ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data.

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling.

BACKGROUND: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics. METHODS: Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor. RESULTS: LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ). CONCLUSIONS: Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

Brain proteomic atlas of alcohol use disorder in adult males.

Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABAB receptor and opioid receptors and may lead to the identification of other potential targets. These results improve our understanding of the molecular alterations of AUD across brain regions that are associated with the development and maintenance of AUD. Proteomic data from this study is publicly available at www.lmdomics.org/AUDBrainProteomeAtlas/ .

Cellular Immunotherapy in Mice Prevents Maternal Hypertension and Restores Anti-Inflammatory Cytokine Balance in Maternal and Fetal Tissues.

Preeclampsia is the leading cause of maternal-fetal morbidity worldwide. The concept that persistent feto-placental intolerance is important in the pathogenesis of preeclampsia (PreE) has been demonstrated by our lab and others. Arginine vasopressin (AVP) infusion during pregnancy induces cardiovascular, renal, and T helper (TH) cell alterations in mice consistent with human PreE. In addition to their conventional immuno-stimulatory role, dendritic cells (DCs) also play a vital role in immune tolerance. In contrast to conventional DCs, regulatory DCs (DCregs) express low levels of co-stimulatory markers, produce anti-inflammatory cytokines, induce T regulatory (Treg) cells, and promote tolerance. In mice, DCregs prevent pro-inflammatory responses and induce antigen-specific tolerance. Given these known functions of DCregs, we hypothesize that DCregs will prevent the development of AVP-induced PreE in mice. C57BL/6J females were infused with AVP (24 ng/h) or saline throughout gestation via an osmotic minipump. Bone-marrow-derived DCregs were injected into AVP-infused dams at the time of the pump implantation or on gestational day (GD) 7. The blood pressure of the mice was taken throughout their pregnancy. The maternal urine proteins and TH-associated cytokines in maternal and fetal tissues were measured on GD 18. The treatment with DCregs effectively prevented the elevation of maternal blood pressure, proteinuria, and fetal growth restriction that were observed in AVP-infused dams. Furthermore, we noted a reduction in the pro-inflammatory TH-associated cytokines IFNγ and IL-17, while anti-inflammatory cytokines IL-4, IL-10, and TGFß showed an increase following DCreg treatment. These outcomes provide strong evidence supporting the potential of DCregs as a valuable therapeutic approach in addressing PreE.

Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients.

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

Jupiter microtubule-associated homolog 1 (JPT1): A predictive and pharmacodynamic biomarker of metformin response in endometrial cancers.

Preoperative use of metformin in obese women with endometrioid endometrial cancer (EEC) reduces tumor proliferation and inhibits the mammalian target of rapamycin pathway, though is only effective in select cases. This study sought to identify a predictive and/or pharmacodynamic proteomic signature of metformin response to tailor its pharmacologic use. Matched pre- and post-metformin-treated tumor tissues from a recently completed preoperative window trial of metformin in EEC patients (ClinicalTrials.gov: NCT01911247) were analyzed by mass spectrometry (MS)-based proteomic and immunohistochemical analyses. Jupiter microtubule-associated homolog 1 (JPT1) was significantly elevated in metformin responders (n = 13) vs nonresponders (n = 7), and found to decrease in abundance in metformin responders following treatment; observations that were verified by immunohistochemical staining for JPT1. Metformin response and loss of JPT1 were assessed in RL95-2 and ACI-181 endometrial cancer (EC) cell lines. We further identified that silencing of JPT1 abundance does not alter cellular response to metformin or basal cell proliferation, but that JPT1 abundance does decrease in response to metformin treatment in RL95-2 and ACI-181 EC cell lines. These data suggest that JPT1 represents a predictive and pharmacodynamic biomarker of metformin response that, if validated in larger patient populations, may enable preoperative EEC patient stratification to metformin treatment and the ability to monitor patient response.