Proteomic Landscape Research Articles

Deciphering the Proteomic Landscape of Mycobacterium tuberculosis in Response to Acid and Oxidative Stresses

The fundamental to the pathogenicity of Mycobacterium tuberculosis (Mtb) is the modulation in the control mechanisms that play a role in sensing and counteracting the microbicidal milieu encompassing various cellular stresses inside the human host. To understand such changes, we measured the cellular proteome of Mtb subjected to different stresses using a quantitative proteomics approach. We identified defined sets of Mtb proteins that are modulated in response to acid and a sublethal dose of diamide and H2O2 treatments. Notably, proteins involved in metabolic, catalytic, and binding functions are primarily affected under these stresses. Moreover, our analysis led to the observations that during acidic stress Mtb enters into energy-saving mode simultaneously modulating the acid tolerance system, whereas under diamide and H2O2 stresses, there were prominent changes in the biosynthesis and homeostasis pathways, primarily modifying the resistance mechanism in diamide-treated bacteria while causing metabolic arrest in H2O2-treated bacilli. Overall, we delineated the adaptive mechanisms that Mtb may utilize under physiological stresses and possible overlap between the responses to these stress conditions. In addition to offering important protein signatures that can be exploited for future mechanistic studies, our study highlights the importance of proteomics in understanding complex adjustments made by the human pathogen during infection.

Quantitative proteomic landscapes of primary and recurrent glioblastoma reveal a protumorigeneic role for FBXO2-dependent glioma-microenvironment interactions.

Recent efforts have described the evolution of glioblastoma from initial diagnosis to post-treatment recurrence on a genomic and transcriptomic level. However, the evolution of the proteomic landscape is largely unknown. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to characterize the quantitative proteomes of two independent cohorts of paired newly diagnosed and recurrent glioblastomas. Recurrence-associated proteins were validated using immunohistochemistry and further studied in human glioma cell lines, orthotopic xenograft models, and human organotypic brain slice cultures. External spatial transcriptomic, single-cell, and bulk RNA sequencing data were analyzed to gain mechanistic insights. Although overall proteomic changes were heterogeneous across patients, we identified BCAS1, INF2, and FBXO2 as consistently upregulated proteins at recurrence and validated these using immunohistochemistry. Knockout of FBXO2 in human glioma cells conferred a strong survival benefit in orthotopic xenograft mouse models and reduced invasive growth in organotypic brain slice cultures. In glioblastoma patient samples, FBXO2 expression was enriched in the tumor infiltration zone and FBXO2-positive cancer cells were associated with synaptic signaling processes. These findings demonstrate a potential role of FBXO2-dependent glioma-microenvironment interactions to promote tumor growth. Furthermore, the published datasets provide a valuable resource for further studies.

Applications of single‐cell multi‐omics sequencing in deep understanding of brain diseases

AbstractIntroductionThe mammalian brain consists of intricate neural networks of millions to billions of highly differentiated and interconnected cells. Single‐cell sequencing (SCS), a newly developed technology, revolutionises our comprehension of the genomic, transcriptomic, proteomic and epigenomic landscapes of cells within the brain. With single‐cell sequencing technology, it's possible to profile brain cell type diversity, to elucidate the specific function, connectivity and state of brain cells and to reveal the neural complexity, functional organisation and dynamics of the brain, which provides novel data sources for exploration of brain development and diseases.MethodsIn this review, we described current single‐cell‐based methodologies used for single‐cell sequencing technology, and then summarised recent applications of this cutting‐edge technology in brain research, including cellular heterogeneity, development and disease mechanisms of the brain.ResultsSingle‐cell sequencing (SCS) has substantially advanced our knowledge of brain functions and diseases by enhancing the resolution of diverse cell subpopulations within the brain, identifying novel gene signatures and cell markers and shedding light upon functional differences and developmental trajectories.ConclusionDespite a large amount of work remains to be accomplished due to the complexity of the brain and the vast amount of single‐cell data, the prospects of single‐cell sequencing in deciphering brain intricacy and facilitating molecular/clinical/earlier diagnosis, targeted treatment, therapy assessment and prognosis of a wide range of brain diseases are promising.

