Kandasamy, Richard K.

Abstract Multiple myeloma (MM) is an incurable plasma cell neoplasm characterized by diverse and complex genetic abnormalities, including translocations of immunoglobulin (Ig) genes and a hyperdiploid (HRD) karyotype. Much of our current understanding of MM genetics, epigenetics, pathogenesis and response/resistance to myeloma directed therapies originated from studies on human MM-derived cell lines (HMCL). In this study, we conducted an integrated multi-omics analysis in five hyperdiploid cell lines established from serial samples from a single relapsed/refractory hyperdiploid MM patient, enabling detailed characterization of the genetic landscape and molecular alterations through disease progression.

Abstract Molecular profiling of human primary cell types is essential for understanding human biology. We present a transcriptome and proteome map of 28 primary human cell types. Three major clusters of epithelial, endothelial, and mesenchymal cell types were observed in both the transcriptome and proteome levels along with the discovery of cell type enriched molecules including GRAP and C1orf116. The epithelial cell specific protein C1orf116 was further validated using immunohistochemistry across various human tissues. An exhaustive protein database search considering 39 post-translational modifications (PTMs) revealed novel insights into the PTM landscape including identification of understudied PTMs such as serine O-acetylation and histidine methylation. This also enabled comprehensive characterization of proteins with diverse PTMs. Interestingly, an unexpectedly higher frequency of dioxidation on tryptophan compared to methionine led to the identification of oxidative mitochondria complex subunit proteins. Further, a search strategy accounting for alternative translational start sites, splice junctions and translational readthrough refined genome annotation using proteomic evidence. For example, peptides from translational readthrough including extended sequence of LDHB and MDH1 were detected representing the first peptide-level evidence of these protein readthrough isoforms. Our comprehensive transcriptome and proteome data revealed cell type-specific molecular cues and heterogeneity, offering new insights into disease mechanisms often overlooked by tissue proteomics.

Background and Aims: Cholangiocarcinoma (CCA) is one of the most lethal cancers, characterized by molecular heterogeneity and treatment resistance. To uncover new biological signals and therapeutic opportunities, we employed multiomic characterization combined with machine learning. Approach and Results: We profiled all anatomical CCA subtypes using whole exome sequencing, mRNA sequencing, and proteome/phosphoproteome analysis. Integrative dimensional reduction revealed RNA, protein, and phosphoprotein features driving tumor heterogeneity, enabling clustering. Machine learning algorithms identified molecular features for each cluster and mapped external datasets and patient-derived xenograft (PDX) models onto these clusters. Kinase enrichment analysis highlighted targetable kinases active in each cluster. In vivo validation was performed in cluster-specific PDX models using the selective TNK1 inhibitor, TP-5801. We identified 3 molecular clusters with distinct pathway characterization: immunomodulatory (cluster 1), metabolic (cluster 2), and gene regulation/cellular fate (cluster 3). Cluster assignment was independent of anatomic subtype but correlated with overall survival following curative-intent resection. We also identified multiomic features and pathways linked to overall survival and lymph node metastases, crucial for patient treatment selection. Kinase enrichment analysis pinpointed TNK1 as a highly active kinase in the metabolic cluster. Treatment with TP-5801 significantly reduced tumor growth in a metabolic PDX model, but not in models representing the other clusters. Combining internal data with publicly available datasets, we identified the immunomodulatory cluster as most responsive to gemcitabine/cisplatin therapy, confirmed in vivo using cluster-specific PDX models. Conclusions: Integrated multiomic characterization provides translational insights by defining unique molecular subtypes associated both with therapeutic response and overall clinical outcomes. This approach identified TNK1 as a previously unrecognized therapeutic target in a defined subset of CCA tumors.

