cells to promote lung adenocarcinoma development.

Change within the intratumoral microbiome is a common feature in lung and other cancers and may influence inflammation and immunity in the tumor microenvironment, affecting growth and metastases. We previously characterized the lung cancer microbiome in patients and identified Acidovorax temperans as enriched in tumors. Here, we instilled A.

Frozen tissue coring and layered histological analysis improves cell type-specific proteogenomic characterization of pancreatic adenocarcinoma.

Background: Omics characterization of pancreatic adenocarcinoma tissue is complicated by the highly heterogeneous and mixed populations of cells. We evaluate the feasibility and potential benefit of using a coring method to enrich specific regions from bulk tissue and then perform proteogenomic analyses.

Methods: We used the Biopsy Trifecta Extraction (BioTExt) technique to isolate cores of epithelial-enriched and stroma-enriched tissue from pancreatic tumor and adjacent tissue blocks.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies.

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified.

Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs.

Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles.

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.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases.

Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma.

Background: The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Unlabelled: Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications.