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Clear cell ovarian carcinoma (CCOC) is the second most common subtype of epithelial ovarian carcinoma. Late-stage CCOC is not responsive to gold-standard chemotherapy and results in suboptimal outcomes for patients. In-depth molecular insight is urgently needed to stratify the disease and drive therapeutic development. We conducted global proteomics for 192 cases of CCOC and compared these with other epithelial ovarian carcinoma subtypes. Our results showed distinct proteomic differences in CCOC compared with other epithelial ovarian cancer subtypes including alterations in lipid and purine metabolism pathways. Furthermore, we report potential clinically significant proteomic subgroups within CCOC, suggesting the biologic plausibility of stratified treatment for this cancer. Taken together, our results provide a comprehensive understanding of the CCOC proteomic landscape to facilitate future understanding and research of this disease. © 2022 The Pathological Society of Great Britain and Ireland.

There are two serous ovarian cancer histotypes, low and high grade (LGSOC and HGSOC), which are distinct clinical and biological entities. LGSOC is a rare histotype with a relatively stable genome, while HGSC is more common and genomically unstable. Somewhat surprisingly LGSOC expresses high levels of the stimulator of the interferon genes (STING). The STING pathway recognizes cytoplasmic double-stranded DNA and mounts innate cellular immunity through interferon-beta type I production. Our objective is to investigate the aberrant STING signaling in LGSOC and test the effectiveness of oncolytic viruses against LGSOC. We used immunohistochemistry on tissue microarrays (TMAs) to assess STING protein expression in different ovarian cancer histotypes. Whole proteome analysis was applied to identify differentially expressed proteins in LGSOC and HGSOC patient samples (both n=9). Further, a semi-targeted proteomics approach was used to evaluate the expression levels of the STING pathway-related proteins in LGSOC, HGSOC, and LGSOC precursor tumors (each subtype, n=20). To evaluate the key transcription, phosphorylation, and translocation events in STING signaling, we treated LGSOC cell lines with an agonist (dsDNA90) and performed qPCR, immunoblotting, and immunofluorescence experiments, respectively. We tested the viability of the LGSOC cell lines in response to Vaccinia Virus (VV), and Vesicular Stomatitis Virus (VSV) based oncolytic vectors with or without immunostimulatory transgenes. Our results show that STING protein levels were consistently higher in LGSOC TMAs relative to other histotypes. Proteomics analysis showed that the half of the 16 most differentially expressed proteins were the effectors of STING signaling with unexpectedly lower expression in LGSOC, suggesting that despite the robust levels of STING in LGSOC tumors, the pathway is not fully active. Attenuated STING translocation and expression of IFNB1 and other cytokines in LGSOC cell lines confirm the aberrancy in the STING pathway. Semi-targeted proteomics revealed the considerable overexpression of STIM1 in LGSOC patient tumors, which has previously been shown to sequester STING in the endoplasmic reticulum. The treatment with VV and VSV oncolytic viruses significantly reduced the proliferation of LGSOC cell lines. In summary, we find attenuated STING signaling in LGSOC, possibly due to overexpression of STIM1 preventing STING translocation. Although oncolytic viruses show promising results in LGSOC cell lines, more research is needed to determine the optimal treatment strategy, testing oncolytic viruses expressing various transgenes and combination therapies. Citation Format: Almira Zhantuyakova, Dawn Cochrane, Gian Negri, Sandra E. Spencer Miko, Taha Azad, Jutta Huvila, Marta Llaurado Fernandez, Mark Carey, Gregg B. Morin, John Bell, David Huntsman. Deciphering aberrant STING pathway and exploring oncolytic viruses therapy in low grade serous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6417.

