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.

Multiomic analysis of uterine leiomyomas in self-described Black and White women: molecular insights into health disparities.

BACKGROUND: Black women are at an increased risk of developing uterine leiomyomas and experiencing worse disease prognosis than White women. Epidemiologic and molecular factors have been identified as underlying these disparities, but there remains a paucity of deep, multiomic analysis investigating molecular differences in uterine leiomyomas from Black and White patients. OBJECTIVE: To identify molecular alterations within uterine leiomyoma tissues correlating with patient race by multiomic analyses of uterine leiomyomas collected from cohorts of Black and White women. STUDY DESIGN: We performed multiomic analysis of uterine leiomyomas from Black (42) and White (47) women undergoing hysterectomy for symptomatic uterine leiomyomata. In addition, our analysis included the application of orthogonal methods to evaluate fibroid biomechanical properties, such as second harmonic generation microscopy, uniaxial compression testing, and shear-wave ultrasonography analyses. RESULTS: We found a greater proportion of MED12 mutant uterine leiomyomas from Black women (>35% increase; Mann-Whitney U, P<.001). MED12 mutant tumors exhibited an elevated abundance of extracellular matrix proteins, including several collagen isoforms, involved in the regulation of the core matrisome. Histologic analysis of tissue fibrosis using trichrome staining and secondary harmonic generation microscopy confirmed that MED12 mutant tumors are more fibrotic than MED12 wild-type tumors. Using shear-wave ultrasonography in a prospectively collected cohort, Black patients had fibroids that were firmer than White patients, even when similar in size. In addition, these analyses uncovered ancestry-linked expression quantitative trait loci with altered allele frequencies in African and European populations correlating with differential abundance of several proteins in uterine leiomyomas independently of MED12 mutation status, including tetracoidpeptide repeat protein 38. CONCLUSION: Our study shows that Black women have a higher prevalence of uterine leiomyomas harboring mutations in MED12 and that this mutational status correlates with increased tissue fibrosis compared with wild-type uterine leiomyomas. Our study provides insights into molecular alterations correlating with racial disparities in uterine leiomyomas and improves our understanding of the molecular etiology underlying uterine leiomyoma development within these populations.

Metronomic dosing of ovarian cancer cells with the ATR inhibitor AZD6738 leads to loss of CDC25A expression and resistance to ATRi treatment.

OBJECTIVE: ATR kinase inhibitors promote cell killing by inducing replication stress and through potentiation of genotoxic agents in gynecologic cancer cells. To explore mechanisms of acquired resistance to ATRi in ovarian cancer, we characterized ATRi-resistant ovarian cancer cells generated by metronomic dosing with the clinical ATR inhibitor AZD6738. METHODS: ATRi-resistant ovarian cancer cells (OVCAR3 and OV90) were generated by dosing with AZD6738 and assessed for sensitivity to Chk1i (LY2603618), PARPi (Olaparib) and combination with cisplatin or a CDK4/6 inhibitor (Palbociclib). Models were characterized by diverse methods including silencing CDC25A in OV90 cells and assessing impact on ATRi response. Serum proteomic analysis of ATRi-resistant OV90 xenografts was performed to identify circulating biomarker candidates of ATRi-resistance. RESULTS: AZD6738-resistant cell lines are refractory to LY2603618, but not to Olaparib or combinations with cisplatin. Cell cycle analyses showed ATRi-resistant cells exhibit G1/S arrest following AZD6738 treatment. Accordingly, combination with Palbociclib confers resistance to AZD6738. AZD6738-resistant cells exhibit altered abundances of G1/S phase regulatory proteins, including loss of CDC25A in AZD6738-resistant OV90 cells. Silencing of CDC25A in OV90 cells confers resistance to AZD6738. Serum proteomics from AZD6738-resistant OV90 xenografts identified Vitamin D-Binding Protein (GC), Apolipoprotein E (APOE) and A1 (APOA1) as significantly elevated in AZD6738-resistant backgrounds. CONCLUSIONS: We show that metronomic dosing of ovarian cancer cells with AZD6738 results in resistance to ATR/ Chk1 inhibitors, that loss of CDC25A expression represents a mechanism of resistance to ATRi treatment in ovarian cancer cells and identify several circulating biomarker candidates of CDC25A low, AZD6738-resistant ovarian cancer cells.

