Abstract: Allele expression (AE) analysis robustly measures cis -regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis -regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

Abstract: Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing 〉 20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.

Abstract: Post-translational modifications (PTMs) (e.g., ubiquitylation, phosphorylation, acetylation) have been studied for their key role in cell signaling and in regulating cell physiology. Advances in mass spectrometry now enable measuring PTMs and studying their role and prevalence in cancer. Although most studies have focused on a single PTM and its impact on downstream signaling in a single cancer type, understanding PTM-driven commonalities, disparities, and their crosstalk across cancer types will be critical in understanding fundamental oncogenic principles governed by PTMs. Thus, we aim to understand the underlying patterns of PTMs in molecular signaling pathways shared across multiple cancer types by studying changes in protein acetylation and phosphorylation within the largest collection of in-depth genomic, transcriptomic, proteomic, and PTM profiles compiled from 11 cancer types generated across the CPTAC projects.We used matrix factorization methods to extract expression signatures jointly from transcriptomic, proteomic, and PTM data across multiple cancer types. Preliminary analysis of 6 tumor types identified 18 pan-cancer, multi-omic expression signatures. Characterization of these signatures using ranked gene-set enrichment analysis (GSEA) and site-specific PTM signature enrichment analysis (PTM-SEA) highlighted pathways including DNA damage response, immune inactivation/deactivation, tumor invasiveness, and metabolic pathways. To investigate the effect of driver alterations on PPIs, we (i) compute rank correlations of pan-cancer mutational signatures to both expression levels and our multi-omic expression signatures, and (ii) map PTMs and mutations to available crystal structures. We additionally investigate mutations that recur across cancer types (e.g., TP53, PIK3CA, CTNNB1) and impact expression profiles of downstream PTMs. We further connect pan-cancer phosphoproteomic data to a library of biochemical specificities of the human kinome using a novel, unbiased computational platform that builds on extensive and experimentally validated kinase-substrate relationships. We identified activated and deactivated kinases/acetylases based on their altered PTM sites within and across the multi-omic subtypes and compared the effects on different targets. We also characterize the crosstalk between acetylation and phosphorylation across cancer, and, systematically identify acetylation events that prime and enhance kinase activity. Finally, we define kinases, acetylases, and PTM outliers as potential druggable targets (using The Drug Gene Interaction Database and DepMap). Overall, this study presents the landscape of PTMs across cancer and will serve as a community resource to promote a deeper understanding of PTM-governed processes leading to cancer progression, with the potential to improve current therapies or help design new treatment approaches against cancer. Citation Format: Yifat Geffen, Shankara Anand, Yo Akiyama, Tommer M. Yaron, Alexander Kerelsky, Jared L. Johnson, Karsten Krug, David Heiman, Shankha Satpathy, Karl Clauser, Michael Gillette, D. R. Mani, Chet Birger, Steven Carr, Lewis C. Cantley, Francois Aguet, Gad Getz, Oncogenic Drivers and Pathways Group, Clinical Proteomic Tumor Analysis Consortium (CPTAC). Patterns and regulation of post translational modifications in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 16.

Abstract: Non-clear cell renal cell carcinomas (non-ccRCCs) represent ~15-20% RCCs cases comprising nearly 20 different disease subtypes and a wide spectrum of clinical behavior from benign to highly aggressive course. Clinically, metastatic non-ccRCC patients, regardless of subtypes with distinct genomic aberrations, are all treated with the same standard of care therapies, underscoring the need for precision therapeutic strategies. Diagnostic challenges also exist as benign and malignant entities often display overlapping histomorphologies that current diagnostic cytokeratin markers cannot resolve. Therefore, identification of more reliable diagnostic and prognostic non-ccRCC biomarkers remains an unmet need in this field. As part of the Clinical Tumor Analysis Consortium (CPTAC), we performed integrative analysis of multi-omics data including genomic next generation sequencing-based whole exome, whole genome, RNAseq, snRNAseq and mass spectrometry-based proteomics, post translational modifications (glycosylation and phosphorylation) and metabolomic profiles generated by CPTAC. The composition of the kidney tumor cohort (n=151) included 103 ccRCC, 15 oncocytomas, 13 papillary RCC (PRCC), 11 other rare tumors and 8 unclassified RCCs. Our multi-omic analysis revealed both unique and shared molecular features of RCC subtypes. We characterized