A Designer Nanoparticle Platform for Controlled Intracellular Delivery of Bioactive Macromolecules: Inhibition of Ubiquitin-Specific Protease 7 in Breast Cancer Cells.

Biological therapeutics represent an increasing and critical component of newly approved drugs; however, the inability to deliver biologics intracellularly in a controlled manner remains a major limitation. We have developed a semi-synthetic, tunable phage-like particle (PLP) platform derived from bacteriophage λ. The shell surface can be decorated with small-molecule, biological and synthetic moieties, alone or in combination and in defined ratios. Here, we demonstrate that the platform can be used to deliver biological macromolecules intracellularly and in a controlled manner. Ubiquitin-specific protease 7 (USP7) is a deubiquitinating enzyme that has been widely recognized as an ideal target for the treatment of a variety of cancers. Recently, UbV.7.2, a novel biologic derived from the ubiquitin scaffold, was developed for inhibition of USP7, but issues remain in achieving efficient and controlled intracellular delivery of the biologic. We have shown that decoration of PLPs with trastuzumab (Trz), a HER2-targeted therapeutic used in the treatment of various cancers, results in specific targeting and uptake of Trz-PLPs into HER2-overexpressing breast cancer cells. By simultaneously decorating PLPs with Trz and UbV.7.2, we now show that these particles are also internalized by HER2-positive cells, thus providing a means for intracellular delivery of the biologic in a controlled fashion. Internalized particles retain USP7 inhibition activity of UbV.7.2 and alter the metabolic and proteomic landscapes of these cells. This study demonstrates that the λ "designer nanoparticles" represent a powerful system for the intracellular delivery of biologics in a defined dose.

Biomarkers of mitochondrial origin: a futuristic cancer diagnostic.

Cancer is a highly fatal disease without effective early-stage diagnosis and proper treatment. Along with the oncoproteins and oncometabolites, several organelles from cancerous cells are also emerging as potential biomarkers. Mitochondria isolated from cancer cells are one such biomarker candidates. Cancerous mitochondria exhibit different profiles compared with normal ones in morphology, genomic, transcriptomic, proteomic and metabolic landscape. Here, the possibilities of exploring such characteristics as potential biomarkers through single-cell omics and Artificial Intelligence (AI) are discussed. Furthermore, the prospects of exploiting the biomarker-based diagnosis and its futuristic utilization through circulatory tumor cell technology are analyzed. A successful alliance of circulatory tumor cell isolation protocols and a single-cell omics platform can emerge as a next-generation diagnosis and personalized treatment procedure.

Charting the proteome landscape in major psychiatric disorders: From biomarkers to biological pathways towards drug discovery

Schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) are major mental disorders that affect a significant proportion of the global population. Advancing our knowledge of the pathophysiology of these disorders and identifying biomarkers are urgent needs for developing objective diagnostic tests and new therapeutics. In this study, we performed a systematic review and then extracted, curated, and analyzed proteomics data from published studies, aiming to assess the proteome in peripheral blood of individuals with SZ, BD, or MDD. Then, we performed pathway and network analyses to illuminate the biological themes concatenated by the differentially expressed proteins by systematically interrogating the literature to uncover biological pathways with more robust biological meaning. We identified 486 differentially expressed proteins from 51 studies across the three disorders with 9,423 participants. The great majority of pathways were common to SZ, BD, and MDD. They were related to the immune system, including signaling by interleukins, Toll-like receptor signaling pathway, and complement cascade, and to signal transduction, notably MAPK1/MAPK3 signaling, PI3K-Akt Signaling Pathway, Focal Adhesion-PI3K-Akt-mTOR-signaling, rhodopsin-like receptors, GPCR signaling, and the JAK-STAT signaling pathway. Other shared pathways included advanced glycosylation end-product receptor signaling, Regulation of Insulin-like Growth Factor, cholesterol metabolism, and IL-17 signaling pathway. Pathways shared between SZ and BD were integrin cell-surface interactions, GRB2:SOS provides linkage to MAPK signaling for integrins, and syndecan interactions. Shared between BD and MDD were the NRF2 pathway and signaling by EGFR pathways. Our findings advance our understanding of the protein variations and associations with these disorders, which are useful for accelerating biomarker development and drug discovery.

Abstract 3074: (Phospho)proteomics profiling of patient-derived colon cancer organoids for the discovery of putative drug targets

Abstract Introduction: Colorectal cancer is the second cause of cancer related deaths worldwide, with the poor survival outcomes attributable to the presence of metastases. To tackle this problem, (phospho)proteomics analysis enables valuable insights into changes of protein expression and signalling in cancer that can be perturbed by drugs. To study mechanisms driving metastasis and perform subsequent drug testing, patient derived organoids (PDOs) are in development as preclinical models. PDOs are obtained by 3D culture of tumour tissue ex-vivo, which enables them to retain the heterogeneity and architecture of the tumor source. To identify putative drug targets for colon cancer metastasis, we performed comparative (phospho)proteomics analysis of metastatic colon tissues and their matched PDOs. Methods: (Phospho)proteomics profiling was performed on PDOs generated from 10 patients with colon metastases to the liver, 10 matched tumour tissues and 4 normal colon mucosa. Unsupervised analysis of the (phospho)proteomic landscape was used to identify differentially expressed genes and pathways in colon metastases and their matched PDOs, compared to normal colon mucosa. We focused on phosphosites, proteins and pathways showing consistently altered expression in tumour tissues and PDOs. Kinase-substrate enrichment analysis was used to identify aberrantly activated kinases, based on the abundance of phosphorylation on the substrates. Putative drugs were selected using the consensus expression response to multiple small molecule drugs across cell lines and conditions from the Library of Integrated Network-Based Cellular Signatures (LINCS) database. Drug treatment of drug candidates was performed using the MTT Cell Proliferation Assay. Results: Using the approach described above we identified 103 differentially expressed proteins and 236 phosphosites between tumour tissues and normals, which were also detected in PDOs, with overall high correlation of t statistics (0.6 Spearman’s rho) between tumor tissues and PDOs. MYC-targets, G2M checkpoints and E2F-targets were amongst the top positively enriched pathways in common, and the LINCS analysis identified multi-kinase inhibitor Nintedanib and NFKB pathway-targeting KIN0-260 as putative drugs for upregulated proteins. The kinase CSNK2A1 was overactivated in both groups, pointing towards the use of CK2 inhibitors for drug testing. Treatment at 5 days with Nintedanib and KIN001-260 on the PDOs resulted in significant reduction of cell viability compared with 5-FU. Conclusion: Our study provides evidence that PDOs recapitulate relevant tumor features at the proteomic and phosphoproteomic levels, supporting the utility of this ex-vivo model as a tool for drug sensitivity testing for metastatic colon cancer. Citation Format: Gina Faye Boot, Federica Panebianco, John Gallon, Charlotte Kiu Yan Ng, Salvatore Piscuoglio. (Phospho)proteomics profiling of patient-derived colon cancer organoids for the discovery of putative drug targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3074.

Abstract 1829: Characterization of factors affecting sensitivity and resistance to PRMT5 inhibition in glioblastoma

Abstract BACKGROUND: Glioblastoma (GBM) is a highly infiltrative and aggressive malignancy with few treatment options; all patients develop recurrence after initial therapy. Due to the dismal outcome of these patients, identification of GBM-specific targets for therapeutic development is urgently needed. PRMT5 is a protein arginine methyltransferase that catalyzes the symmetric dimethylation of arginine residues within histones marks, resulting in chromatin restructuring, which in turn promotes oncogenic processes. PRMT5 inhibition has shown efficacy against multiple malignancies; MTAP loss has been associated with increased sensitivity to PRMT5 inhibitors. Here, we examined the effects of pharmacological abrogation of PRMT5 function using highly specific, brain penetrant, orally bioavailable inhibitors and assessed the role of MTAP and p53 expression on sensitivity to these agents. MATERIALS AND METHODS: Using pharmacological inhibition of PRMT5 using with the highly specific inhibitors PRT808 and PRT811, we examined their effects on apoptosis, cell proliferation, cell cycle distribution, and methylation markers in patient-derived glioma stem-like cells (GSC) with epigenetic and genetic signaling. Additional studies to identify transcriptomic (RNA-seq), and proteomic (RPPA) landscape related to PRMT5 in gliomas are ongoing. RESULTS: PRT808 and PRT811 induced potent reduction of symmetrical dimethylation (SDMA) protein marks in all GSC tested. However, treatment of GSC214 (mutant p53), GSC262 (mutant p53), GSC811 (truncated p53), and GSC11 (wild type p53) showed that wild type and truncated p53-expressing lines (GSC811 and GSC11) were more sensitive than GSC cell lines expressing mutant p53 (GSC214 and GSC262). There was no correlation between MTAP status and sensitivity to PRMT5 inhibition. In addition, PRMT5 inhibition resulted in reduced proliferation and alteration of several cell survival pathways; induction of apoptosis in GSC cell lines at late time points around 8-9 days after single dose treatment even though SDMA reduction occurred as early as 3 days. CONCLUSIONS: Our results demonstrate pharmacological PRMT5 inhibition induced SDMA reduction and late apoptosis in genetically and epigenetically heterogeneous patient-derived GSC lines and that mutant p53 lines are less sensitive to PRMT5 inhibition. Additional studies related to splicing defects upon PRMT5 inhibition are ongoing and will be presented at the meeting. Citation Format: Tsung-Lin (Gavin) Tsai. Characterization of factors affecting sensitivity and resistance to PRMT5 inhibition in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1829.