Integrated multi-omic analysis of low-grade ovarian serous carcinoma collected from short and long-term survivors.

BACKGROUND: Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors. METHODS: Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed. RESULTS: We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets. CONCLUSIONS: This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC.

Proteomic alterations associated with residual disease in neoadjuvant chemotherapy treated ovarian cancer tissues.

BACKGROUND: Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome for high-grade serous ovarian cancer (HGSOC) patients. Treatment of HGSOC patients with neoadjuvant chemotherapy, however, may select for tumor cells harboring alterations in hallmark cancer pathways including metastatic potential. This study assessed this hypothesis by performing proteomic analysis of matched, chemotherapy naïve and neoadjuvant chemotherapy (NACT)-treated HGSOC tumors obtained from patients who had suboptimal (R1, n = 6) versus optimal (R0, n = 14) debulking at interval debulking surgery (IDS). METHODS: Tumor epithelium was harvested by laser microdissection from formalin-fixed, paraffin-embedded tissues from matched, pre- and post-NACT treated tumors for twenty HGSOC patients and analyzed by quantitative mass spectrometry-based proteomics. RESULTS: Differential analysis of patient matched pre- and post-NACT treated tumors revealed proteins associated with cell survival and metabolic signaling to be significantly altered in post-NACT treated tumor cells. Comparison of pre-NACT treated tumors from suboptimal (R1) versus optimally (R0) debulked patients identified proteins associated with tumor cell viability and invasion signaling enriched in R1 patients. We identified five proteins altered between R1 and R0 patients in pre- NACT treated tumors that significantly correlated with PFS in an independent cohort of HGSOC patients, including Fermitin family homolog 2 (FERMT2), a protein elevated in R1 that correlated with disease progression in HGSOC patients (multivariate Cox HR = 1.65, Wald p = 0.022) and increased metastatic potential in solid-tumor malignancies. CONCLUSIONS: This study identified distinct proteome profiles in patient matched pre- and post-NACT HGSOC tumors that correlate with NACT resistance and that may predict residual disease status at IDS that collectively warrant further pre-clinical investigation.

CYPOR is a novel and independent prognostic biomarker of recurrence-free survival in triple-negative breast cancer patients.

Prognostic and predictive biomarkers of disease and treatment outcome are needed to ensure optimal treatment of patients with triple-negative breast cancer (TNBC). In a mass spectrometry-based global proteomic study of 44 formalin-fixed, paraffin-embedded (FFPE) primary TNBC tumors and 10 corresponding metastases, we found that Cytochrome P450 reductase (CYPOR) expression correlated with patient outcome. The correlation between CYPOR expression and outcome was further evaluated in a Danish cohort of 113 TNBC patients using immunohistochemistry and publicly available gene expression data from two cohorts of TNBC and basal-like breast cancer patients, respectively (N = 249 and N = 580). A significant correlation between high CYPOR gene expression and shorter recurrence-free survival (RFS), but not overall survival, was found in the cohort of 249 TNBC patients (p = 0.018, HR = 1.77, 95% CI 1.1-2.85), and this correlation was recapitulated in a cohort of 580 basal-like breast cancer patients (p = 0.018, HR = 1.4, 95% CI 1.06-1.86). High CYPOR protein expression was also associated with shorter RFS in the cohort of 113 TNBC patients (p = 0.017, HR = 2.73, 95% CI 1.20-6.19), particularly those who were lymph node tumor-negative (p = 0.029, HR = 5.22). Multivariate Cox regression analysis identified CYPOR as an independent prognostic factor for shorter RFS in TNBC patients (p = 0.032, HR = 2.19, 95% CI 1.07-4.47). Together, these data suggest high expression of CYPOR as an independent prognostic biomarker of shorter RFS, which could be used to identify patients who should receive more extensive adjuvant treatment and more aggressive surveillance.

Biomarker panel for early detection of endometrial cancer in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial.

BACKGROUND: Endometrial cancer is the most common gynecological cancer in the United States. However, no early detection test exists for asymptomatic women at average risk for endometrial cancer. OBJECTIVE: We sought to identify early detection biomarkers for endometrial cancer using prediagnostic serum. STUDY DESIGN: We performed a nested case-control study of postmenopausal women in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial (n = 78,216), including 112 incident endometrial cancer cases and 112 controls. Prediagnostic serum was immunodepleted of high-abundance proteins and digested with sequencing grade porcine trypsin via pressure cycling technology. Quantitative proteomics and phosphoproteomics was performed using high-resolution liquid chromatography-tandem mass spectrometry and highly multiplexed isobaric mass tag combined with basic reversed-phase liquid chromatography. A set of proteins able to predict cancer status was identified with an integrated score assessed by receiver-operator curve analysis. RESULTS: Mean time from blood draw to endometrial cancer diagnosis was 3.5 years (SD, 1.9 years). There were 47 differentially abundant proteins between cases and controls (P < .05). Protein alterations with high predictive potential were selected by regression analysis and compiled into an aggregate score to determine the ability to predict endometrial cancer. An integrated risk score of 6 proteins was directly related to disease incidence in cases with blood draw ≤2 years, >2 years to ≤5 years or >5 years prior to cancer diagnosis. The integrated score distinguished cases from controls with an area under the curve of 0.80 (95% confidence interval, 0.72-0.88). CONCLUSION: An integrated score of 6 proteins using prediagnostic serum from the Prostate, Lung, Colorectal, and Ovarian cancer screening trial distinguishes postmenopausal endometrial cancer cases from controls. Validation is needed to evaluate whether this test can improve prediction or detection of endometrial cancer among postmenopausal women.

Therapeutic and prognostic significance of PARP-1 in advanced mycosis fungoides and Sezary syndrome.

While mycosis fungoides (MF) is typically an indolent malignancy, it may infrequently undertake an aggressive course. We used proteomic analyses to identify a biomarker of the aggressive course of MF. Results of this investigation demonstrated that PARP-1, heat-shock protein family A (Hsp70) member 1 like (HSAP1L), Hsp70 member 1A (HSPA1A), ATP-depending RNA helicase (DDX17) and the α-isoform of lamina-associated polypeptide 2 (TMPO) had higher expression in aggressive disease versus non-aggressive. Moreover, PARP-1 was overexpressed in patients with early stage of MF who developed later an aggressive disease. PARP-1 was evaluated as a new target for therapy, demonstrating the selective dose-dependent cytotoxic effect of PARP inhibitors on Sézary cells in comparison with non-malignant lymphocytes. In conclusion, we believe that PARP-1 may serve not only as a biomarker at initial biopsies for a disease that may become aggressive but also as a new therapeutic target of advanced MF and Sézary syndrome.

Race-specific molecular alterations correlate with differential outcomes for black and white endometrioid endometrial cancer patients.

