Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis

Proteomic Profiling of Serum Extracellular Vesicles Identifies Diagnostic Signatures and Therapeutic Targets in Breast Cancer

Analysis of extracellular vesicles (EV) is a promising noninvasive liquid biopsy approach for breast cancer detection, prognosis, and therapeutic monitoring. A comprehensive understanding of the characteristics and proteomic composition of breast cancer-specific EVs from human samples is required to realize the potential of this strategy. In this study, we applied a mass spectrometry-based, data-independent acquisition proteomic approach to characterize human serum EVs derived from patients with breast cancer (n = 126) and healthy donors (n = 70) in a discovery cohort and validated the findings in five independent cohorts. Examination of the EV proteomes enabled the construction of specific EV protein classifiers for diagnosing breast cancer and distinguishing patients with metastatic disease. Of note, TALDO1 was found to be an EV biomarker of distant metastasis of breast cancer. In vitro and in vivo analysis confirmed the role of TALDO1 in stimulating breast cancer invasion and metastasis. Finally, high-throughput molecular docking and virtual screening of a library consisting of 271,380 small molecules identified a potent TALDO1 allosteric inhibitor, AO-022, which could inhibit breast cancer migration in vitro and tumor progression in vivo. Together, this work elucidates the proteomic alterations in the serum EVs of breast cancer patients to guide the development of improved diagnosis, monitoring, and treatment strategies. Significance: Characterization of the proteomic composition of circulating extracellar vesicles in breast cancer patients identifies signatures for diagnosing primary and metastatic tumors and reveals tumor-promoting cargo that can be targeted to improve outcomes.

Proteogenomic characterization of skull-base chordoma

Skull-base chordoma is a rare, aggressive bone cancer with a high recurrence rate. Despite advances in genomic studies, its molecular characteristics and effective therapies remain unknown. Here, we conduct integrative genomics, transcriptomics, proteomics, and phosphoproteomics analyses of 187 skull-base chordoma tumors. In our study, chromosome instability is identified as a prognostic predictor and potential therapeutic target. Multi-omics data reveals downstream effects of chromosome instability, with RPRD1B as a putative target for radiotherapy-resistant patients. Chromosome 1q gain, associated with chromosome instability and upregulated mitochondrial functions, lead to poorer clinical outcomes. Immune subtyping identify an immune cold subtype linked to chromosome 9p/10q loss and immune evasion. Proteomics-based classification reveals subtypes (P-II and P-III) with high chromosome instability and immune cold features, with P-II tumors showing increased invasiveness. These findings, confirmed in 17 paired samples, provide insights into the biology and treatment of skull-base chordoma.

Comprehensive Proteogenomic Profiling Reveals the Molecular Characteristics of Colorectal Cancer at Distinct Stages of Progression

Colorectal cancer is the second most common malignant tumor worldwide. Analysis of the changes that occur during colorectal cancer progression could provide insights into the molecular mechanisms driving colorectal cancer development and identify improved treatment strategies. In this study, we performed an integrated multiomic analysis of 435 trace tumor samples from 148 patients with colorectal cancer, covering nontumor, intraepithelial neoplasia (IEN), infiltration, and advanced stage colorectal cancer phases. Proteogenomic analyses demonstrated that KRAS and BRAF mutations were mutually exclusive and elevated oxidative phosphorylation in the IEN phase. Chr17q loss and chr20q gain were also mutually exclusive, which occurred predominantly in the IEN and infiltration phases, respectively, and impacted the cell cycle. Mutations in TP53 were frequent in the advanced stage colorectal cancer phase and associated with the tumor microenvironment, including increased extracellular matrix rigidity and stromal infiltration. Analysis of the profiles of colorectal cancer based on consensus molecular subtype and colorectal cancer intrinsic subtype classifications revealed the progression paths of each subtype and indicated that microsatellite instability was associated with specific subtype classifications. Additional comparison of molecular characteristics of colorectal cancer based on location showed that ANKRD22 amplification by chr10q23.31 gain enhanced glycolysis in the right-sided colorectal cancer. The AOM/DSS-induced colorectal cancer carcinogenesis mouse model indicated that DDX5 deletion due to chr17q loss promoted colorectal cancer development, consistent with the findings from the patient samples. Collectively, this study provides an informative resource for understanding the driving events of different stages of colorectal cancer and identifying the potential therapeutic targets. Significance: Characterization of the proteogenomic landscape of colorectal cancer during progression provides a multiomic map detailing the alterations in each stage of carcinogenesis and suggesting potential diagnostic and therapeutic approaches for patients.

quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data

The volume of public proteomics data is rapidly increasing, causing a computational challenge for large-scale reanalysis. Here, we introduce quantms ( https://quant,ms.org/ ), an open-source cloud-based pipeline for massively parallel proteomics data analysis. We used quantms to reanalyze 83 public ProteomeXchange datasets, comprising 29,354 instrument files from 13,132 human samples, to quantify 16,599 proteins based on 1.03 million unique peptides. quantms is based on standard file formats improving the reproducibility, submission and dissemination of the data to ProteomeXchange.

The relationship between resistance evolution and carbon metabolism in Staphylococcus xylosus under ceftiofur sodium stress

Staphylococcus xylosus has emerged as a bovine mastitis pathogen with increasing drug resistance, resulting in substantial economic impacts. This study utilized iTRAQ analysis to investigate the mechanisms driving resistance evolution in S. xylosus under ceftiofur sodium stress. Findings revealed notable variations in the expression of 143 proteins, particularly glycolysis-related proteins (TpiA, Eno, GlpD, Ldh) and peptidoglycan (PG) hydrolase Atl. Following the induction of ceftiofur sodium resistance in S. xylosus, the emergence of resistant strains displaying characteristics of small colony variants (SCVs) was observed. The transcript levels of TpiA, Eno, GlpD and Ldh were up-regulated, TCA cycle proteins (ICDH, MDH) and Atl were down-regulated, lactate content was increased, and NADH concentration was decreased in SCV compared to the wild strain. That indicates a potential role of carbon metabolism, specifically PG hydrolysis, glycolysis, and the TCA cycle, in the development of resistance to ceftiofur sodium in S. xylosus.

Comprehensive proteomic characterization of urethral stricture disease in the Chinese population

Background

Male urethral stricture disease (USD) is predominantly characterized by scar formation. There are few effective therapeutic drugs, and comprehensive molecular characterizations of USD formation remain undefined.

Methods

The proteomic profiling of twelve scar tissues and five matched normal adjacent tissues (NATs). Proteomic analysis methods were applied to explore the molecular characterizations of USD formation, including uncovering mechanistic pathways and providing novel biomarkers for scar formation.

Results

Comparative proteomic analysis showed that the extracellular matrix (ECM) and complement cascade signaling were predominant in scar tissues. COL11A1 and CD248 significantly contributed to the accumulation of ECM components. Our study presented diverse molecular mechanisms of scar formation across different ages and suggested the potential effects of PXK in Age 1 (<45) patients. Furthermore, immune infiltration studies indicated the therapeutic potential of inhibiting the complement system (C4A, C4B) in Age 2 (≥45) patients, providing a potential clinical strategy for USD.

Conclusion

This study illustrated the pathogenesis of USD formation and the diverse characteristics of USD patients with different ages, enhancing our understanding of the disease's pathogenesis and providing a valuable resource for USD treatment.

Proteogenomic insights into the biology and treatment of pan-melanoma

Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.

Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current tumor-node-metastasis or Veterans Administration Lung Study Group staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent cohort, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggested potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better progression-free survival and overall survival after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Integrative multiomics analysis identifies molecular subtypes and potential targets of hepatocellular carcinoma

BACKGROUND

The liver is anatomically divided into eight segments based on the distribution of Glisson's triad. However, the molecular mechanisms underlying each segment and its association with hepatocellular carcinoma (HCC) heterogeneity are not well understood. In this study, our objective is to conduct a comprehensive multiomics profiling of the segmentation atlas in order to investigate potential subtypes and therapeutic approaches for HCC.

METHODS

A high throughput liquid chromatography-tandem mass spectrometer strategy was employed to comprehensively analyse proteome, lipidome and metabolome data, with a focus on segment-resolved multiomics profiling. To classify HCC subtypes, the obtained data with normal reference profiling were integrated. Additionally, potential therapeutic targets for HCC were identified using immunohistochemistry assays. The effectiveness of these targets were further validated through patient-derived organoid (PDO) assays.

RESULTS

A multiomics profiling of 8536 high-confidence proteins, 1029 polar metabolites and 3381 nonredundant lipids was performed to analyse the segmentation atlas of HCC. The analysis of the data revealed that in normal adjacent tissues, the left lobe was primarily involved in energy metabolism, while the right lobe was associated with small molecule metabolism. Based on the normal reference atlas, HCC patients with segment-resolved classification were divided into three subtypes. The C1 subtype showed enrichment in ribosome biogenesis, the C2 subtype exhibited an intermediate phenotype, while the C3 subtype was closely associated with neutrophil degranulation. Furthermore, using the PDO assay, exportin 1 (XPO1) and 5-lipoxygenase (ALOX5) were identified as potential targets for the C1 and C3 subtypes, respectively.

CONCLUSION

Our extensive analysis of the segmentation atlas in multiomics profiling defines molecular subtypes of HCC and uncovers potential therapeutic strategies that have the potential to enhance the prognosis of HCC.

Itaconate alleviates diet-induced obesity via activation of brown adipocyte thermogenesis

Despite medical advances, there remains an unmet need for better treatment of obesity. Itaconate, a product of the decarboxylation of the tricarboxylic acid cycle intermediate cis-aconitate, plays a regulatory role in both metabolism and immunity. Here, we show that itaconate, as an endogenous compound, counteracts high-fat-diet (HFD)-induced obesity through leptin-independent mechanisms in three mouse models. Specifically, itaconate reduces weight gain, reverses hyperlipidemia, and improves glucose tolerance in HFD-fed mice. Additionally, itaconate enhances energy expenditure and the thermogenic capacity of brown adipose tissue (BAT). Unbiased proteomic analysis reveals that itaconate upregulates key proteins involved in fatty acid oxidation and represses the expression of lipogenic genes. Itaconate may provoke a major metabolic reprogramming by inducing fatty acid oxidation and suppression of fatty acid synthesis in BAT. These findings highlight itaconate as a potential activator of BAT-mediated thermogenesis and a promising candidate for anti-obesity therapy.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

PhosMap: An ensemble bioinformatic platform to empower interactive analysis of quantitative phosphoproteomics

BACKGROUND

Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application.

METHODS

Here, we develop PhosMap, a versatile and scalable tool to accomplish phosphoproteomics data analysis. A standardized phosphorylation data format was created for data analyses, from data preprocessing to downstream bioinformatic analyses such as dimension reduction, differential phosphorylation analysis, kinase activity, survival analysis, and so on. For better usability, we distribute PhosMap as a Docker image for easy local deployment upon any of Windows, Linux, and Mac system.

RESULTS

The source code is deposited at https://github.com/BADD-XMU/PhosMap. A free PhosMap webserver (https://huggingface.co/spaces/Bio-Add/PhosMap), with easy-to-follow fashion of dashboards, is curated for interactive data analysis.

CONCLUSIONS

PhosMap fills the technical gap of large-scale phosphorylation research by empowering researchers to process their own phosphoproteomics data expediently and efficiently, and facilitates better data interpretation.

Proteomic Characterization Identifies Clinically Relevant Subgroups of Gastrointestinal Stromal Tumors

BACKGROUND & AIMS

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract, and it has high metastatic and recurrence rates. We aimed to characterize the proteomic features of GIST to understand biological processes and treatment vulnerabilities.

METHODS

Quantitative proteomics and phosphoproteomics analyses were performed on 193 patients with GIST to reveal the biological characteristics of GIST. Data-driven hypotheses were tested by performing functional experiments using both GIST cell lines and xenograft mouse models.

RESULTS

Proteomic analysis revealed differences in the molecular features of GISTs from different locations or with different histological grades. MAPK7 was identified and functionally proved to be associated with tumor cell proliferation in GIST. Integrative analysis revealed that increased SQSTM1 expression inhibited the patient response to imatinib mesylate. Proteomics subtyping identified 4 clusters of tumors with different clinical and molecular attributes. Functional experiments confirmed the role of SRSF3 in promoting tumor cell proliferation and leading to poor prognosis.

CONCLUSIONS

Our study provides a valuable data resource and highlights potential therapeutic approaches for GIST.