Abstract 2013: Integrated proteomic analysis identifies four distinct subtypes of high-risk neuroblastoma

Abstract Neuroblastoma is the most common solid extracranial tumor in children. Despite intensive multi-modal therapy, 5-year survival rates for patients with high-risk disease remain at approximately 50%. Neuroblastomas typically have low mutational burden and harbor few recurrent mutations making the identification of new therapeutic targets challenging. To characterize the proteomic landscape of high-risk neuroblastoma, we performed liquid chromatography-mass spectrometry-based deep expression proteomics and phosphoproteomics on 30 neuroblastoma tumors from 26 patients with high-risk disease. Our integrated analysis identified four distinct proteomic subgroups of high-risk neuroblastoma that were not otherwise apparent based on clinical or genomic features. The four subgroups were named based on their defining proteomic signature: C1-Mixed, C2-Neuronal, C3-Functional MYCN and C4-Stromal. Only one third of C3-Functional MYCN tumors had amplification of MYCN. Segmental chromosomal losses and gains were enriched in, but not exclusive to, C1-Mixed and C3-Functional MYCN tumors. The activities of multiple kinases including CDK2, CDK7 and MEK2 differed significantly between subgroups. C3-Functional MYCN and C4-Stromal tumors were enriched for immune and stromal cells, respectively. Focal adhesion signaling was specifically upregulated in C4-Stromal tumors suggesting increased extracellular matrix interactions in this tumor subgroup. C2-Neuronal tumors were enriched for axon guidance and neurotrophin signaling pathways. Rho family GTPase signaling was also evident in multiple tumor subgroups. C1-Mixed and C3-Functional MYCN tumors had elevated expression of RNA processing proteins which was associated with increased alternative splicing. Splicing analysis also identified multiple novel protein coding splice events that were shared amongst multiple neuroblastoma tumors and outliers compared to both the Genotype-Tissue Expression (GTEx) dataset and a panel of commercial reference tissues. Protein domain analysis of these novel splice variants suggested that these novel protein isoforms may have aberrant functions that contribute to tumorigenesis. In conclusion, phosphoproteomic analysis can identify candidate pathways for the development of new therapies for patients with high-risk neuroblastoma. Citation Format: Kristin L. Leskoske, Sara A. Byron, Seema Plaisier, Apurva M. Hegde, Krystine Garcia-Mansfield, Ritin Sharma, Genevieve Bergendahl, Abhinav Nagulapally, William Ferguson, Jaqueline Kraveka, Javier Oesterheld, William P. Hendricks, Giselle L. Saulnier Sholler, Jeffrey M. Trent, Patrick Pirrotte. Integrated proteomic analysis identifies four distinct subtypes of high-risk neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2013.