BACKGROUND: The objective of this study was to identify molecular alterations associated with disease outcomes for white and black patients with endometrioid endometrial cancer (EEC). METHODS: EEC samples from black (n = 17) and white patients (n = 13) were analyzed by proteomics (liquid chromatography-tandem mass spectrometry) and transcriptomics (RNA-seq). Coordinate alterations were validated with RNA-seq data from black (n = 49) and white patients (n = 216). Concordantly altered candidates were further tested for associations with race-specific progression-free survival (PFS) in black (n = 64) or white patients (n = 267) via univariate and multivariate Cox regression modeling and log-rank testing. RESULTS: Discovery analyses revealed significantly altered candidate proteins and transcripts between black and white patients, suggesting modulation of tumor cell viability in black patients and cell death signaling in black and white patients. Eighty-nine candidates were validated as altered between these patient cohorts, and a subset significantly correlated with differential PFS. White-specific PFS candidates included serpin family A member 4 (SERPINA4; hazard ratio [HR], 0.89; Wald P value = .02), integrin subunit α3 (ITGA3; HR, 0.76; P = .03), and Bet1 Golgi vesicular membrane trafficking protein like (BET1L; HR, 0.48; P = .04). Black-specific PFS candidates included family with sequence similarity 228 member B (FAM228B; HR, 0.13; P = .001) and HEAT repeat containing 6 (HEATR6; HR, 4.94; P = .047). Several candidates were also associated with overall survival (SERPINA4 and ITGA3) as well as PFS independent of disease stage, grade and myometrial invasion (SERPINA4, BET1L and FAM228B). CONCLUSIONS: This study has identified and validated molecular alterations in tumors from black and white EEC patients, including candidates significantly associated with altered disease outcomes within these patient cohorts. Cancer 2017;123:4004-12. © 2017 American Cancer Society.

The assembly of miRNA-mRNA-protein regulatory networks using high-throughput expression data.

MOTIVATION: Inference of gene regulatory networks from high throughput measurement of gene and protein expression is particularly attractive because it allows the simultaneous discovery of interactive molecular signals for numerous genes and proteins at a relatively low cost. RESULTS: We developed two score-based local causal learning algorithms that utilized the Markov blanket search to identify direct regulators of target mRNAs and proteins. These two algorithms were specifically designed for integrated high throughput RNA and protein data. Simulation study showed that these algorithms outperformed other state-of-the-art gene regulatory network learning algorithms. We also generated integrated miRNA, mRNA, and protein expression data based on high throughput analysis of primary trophoblasts, derived from term human placenta and cultured under standard or hypoxic conditions. We applied the new algorithms to these data and identified gene regulatory networks for a set of trophoblastic proteins found to be differentially expressed under the specified culture conditions.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Elevated AKAP12 in paclitaxel-resistant serous ovarian cancer cells is prognostic and predictive of poor survival in patients.

A majority of high-grade (HG) serous ovarian cancer (SOC) patients develop resistant disease despite high initial response rates to platinum/paclitaxel-based chemotherapy. We identified shed/secreted proteins in preclinical models of paclitaxel-resistant human HGSOC models and correlated these candidate proteins with patient outcomes using public data from HGSOC patients. Proteomic analyses of a HGSOC cell line secretome was compared to those from a syngeneic paclitaxel-resistant variant and from a line established from an intrinsically chemorefractory HGSOC patient. Associations between the identified candidate proteins and patient outcome were assessed in a discovery cohort of 545 patients and two validation cohorts totaling 795 independent SOC patients. Among the 81 differentially abundant proteins identified (q < 0.05) from paclitaxel-sensitive vs -resistant HGSOC cell secretomes, AKAP12 was verified to be elevated in all models of paclitaxel-resistant HGSOC. Furthermore, elevated AKAP12 transcript expression was associated with worse progression-free and overall survival. Associations with outcome were observed in three independent cohorts and remained significant after adjusted multivariate modeling. We further provide evidence to support that differential gene methylation status is associated with elevated expression of AKAP12 in taxol-resistant ovarian cancer cells and ovarian cancer patient subsets. Elevated expression and shedding/secretion of AKAP12 is characteristic of paclitaxel-resistant HGSOC cells, and elevated AKAP12 transcript expression is a poor prognostic and predictive marker for progression-free and overall survival in SOC patients.

Proteomics of the human endometrial glandular epithelium and stroma from the proliferative and secretory phases of the menstrual cycle.