Introduction: Immunotherapeutic strategies have produced remarkable results in some malignancies. However, optimal cell surface targets in many childhood cancers remain elusive and tools for novel target discovery are limited. We developed a proteogenomic approach to identify high confidence cell surface proteins for immunotherapy development and applied it to neuroblastoma, an often fatal childhood cancer. Through the Pediatric Immunotherapy Discovery and Development Network (PI-DDN), we have extended this approach to 14 high-risk childhood cancers. This effort includes MS-based surfaceome data generation for 175 patient-derived xenograft (PDX) models, 30 primary patient tumors, and 10 human derived cell line models. Methods/Results: To optimize the utility of our approach and data, we are developing a web-based application called PIONEER (Pediatric Integrative Omics Network Enhancing Early Research). The goal of PIONEER is to disseminate data to the broader scientific community and to provide the necessary analysis, query and visualization tools to make these data accessible to everyone, regardless of computational expertise. A pilot version of PIONEER was developed using R Shiny Dashboard and is derived from our neuroblastoma efforts. The application is comprised of two main categories: (1) target discovery data and prioritization (2) target validation and preclinical development. Modules include proteomics, transcriptomics, epigenomics, multi-omics, validation and pre-clinical drug development. Cancer ‘omics data currently housed in PIONEER include tumor and cancer cell line mass-spectrometry based proteomics, RNA-sequencing, and chromatin immunoprecipitation (ChIP) sequencing. Extensive normal tissue expression data from GTEx and mass spectrometry will be integrated. Surface proteins are prioritized through an integrative multi-omic analysis of tumor and normal tissue data. Users can perform queries and cancer subtype and cross-histotype studies, apply custom cutoffs, and generate plots for visualization. We are currently adding functionality to support automatic data analysis and integration for surface proteins (SPACE: Surface Protein Analysis for Collaborative Efforts). Through the target validation and preclinical development modules, users can view an antibody repository, immunofluorescence, immunohistochemistry, drugs in development for each protein, and efficacy in patient derived xenograft models. PIONEER will be deployed using R Connect; data for additional histotypes will be incorporated as available. Conclusion: PIONEER will provide a comprehensive characterization of the surfaceome of high-risk pediatric cancers and a web-based application for data integration, visualization and sharing. This interface facilitates the discovery of optimal immunotherapeutic drug targets in high-risk childhood cancers. Citation Format: Amber K. Weiner, Hemma Murali, Rawan Shraim, Karina L. Conkrite, Alexander B. Radaoui, Daniel Martinez, Brian Mooney, Sandra E. Spencer Miko, Gian Negri, Alberto Delaidelli, Caitlyn de Jong, Yuankun Zhu, Allison P. Heath, Jennifer Pogoriler, Yael P. Mosse, Deanne M. Taylor, Poul H. Sorensen, Gregg B. Morin, Benjamin A. Garcia, John M. Maris, Sharon J. Diskin. PIONEER: harnessing multi-omics data to enhance immunotherapeutic target discovery and development. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4515.

High-throughput phenotype-based screening of large libraries of novel compounds without known targets can identify small molecules that elicit a desired cellular response, but additional approaches are required to find and characterize their targets and mechanisms of action. Here we show that a compound termed lung cancer screen 3 (LCS3), previously selected for its ability to impair the growth of human lung adenocarcinoma (LUAD) cell lines, but not normal lung cells, induces oxidative stress and activates the NRF2 signaling pathway by generating reactive oxygen species (ROS) in sensitive LUAD cell lines. To identify the target that mediates this effect, we applied thermal proteome profiling (TPP) and uncovered the disulfide reductases GSR and TXNRD1 as LCS3 targets. Through enzymatic assays using purified protein, we confirmed that LCS3 inhibits disulfide reductase activity through a reversible, uncompetitive mechanism. Further, we demonstrate that LCS3-sensitive LUAD cells are correspondingly sensitive to the synergistic inhibition of glutathione and thioredoxin pathways. Lastly, a genome-wide CRISPR knockout screen identified the loss of NQO1 as a mechanism of LCS3 resistance. This work highlights the ability of TPP to uncover targets of small molecules identified by high-throughput screens and demonstrates the potential utility of inhibiting disulfide reductases as a therapeutic strategy for LUAD.

The ribosome is an RNA-protein complex that is essential for translation in all domains of life. The structural and catalytic core of the ribosome is its ribosomal RNA (rRNA). While mutations in ribosomal protein (RP) genes are known drivers of oncogenesis, oncogenic rRNA variants have remained elusive. We identify a cancer-specific single-nucleotide variation in 18S rRNA at nucleotide 1248.U in up to 45.9% of patients with colorectal carcinoma (CRC) and present across22 cancer types. This is the site of a unique hyper-modified base, 1-methyl-3-α-amino-α-carboxyl-propyl pseudouridine (m