1281-P: Understanding the Interaction between Type 2 Diabetes and COVID-via Extracellular Vesicle Proteomic and Phosphoproteomic Signatures

Evidence supporting the involvement of EVs in the pathogenesis/severity of SARS-CoV-2 infection is starting to accumulate. However, little is known about their specific associations in the context of COVID-and type 2 diabetes interaction. Our study included 48 plasma samples (N=12/group) obtained from COVID-patients with and without diabetes and from patients with non-COVID-acute respiratory diagnosis (RSP) with and without diabetes. Participants were identified from a set of 494 patients hospitalized at AdventHealth in June-August 2020. Important efforts were made to ensure the homogeneity of the study cohort. Patients with type 1 diabetes, or pregnant, or that went directly into the ICU were excluded, and 4 balanced groups were identified after 10,000 random cohorts were generated and differences in age, gender, race, and ethnicity statistically assessed. EVs were isolated using EVTRAP (Tymora) . Mass spectrometry-based methods were used to detect the global EV proteome and phosphoproteome. Differentially expressed features, enriched pathways, and enriched tissue-specific protein sets were identified. Multidimensional scaling of all EV proteomic and phosphoproteomic data and unsupervised clustering of differentially expressed (absolute fold change ≥ 2, P < 0.05, FDR < 0.05) EV proteins and phosphoproteins successfully distinguished the 4 study groups with close to 100% accuracy. Importantly, we detected enriched pathway networks that suggest the potential therapeutic utility of PKC inhibitors such as bisindolylmaleimide IX, sotrastaurin, and enzastaumn, and inhibitors of ROCK1 such the isoquinoline derivative Fasudil. In conclusion, we characterized the proteomic landscape of the interaction between type 2 diabetes and COVID-and defined disease-specific EV proteomic signatures that provide insight into the disease pathobiology and druggable targets with potential clinical utility. Disclosure Y.O.Nunez lopez: None. A.Iliuk: None. A.Casu: None. D.S.Lupu: None. R.E.Pratley: Other Relationship; Bayer AG, Corcept Therapeutics, Dexcom, Inc., Hanmi Pharm. Co., Ltd., Merck & Co., Inc., Metavention, Novo Nordisk, Pfizer Inc., Poxel SA, Sanofi, Scohia Pharma Inc., Sun Pharmaceutical Industries Ltd.

Identification of exosome protein biomarkers in patients with advanced hormone receptor-positive breast cancer treated with palbociclib and tamoxifen.

e13014 Background: The combination of a CDK4/6 inhibitor (CDK4/6i) plus endocrine therapy (ET) doubles progression free survival compared with ET alone in hormone receptor (HR)-positive, advanced breast cancer (BC), although not all patients respond and responders eventually develop resistance and disease progression. Exosomes are membrane-bound extracellular vesicles that are released from tumors for cell-to-cell transfer of lipids, proteins, and nucleic acids. Analysis of exosome cargo provides a dynamic and functional read-out of biological pathways that are activated in cancer cells. We performed deep proteomic analysis of plasma exosomes from patients receiving palbociclib/tamoxifen to identify protein networks that predict response to CDK4/6i and ET and that may contribute to drug resistance. Methods: The Big Ten Cancer Research Consortium conducted a phase II trial of palbociclib plus tamoxifen as first line therapy for patients with advanced, HR+/HER2- BC (NCT02668666). Whole blood was collected in Streck tubes from all participants at baseline and at time points during study treatment. Plasma was separated and stored at -80C within 48 hours of collection. Exosome extraction and purification was optimized for maximum proteomic coverage. Proteins were labeled with tandem mass tag 10plex and quantified with ultrasensitive mass spectrometry. Detected proteins were mapped to pathways with the Reactome Pathway Database. An unsupervised machine learning approach with modified graphic neural networks was used to determine whether differential expression of protein networks in plasma exosomes predicts treatment response. Results: We detected more than 700 exosome proteins from100 μl plasma in 16 study participants (responders, n = 11; non-responders, n = 5). Significant enrichment of exosome-specific markers was observed when comparing patient samples with healthy donor samples. Exosomal protein networks in pretreatment samples predicted treatment response with 95% sensitivity and 85% specificity in unsupervised clustering. The top weighted protein networks in the treatment response model are enriched for membrane attack complex, complement activation and lipoprotein receptor binding pathways. Conclusions: Ultrasensitive proteomic analysis combined with deep learning methods provides a detailed picture of the proteome landscape of plasma exosomes in advanced breast cancer patients and is ideally suited for serial analyses to study emergence of resistance mechanisms. This approach also demonstrated unparalleled accuracy as a predictive biomarker to identify patients unlikely to respond to CDK4/6i and ET. If results are confirmed, this novel approach could hold great promise for identifying protein biomarkers and mechanisms of resistance that emerge during anticancer therapy. Clinical trial information: NCT02668666.