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma

Soft tissue sarcoma is a broad family of mesenchymal malignancies exhibiting remarkable histological diversity. We portray the proteomic landscape of 272 soft tissue sarcomas representing 12 major subtypes. Hierarchical classification finds the similarity of proteomic features between angiosarcoma and epithelial sarcoma, and elevated expression of SHC1 in AS and ES is correlated with poor prognosis. Moreover, proteomic clustering classifies patients of soft tissue sarcoma into 3 proteomic clusters with diverse driven pathways and clinical outcomes. In the proteomic cluster featured with the high cell proliferation rate, APEX1 and NPM1 are found to promote cell proliferation and drive the progression of cancer cells. The classification based on immune signatures defines three immune subtypes with distinctive tumor microenvironments. Further analysis illustrates the potential association between immune evasion markers (PD-L1 and CD80) and tumor metastasis in soft tissue sarcoma. Overall, this analysis uncovers sarcoma-type-specific changes in proteins, providing insights about relationships of soft tissue sarcoma.

Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Evolutionary proteogenomic landscape from pre-invasive to invasive lung adenocarcinoma

Lung adenocarcinoma follows a stepwise progression from pre-invasive to invasive. However, there remains a knowledge gap regarding molecular events from pre-invasive to invasive. Here, we conduct a comprehensive proteogenomic analysis comprising whole-exon sequencing, RNA sequencing, and proteomic and phosphoproteomic profiling on 98 pre-invasive and 99 invasive lung adenocarcinomas. The deletion of chr4q12 contributes to the progression from pre-invasive to invasive adenocarcinoma by downregulating SPATA18, thus suppressing mitophagy and promoting cell invasion. Proteomics reveals diverse enriched pathways in normal lung tissues and pre-invasive and invasive adenocarcinoma. Proteomic analyses identify three proteomic subtypes, which represent different stages of tumor progression. We also illustrate the molecular characterization of four immune clusters, including endothelial cells, B cells, DCs, and immune depression subtype. In conclusion, this comprehensive proteogenomic study characterizes the molecular architecture and hallmarks from pre-invasive to invasive lung adenocarcinoma, guiding the way to a deeper understanding of the tumorigenesis and progression of this disease.

Epigenetic inhibition of CTCF by HN1 promotes dedifferentiation and stemness of anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is one of the deadliest cancers, whose important malignant feature is dedifferentiation. Chromatin remodeling is critical for tumorigenesis and progression, while its roles and regulator in facilitating dedifferentiation of ATC had been poorly understood. In our study, an emerging function of hematological and neurological expressed 1 (HN1) in promoting dedifferentiation of ATC cells was uncovered. HN1 expression was negatively correlated with the thyroid differentiation markers both at mRNA and protein level. Knockdown of HN1 in ATC cells effectively upregulated the thyroid differentiation markers and impeded the sphere formation capacity, accompanying with the loss of cancer stemness. In contrast, overexpression of HN1 drove the gain of stemness and the loss of thyroid differentiation markers. Nude mouse and zebrafish xenograft models showed that inhibition of HN1 in ATC cells effectively hindered tumor growth due to the loss of cancer stemness. Further study showed that HN1 was negatively correlated with CTCF in an independent thyroid-cancer cohort, and inhibition of HN1 enhanced the expression of CTCF in ATC cells. Overexpression of CTCF significantly reversed the dedifferentiation phenotypes of ATC cells, whereas simultaneously inhibiting HN1 and CTCF was unable to recover the level of thyroid differentiation markers. The combination of ATAC-seq and ChIP-seq analysis confirmed that CTCF regulated genes relating with thyroid gland development through influencing their chromatin accessibility. HN1 inhibited the acetylation of H3K27 at the promoter of CTCF by recruiting HDAC2, thereby inhibiting the transcriptional activation of CTCF. These findings demonstrated an essential role of HN1 in regulating the chromatin accessibility of thyroid differentiation genes during ATC dedifferentiation.

Proteogenomic Workflow for Characterization of Microphthalmia Transcription Factor (MiT) Family Translocation Renal Cell Carcinoma

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare, aggressive, and heterogeneous subtype of kidney cancer, which is not well characterized. Since genetic alterations are always associated with carcinogenesis, and proteins are the major executors of biological features, multi-omics studies can reveal the systematic tRCC biological process comprehensively. Here, we describe the proteogenomic workflow for characterization of tRCC in detail to provide the knowledge foundation for integrated proteogenomic analysis of tRCC and other malignant tumors in the future.

Proteomic characterization of the colorectal cancer response to chemoradiation and targeted therapies reveals potential therapeutic strategies

Chemoradiation and targeted therapies are the major treatments for colorectal cancer (CRC); however, molecular properties associated with therapy resistance are incompletely characterized. Here, we profile the proteome of 254 tumor tissues from patients with CRC undergoing chemotherapy, chemoradiation, or chemotherapy combined with targeted therapy. Proteome-based classification reveals four subtypes featured with distinct biological and therapeutic characteristics. The integrative analysis of CRC cell lines and clinical samples indicates that immune regulation is significantly associated with drug sensitivity. HSF1 can increase DNA damage repair and cell cycle, thus inducing resistance to radiation, while high expression of HDAC6 is negatively associated with response of cetuximab. Furthermore, we develop prognostic models with high accuracy to predict the therapeutic response, further validated by parallel reaction monitoring (PRM) assay in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemoradiation and targeted therapy in CRC.

Proteome profiling of early gestational plasma reveals novel biomarkers of congenital heart disease

Prenatal diagnosis of congenital heart disease (CHD) relies primarily on fetal echocardiography conducted at mid-gestational age-the sensitivity of which varies among centers and practitioners. An objective method for early diagnosis is needed. Here, we conducted a case-control study recruiting 103 pregnant women with healthy offspring and 104 cases with CHD offspring, including VSD (42/104), ASD (20/104), and other CHD phenotypes. Plasma was collected during the first trimester and proteomic analysis was performed. Principal component analysis revealed considerable differences between the controls and the CHDs. Among the significantly altered proteins, 25 upregulated proteins in CHDs were enriched in amino acid metabolism, extracellular matrix receptor, and actin skeleton regulation, whereas 49 downregulated proteins were enriched in carbohydrate metabolism, cardiac muscle contraction, and cardiomyopathy. The machine learning model reached an area under the curve of 0.964 and was highly accurate in recognizing CHDs. This study provides a highly valuable proteomics resource to better recognize the cause of CHD and has developed a reliable objective method for the early recognition of CHD, facilitating early intervention and better prognosis.