proteogenomic, PTM and glycoproteome impact of genome instability (GI), a feature that is associated with poor prognosis in both ccRCC and non-ccRCC and affects 10-15% of cases. These analyses identified new prognostic signatures, outlier targetable kinase expression patterns, kinase-substrate relationships and differential protein glycosylation events. Glycoproteome analysis also revealed variation in cell-type specific marker expression among RCC subtypes such as FUT8 (core-fucosyltransferase) associated protein glycosylation in PRCC. Integrative analysis of snRNA-seq data predicted diverse tumor cell-of-origin and stratified RCC subtype specific proteogenomic signatures. Differential expression analysis revealed several novel diagnostic makers including MAPRE3, GPNMB, PIGR, SOSTDC1. These biomarkers were validated by IHC and their addition to existing panels results in improved diagnostic specificity. Metabolic characterization revealed RCC subtype-specific differences and increased oncometabolite SAICAR in oncocytomas that may have functional significance. The valuable proteogenomic data resource we generated contains several rare tumor types that are hard to obtain for proteogenomic characterization at the scale described here, and will certainly aid in future pan-RCC studies. Citation Format: Ginny Xiaohe Li, Yi Hsiao, Lijun Chen, Rahul Mannan, Yuping Zhang, Francesca Petralia, Hanbyul Cho, Noshad Hosseini, Anna Calinawan, Yize Li, Shankara Anand, Aniket Dagar, Yifat Geffen, Felipe V. Leprevost, Anne Le, Sean Ponce, Michael Schnaubelt, Nataly Naser Al Deen, Wagma Caravan, Andrew Houston, Chandan Kumar-Sinha, Xiaoming Wang, Seema Chugh, Gilbert S. Omenn, Daniel W. Chan, Christopher Ricketts, Rohit Mehra, Arul Chinnaiyan, Li Ding, Marcin Cieslik, Hui Zhang, Saravana M. Dhanasekaran, Alexey I. Nesvizhskii. Comprehensive proteogenomic characterization of rare kidney tumors [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 3127.

Abstract: Post-translational modifications (PTMs) play key roles in regulating cell signaling in health and disease processes. Recent advances in mass spectrometry enable comprehensive investigation of PTMs. However, identifying functionally relevant PTMs and protein domains implicated in disease remains a key challenge. We present CLUMPS-PTM, an algorithm for spatial clustering of PTMs to propose functional domains. We apply CLUMPS-PTM to the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset (one of the largest proteogenomic pan-cancer PTM datasets) comprising 1110 samples spanning 11 tumor types. First, we map over 14K phospho-sites and 13K acetyl-sites detected in the CPTAC dataset to protein data bank (PDB) files. We expand this to the predicted AlphaFold proteome and recover additional 12K phospho-sites and 10K acetyl-sites exceeding model confidence (pLDDT) of 70%. Consistent with previous research, phospho-sites are found on residues with lower AlphaFold prediction confidence than acetyl-sites due to their abundance in unstructured domains (p-value & lt; 1e-4). To identify functionally relevant protein domains in the pan-cancer context, we characterize the 1110 samples by applying SignatureAnalyzer, a Bayesian non-negative matrix factorization method, to discover multi-omic patterns. This analysis identifies strong signatures associated with DNA damage response (DDR) and stratifies the CPTAC cohort into DDR-high (n=442) and DDR-low (n=668) groups. Next, we applied CLUMPS-PTM to differentially modified phospho/acetyl-sites between these groups. We identified 22 proteins (including GMPS, NCBP1, and ANPEP (CD13)) with significant clusters of differentially phosphorylated sites (q-value & lt; 0.1) in DDR-high samples. ANPEP is a zinc-dependent aminopeptidase with a significant cluster (q-value = 0.0129) of differentially phosphorylated sites in the ERAP1-C domain that faces peptidase active sites known to have proliferative activity via the MAPK pathway. CLUMPS-PTM also identified a significant cluster of acetyl-sites on ARID1A (a SWI/SNF chromatin remodeler known to be mutated in cancer) in DDR-high samples (q-value = 0.085). The ARID1A cluster is on the C-terminal tail of the protein within the glucocorticoid receptor (GR) domain, an upstream regulator of proteins that increase catabolism, reduce inflammation, and increase cell survival. Increased acetylation may block a ubiquitination site at the C-terminus of the protein, resulting in increased protein levels, likely due to reduced ARID1A degradation, and increased GR signaling. Overall, CLUMPS-PTM is an open-source tool that allows near proteome-wide spatial analysis with the growing availability of PTM data. We anticipate that it will be useful to the broader proteomic community for the discovery of novel targets and generation of insights into functional mechanisms. Citation Format: Shankara K. Anand, Yifat Geffen, Yo Akiyama, Francois Aguet, Gad Getz. CLUMPS-PTM: Spatial clustering of post-translational modifications across cancer types [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 3132.