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape.

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Proteomics and Phosphoproteomics of Circulating Extracellular Vesicles Provide New Insights into Diabetes Pathobiology.

The purpose of this study was to define the proteomic and phosphoproteomic landscape of circulating extracellular vesicles (EVs) in people with normal glucose tolerance (NGT), prediabetes (PDM), and diabetes (T2DM). Archived serum samples from 30 human subjects (n = 10 per group, ORIGINS study, NCT02226640) were used. EVs were isolated using EVtrap®. Mass spectrometry-based methods were used to detect the global EV proteome and phosphoproteome. Differentially expressed features, correlation, enriched pathways, and enriched tissue-specific protein sets were identified using custom R scripts. Phosphosite-centric analyses were conducted using directPA and PhosR software packages. A total of 2372 unique EV proteins and 716 unique EV phosphoproteins were identified among all samples. Unsupervised clustering of the differentially expressed (fold change ≥ 2, p < 0.05, FDR < 0.05) proteins and, particularly, phosphoproteins showed excellent discrimination among the three groups. CDK1 and PKCδ appear to drive key upstream phosphorylation events that define the phosphoproteomic signatures of PDM and T2DM. Circulating EVs from people with diabetes carry increased levels of specific phosphorylated kinases (i.e., AKT1, GSK3B, LYN, MAP2K2, MYLK, and PRKCD) and could potentially distribute activated kinases systemically. Among characteristic changes in the PDM and T2DM EVs, “integrin switching” appeared to be a central feature. Proteins involved in oxidative phosphorylation (OXPHOS), known to be reduced in various tissues in diabetes, were significantly increased in EVs from PDM and T2DM, which suggests that an abnormally elevated EV-mediated secretion of OXPHOS components may underlie the development of diabetes. A highly enriched signature of liver-specific markers among the downregulated EV proteins and phosphoproteins in both PDM and T2DM groups was also detected. This suggests that an alteration in liver EV composition and/or secretion may occur early in prediabetes. This study identified EV proteomic and phosphoproteomic signatures in people with prediabetes and T2DM and provides novel insight into the pathobiology of diabetes.

Complement factor D as a predictor of Achilles tendon healing and long‐term patient outcomes

Dense connective tissue healing, such as tendon, is protracted leading to highly variable and unsatisfactory patient outcomes. Biomarkers prognostic of long-term clinical outcomes is, however, unknown. The present study was designed to investigate the proteomic profile of healing, identify potential biomarkers, and assess their association with the patient's long-term outcomes after ATR. Quantitative mass spectrometry analysis demonstrated 1423 proteins in healing and contralateral healthy Achilles tendons of 28 ATR patients. Comparing healing at 2weeks and healthy protein profiles, we identified 821 overlapping, 390 upregulated, and 17 downregulated proteins. Upregulated proteins are related mainly to extracellular matrix organization and metabolism, while downregulated pathways were associated with exocytosis in immune modulation and thrombosis formation. Further proteomic profiling in relation to validated patient outcomes revealed the downregulated pro-inflammatory complement factor D (CFD) as the most reliable predictive biomarker of successful tendon healing. Our finding showed a comprehensive proteomic landscape and bioinformatics on human connective tissue, indicating subtype-specific and shared biological processes and proteins in healing and healthy Achilles tendons, as well as in tendons related to good and poor patient outcomes. Inflammatory protein CFD and serpin family B member 1 were finally identified as potential predictive biomarkers of effective healing outcomes when combined the proteomic profiles with a validated clinical database. Following the future elucidation of the mechanisms associated with the identified biomarkers as predictors of good outcomes, our findings could lead to improved prognostic accuracy and development of targeted treatments, thus improving the long-term healing outcomes for all patients.

Proteomic Characterization of the Oral Pathogen Filifactor alocis Reveals Key Inter-Protein Interactions of Its RTX Toxin: FtxA

Filifactor alocis is a Gram-positive asaccharolytic, obligate anaerobic rod that has been isolated from a variety of oral infections including periodontitis, peri-implantitis, and odontogenic abscesses. As a newly emerging pathogen, its type strain has been investigated for pathogenic properties, yet little is known about its virulence variations among strains. We previously screened the whole genome of nine clinical oral isolates and a reference strain of F. alocis, and they expressed a novel RTX toxin, FtxA. In the present study, we aimed to use label-free quantification proteomics to characterize the full proteome of those ten F. alocis strains. A total of 872 proteins were quantified, and 97 among them were differentially expressed in FtxA-positive strains compared with the negative strains. In addition, 44 of these differentially expressed proteins formed 66 pairs of associations based on their predicted functions, which included clusters of proteins with DNA repair/mediated transformation and catalytic activity-related function, indicating different biosynthetic activities among strains. FtxA displayed specific interactions with another six intracellular proteins, forming a functional cluster that could discriminate between FtxA-producing and non-producing strains. Among them were FtxB and FtxD, predicted to be encoded by the same operon as FtxA. While revealing the broader qualitative and quantitative proteomic landscape of F. alocis, this study also sheds light on the deeper functional inter-relationships of FtxA, thus placing this RTX family member into context as a major virulence factor of this species.

The genomic and proteomic landscape in oral lichen planus versus oral squamous cell carcinoma: a scoping review.

Oral lichen planus (OLP), a World Health Organization (WHO)-classified oral potentially malignant condition, confers a 1% risk of transformation to oral squamous cell carcinoma (OSCC). There does not appear to be a consensus understanding of the underlying molecular events. This scoping review aimed to identify critical molecular pathways and highlight gaps in existing knowledge on malignant transformation in OLP. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines, a comprehensive literature search and methodical screening identified 61 relevant studies detailing molecular differences between OLP and OSCC. Molecular changes shared between OLP and OSCC included those affecting cellular proliferation (altered p53 expression, hypermethylation of p16/CDKN2A, MYC gains, increased ki-67), apoptosis (increased bcl-2 and survivin expression), extracellular matrix (ECM) remodeling (increased matrix metalloproteinase [MMP] expression), and transcriptional control (altered bmi1 and microRNA [miRNA] expression). In addition, some molecular alterations accumulated incrementally from control to OLP to OSCC or were present in higher-risk erosive variants of OLP or transformed OLP. Few studies included rigorous diagnostic inclusion criteria or unbiased discovery methods. Results of this review support the potentially malignant nature of OLP and imply that molecular events associated with malignant transformation may be heterogeneous. In addition, findings in this review highlight the need for additional studies using rigorous diagnostic inclusion criteria and unbiased discovery methods to further understand this process.

Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages

Proteogenomic analyses of hepatocellular carcinomas (HCC) have focused on early-stage, HBV-associated HCCs. Here we present an integrated proteogenomic analysis of HCCs across clinical stages and etiologies. Pathways related to cell cycle, transcriptional and translational control, signaling transduction, and metabolism are dysregulated and differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. We describe candidate copy number-driven driver genes involved in epithelial-to-mesenchymal transition, the Wnt-β-catenin, AKT/mTOR and Notch pathways, cell cycle and DNA damage regulation. The targetable aurora kinase A and CDKs are upregulated. CTNNB1 and TP53 mutations are associated with altered protein phosphorylation related to actin filament organization and lipid metabolism, respectively. Integrative proteogenomic clusters show that HCC constitutes heterogeneous subgroups with distinct regulation of biological processes, metabolic reprogramming and kinase activation. Our study provides a comprehensive overview of the proteomic and phophoproteomic landscapes of HCCs, revealing the major pathways altered in the (phospho)proteome.