Identification of novel diagnostic panel for mild cognitive impairment and Alzheimer's disease: findings based on urine proteomics and machine learning

BACKGROUND

Alzheimer's disease is a prevalent disease with a heavy global burden. Proteomics is the systematic study of proteins and peptides to provide comprehensive descriptions. Aiming to obtain a more accurate and convenient clinical diagnosis, researchers are working for better biomarkers. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels.

METHODS

We firstly enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples, and conducted an LC-MS/MS analysis. In parallel, clinical data were collected, and clinical examinations were performed. After statistical and bioinformatics analyses, significant risk factors and differential urinary proteins were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM.

RESULTS

Fifty-seven AD patients, 43 MCI patients, and 62 CN subjects were enrolled. A total of 3366 proteins were identified, and 608 urine proteins were finally included in the analysis. There were 33 significantly differential proteins between the AD and CN groups and 15 significantly differential proteins between the MCI and CN groups. AD diagnostic panel included DDC, CTSC, EHD4, GSTA3, SLC44A4, GNS, GSTA1, ANXA4, PLD3, CTSH, HP, RPS3, CPVL, age, and APOE ε4 with an AUC of 0.9989 in the training test and 0.8824 in the test set while MCI diagnostic panel included TUBB, SUCLG2, PROCR, TCP1, ACE, FLOT2, EHD4, PROZ, C9, SERPINA3, age, and APOE ε4 with an AUC of 0.9985 in the training test and 0.8143 in the test set. Besides, diagnostic proteins were weakly correlated with cognitive functions.

CONCLUSIONS

In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN.

Single-Cell RNA Sequencing Provides New Insights into Therapeutic Roles of Thyroid Hormone in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive fatal interstitial lung disease without an effective cure. Herein, we explore the role of 3,5,3'-triiodothyronine (T3) administration on lung alveolar regeneration and fibrosis at the single-cell level. T3 supplementation significantly altered the gene expression in fibrotic lung tissues. Immune cells were rapidly recruited into the lung after the injury; there were much more M2 macrophages than M1 macrophages in the lungs of bleomycin-treated mice; and M1 macrophages increased slightly, whereas M2 macrophages were significantly reduced after T3 treatment. T3 enhanced the resolution of pulmonary fibrosis by promoting the differentiation of Krt8+ transitional alveolar type II epithelial cells into alveolar type I epithelial cells and inhibiting fibroblast activation and extracellular matrix production potentially by regulation of Nr2f2. In addition, T3 regulated the crosstalk of macrophages with fibroblasts, and the Pros1-Axl signaling axis significantly facilitated the attenuation of fibrosis. The findings demonstrate that administration of a thyroid hormone promotes alveolar regeneration and resolves fibrosis mainly by regulation of the cellular state and cell-cell communication of alveolar epithelial cells, macrophages, and fibroblasts in mouse lungs in comprehensive ways.

Plasma proteomic profiling discovers molecular features associated with upper tract urothelial carcinoma

Upper tract urothelial carcinoma (UTUC) is often diagnosed late and exhibits poor prognosis. Limited data are available on potential non-invasive biomarkers for disease monitoring. Here, we investigate the proteomic profile of plasma in 362 UTUC patients and 239 healthy controls. We present an integrated tissue-plasma proteomic approach to infer the signature proteins for identifying patients with muscle-invasive UTUC. We discover a protein panel that reflects lymph node metastasis, which is of interest in identifying UTUC patients with high risk and poor prognosis. We also identify a ten-protein classifier and establish a progression clock predicting progression-free survival of UTUC patients. Finally, we further validate the signature proteins by parallel reaction monitoring assay in an independent cohort. Collectively, this study portrays the plasma proteomic landscape of a UTUC cohort and provides a valuable resource for further biological and diagnostic research in UTUC.

Proteogenomics of different urothelial bladder cancer stages reveals distinct molecular features for papillary cancer and carcinoma in situ

The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics

BACKGROUND

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories.

RESULTS

Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics.

CONCLUSION

Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method

BACKGROUND

Batch effects are notoriously common technical variations in multiomics data and may result in misleading outcomes if uncorrected or over-corrected. A plethora of batch-effect correction algorithms are proposed to facilitate data integration. However, their respective advantages and limitations are not adequately assessed in terms of omics types, the performance metrics, and the application scenarios.

RESULTS

As part of the Quartet Project for quality control and data integration of multiomics profiling, we comprehensively assess the performance of seven batch effect correction algorithms based on different performance metrics of clinical relevance, i.e., the accuracy of identifying differentially expressed features, the robustness of predictive models, and the ability of accurately clustering cross-batch samples into their own donors. The ratio-based method, i.e., by scaling absolute feature values of study samples relative to those of concurrently profiled reference material(s), is found to be much more effective and broadly applicable than others, especially when batch effects are completely confounded with biological factors of study interests. We further provide practical guidelines for implementing the ratio based approach in increasingly large-scale multiomics studies.

CONCLUSIONS

Multiomics measurements are prone to batch effects, which can be effectively corrected using ratio-based scaling of the multiomics data. Our study lays the foundation for eliminating batch effects at a ratio scale.

Hierarchical helical carbon nanotube fibre as a bone-integrating anterior cruciate ligament replacement

High rates of ligament damage require replacements; however, current synthetic materials have issues with bone integration leading to implant failure. Here we introduce an artificial ligament that has the required mechanical properties and can integrate with the host bone and restore movement in animals. The ligament is assembled from aligned carbon nanotubes formed into hierarchical helical fibres bearing nanometre and micrometre channels. Osseointegration of the artificial ligament is observed in an anterior cruciate ligament replacement model where clinical polymer controls showed bone resorption. A higher pull-out force is found after a 13-week implantation in rabbit and ovine models, and animals can run and jump normally. The long-term safety of the artificial ligament is demonstrated, and the pathways involved in integration are studied.