Background: Genomic classification of breast cancer has advanced breast cancer diagnosis and outcomes. However, extensive heterogeneity still exists beyond their DNA or RNA profiles. Newer classifications based on protein profiling are being developed to investigate the molecular oncology of breast cancers at the level where most drugs act. Using a recently-developed technology, we performed global proteomic profiling of 300 breast cancer specimens linked to outcome data. Methods: Sections of 75 samples from each PAM50 intrinsic subtype (Luminal A, Luminal B, Her2-enriched, Basal-like; n = 300) were macrodissected and analyzed using the Single-Pot Solid-Phase enhanced Sample Preparation Clinical Tissue Proteomics, a highly sensitive 11-sample multiplex massspectrometry protocol applicable to formalin-fixed, paraffin embedded (FFPE) specimens. This methodology enables comprehensive quantification of protein expression for classifier and biomarker discovery. Patients were diagnosed during 2008-2013 (n = 178, dataset I) and 1986-1992 (n = 122, dataset II). Results: In-depth proteomic analysis measured 9088 proteins in total, including 4214 proteins quantified in every sample. Consensus clustering of 174 evaluable cases in dataset I identified four distinct groups based on expression values for 1054 highly variant proteins. Cluster 3 (n = 47, mostly basal-like with HER2-Enriched) displayed the most favorable recurrence free survival (RFS) when compared to other clusters (HR = 0.22, 95%CI [0.08-0.63], p = 0.005). This cluster was enriched for immune related pathways including antigen processing and presentation and type I & II interferon signaling, and displayed high tumor infiltrating lymphocyte counts, characterizing this cluster as “immune hot”. In contrast, cluster 2 (n = 50, mostly basal-like) exhibited the poorest RFS (HR = 2.88, 95%CI [1.45-5.70], p = 0.002) and was enriched for proteins related to stromal and extracellular matrix with few immune related peptides. Cluster 1 (n = 34, luminal B and HER2-Enriched) was associated with lipid metabolism, whereas cluster 4 (n = 43, mostly HER2-Enriched with luminal A and luminal B) had a profile enriched for extracellular matrix, blood coagulation and complement activation. Conclusions: Global proteomic analysis on FFPE specimens can characterize the heterogeneity of breast cancer in a reliable and clinically-applicable high throughput manner. Our methodology identifies protein candidates that potentially serve as therapeutic targets and could be adapted to archived clinical specimens from other tumors. Citation Format: Karama Asleh, Gian Luca Negri, Sandra E. Spencer Miko, Shane Colborne, Christopher S. Hughes, Xiu Q. Wang, Dongxia Gao, C. Blake Gilks, Stephen K.L. Chia, Torsten O. Nielsen, Gregg B. Morin. Proteomic analysis of breast cancer formalin-fixed paraffin-embedded clinical specimens identifies biologically-important subtypes with distinct clinical outcomes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-06.

Background Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous neoplasms with variable patient outcomes. Our study aims to uncover the molecular factors that underlie the clinical and biological heterogeneity among PNENs for a better understanding and potential classification of this disease. Methods Formalin-fixed paraffin-embedded primary tumour specimens from 92 patients with PNEN were procured for the study and split into two cohorts for discovery and validation purposes. Next-generation sequencing profiled the exome and transcriptome, and quantitative mass-spectrometry profiled the global proteome of specimens. Non-negative matrix factorization was used to identify subgroups, followed by differential analysis to identify subgroup-specific features. To corroborate subgroup-specific RNA- and protein- level distinctions, activities of key cellular regulators were inferred from target gene expression or co-expression signatures. Results Unsupervised clustering analysis of transcriptome data identified four robust molecular subgroups that were substantiated by proteome analysis (p=0.0005) within the discovery cohort and validated with the validation cohort and an external cohort of PNENs from a previous microarray-based gene expression study. A proliferative subgroup was enriched with neuroendocrine carcinomas and specimens with >20% Ki67, concomitant with reduced survival probability (p=0.0024; logrank test) and higher mRNA expression and protein abundance of cell cycle-related genes. Increased mRNA expression of ARX or PDX1 (adjusted p Citation Format: Kevin C. Yang, Steve Kalloger, John Aird, Michael Lee, Christopher Rushton, Sandra E. Spencer Miko, Karen L. Mungall, Andrew J. Mungall, Shane Colborne, Ryan D. Morin, Jonathan M. Loree, Marco A. Marra, Daniel J. Renouf, Gregg B. Morin, David F. Schaeffer, Sharon M. Gorski. Proteotranscriptomic classification and characterization of pancreatic neuroendocrine neoplasms [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-009.

SummaryThe ribosome is an RNA-protein complex essential for translation in all domains of life. The structural and catalytic core of the ribosome is its ribosomal RNA (rRNA). While mutations in ribosomal protein (RP) genes are known drivers of oncogenesis, oncogenic rRNA variants have remained elusive. We discovered a cancer-specific single nucleotide variation in 18S rRNA at nucleotide 1248.U in up to 45.9% of colorectal carcinoma (CRC) patients and present across >22 cancer types. This is the site of a unique hyper-modified base, 1-methyl-3-α-amino-α-carboxyl-propyl pseudouridine (m1acp3Ψ), a >1 billion years conserved RNA modification at the ribosome’s peptidyl decoding-site. A sub-set of CRC tumors we term ‘hypo-m1acp3Ψ’, show sub-stoichiometric m1acp3Ψ-modification unlike normal control tissues. A m1acp3Ψ knockout model and hypo-m1acp3Ψ patient tumors share a translational signature, characterized by highly abundant ribosomal proteins. Thus, m1acp3Ψ-deficient rRNA forms an uncharacterized class of ‘onco-ribosome’ which may serve as a chemotherapeutic target for treating cancer patients.