Despite its importance in reproductive biology and women's health, a detailed molecular-level understanding of the human endometrium is lacking. Indeed, no comprehensive studies have been undertaken to elucidate the important protein expression differences between the endometrial glandular epithelium and surrounding stroma during the proliferative and midsecretory phases of the menstrual cycle. We utilized laser microdissection to harvest epithelial cells and stromal compartments from proliferative and secretory premenopausal endometrial tissue and performed a global, quantitative mass spectrometry-based proteomics analysis. This analysis identified 1224 total proteins from epithelial cells, among which 318 were differentially abundant between the proliferative and secretory phases (q < 0.05), and 1005 proteins from the stromal compartments, 19 of which were differentially abundant between the phases (q < 0.05). Several proteins were chosen for validation by immunohistochemistry in an independent set of uterine tissues, including carboxypeptidase M, tenascin C, neprilysin, and ectonucleotide pyrophosphatase/phosphodiesterase family member 3 (ENPP3). ENPP3, which was elevated in epithelial glandular cells in the secretory phase, was confirmed to be elevated in midsecretory-phase baboon uterine lavage samples and also observed to have an N-linked glycosylated form that was not observed in the proliferative phase. This study provides a detailed view into the global proteomic alterations of the epithelial cells and stromal compartments of the cycling premenopausal endometrium. These proteomic alterations during endometrial remodeling provide a basis for numerous follow-up investigations on the function of these differentially regulated proteins and their role in reproductive biology and endometrial pathologies.

Evaluation of a 4-protein serum biomarker panel-biglycan, annexin-A6, myeloperoxidase, and protein S100-A9 (B-AMP)-for the detection of esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) is associated with a dismal prognosis. The identification of cancer biomarkers can advance the possibility for early detection and better monitoring of tumor progression and/or response to therapy. The authors present results from the development of a serum-based, 4-protein (biglycan, myeloperoxidase, annexin-A6, and protein S100-A9) biomarker panel for EAC. METHODS: A vertically integrated, proteomics-based biomarker discovery approach was used to identify candidate serum biomarkers for the detection of EAC. Liquid chromatography-tandem mass spectrometry analysis was performed on formalin-fixed, paraffin-embedded tissue samples that were collected from across the Barrett esophagus (BE)-EAC disease spectrum. The mass spectrometry-based spectral count data were used to guide the selection of candidate serum biomarkers. Then, the serum enzyme-linked immunosorbent assay data were validated in an independent cohort and were used to develop a multiparametric risk-assessment model to predict the presence of disease. RESULTS: With a minimum threshold of 10 spectral counts, 351 proteins were identified as differentially abundant along the spectrum of Barrett esophagus, high-grade dysplasia, and EAC (P<.05). Eleven proteins from this data set were then tested using enzyme-linked immunosorbent assays in serum samples, of which 5 proteins were significantly elevated in abundance among patients who had EAC compared with normal controls, which mirrored trends across the disease spectrum present in the tissue data. By using serum data, a Bayesian rule-learning predictive model with 4 biomarkers was developed to accurately classify disease class; the cross-validation results for the merged data set yielded accuracy of 87% and an area under the receiver operating characteristic curve of 93%. CONCLUSIONS: Serum biomarkers hold significant promise for the early, noninvasive detection of EAC.

Choline phosphate cytidylyltransferase-α is a novel antigen detected by the anti-ERCC1 antibody 8F1 with biomarker value in patients with lung and head and neck squamous cell carcinomas.