Celastrol Combats Methicillin-Resistant Staphylococcus aureus by Targeting Δ1 -Pyrroline-5-Carboxylate Dehydrogenase

The emergence and rapid spread of methicillin-resistant Staphylococcus aureus (MRSA) raise a critical need for alternative therapeutic options. New antibacterial drugs and targets are required to combat MRSA-associated infections. Based on this study, celastrol, a natural product from the roots of Tripterygium wilfordii Hook. f., effectively combats MRSA in vitro and in vivo. Multi-omics analysis suggests that the molecular mechanism of action of celastrol may be related to Δ1 -pyrroline-5-carboxylate dehydrogenase (P5CDH). By comparing the properties of wild-type and rocA-deficient MRSA strains, it is demonstrated that P5CDH, the second enzyme of the proline catabolism pathway, is a tentative new target for antibacterial agents. Using molecular docking, bio-layer interferometry, and enzyme activity assays, it is confirmed that celastrol can affect the function of P5CDH. Furthermore, it is found through site-directed protein mutagenesis that the Lys205 and Glu208 residues are key for celastrol binding to P5CDH. Finally, mechanistic studies show that celastrol induces oxidative stress and inhibits DNA synthesis by binding to P5CDH. The findings of this study indicate that celastrol is a promising lead compound and validate P5CDH as a potential target for the development of novel drugs against MRSA.

Investigating phase separation properties of chromatin-associated proteins using gradient elution of 1,6-hexanediol

BACKGROUND

Chromatin-associated phase separation proteins establish various biomolecular condensates via liquid-liquid phase separation (LLPS), which regulates vital biological processes spatially and temporally. However, the widely used methods to characterize phase separation proteins are still based on low-throughput experiments, which consume time and could not be used to explore protein LLPS properties in bulk.

RESULTS

By combining gradient 1,6-hexanediol (1,6-HD) elution and quantitative proteomics, we developed chromatin enriching hexanediol separation coupled with liquid chromatography-mass spectrometry (CHS-MS) to explore the LLPS properties of different chromatin-associated proteins (CAPs). First, we found that CAPs were enriched more effectively in the 1,6-HD treatment group than in the isotonic solution treatment group. Further analysis showed that the 1,6-HD treatment group could effectively enrich CAPs prone to LLPS. Finally, we compared the representative proteins eluted by different gradients of 1,6-HD and found that the representative proteins of the 2% 1,6-HD treatment group had the highest percentage of IDRs and LCDs, whereas the 10% 1,6-HD treatment group had the opposite trend.

CONCLUSION

This study provides a convenient high-throughput experimental method called CHS-MS. This method can efficiently enrich proteins prone to LLPS and can be extended to explore LLPS properties of CAPs in different biological systems.

Multisite and multitimepoint proteomics reveal that patent foramen ovale closure improves migraine and epilepsy by reducing right-to-left shunt-induced hypoxia

Patent foramen ovale (PFO) is a congenital defect in the partition between two atria, which may cause right-to-left shunt (RLS), leading to neurological chronic diseases with episodic manifestations (NCDEMs), such as migraine and epilepsy. However, whether PFO closure was effective in improving NCDEMs and the mechanism were unclear. Twenty-eight patients with migraine or epilepsy who underwent PFO closure were recruited. Notably, approximately half of patients received 50% or more reduction in seizure or headache attacks. Meanwhile, the postoperative blood oxygen partial pressure and oxygen saturation were elevated after PFO closure. Multisite (peripheral, right, and left atrial) and multitimepoint (before and after surgery) plasma proteomics from patients showed that the levels of free hemoglobin and cell adhesion molecules (CAMs) were significantly increased after PFO closure, which may be related to the relief of the hypoxic state. Furtherly, the omics data from multiple brain regions of mice revealed that a large number of proteins were differentially expressed in the occipital region in response to PFO, including redox molecules and CAMs, suggesting PFO-caused hypoxia may have great impacts on occipital region. Collectively, PFO may cause NCDEMs due to RLS-induced hypoxia, and PFO closure could prevent RLS to improve migraine and epilepsy.

Proteogenomics of clear cell renal cell carcinoma response to tyrosine kinase inhibitor

The tyrosine kinase inhibitor (TKI) Sunitinib is one the therapies approved for advanced renal cell carcinoma. Here, we undertake proteogenomic profiling of 115 tumors from patients with clear cell renal cell carcinoma (ccRCC) undergoing Sunitinib treatment and reveal the molecular basis of differential clinical outcomes with TKI therapy. We find that chromosome 7q gain-induced mTOR signaling activation is associated with poor therapeutic outcomes with Sunitinib treatment, whereas the aristolochic acid signature and VHL mutation synergistically caused enhanced glycolysis is correlated with better prognosis. The proteomic and phosphoproteomic analysis further highlights the responsibility of mTOR signaling for non-response to Sunitinib. Immune landscape characterization reveals diverse tumor microenvironment subsets in ccRCC. Finally, we construct a multi-omics classifier that can detect responder and non-responder patients (receiver operating characteristic-area under the curve, 0.98). Our study highlights associations between ccRCC molecular characteristics and the response to TKI, which can facilitate future improvement of therapeutic responses.

High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer

Adjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derived classifier for stage II/III CRC using 3 markers, including FHL3, GGA1, TGFBI. The proteomics profiling-derived signature for stage II/III CRC (PS) not only shows good accuracy to classify patients into high and low risk of relapse and mortality in all three cohorts, but also works independently of clinicopathologic features. ACT was associated with improved disease-free survival (DFS) and overall survival (OS) in stage II (pN0) patients with high PS and pN2 patients with high PS. This study demonstrated the clinical significance of proteomic features, which serve as a valuable source for potential biomarkers. The PS classifier provides prognostic value for identifying patients at high risk of relapse and mortality and optimizes individualized treatment strategy by detecting patients who may benefit from ACT for survival.

The Glomerulus Multiomics Analysis Provides Deeper Insights into Diabetic Nephropathy

Although diabetic nephropathy (DN) is the leading cause of the end-stage renal disease, the exact regulation mechanisms remain unknown. In this study, we integrated the transcriptomics and proteomics profiles of glomeruli isolated from 50 biopsy-proven DN patients and 25 controls to investigate the latest findings about DN pathogenesis. First, 1152 genes exhibited differential expression at the mRNA or protein level, and 364 showed significant association. These strong correlated genes were divided into four different functional modules. Moreover, a regulatory network of the transcription factors (TFs)-target genes (TGs) was constructed, with 30 TFs upregulated at the protein levels and 265 downstream TGs differentially expressed at the mRNA levels. These TFs are the integration centers of several signal transduction pathways and have tremendous therapeutic potential for regulating the aberrant production of TGs and the pathological process of DN. Furthermore, 29 new DN-specific splice-junction peptides were discovered with high confidence; these peptides may play novel functions in the pathological course of DN. So, our in-depth integrative transcriptomics-proteomics analysis provided deeper insights into the pathogenesis of DN and opened the potential avenue for finding new therapeutic interventions. MS raw files were deposited into the proteomeXchange with the dataset identifier PXD040617.

Comprehensive proteogenomic characterization of early duodenal cancer reveals the carcinogenesis tracks of different subtypes

The subtypes of duodenal cancer (DC) are complicated and the carcinogenesis process is not well characterized. We present comprehensive characterization of 438 samples from 156 DC patients, covering 2 major and 5 rare subtypes. Proteogenomics reveals LYN amplification at the chromosome 8q gain functioned in the transmit from intraepithelial neoplasia phase to infiltration tumor phase via MAPK signaling, and illustrates the DST mutation improves mTOR signaling in the duodenal adenocarcinoma stage. Proteome-based analysis elucidates stage-specific molecular characterizations and carcinogenesis tracks, and defines the cancer-driving waves of the adenocarcinoma and Brunner's gland subtypes. The drug-targetable alanyl-tRNA synthetase (AARS1) in the high tumor mutation burden/immune infiltration is significantly enhanced in DC progression, and catalyzes the lysine-alanylation of poly-ADP-ribose polymerases (PARP1), which decreases the apoptosis of cancer cells, eventually promoting cell proliferation and tumorigenesis. We assess the proteogenomic landscape of early DC, and provide insights into the molecular features corresponding therapeutic targets.

Integrative proteogenomic characterization of early esophageal cancer

Esophageal squamous cell carcinoma (ESCC) is malignant while the carcinogenesis is still unclear. Here, we perform a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 ESCC patients, covering 9 histopathological stages and 3 phases. Proteogenomics elucidates cancer-driving waves in ESCC progression, and reveals the molecular characterization of alcohol drinking habit associated signatures. We discover chromosome 3q gain functions in the transmit from nontumor to intraepithelial neoplasia phases, and find TP53 mutation enhances DNA replication in intraepithelial neoplasia phase. The mutations of AKAP9 and MCAF1 upregulate glycolysis and Wnt signaling, respectively, in advanced-stage ESCC phase. Six major tracks related to different clinical features during ESCC progression are identified, which is validated by an independent cohort with another 256 samples. Hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) is considered as a drug target in ESCC progression. This study provides insight into the understanding of ESCC molecular mechanism and the development of therapeutic targets.

Expanding individualized therapeutic options via genoproteomics

Clinical next-generation sequencing (NGS)² tests have enabled treatment recommendations for cancer patients with driver gene mutations. Targeted therapy options for patients without driver gene mutations are currently unavailable. Herein, we performed NGS and proteomics tests on 169 formalin-fixed paraffin-embedded (FFPE)³ samples of non-small cell lung cancers (NSCLC, 65),⁴ colorectal cancers (CRC, 61),⁵ thyroid carcinomas (THCA, 14),⁶ gastric cancers (GC, 2),⁷ gastrointestinal stromal tumors (GIST, 11),⁸ and malignant melanomas (MM, 6).⁹ Of the 169 samples, NGS detected 14 actionable mutated genes in 73 samples, providing treatment options for 43% of the patients. Proteomics identified 61 actionable clinical drug targets approved by the FDA or undergoing clinical trials in 122 samples, providing treatment options for 72% of the patients. In vivo experiments demonstrated that the Mitogen-Activated Protein Kinase (MEK)¹⁰ inhibitor induced the overexpression of MEK1 (Map2k1) to block lung tumor growth in mice. Therefore, protein overexpression is a potentially feasible indicator for guiding targeted therapies. Collectively, our analysis suggests that combining NGS and proteomics (genoproteomics) could expand the targeted treatment options to 85% of cancer patients.

Comparison of Pairwise Venous and Fingertip Plasma Using Quantitative Proteomics Based on Data-Independent Acquisition

Blood contains a great deal of health-related information and can be used to monitor human health status. Clinically, venous or fingertip blood is usually used for blood tests. However, the clinical application settings of the two sources of blood are unclear. In this study, the proteomes of pairwise venous plasma (VP) and fingertip plasma (FP) were analyzed, and the levels of 3797 proteins were compared between VP and FP. The Spearman's correlation coefficient for the relationship between protein levels of VP and FP ranges from 0.64 to 0.78 (p < 0.0001). The common pathways of VP and FP are related to cell-cell adhesion, protein stabilization, innate immune response, and complement activation, the classical pathway. The VP-overrepresented pathway is related to actin filament organization, while the FP-overrepresented pathway is related to the hydrogen peroxide catabolic process. ADAMTSL4, ADIPOQ, HIBADH, and XPO5 both in VP and FP are potential gender-related proteins. Notably, the VP proteome has a higher interpretation on age than the FP proteome, and CD14 is a potential age-related protein in VP but not in FP. Our study mapped the different proteomes between VP and FP, which can provide value for the standardization of clinical blood tests.

Reprogramming of palmitic acid induced by dephosphorylation of ACOX1 promotes β-catenin palmitoylation to drive colorectal cancer progression

Metabolic reprogramming is a hallmark of cancer. However, it is not well known how metabolism affects cancer progression. We identified that metabolic enzyme acyl-CoA oxidase 1 (ACOX1) suppresses colorectal cancer (CRC) progression by regulating palmitic acid (PA) reprogramming. ACOX1 is highly downregulated in CRC, which predicts poor clinical outcome in CRC patients. Functionally, ACOX1 depletion promotes CRC cell proliferation in vitro and colorectal tumorigenesis in mouse models, whereas ACOX1 overexpression inhibits patient-derived xenograft growth. Mechanistically, DUSP14 dephosphorylates ACOX1 at serine 26, promoting its polyubiquitination and proteasomal degradation, thereby leading to an increase of the ACOX1 substrate PA. Accumulated PA promotes β-catenin cysteine 466 palmitoylation, which inhibits CK1- and GSK3-directed phosphorylation of β-catenin and subsequent β-Trcp-mediated proteasomal degradation. In return, stabilized β-catenin directly represses ACOX1 transcription and indirectly activates DUSP14 transcription by upregulating c-Myc, a typical target of β-catenin. Finally, we confirmed that the DUSP14-ACOX1-PA-β-catenin axis is dysregulated in clinical CRC samples. Together, these results identify ACOX1 as a tumor suppressor, the downregulation of which increases PA-mediated β-catenin palmitoylation and stabilization and hyperactivates β-catenin signaling thus promoting CRC progression. Particularly, targeting β-catenin palmitoylation by 2-bromopalmitate (2-BP) can efficiently inhibit β-catenin-dependent tumor growth in vivo, and pharmacological inhibition of DUSP14-ACOX1-β-catenin axis by Nu-7441 reduced the viability of CRC cells. Our results reveal an unexpected role of PA reprogramming induced by dephosphorylation of ACOX1 in activating β-catenin signaling and promoting cancer progression, and propose the inhibition of the dephosphorylation of ACOX1 by DUSP14 or β-catenin palmitoylation as a viable option for CRC treatment.

Region-resolved multi-omics of the mouse eye

The eye is a complex organ consisting of multiple compartments with unique and specialized properties, and small disturbances in one eye region can result in impaired vision and blindness. Although there have been advancements in ocular research, the hierarchical molecular network in region-wide resolution, indicating the division of labor and crosstalk among different eye regions, is not yet comprehensively illuminated. Here, we present an atlas of region-resolved proteome and lipidome of mouse eye. Multiphoton microscopy-guided laser microdissection combined with in-depth label-free proteomics identifies 13,536 proteins across various mouse eye regions. Further integrative analysis of spectral imaging, label-free proteome, and imaging mass spectrometry of the lipidome and phosphoproteome reveals distinctive molecular features, including proteins and lipids of various anatomical mouse eye regions. These deposited datasets and our open proteome server integrating all information provide a valuable resource for future functional and mechanistic studies of mouse eye and ocular disease.

Transcriptomics-proteomics Integration reveals alternative polyadenylation driving inflammation-related protein translation in patients with diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN) is a complex disease involving the upregulation of many inflammation-related proteins. Alternative polyadenylation (APA), a crucial post-transcriptional regulatory mechanism, has been proven to play vital roles in many inflammatory diseases. However, it is largely unknown whether and how APA exerts function in DN.

METHODS

We performed transcriptomics and proteomics analysis of glomeruli samples isolated from 50 biopsy-proven DN patients and 25 control subjects. DaPars and QAPA algorithms were adopted to identify APA events from RNA-seq data. The qRT-PCR analysis was conducted to verify 3'UTR length alteration. Short and long 3'UTRs isoforms were also overexpressed in podocytes under hyperglycemia condition for examining protein expression.

RESULTS

We detected transcriptome-wide 3'UTR APA events in DN, and found that APA-mediated 3'UTR lengthening of genes (APA genes) increased their expression at protein but not mRNA level. Increased protein level of 3'UTR lengthening gene was validated in podocytes under hyperglycemia condition. Pathway enrichment analysis showed that APA genes were enriched in inflammation-related biological processes including endoplasmic reticulum stress pathways, NF-κB signaling and autophagy. Further bioinformatics analysis demonstrated that 3'UTR APA of genes probably altered the binding sites for RNA-binding proteins, thus enhancing protein translation.

CONCLUSION

This study revealed for the first time that 3'UTR lengthening of APA genes contributed to the progression of DN by elevating the translation of corresponding proteins, providing new insight and a rich resource for investigating DN mechanisms.

Proteogenomics of diffuse gliomas reveal molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms

Diffuse gliomas are devastating brain tumors. Here, we perform a proteogenomic profiling of 213 retrospectively collected glioma tumors. Proteogenomic analysis reveals the downstream biological events leading by EGFR-, IDH1-, TP53-mutations. The comparative analysis illustrates the distinctive features of GBMs and LGGs, indicating CDK2 inhibitor might serve as a promising drug target for GBMs. Further proteogenomic integrative analysis combined with functional experiments highlight the cis-effect of EGFR alterations might lead to glioma tumor cell proliferation through ERK5 medicates nucleotide synthesis process. Proteome-based stratification of gliomas defines 3 proteomic subgroups (S-Ne, S-Pf, S-Im), which could serve as a complement to WHO subtypes, and would provide the essential framework for the utilization of specific targeted therapies for particular glioma subtypes. Immune clustering identifies three immune subtypes with distinctive immune cell types. Further analysis reveals higher EGFR alteration frequencies accounts for elevation of immune check point protein: PD-L1 and CD70 in T-cell infiltrated tumors.

Proteomics and weighted gene correlated network analysis reveal glutamatergic synapse signaling in diazepam treatment of alcohol withdrawal

Background: Alcohol use disorder (AUD) is characterized by chronic excessive alcohol consumption, often alternating with periods of abstinence known as alcohol withdrawal syndrome (AWS). Diazepam is the preferred benzodiazepine for treatment of alcohol withdrawal syndrome under most circumstances, but the specific mechanism underlying the treatment needs further research. Methods: We constructed an animal model of two-bottle choices and chronic intermittent ethanol exposure. LC-MS/MS proteomic analysis based on the label-free and intensity-based quantification approach was used to detect the protein profile of the whole brain. Weighted gene correlated network analysis was applied for scale-free network topology analysis. We established a protein-protein interaction network based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software and identified hub proteins by CytoHubba and MCODE plugins of Cytoscape. The online tool Targetscan identified miRNA-mRNA pair interactions. Results: Seven hub proteins (Dlg3, Dlg4, Shank3, Grin2b, Camk2b, Camk2a and Syngap1) were implicated in alcohol withdrawal syndrome or diazepam treatment. In enrichment analysis, glutamatergic synapses were considered the most important pathway related to alcohol use disorder. Decreased glutamatergic synapses were observed in the late stage of withdrawal, as a protective mechanism that attenuated withdrawal-induced excitotoxicity. Diazepam treatment during withdrawal increased glutamatergic synapses, alleviating withdrawal-induced synapse inhibition. Conclusion: Glutamatergic synapses are considered the most important pathway related to alcohol use disorder that may be a potential molecular target for new interventional strategies.

