Delineating functional and molecular impact of ex vivo sample handling in precision medicine.

Consistent handling of samples is crucial for achieving reproducible molecular and functional testing results in translational research. Here, we used 229 acute myeloid leukemia (AML) patient samples to assess the impact of sample handling on high-throughput functional drug testing, mass spectrometry-based proteomics, and flow cytometry. Our data revealed novel and previously described changes in cell phenotype and drug response dependent on sample biobanking. Specifically, myeloid cells with a CD117 (c-KIT) positive phenotype decreased after biobanking, potentially distorting cell population representations and affecting drugs targeting these cells. Additionally, highly granular AML cell numbers decreased after freezing. Secondly, protein expression levels, as well as sensitivity to drugs targeting cell proliferation, metabolism, tyrosine kinases (e.g., JAK, KIT, FLT3), and BH3 mimetics were notably affected by biobanking. Moreover, drug response profiles of paired fresh and frozen samples showed that freezing samples can lead to systematic errors in drug sensitivity scores. While a high correlation between fresh and frozen for the entire drug library was observed, freezing cells had a considerable impact at an individual level, which could influence outcomes in translational studies. Our study highlights conditions where standardization is needed to improve reproducibility, and where validation of data generated from biobanked cohorts may be particularly important.

Prediction model for drug response of acute myeloid leukemia patients.

Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI: [0.64, 0.68]) in the BeatAML validation set, -0.49 (95% CI: [-0.53, -0.44]) in the Swedish cohort and 0.59 (95% CI: [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https://www.meb.ki.se/shiny/truvu/MDREAM/ .

Proteogenomic analysis of acute myeloid leukemia associates relapsed disease with reprogrammed energy metabolism both in adults and children.

Despite improvement of current treatment strategies and novel targeted drugs, relapse and treatment resistance largely determine the outcome for acute myeloid leukemia (AML) patients. To identify the underlying molecular characteristics, numerous studies have been aimed to decipher the genomic- and transcriptomic landscape of AML. Nevertheless, further molecular changes allowing malignant cells to escape treatment remain to be elucidated. Mass spectrometry is a powerful tool enabling detailed insights into proteomic changes that could explain AML relapse and resistance. Here, we investigated AML samples from 47 adult and 22 pediatric patients at serial time-points during disease progression using mass spectrometry-based in-depth proteomics. We show that the proteomic profile at relapse is enriched for mitochondrial ribosomal proteins and subunits of the respiratory chain complex, indicative of reprogrammed energy metabolism from diagnosis to relapse. Further, higher levels of granzymes and lower levels of the anti-inflammatory protein CR1/CD35 suggest an inflammatory signature promoting disease progression. Finally, through a proteogenomic approach, we detected novel peptides, which present a promising repertoire in the search for biomarkers and tumor-specific druggable targets. Altogether, this study highlights the importance of proteomic studies in holistic approaches to improve treatment and survival of AML patients.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia.

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

SubCellBarCode: integrated workflow for robust spatial proteomics by mass spectrometry.

The molecular functions of a protein are defined by its inherent properties in relation to its environment and interaction network. Within a cell, this environment and network are defined by the subcellular location of the protein. Consequently, it is crucial to know the localization of a protein to fully understand its functions. Recently, we have developed a mass spectrometry- (MS) and bioinformatics-based pipeline to generate a proteome-wide resource for protein subcellular localization across multiple human cancer cell lines ( www.subcellbarcode.org ). Here, we present a detailed wet-lab protocol spanning from subcellular fractionation to MS-sample preparation and analysis. A key feature of this protocol is that it includes all generated cell fractions without discarding any material during the fractionation process. We also describe the subsequent quantitative MS-data analysis, machine learning-based classification, differential localization analysis and visualization of the output. For broad applicability, we evaluated the pipeline by using MS data generated by two different peptide pre-fractionation approaches, namely high-resolution isoelectric focusing and high-pH reverse-phase fractionation, as well as direct analysis without pre-fractionation by using long-gradient liquid chromatography-MS. Moreover, an R package covering the dry-lab part of the method was developed and made available through Bioconductor. The method is straightforward and robust, and the entire protocol, from cell harvest to classification output, can be performed within 1-2 weeks. The protocol enables accurate classification of proteins to 15 compartments and 4 neighborhoods, visualization of the output data and differential localization analysis including treatment-induced protein relocalization, condition-dependent localization or cell type-specific localization. The SubCellBarCode package is freely available at https://bioconductor.org/packages/devel/bioc/html/SubCellBarCode.html .

Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although standard-of-care chemotherapeutics are sufficient for most ALL cases, there are subsets of patients with poor response who relapse in disease. The biology underlying differences between subtypes and their response to therapy has only partially been explained by genetic and transcriptomic profiling. Here, we perform comprehensive multi-omic analyses of 49 readily available childhood ALL cell lines, using proteomics, transcriptomics, and pharmacoproteomic characterization. We connect the molecular phenotypes with drug responses to 528 oncology drugs, identifying drug correlations as well as lineage-dependent correlations. We also identify the diacylglycerol-analog bryostatin-1 as a therapeutic candidate in the MEF2D-HNRNPUL1 fusion high-risk subtype, for which this drug activates pro-apoptotic ERK signaling associated with molecular mediators of pre-B cell negative selection. Our data is the foundation for the interactive online Functional Omics Resource of ALL (FORALL) with navigable proteomics, transcriptomics, and drug sensitivity profiles at https://proteomics.se/forall .

SOCS3 Expression by Thymic Stromal Cells Is Required for Normal T Cell Development.

The suppressor of cytokine signaling 3 (SOCS3) is a major regulator of immune responses and inflammation as it negatively regulates cytokine signaling. Here, the role of SOCS3 in thymic T cell formation was studied in Socs3fl/flActin-creER mice (Δsocs3) with a tamoxifen inducible and ubiquitous Socs3 deficiency. Δsocs3 thymi showed a 90% loss of cellularity and altered cortico-medullary organization. Thymocyte differentiation and proliferation was impaired at the early double negative (CD4-CD8-) cell stage and apoptosis was increased during the double positive (CD4+CD8+) cell stage, resulting in the reduction of recent thymic emigrants in peripheral organs. Using bone marrow chimeras, transplanting thymic organoids and using mice deficient of SOCS3 in thymocytes we found that expression in thymic stromal cells rather than in thymocytes was critical for T cell development. We found that SOCS3 in thymic epithelial cells (TECs) binds to the E3 ubiquitin ligase TRIM 21 and that Trim21-/- mice showed increased thymic cellularity. Δsocs3 TECs showed alterations in the expression of genes involved in positive and negative selection and lympho-stromal interactions. SOCS3-dependent signal inhibition of the common gp130 subunit of the IL-6 receptor family was redundant for T cell formation. Together, SOCS3 expression in thymic stroma cells is critical for T cell development and for maintenance of thymus architecture.

The transcriptome-wide landscape of molecular subtype-specific mRNA expression profiles in acute myeloid leukemia.

Molecular classification of acute myeloid leukemia (AML) aids prognostic stratification and clinical management. Our aim in this study is to identify transcriptome-wide mRNAs that are specific to each of the molecular subtypes of AML. We analyzed RNA-sequencing data of 955 AML samples from three cohorts, including the BeatAML project, the Cancer Genome Atlas, and a cohort of Swedish patients to provide a comprehensive transcriptome-wide view of subtype-specific mRNA expression. We identified 729 subtype-specific mRNAs, discovered in the BeatAML project and validated in the other two cohorts. Using unique proteomics data, we also validated the presence of subtype-specific mRNAs at the protein level, yielding a rich collection of potential protein-based biomarkers for the AML community. To enable the exploration of subtype-specific mRNA expression by the broader scientific community, we provide an interactive resource to the public.

Cell Cycle Profiling Reveals Protein Oscillation, Phosphorylation, and Localization Dynamics.

The cell cycle is a highly conserved process involving the coordinated separation of a single cell into two daughter cells. To relate transcriptional regulation across the cell cycle with oscillatory changes in protein abundance and activity, we carried out a proteome- and phospho-proteome-wide mass spectrometry profiling. We compared protein dynamics with gene transcription, revealing many transcriptionally regulated G2 mRNAs that only produce a protein shift after mitosis. Integration of CRISPR/Cas9 survivability studies further highlighted proteins essential for cell viability. Analyzing the dynamics of phosphorylation events and protein solubility dynamics over the cell cycle, we characterize predicted phospho-peptide motif distributions and predict cell cycle-dependent translocating proteins, as exemplified by the S-adenosylmethionine synthase MAT2A. Our study implicates this enzyme in translocating to the nucleus after the G1/S-checkpoint, which enables epigenetic histone methylation maintenance during DNA replication. Taken together, this data set provides a unique integrated resource with novel insights on cell cycle dynamics.

PCSK6 Is a Key Protease in the Control of Smooth Muscle Cell Function in Vascular Remodeling.

RATIONALE: PCSKs (Proprotein convertase subtilisins/kexins) are a protease family with unknown functions in vasculature. Previously, we demonstrated PCSK6 upregulation in human atherosclerotic plaques associated with smooth muscle cells (SMCs), inflammation, extracellular matrix remodeling, and mitogens. OBJECTIVE: Here, we applied a systems biology approach to gain deeper insights into the PCSK6 role in normal and diseased vessel wall. METHODS AND RESULTS: Genetic analyses revealed association of intronic PCSK6 variant rs1531817 with maximum internal carotid intima-media thickness progression in high-cardiovascular risk subjects. This variant was linked with PCSK6 mRNA expression in healthy aortas and plaques but also with overall plaque SMA+ cell content and pericyte fraction. Increased PCSK6 expression was found in several independent human cohorts comparing atherosclerotic lesions versus healthy arteries, using transcriptomic and proteomic datasets. By immunohistochemistry, PCSK6 was localized to fibrous cap SMA+ cells and neovessels in plaques. In human, rat, and mouse intimal hyperplasia, PCSK6 was expressed by proliferating SMA+ cells and upregulated after 5 days in rat carotid balloon injury model, with positive correlation to PDGFB (platelet-derived growth factor subunit B) and MMP (matrix metalloprotease) 2/MMP14. Here, PCSK6 was shown to colocalize and cointeract with MMP2/MMP14 by in situ proximity ligation assay. Microarrays of carotid arteries from Pcsk6-/- versus control mice revealed suppression of contractile SMC markers, extracellular matrix remodeling enzymes, and cytokines/receptors. Pcsk6-/- mice showed reduced intimal hyperplasia response upon carotid ligation in vivo, accompanied by decreased MMP14 activation and impaired SMC outgrowth from aortic rings ex vivo. PCSK6 silencing in human SMCs in vitro leads to downregulation of contractile markers and increase in MMP2 expression. Conversely, PCSK6 overexpression increased PDGFBB (platelet-derived growth factor BB)-induced cell proliferation and particularly migration. CONCLUSIONS: PCSK6 is a novel protease that induces SMC migration in response to PDGFB, mechanistically via modulation of contractile markers and MMP14 activation. This study establishes PCSK6 as a key regulator of SMC function in vascular remodeling. Visual Overview: An online visual overview is available for this article.

TcellSubC: An Atlas of the Subcellular Proteome of Human T Cells.

We have curated an in-depth subcellular proteomic map of primary human CD4+ T cells, divided into cytosolic, nuclear and membrane fractions generated by an optimized fractionation and HiRIEF-LC-MS/MS workflow for limited amounts of primary cells. The subcellular proteome of T cells was mapped under steady state conditions, as well as upon 15 min and 1 h of T cell receptor (TCR) stimulation, respectively. We quantified the subcellular distribution of 6,572 proteins and identified a subset of 237 potentially translocating proteins, including both well-known examples and novel ones. Microscopic validation confirmed the localization of selected proteins with previously known and unknown localization, respectively. We further provide the data in an easy-to-use web platform to facilitate re-use, as the data can be relevant for basic research as well as for clinical exploitation of T cells as therapeutic targets.

Proteomics identifies neddylation as a potential therapy target in small intestinal neuroendocrine tumors.

Patients with small intestinal neuroendocrine tumors (SI-NETs) frequently develop spread disease; however, the underlying molecular mechanisms of disease progression are not known and effective preventive treatment strategies are lacking. Here, protein expression profiling was performed by HiRIEF-LC-MS in 14 primary SI-NETs from patients with and without liver metastases detected at the time of surgery and initial treatment. Among differentially expressed proteins, overexpression of the ubiquitin-like protein NEDD8 was identified in samples from patients with liver metastasis. Further, NEDD8 correlation analysis indicated co-expression with RBX1, a key component in cullin-RING ubiquitin ligases (CRLs). In vitro inhibition of neddylation with the therapeutic agent pevonedistat (MLN4924) resulted in a dramatic decrease of proliferation in SI-NET cell lines. Subsequent mass spectrometry-based proteomics analysis of pevonedistat effects and effects of the proteasome inhibitor bortezomib revealed stabilization of multiple targets of CRLs including p27, an established tumor suppressor in SI-NET. Silencing of NEDD8 and RBX1 using siRNA resulted in a stabilization of p27, suggesting that the cellular levels of NEDD8 and RBX1 affect CRL activity. Inhibition of CRL activity, by either NEDD8/RBX1 silencing or pevonedistat treatment of cells resulted in induction of apoptosis that could be partially rescued by siRNA-based silencing of p27. Differential expression of both p27 and NEDD8 was confirmed in a second cohort of SI-NET using immunohistochemistry. Collectively, these findings suggest a role for CRLs and the ubiquitin proteasome system in suppression of p27 in SI-NET, and inhibition of neddylation as a putative therapeutic strategy in SI-NET.

Breast cancer quantitative proteome and proteogenomic landscape.

In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

Proteogenomics and Hi-C reveal transcriptional dysregulation in high hyperdiploid childhood acute lymphoblastic leukemia.

Hyperdiploidy, i.e. gain of whole chromosomes, is one of the most common genetic features of childhood acute lymphoblastic leukemia (ALL), but its pathogenetic impact is poorly understood. Here, we report a proteogenomic analysis on matched datasets from genomic profiling, RNA-sequencing, and mass spectrometry-based analysis of >8,000 genes and proteins as well as Hi-C of primary patient samples from hyperdiploid and ETV6/RUNX1-positive pediatric ALL. We show that CTCF and cohesin, which are master regulators of chromatin architecture, display low expression in hyperdiploid ALL. In line with this, a general genome-wide dysregulation of gene expression in relation to topologically associating domain (TAD) borders were seen in the hyperdiploid group. Furthermore, Hi-C of a limited number of hyperdiploid childhood ALL cases revealed that 2/4 cases displayed a clear loss of TAD boundary strength and 3/4 showed reduced insulation at TAD borders, with putative leukemogenic effects.

SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization.

Subcellular localization is a main determinant of protein function; however, a global view of cellular proteome organization remains relatively unexplored. We have developed a robust mass spectrometry-based analysis pipeline to generate a proteome-wide view of subcellular localization for proteins mapping to 12,418 individual genes across five cell lines. Based on more than 83,000 unique classifications and correlation profiling, we investigate the effect of alternative splicing and protein domains on localization, complex member co-localization, cell-type-specific localization, as well as protein relocalization after growth factor inhibition. Our analysis provides information about the cellular architecture and complexity of the spatial organization of the proteome; we show that the majority of proteins have a single main subcellular location, that alternative splicing rarely affects subcellular location, and that cell types are best distinguished by expression of proteins exposed to the surrounding environment. The resource is freely accessible via www.subcellbarcode.org.

Novel Multiomics Profiling of Human Carotid Atherosclerotic Plaques and Plasma Reveals Biliverdin Reductase B as a Marker of Intraplaque Hemorrhage.

Clinical tools to identify individuals with unstable atherosclerotic lesions are required to improve prevention of myocardial infarction and ischemic stroke. Here, a systems-based analysis of atherosclerotic plaques and plasma from patients undergoing carotid endarterectomy for stroke prevention was used to identify molecular signatures with a causal relationship to disease. Local plasma collected in the lesion proximity following clamping prior to arteriotomy was profiled together with matched peripheral plasma. This translational workflow identified biliverdin reductase B as a novel marker of intraplaque hemorrhage and unstable carotid atherosclerosis, which should be investigated as a potential predictive biomarker for cardiovascular events in larger cohorts.

Metabolic reprogramming of acute lymphoblastic leukemia cells in response to glucocorticoid treatment.

Glucocorticoids (GCs) are metabolic hormones with immunosuppressive effects that have proven effective drugs against childhood acute lymphoblastic leukemia (ALL). Yet, the role of metabolic reprogramming in GC-induced ALL cell death is poorly understood. GCs efficiently block glucose uptake and metabolism in ALL cells, but this does not fully explain the observed induction of autophagy and cell death. Here, we have performed parallel time-course proteomics, metabolomics, and isotope-tracing studies to examine in detail the metabolic effects of GCs on ALL cells. We observed metabolic events associated with growth arrest, autophagy, and catabolism prior to onset of apoptosis: nucleotide de novo synthesis was reduced, while certain nucleobases accumulated; polyamine synthesis was inhibited; and phosphatidylcholine synthesis was induced. GCs suppressed not only glycolysis but also entry of both glucose and glutamine into the TCA cycle. In contrast, expression of glutamine-ammonia ligase (GLUL) and cellular glutamine content was robustly increased by GC treatment, suggesting induction of glutamine synthesis, similar to nutrient-starved muscle. Modulating medium glutamine and dimethyl-α-ketoglutarate (dm-αkg) to favor glutamine synthesis reduced autophagosome content of ALL cells, and dm-αkg also rescued cell viability. These data suggest that glutamine synthesis affects autophagy and possibly onset of cell death in response to GCs, which should be further explored to understand mechanism of action and possible sources of resistance.

An antisense RNA capable of modulating the expression of the tumor suppressor microRNA-34a.

The microRNA-34a is a well-studied tumor suppressor microRNA (miRNA) and a direct downstream target of TP53 with roles in several pathways associated with oncogenesis, such as proliferation, cellular growth, and differentiation. Due to its broad tumor suppressive activity, it is not surprising that miR34a expression is altered in a wide variety of solid tumors and hematological malignancies. However, the mechanisms by which miR34a is regulated in these cancers is largely unknown. In this study, we find that a long noncoding RNA transcribed antisense to the miR34a host gene, is critical for miR34a expression and mediation of its cellular functions in multiple types of human cancer. We name this long noncoding RNA lncTAM34a, and characterize its ability to facilitate miR34a expression under different types of cellular stress in both TP53-deficient and wild-type settings.

Publisher Correction: Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow.

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Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow.

Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.