Abstract: Our understanding of disease progression in multiple myeloma (MM) and its precursor conditions, monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM), is classically founded on bulk analysis studies. Low disease burden at the precursor stages has precluded comprehensive analyses of the transcriptomic events underlying malignant transformation. Here, we use single-cell RNA sequencing data from 29,387 bone marrow plasma cells from 26 patients with MGUS, SMM, or MM and 9 healthy controls to characterize the transcriptional transformation at each step of progression. Due to varying disease burdens, many samples contained a mixture of healthy and neoplastic plasma cells. We leveraged this impurity to perform a patient-specific characterization of the disease, comparing each patient's neoplastic and healthy plasma cells. This approach isolated the disease phenotype in each patient, which is usually confounded by biological and technical variability when comparing tumors to samples from healthy donors. We found that neoplastic cells from patients with MGUS and SMM already exhibit phenotypic changes similar to those of advanced myeloma. We observed upregulation of genes corresponding to known MM subtypes, such as CCND1 in patients with t(11;14) translocations and other known driver genes such as HIST1H1C. We also found universal downregulation of certain genes such as CD27, a member of the tumor necrosis factor receptor family associated with the differentiation of B cells into plasma cells, which may signify a common loss of a normal plasma phenotype across samples with different driver events and stages. Pathway analysis of differentially expressed genes further revealed that biological pathways related to myeloma were altered as early as MGUS. We observed that SMM patients with hyperdiploidy exhibit upregulation of ribosomal proteins, as reported in advanced disease. Upregulated genes in select MGUS and SMM samples were enriched for the eukaryotic translation initiation factor 3 (eIF3) complex, which plays important roles in translation, as well as proteasome activity, a function central to the survival of MM and targeted by therapies such as bortezomib. We observed enrichment of the E2F family of transcription factors in MGUS and SMM samples; these are master regulators of proliferation that have been suggested as therapeutic targets in myeloma. Five samples were enriched for genes associated with extracellular exosomes, which has been reported to play an important role in cancer cell signaling and to contribute to osteolysis and drug resistance in MM. Pathway enrichment of genes downregulated in neoplastic cell populations revealed weakened response to endoplasmic reticulum and oxidative stress, presumably allowing myeloma cells to tolerate high volumes of abnormal protein production without apoptosing. To further identify shared gene expression patterns across samples, we employed a Bayesian Non-Negative Matrix Factorization method to decompose our data into 31 gene signatures that capture its variability. In addition to recovering signatures corresponding to known MM subtypes, demonstrating that our method captures cohesive transcriptional networks, we find signatures that capture disease biology shared across subtypes. Most notably, we identified a signature that is active in healthy plasma cells across disease stages and dramatically lost in MM and precursor cells. The top genes in this signature include CD27 and CD79A, which are associated with the B cell lineage and whose downregulation may signify dedifferentiation of premalignant cells as early as MGUS, and JSRP1, CTSH, and HCST, genes as of yet unreported to be involved in plasma and MM cell biology. This phenotype would be obscured at early disease stages by bulk analysis. We validated the discovery and behavior of this signature in an external single-cell dataset from Ledergor et al. (Nature Medicine 2018). In summary, using single-cell RNA sequencing, we discovered that canonical MM pathways are altered as early as MGUS and identified a signature of genes which distinguishes healthy and neoplastic cells even at early disease stages. Our identification of patient-specific transcriptional changes as early as MGUS paves the way for future work exploring personalized treatment approaches prior to malignant disease. Disclosures Haradhvala: Constellation Pharmaceuticals a MorphoSys Company: Consultancy. Zavidij: Constellation Pharmaceuticals: Current Employment. Sontag: curai health: Current holder of individual stocks in a privately-held company; Takeda Pharmaceuticals: Research Funding; Genentech: Research Funding; IBM: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees.