ABSTRACT T‐cell receptor (TCR) signaling plays a crucial role in various biological processes and is usually studied using global mass spectrometry‐based phosphoproteomic studies. Despite advancements in targeted mass spectrometry‐based assays for protein quantification, their application in studying signaling processes, for example, reproducible measurements of post‐translational modifications (PTMs) such as phosphorylation, remains limited. Tyrosine phosphorylation is critical for many signaling pathways but presents challenges due to the low abundance of phosphotyrosine‐containing peptides. Conventional untargeted methods often encounter data gaps when analyzing large sample sets, particularly for low‐abundance peptides. To address this issue, a targeted proteomics method called “SureQuant” was employed, which relies on triggered data acquisition with heavy isotope‐labeled peptides. This method has been shown to provide sensitive and reproducible quantification of low‐abundance peptides. Here we describe the development of a SureQuant‐based method to quantify phosphotyrosine peptides that are involved in the TCR signaling pathway. To monitor the change in phosphotyrosine signals upon activation, the T‐cells were stimulated with anti‐CD3/CD28 antibodies. We successfully quantified changes in important phosphotyrosine peptides in primary T‐cells upon stimulation with anti‐CD3/CD28 antibodies. This study showcases the ability of the SureQuant approach to accurately quantify low‐abundance phosphotyrosine peptides, highlighting its broader potential to study a diverse set of PTMs in physiological or clinical settings. Summary T‐cell receptor (TCR) signaling plays a fundamental role in immune responses, regulating T‐cell activation, differentiation, and function. While tyrosine phosphorylation is a key regulatory mechanism in this pathway, the low abundance of phosphotyrosine peptides presents a major challenge for their detection and quantification in complex biological samples. By employing the SureQuant targeted mass spectrometry approach, we achieved highly sensitive and reproducible quantification of key phosphotyrosine sites involved in T‐cell activation. This study provides a systematic view of TCR signaling dynamics, revealing distinct phosphorylation patterns across different activation timepoints. Our findings demonstrate the effectiveness of SureQuant in quantifying low‐abundance, post‐translationally modified peptides, offering a valuable tool for studying signaling pathways with greater precision. Additionally, this methodological framework can be extended to investigate other signaling networks, immune cell functions, and disease‐associated phosphotyrosine modifications.

Multiple cell death and inflammatory signaling pathways converge on two critical factors: receptor-interacting serine/threonine kinase 1 (RIPK1) and caspase-8. Careful regulation of these molecules is critical to control apoptosis, pyroptosis, and inflammation. Here, we found a pivotal role of Raver1 as an essential regulator of Ripk1 pre-mRNA splicing, expression, and functionality and the subsequent caspase-8-dependent inflammatory cell death. We show that Raver1 influences mRNA diversity primarily by repressing alternative exon inclusion. Macrophages from Raver1 -deficient mice exhibit altered splicing of Ripk1 . As a result, Raver1 -deficient primary macrophages display diminished cell death and decreased interleukin-18 and interleukin-1ß production, when infected with Yersinia bacteria, or by restraining TGF-ß-activated kinase 1 or IKKβ in the presence of lipopolysaccharide, tumor necrosis factor family members, or interferon-γ. These responses are accompanied by reduced activation of caspase-8, Gasdermin D and E, and caspase-1 in the absence of Raver1 . Consequently, Raver1 -deficient mice showed heightened susceptibility to Yersinia infection. Raver1 and RIPK1 also controlled the expression and function of the C-type lectin receptor Mincle. Our study underscores the critical regulatory role of Raver1 in modulating innate immune responses and highlights its significance in directing in vivo and in vitro inflammatory processes.

Introduction The major primary genetic events in multiple myeloma (MM) include translocations of immunoglobulin heavy chain (IgH) and a hyperdiploidy (HRD) karyotype (Kuehl, 2002). The main drivers of pathogenesis in HRD MM are unknown (Fonseca, 2003), therefore further research is needed in this subgroup. Translational research in HRD MM has relied on analysis of genomic and transcriptomic alterations, however changes at the genome and transcriptome level do not always correlate directionally with protein abundance. Because proteins are considered the main and final effectors of most cellular processes, proteogenomics can improve our understanding of the drivers of HRD MM. We employed it here to identify potential biomarkers in HRD MM and determine whether any given trisomy may lead to a selective advantage. Methods: Protein and mRNA were extracted from CD138+ cells from 47 HRD MM and 14 t(11;14) MM samples. RNA-seq data was processed using MAPR-Seq pipeline using default parameters and gene-wise raw counts were extracted for each sample. Proteomics data was processed using Specranaut and protein-wise intensities were extracted for each sample. A generalized linear model configured with negative binomial distribution was used to analyze gene-wise count data in edgeR software. Genes with an adjusted p-value of <=0.05 were considered significantly differentially expressed. Protein intensity data were normalized using trimmed mean of M-values and log2 transformed. A generalized linear model configured with Gaussian distribution was used to compare protein intensities between the groups. Proteins with an adjusted p-value <= 0.05 were considered significantly differentially expressed. Two separate rank lists for protein and mRNA data were generated for pathway analysis. Results When comparing our small cohort of HRD MM patient samples to those with t(11;14) MM, out of approximately 16,600 total transcripts and 9,700 proteins evaluated we identified approximately 2,100 significantly variant transcripts and 500 significantly variant proteins in HRD MM. GSEA pathway analysis of the transcriptome and proteome revealed significantly upregulated translational and ribosomal processing pathways in HRD MM. Transcriptional MYC target pathways were also significantly upregulated. RNAseq revealed significantly higher expression of MYC (Rank 24.5, p=5.3E-6) in HRD MM. It is known that patients with t(11;14) MM have increased expression of CCND1 (Kuehl and Bergsagel, 2012). As expected, we found that the HRD MM subgroup had significantly lower expression of CCND1 compared to the t(11;14) MM subgroup (Rank -79.9, p=2.8E-21) and this was also true at the protein level (Rank -21.7, p=2.2E-5). The most significantly abundant protein in the HRD MM subgroup compared to t(11;14) MM was BAHD1, which is a protein that targets H3K27me3 and recruits transcriptional co-repressors (Fan, 2020). BAHD1 has been shown to repress erythroid genes and may recruit HDAC5, which plays a role in osteoblast differentiation (Rank 72.3, p=2.9E-20; Xu, 2021). The second most abundant protein in HRD MM was CKS2, which binds to the catalytic subunit of cyclin-dependent kinases (CDKs) and therefore positively regulates cell proliferation, invasion, and migration and has been shown to be implicated in tumor progression in several solid tumors (Rank 72.3, p=2.9E-20; You, 2015). TRIM proteins promote tumorigenesis and cancer development. TRIM14 mediates cancer development through mediating the JAK/STAT, PI3K/AKT, NFkB, and p53 pathways and was found to be significantly higher in HRD MM (Rank 70.6, p=9.0E-20; Huang, 2022). We also found increased protein abundance of LAMP5 in HRD MM (Rank 20.1, p=6.0E-5). LAMP5 may play an important role in MM progression and has been shown to be highly expressed in patients with mixed-lineage leukemia and is associated with a poor prognosis (Wang, 2023; Gracia-Maldonado, 2022). We identified many proteins (not all discussed here) that have not been well described in HRD MM and thus may be biomarkers/targets of disease pathogenesis of this subgroup. Conclusion Proteins are the final effectors of most cellular processes. Proteogenomics can improve our understanding of the drivers of HRD MM. Using a proteogenomic approach we identified proteins that may lead to selective advantage and/or pathogenesis of trisomies in HRD MM.

Hurler–Scheie syndrome (MPS IH/S), also known as mucopolysaccharidosis type I-H/S (MPS IH/S), is a lysosomal storage disorder caused by deficiency of the enzyme alpha-L-iduronidase (IDUA) leading to the accumulation of glycosaminoglycans (GAGs) in various tissues, resulting in a wide range of symptoms affecting different organ systems. Postgenomic omics technologies offer the promise to understand the changes in proteome, phosphoproteome, and phosphorylation-based signaling in MPS IH/S. Accordingly, we report here a large dataset and the proteomic and phosphoproteomic analyses of fibroblasts derived from patients with MPS IH/S ( n = 8) and healthy individuals ( n = 8). We found that protein levels of key lysosomal enzymes such as cathepsin D, prosaposin, arylsulfatases (arylsulfatase A and arylsulfatase B), and IDUA were downregulated. We identified 16,693 unique phosphopeptides, corresponding to 4,605 proteins, in patients with MPS IH/S. We found that proteins related to the cell cycle, mitotic spindle assembly, apoptosis, and cytoskeletal organization were differentially phosphorylated in MPS IH/S. We identified 12 kinases that were differentially phosphorylated, including hyperphosphorylation of cyclin-dependent kinases 1 and 2, hypophosphorylation of myosin light chain kinase, and calcium/calmodulin-dependent protein kinases. Taken together, the findings of the present study indicate significant alterations in proteins involved in cytoskeletal changes, cellular dysfunction, and apoptosis. These new observations significantly contribute to the current understanding of the pathophysiology of MPS IH/S specifically, and the molecular mechanisms involved in the storage of GAGs in MPS more generally. Further translational clinical omics studies are called for to pave the way for diagnostics and therapeutics innovation for patients with MPS IH/S.