Proteogenomic characterization of MiT family translocation renal cell carcinoma

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

Integrated proteogenomic characterization across major histological types of pituitary neuroendocrine tumors

Pituitary neuroendocrine tumor (PitNET) is one of the most common intracranial tumors. Due to its extensive tumor heterogeneity and the lack of high-quality tissues for biomarker discovery, the causative molecular mechanisms are far from being fully defined. Therefore, more studies are needed to improve the current clinicopathological classification system, and advanced treatment strategies such as targeted therapy and immunotherapy are yet to be explored. Here, we performed the largest integrative genomics, transcriptomics, proteomics, and phosphoproteomics analysis reported to date for a cohort of 200 PitNET patients. Genomics data indicate that GNAS copy number gain can serve as a reliable diagnostic marker for hyperproliferation of the PIT1 lineage. Proteomics-based classification of PitNETs identified 7 clusters, among which, tumors overexpressing epithelial-mesenchymal transition (EMT) markers clustered into a more invasive subgroup. Further analysis identified potential therapeutic targets, including CDK6, TWIST1, EGFR, and VEGFR2, for different clusters. Immune subtyping to explore the potential for application of immunotherapy in PitNET identified an association between alterations in the JAK1-STAT1-PDL1 axis and immune exhaustion, and between changes in the JAK3-STAT6-FOS/JUN axis and immune infiltration. These identified molecular markers and alternations in various clusters/subtypes were further confirmed in an independent cohort of 750 PitNET patients. This proteogenomic analysis across traditional histological boundaries improves our current understanding of PitNET pathophysiology and suggests novel therapeutic targets and strategies.

Integrated proteomic and transcriptomic landscape of macrophages in mouse tissues

Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server ( http://macrophage.mouseprotein.cn ) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.

Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor prognosis. Proteogenomic characterization and integrative proteomic analysis provide a functional context to annotate genomic abnormalities with prognostic value.

METHODS

We performed an integrated multi-omics analysis, including whole-exome sequencing, RNA-seq, proteomic, and phosphoproteomic analysis of 217 PDAC tumors with paired non-tumor adjacent tissues. In vivo functional experiments were performed to further illustrate the biological events related to PDAC tumorigenesis and progression.

RESULTS

A comprehensive proteogenomic landscape revealed that TP53 mutations upregulated the CDK4-mediated cell proliferation process and led to poor prognosis in younger patients. Integrative multi-omics analysis illustrated the proteomic and phosphoproteomic alteration led by genomic alterations such as KRAS mutations and ADAM9 amplification of PDAC tumorigenesis. Proteogenomic analysis combined with in vivo experiments revealed that the higher amplification frequency of ADAM9 (8p11.22) could drive PDAC metastasis, though downregulating adhesion junction and upregulating WNT signaling pathway. Proteome-based stratification of PDAC revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Immune clustering defined a metabolic tumor subset that harbored FH amplicons led to better prognosis. Functional experiments revealed the role of FH in altering tumor glycolysis and in impacting PDAC tumor microenvironments. Experiments utilizing both in vivo and in vitro assay proved that loss of HOGA1 promoted the tumor growth via activating LARP7-CDK1 pathway.

CONCLUSIONS

This proteogenomic dataset provided a valuable resource for researchers and clinicians seeking for better understanding and treatment of PDAC.

Urinary protein biomarker panel predicts esophageal squamous carcinoma from control cases and other tumors

PURPOSE

Discovery of noninvasive urinary biomarkers for the early diagnosis of esophageal squamous carcinoma (ESCC).

METHODS

We conducted proteomic analyses of 499 human urine samples obtained from healthy individuals (n = 321) and ESCC (n = 83), bladder cancer (n = 17), breast cancer (n = 12), colorectal cancer (n = 16), lung cancer (n = 33) and thyroid cancer (n = 17) patients from multiple medical centers. Those samples were divided into a discovery set (n = 247) and an independent validation set (n = 157).

RESULTS

Among urinary proteins identified in the comprehensive quantitative proteomics analysis, we selected a panel of three urinary biomarkers (ANXA1, S100A8, TMEM256), and established a logistic regression model in the discovery set that can correctly classify the majority of ESCC cases in the validation sets with the area under the curve (AUC) values of 0.825. This urinary biomarker panel not only discriminates ESCC patients from healthy individuals but also differentiates ESCC from other common tumors. Notably, the panel distinguishes stage I ESCC patients from healthy individuals with AUC values of 0.886. On the analysis of stage-specific biomarkers, another combination panel of protein (ANXA1, S100A8, SOD3, TMEM256) demonstrated a good AUC value of 0.792 for stage I ESCC.

CONCLUSIONS

Urinary biomarker panel represents a promising auxiliary diagnostic tool for ESCC, including early-stage ESCC.

Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals new therapeutic strategies

Chemotherapy and targeted therapy are the major treatments for gastric cancer (GC), but drug resistance limits its effectiveness. Here, we profile the proteome of 206 tumor tissues from patients with GC undergoing either chemotherapy or anti-HER2-based therapy. Proteome-based classification reveals four subtypes (G-I-G-IV) related to different clinical and molecular features. MSI-sig high GC patients benefit from docetaxel combination treatment, accompanied by anticancer immune response. Further study reveals patients with high T cell receptor signaling respond to anti-HER2-based therapy; while activation of extracellular matrix/PI3K-AKT pathway impair anti-tumor effect of trastuzumab. We observe CTSE functions as a cell intrinsic enhancer of chemosensitivity of docetaxel, whereas TKTL1 functions as an attenuator. Finally, we develop prognostic models with high accuracy to predict therapeutic response, further validated in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemotherapy and targeted therapy in GC.

A urinary proteomic landscape of COVID-19 progression identifies signaling pathways and therapeutic options

Signaling pathway alterations in COVID-19 of living humans as well as therapeutic targets of the host proteins are not clear. We analyzed 317 urine proteomes, including 86 COVID-19, 55 pneumonia and 176 healthy controls, and identified specific RNA virus detector protein DDX58/RIG-I only in COVID-19 samples. Comparison of the COVID-19 urinary proteomes with controls revealed major pathway alterations in immunity, metabolism and protein localization. Biomarkers that may stratify severe symptoms from moderate ones suggested that macrophage induced inflammation and thrombolysis may play a critical role in worsening the disease. Hyper activation of the TCA cycle is evident and a macrophage enriched enzyme CLYBL is up regulated in COVID-19 patients. As CLYBL converts the immune modulatory TCA cycle metabolite itaconate through the citramalyl-CoA intermediate to acetyl-CoA, an increase in CLYBL may lead to the depletion of itaconate, limiting its anti-inflammatory function. These observations suggest that supplementation of itaconate and inhibition of CLYBL are possible therapeutic options for treating COVID-19, opening an avenue of modulating host defense as a means of combating SARS-CoV-2 viruses.