Single‐Cell Reconstruction of Cellular Heterogeneity of Congenital Heart Disease

Congenital heart disease (CHD) involves cardiovascular malformations and, are one of the most common type of birth defect. The estimated prevalence ranges from ~1‐3% of live births and it causes significant mortality worldwide. Although etiology and pathophysiology of CHD remains elusive, genetic factors are known to be a major contributor. In this study, we aim at deciphering the genomic, transcriptomic, and proteomic landscape of the mutations associated with CHD. We collected 14209 SNVs, and 63 CNVs representing a sample size of 3,408 individuals, from 58 different articles published between January 2000 and December 2020. We identified 6,641 genes impacted by these mutations of which the MYH6, GATA6, NOTCH1, OBSCN and PTPN11 harbour the most number of recurrent mutations. We observed a high prevalence of early onset and male subjects with CHD, carrying a mutation. Stringent downstream meta‐analysis will be performed on this preliminary dataset. We plan to first comprehensively annotate the collected mutations using ANNOVAR and GenomeArc Analytics. The mutations will be then classified on the basis of American College of Medical Genetics (ACMG) guidelines to retain clinically relevant (pathogenic, likely pathogenic and variant of unknown significance) rare mutations. Next, we will analyse the mutation hotspots using 3D protein structures to determine domains which are most affected by these mutations. Furthermore, we will investigate the spatiotemporal developmental (prenatal to adult) human heart single‐cell OMICs (transcriptome and proteome) datasets in order to identify CHD associated cell types. Our analysis will detect cell types where marker genes are enriched with clinically relevant mutations. Our study aims to uncover the genetic and cellular heterogeneity of CHD which will aid precision diagnosis and therapeutics.

Genomic and transcriptomic analysis of a library of small cell lung cancer patient-derived xenografts

Access to clinically relevant small cell lung cancer (SCLC) tissue is limited because surgical resection is rare in metastatic SCLC. Patient-derived xenografts (PDX) and circulating tumor cell-derived xenografts (CDX) have emerged as valuable tools to characterize SCLC. Here, we present a resource of 46 extensively annotated PDX/CDX models derived from 33 patients with SCLC. We perform multi-omic analyses, using targeted tumor next-generation sequencing, RNA-sequencing, and immunohistochemistry to deconvolute the mutational landscapes, global expression profiles, and molecular subtypes of these SCLC models. SCLC subtypes characterized by transcriptional regulators, ASCL1, NEUROD1 and POU2F3 are confirmed in this cohort. A subset of SCLC clinical specimens, including matched PDX/CDX and clinical specimen pairs, confirm that the primary features and genomic and proteomic landscapes of the tumors of origin are preserved in the derivative PDX models. This resource provides a powerful system to study SCLC biology.

Analysis of human brain tissue derived from DBS surgery

BackgroundTranscriptomic and proteomic profiling of human brain tissue is hindered by the availability of fresh samples from living patients. Postmortem samples usually represent the advanced disease stage of the patient. Furthermore, the postmortem interval can affect the transcriptomic and proteomic profiles. Therefore, fresh brain tissue samples from living patients represent a valuable resource of metabolically intact tissue. Implantation of deep brain stimulation (DBS) electrodes into the human brain is a neurosurgical treatment for, e.g., movement disorders. Here, we describe an improved approach to collecting brain tissues from surgical instruments used in implantation of DBS device for transcriptomics and proteomics analyses.MethodsSamples were extracted from guide tubes and recording electrodes used in routine DBS implantation procedure to treat patients with Parkinson’s disease, genetic dystonia and tremor. RNA sequencing was performed in tissues extracted from the recording microelectrodes and liquid chromatography-mass spectrometry (LC-MS) performed in tissues from guide tubes. To assess the performance of the current approach, the obtained datasets were compared with previously published datasets representing brain tissues.ResultsAltogether, 32,034 RNA transcripts representing the unique Ensembl gene identifiers were detected from eight samples representing both hemispheres of four patients. By using LC-MS, we identified 734 unique proteins from 31 samples collected from 14 patients. The datasets are available in the BioStudies database (accession number S-BSST667). Our results indicate that surgical instruments used in DBS installation retain brain material sufficient for protein and gene expression studies. Comparison with previously published datasets obtained with similar approach proved the robustness and reproducibility of the protocol.ConclusionsThe instruments used during routine DBS surgery are a useful source for obtaining fresh brain tissues from living patients. This approach overcomes the issues that arise from using postmortem tissues, such as the effect of postmortem interval on transcriptomic and proteomic landscape of the brain, and can be used for studying molecular aspects of DBS-treatable diseases.