Abstract: Background Patients with Smoldering Multiple Myeloma (SMM) are typically observed until progression to overt Multiple Myeloma (MM), but early treatment of high-risk patients may improve outcomes. Clinical and genomic biomarkers can help to identify SMM patients at high risk of progression, but whether parallel profiling of the tumor immune microenvironment can further improve our models remains to be determined. Methods We performed single-cell RNA sequencing on CD138- immune cells from 40 samples of 14 patients with high-risk SMM enrolled in a Phase II trial of Elotuzumab, Lenalidomide, and Dexamethasone (NCT02279394), to develop biomarkers for optimal patient selection and monitoring of response to treatment. This study was approved by the Dana-Farber Cancer Institute's Institutional Review Board (#14-338). Specifically, we used the Chromium Single Cell 3' Gene Expression system by 10X Genomics to profile 33 magnetically sorted (Miltenyi Biotec) CD138- bone marrow (BM) samples collected at baseline (n=11), cycle 9 day 1 (C9D1, n=13), and end of treatment (EOT, n=9), and 7 peripheral blood mononuclear cell (PBMC) samples collected at baseline (n=4) and C9D1 (n=3). We integrated this data with our cohort of non-trial patients with Monoclonal Gammopathy of Undetermined Significance (n=5), low-risk SMM (n=3), high-risk SMM (n=8), newly diagnosed MM (n=9) and healthy donors (n=10), reaching a total of 75 samples. Results We found that higher abundance of mature B-cells, Th17, and Granzyme K (GZMK)+ T-cells, as well as gene expression signatures marked by type 17 genes and GZMK, are associated with significantly longer progression-free survival (PFS) in SMM patients under treatment. Although immunoparesis is a significant predictor of PFS in our cohort and could thus be confounding our B-cell signal, we showed that immunoparesis is not associated with lower number of B-cells in the BM and is instead associated with the upregulation of transcription factor Kruppel-like Factor 2 (KLF2, q=2e-05), which we hypothesize may oppose differentiation into antibody-secreting plasma cells. We found that these differences in abundance can be summarized by how normal-like the patients' immune composition is at baseline, whereby patients whose immune composition is not normal-like have significantly longer PFS (p=0.031). This model suggests that at least some of the compositional changes observed in disease may reflect the immune system's capacity to react successfully to the immune challenge posed by the tumor, which we termed 'immune reactivity'. Baseline immune reactivity may help to identify patients who will benefit the most from early treatment. Furthermore, we found that the expansion of tissue-resident NK cells and exhausted GZMK+ CD8+ T-cells at C9D1 of treatment, as well as higher levels of a gene expression signature marked by amphiregulin (AREG), are associated with significantly shorter PFS (p=0.039). These biomarkers may improve monitoring of response to immunotherapy, which may not be fully explained by residual tumor burden alone. Lastly, patients whose immune profile was normal-like at EOT (Post-therapy Immune Normalization, PIN), potentially signifying the resolution of the immune challenge, had significantly longer biochemical PFS (p=0.04). Assessment of PIN at EOT may improve stratification of patients with minimal residual disease. Importantly, we found that biomarker status could be assessed in both the patients' peripheral blood and their BM, suggesting that minimally invasive immune profiling for prognostication and monitoring may be feasible. Conclusions Our study has nominated novel immune biomarkers for optimal patient selection and assessment of response to immunotherapy and uncovered a previously unappreciated mechanism of B-cell immunosuppression in MM, which could lead to the development of novel therapeutics. Our findings may usher in a next generation of clinical assays that assess both tumor biology and immune state, as well as common clinical biomarkers, in the marrow or blood, to accurately predict who may benefit from early treatment, monitor response to immunotherapy, and improve patient outcomes. Disclosures Dutta: Menarini Silicon Biosystems: Consultancy. Haradhvala: Constellation Pharmaceuticals a MorphoSys Company: Consultancy. Zavidij: Constellation Pharmaceuticals: Current Employment. Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Rosenblatt: Attivare: Consultancy; Imaging Endpoints: Consultancy; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Parexel: Consultancy; Wolters Kluwer Health Inc: Consultancy, Patents & Royalties. Zonder: Caelum Biosciences: Consultancy; Intellia: Consultancy; Alnylam: Consultancy; Regeneron: Consultancy; Janssen: Consultancy; BMS: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy. Bhutani: Janssen, MedImmune, Takeda, Celgene, BMS, Cerecor, Celularity: Research Funding; Sanofi: Consultancy; Amgen, BMS, Takeda: Speakers Bureau. Usmani: Array BioPharma: Consultancy, Research Funding; Abbvie: Consultancy; Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; GSK: Consultancy, Research Funding; EdoPharma: Consultancy; Janssen: Consultancy, Research Funding, Speakers Bureau; Sanofi: Consultancy, Research Funding, Speakers Bureau; Merck: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; SkylineDX: Consultancy, Research Funding; Takeda: Consultancy, Research Funding, Speakers Bureau; Janssen Oncology: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Consultancy, Research Funding, Speakers Bureau. Yee: Bristol Myers Squibb: Consultancy; Oncopeptides: Consultancy; Amgen: Consultancy; Janssen: Consultancy; GSK: Consultancy; Adaptive: Consultancy; Sanofi: Consultancy; Takeda: Consultancy; Karyopharm: Consultancy. Jakubowiak: Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Gracell: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees. Manier: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene - Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Regeneron: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Nadeem: GSK: Consultancy; Adaptive: Consultancy; Bristol Myer Squibb: Consultancy; Takeda: Consultancy; Karyopharm: Consultancy. Richardson: GlaxoSmithKline: Consultancy; Takeda: Consultancy, Research Funding; AbbVie: Consultancy; AstraZeneca: Consultancy; Celgene/BMS: Consultancy, Research Funding; Karyopharm: Consultancy, Research Funding; Janssen: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy, Research Funding; Regeneron: Consultancy; Secura Bio: Consultancy; Protocol Intelligence: Consultancy; Jazz Pharmaceuticals: Consultancy, Research Funding. Badros: J & J: Research Funding; BMS: Research Funding; Janssen: Research Funding; GlaxoSmithKline: Research Funding. Mateos: Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.