BACKGROUND: The determination of in situ protein levels of ERCC1 with the 8F1 monoclonal antibody is prognostic of survival in patients with non-small cell lung cancer (NSCLC). The authors previously demonstrated that 8F1 recognizes a second nuclear antigen. This antigen was identified and its value as a biomarker of clinical outcomes analyzed. METHODS: The second antigen was identified by mass spectrometry. Protein identity and antibody specificity were confirmed through knockdown and overexpression experiments. Immunohistochemistry of 187 early-stage NSCLC samples and 60 head and neck squamous cell carcinomas (HNSCCs) was used to examine the influence of the second antigen on 8F1 immunoreactivity and its association with patient outcomes. RESULTS: Choline phosphate cytidylyltransferase-α (CCTα, also known as phosphate cytidylyltransferase 1 choline alpha [PCYT1A], a phospholipid synthesis enzyme regulated by RAS) is the second antigen recognized by 8F1. In NSCLC samples, CCTα contributed (rho, 0.38) to 8F1 immunoreactivity. In samples of squamous cell carcinomas of the lung, CCTα was found to be the dominant determinant of 8F1 immunoreactivity, whereas its contribution in other subtypes of lung cancer was negligible. High expression of CCTα, but not ERCC1, was found to be prognostic of longer disease-free survival (log-rank P = .002) and overall survival (log-rank P = .056). Similarly, in patients with HNSCC, CCTα contributed strongly to 8F1 immunoreactivity (rho, 0.74), and high CCTα expression was found to be prognostic of survival (log-rank P = .022 for disease-free survival and P = .027 for overall survival). CONCLUSIONS: CCTα is the second antigen detected by 8F1. High CCTα expression appears to be prognostic of survival in patients with NSCLC who are treated by surgery alone and patients with HNSCC. CCTα is a promising biomarker of patient survival and deserves further study.

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/.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities.

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

An integrated understanding of the physiological response to elevated extracellular phosphate.

Recent studies have suggested that changes in serum phosphate levels influence pathological states associated with aging such as cancer, bone metabolism, and cardiovascular function, even in individuals with normal renal function. The causes are only beginning to be elucidated but are likely a combination of endocrine, paracrine, autocrine, and cell autonomous effects. We have used an integrated quantitative biology approach, combining transcriptomics and proteomics to define a multi-phase, extracellular phosphate-induced, signaling network in pre-osteoblasts as well as primary human and mouse mesenchymal stromal cells. We identified a rapid mitogenic response stimulated by elevated phosphate that results in the induction of immediate early genes including c-fos. The mechanism of activation requires FGF receptor signaling followed by stimulation of N-Ras and activation of AP-1 and serum response elements. A distinct long-term response also requires FGF receptor signaling and results in N-Ras activation and expression of genes and secretion of proteins involved in matrix regulation, calcification, and angiogenesis. The late response is synergistically enhanced by addition of FGF23 peptide. The intermediate phase results in increased oxidative phosphorylation and ATP production and is necessary for the late response providing a functional link between the phases. Collectively, the results define elevated phosphate, as a mitogen and define specific mechanisms by which phosphate stimulates proliferation and matrix regulation. Our approach provides a comprehensive understanding of the cellular response to elevated extracellular phosphate, functionally connecting temporally coordinated signaling, transcriptional, and metabolic events with changes in long-term cell behavior.

The bc:caa3 supercomplexes from the Gram positive bacterium Bacillus subtilis respiratory chain: a megacomplex organization?

The respiratory chain of some prokaryotes was shown to be organized in supercomplexes. This association has been proposed to improve enzyme stability and the overall efficiency of the oxidative phosphorylation process. Here, we have revisited recent data on the supercomplexes of Bacillus subtilis respiratory chain, by means of 1D and 2D-BN-PAGE, sucrose gradient fractionation of solubilized membranes, and mass spectrometry analysis of BN-PAGE bands detected in gel for succinate and cytochrome c oxidoreductase activities. The cytochrome bc:caa3 oxygen oxidoreductase supercomplex was observed in different stoichiometries, (bc)4:(caa3)2, (bc)2:(caa3)4 and 2[(bc)2:(caa3)4], suggesting for the first time the string association model of supercomplexes in a Gram positive bacterium. In addition, the presence of a succinate:quinone oxidoreductase:nitrate reductase supercomplex was confirmed by the co-localized succinate:nitroblue tetrazolium and methylviologen:nitrate oxidoreductase activities detected in gel and corroborated by LC-MS/MS analysis.

The murine metastatic microenvironment of experimental brain metastases of breast cancer differs by host age in vivo: a proteomic study.

Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients.