Cancer Genomics & Proteomics[JOURNAL]
Sun
200 papers
Parallel Analyses by Mass Spectrometry (MS) and Reverse Phase Protein Array (RPPA) Reveal Complementary Proteomic Profiles in Triple-Negative Breast Cancer (TNBC) Patient Tissues and Cell Cultures.
Wang N, Zhu Y, Wang L … +11 more , Dai W, Hu T, Song Z, Li X, Zhang Q, Ma J, Xia Q, Li J, Liu Y, Long M, Ding Z
Proteomics · 2025 Feb · PMID 39548956 · Publisher ↗
High-plex proteomic technologies have made substantial contributions to mechanism studies and biomarker discovery in complex diseases, particularly cancer. Despite technological advancements, inherent limitations in indi...
High-plex proteomic technologies have made substantial contributions to mechanism studies and biomarker discovery in complex diseases, particularly cancer. Despite technological advancements, inherent limitations in individual proteomic approaches persist, impeding the achievement of comprehensive quantitative insights into the proteome. In this study, we employed two widely used proteomic technologies, mass spectrometry (MS) and reverse phase protein array (RPPA) to analyze identical samples, aiming to systematically assess the outcomes and performance of the different technologies. Additionally, we sought to establish an integrated workflow by combining these two proteomic approaches to augment the coverage of protein targets for discovery purposes. We used 14 fresh frozen tissue samples from triple-negative breast cancer (TNBC: seven tumors versus seven adjacent non-cancerous tissues) and cell line samples to evaluate both technologies and implement this dual-proteomic strategy. Using a single-step protein denaturation and extraction protocol, protein samples were subjected to reverse-phase liquid chromatography (LC) followed by electrospray ionization (ESI)-mediated MS/MS for proteomic profiling. Concurrently, identical sample aliquots were analyzed by RPPA for profiling of over 300 proteins and phosphoproteins that are in key signaling pathways or druggable targets in cancer. Both proteomic methods demonstrated the expected ability to differentiate samples by groups, revealing distinct proteomic patterns under various experimental conditions, albeit with minimal overlap in identified targets. Mechanism-based analysis uncovered divergent biological processes identified with the two proteomic technologies, capitalizing on their complementary exploratory potential.
Proteomic profiling of oral squamous cell carcinoma tissues reveals altered immune-related proteins: implications for personalized therapy.
Palollathil A, Babu S, Abhinand CS … +3 more , Mathew RT, Vijayakumar M, Prasad TSK
Expert Rev Proteomics · 2024 Nov · PMID 39523852 · Publisher ↗
OBJECTIVES: Oral squamous cell carcinoma poses a substantial global health challenge marked by rising mortality rate. Recently, immunotherapy has shown promising results in cancer management by enhancing immune response....
OBJECTIVES: Oral squamous cell carcinoma poses a substantial global health challenge marked by rising mortality rate. Recently, immunotherapy has shown promising results in cancer management by enhancing immune response. Thus, identifying additional immune-related markers is critical for advancing immunotherapy treatments. METHODS: Data-independent acquisition (DIA) mass spectrometry approach was used to explore differentially expressed immune-related proteins in oral cancer tissues compared to adjacent non-cancerous tissues. Functional significance was identified through Gene Ontology, pathway, and network analysis. Gene expression of identified proteins was validated using transcriptomic data. RESULTS: DIA analysis identified 29,459 precursors corresponding to 3429 proteins. Among these, 1060 proteins were differentially expressed, with 166 being immune-related. Differentially regulated proteins were involved in innate immune response, mitochondrial ATP synthesis, and neutrophil degranulation. Pathway analysis of immune-related proteins showed perturbation in anti-tumor immunity-related pathways such as interferon signaling, TCR signaling, PD-1 signaling, and antigen processing and presentation. Significance of these pathways was further reinforced by the strong interactions identified in the protein-protein interaction network analysis. Additionally, gene expression analysis showed similar mRNA expression patterns for key proteins involved in altered pathways, including ISG15, IFIT1/3, HLA-A/C and OAS2/3. CONCLUSIONS: Further validation of these proteins could establish them as potential targets for personalized therapy.
Proteomic insights into the extracellular matrix: a focus on proteoforms and their implications in health and disease.
Bains AK, Naba A
Expert Rev Proteomics · 2024 Nov · PMID 39512072 · Full text
INTRODUCTION: The extracellular matrix (ECM) is a highly organized and dynamic network of proteins and glycosaminoglycans that provides critical structural, mechanical, and biochemical support to cells. The functions of...
INTRODUCTION: The extracellular matrix (ECM) is a highly organized and dynamic network of proteins and glycosaminoglycans that provides critical structural, mechanical, and biochemical support to cells. The functions of the ECM are directly influenced by the conformation of the proteins that compose it. ECM proteoforms, which can result from genetic, transcriptional, and/or post-translational modifications, adopt different conformations and, consequently, confer different structural properties and functionalities to the ECM in both physiological and pathological contexts. AREAS COVERED: In this review, we discuss how bottom-up proteomics has been applied to identify, map, and quantify post-translational modifications (. additions of chemical groups, proteolytic cleavage, or cross-links) and ECM proteoforms arising from alternative splicing or genetic variants. We further illustrate how proteoform-level information can be leveraged to gain novel insights into ECM protein structure and ECM functions in health and disease. EXPERT OPINION: In the Expert opinion section, we discuss remaining challenges and opportunities with an emphasis on the importance of devising experimental and computational methods tailored to account for the unique biochemical properties of ECM proteins with the goal of increasing sequence coverage and, hence, accurate ECM proteoform identification.
4-plex quantitative glycoproteomics using glycan/protein-stable isotope labeling in cell culture.
Jiang P, Hakim MA, Saffarian Delkhosh A … +3 more , Ahmadi P, Li Y, Mechref Y
J Proteomics · 2025 Jan · PMID 39426592 · Full text
Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within b...
Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SIGNIFICANCE: Alternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis. Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems.
DIA proteomic and PRM validation through human granulose cells profiles screen suitable biomarkers for polycystic ovary syndrome patients.
Liu F, Tian L, Zhang Y … +4 more , Deng W, Xu X, Zou Y, An R
J Proteomics · 2024 Oct · PMID 39424224 · Publisher ↗
The aim of this study is to identify differentially expressed proteins (DEPs) in granulose cells (GCs) from women with or withoutpolycystic ovary syndrome (PCOS) via data independent acquisition (DIA) proteomic analysis....
The aim of this study is to identify differentially expressed proteins (DEPs) in granulose cells (GCs) from women with or withoutpolycystic ovary syndrome (PCOS) via data independent acquisition (DIA) proteomic analysis.A total of 63 women were recruited for this study, 34 PCOS patients as experimental group (P), and 29 women without PCOS as Normal group (NP). DIA-based proteomic analysis was performed to identify DEPs in GCs between the P and NP samples. Certain typical DEPs were further validated by Parallel reaction monitoring (PRM), and correlation analysis was performed between these DEPs and the clinical characteristics.Cell vitality was measured by CCK-8 assay. DIA analysis revealed 174 significantly DEPs, of which 7 were upregulated and 167 downregulated. Bioinformatics analysis was performed to analysis the significantly DEPs. The PRM experiment confirmed TOP2A and SPHKAP were upregulated significantly in P by comparing to NP, while GM2A, MRPS16, APOA2 and FGF2 were downregulated significantly. Most notably, Correlation analysis revealed that TOP2A, SPHKAP, MRPS16 and FGF2were positively correlated with TG, AMH and Age, but negatively correlated with Menarche age, DBIL, FT3, Basal serum FSH and LH.Meanwhile, CCK-8 assay has shown that downregulation of FGF2 could weaken cell viability. Finally, a panel of DEPs were identified in the GCs of patients with PCOS, of which certain significant DEPs might play essential roles in the pathogenesis of PCOS, could be regarded as candidate biomarkers for PCOS.
Glycosylation in cancer as a source of biomarkers.
Khorami-Sarvestani S, Hanash SM, Fahrmann JF … +2 more , León-Letelier RA, Katayama H
Expert Rev Proteomics · 2024 · PMID 39376081 · Publisher ↗
INTRODUCTION: Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity,...
INTRODUCTION: Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity, charge, solubility, structure, localization, function, and protection from proteolysis. Aberrant glycosylation in proteins can reveal new detection and therapeutic Glyco-biomarkers, which help to improve accurate early diagnosis and personalized treatment. This review underscores the pivotal role of glycans and glycoproteins as a source of biomarkers in human diseases, particularly cancer. AREAS COVERED: This review delves into the implications of glycosylation, shedding light on its intricate roles in cancer-related cellular processes influencing biomarkers. It is underpinned by a thorough examination of literature up to June 2024 in PubMed, Scopus, and Google Scholar; concentrating on the terms: (Glycosylation[Title/Abstract]) OR (Glycan[Title/Abstract]) OR (glycoproteomics[Title/Abstract]) OR (Proteoglycans[Title/Abstract]) OR (Glycomarkers[Title/Abstract]) AND (Cancer[Title/Abstract]) AND ((Diagno*[Title/Abstract]) OR (Progno*[Title/Abstract])). EXPERT OPINION: Glyco-biomarkers enhance early cancer detection, allow early intervention, and improve patient prognoses. However, the abundance and complex dynamic glycan structure may make their scientific and clinical application difficult. This exploration of glycosylation signatures in cancer biomarkers can provide a detailed view of cancer etiology and instill hope in the potential of glycosylation to revolutionize cancer research.
TMT-Based Quantitative Proteomic Profiling of Human Esophageal Cancer Cells Reveals the Potential Mechanism and Potential Therapeutic Targets Associated With Radioresistance.
Gao A, He C, Chen H … +8 more , Liu Q, Chen Y, Sun J, Wu C, Pan Y, Rocha S, Wang M, Zhou J
Proteomics Clin Appl · 2025 Jan · PMID 39375892 · Full text
PURPOSE: The recurrence of esophageal squamous cell carcinoma (ESCC) in radiation therapy treatment presents a complex challenge due to its resistance to radiation. However, the mechanism underlying the development of ra...
PURPOSE: The recurrence of esophageal squamous cell carcinoma (ESCC) in radiation therapy treatment presents a complex challenge due to its resistance to radiation. However, the mechanism underlying the development of radioresistance in ESCC remains unclear. In this study, we aim to uncover the mechanisms underlying radioresistance in ESCC cells and identify potential targets for radiosensitization. METHODS: We established two radio-resistant cell lines, TE-1R and KYSE-150R, from the parental ESCC cell lines TE-1 and KYSE-150 through fractionated irradiation. A TMT-based quantitative proteomic profiling approach was applied to identify changes in protein expression patterns. Cell Counting Kit-8, colony formation, γH2AX foci immunofluorescence and comet assays were utilized to validate our findings. The downstream effectors of the DNA repair pathway were confirmed using an HR/NHEJ reporter assay and Western blot analysis. Furthermore, we evaluated the expression of potential targets in ESCC tissues through immunohistochemistry combined with mass spectrometry. RESULTS: Over 2,000 proteins were quantitatively identified in the ESCC cell lysates. A comparison with radio-sensitive cells revealed 61 up-regulated and 14 down-regulated proteins in the radio-resistant cells. Additionally, radiation treatment induced 24 up-regulated and 12 down-regulated proteins in the radio-sensitive ESCC cells. Among the differentially expressed proteins, S100 calcium binding protein A6 (S100A6), glutamine gamma-glutamyltransferase 2 (TGM2), glycogen phosphorylase, brain form (PYGB), and Thymosin Beta 10 (TMSB10) were selected for further validation studies as they were found to be over-expressed in the accumulated radio-resistant ESCC cells and radio-resistant cells. Importantly, high S100A6 expression showed a positive correlation with cancer recurrence in ESCC patients. Our results suggest that several key proteins, including S100A6, TGM2, and PYGB, play a role in the development of radioresistance in ESCC. CONCLUSIONS: Our results revealed that several proteins including Protein S100-A6 (S100A6), Protein-glutamine gamma-glutamyltransferase 2 (TGM2), Glycogen phosphorylase, brain form (PYGB) were involved in radio-resistance development. These proteins could potentially serve as biomarkers for ESCC radio-resistance and as therapeutic targets to treat radio-resistant ESCC cells.
Digitalomics - digital transformation leading to omics insights.
Balasubramaniam NK, Penberthy S, Fenyo D … +3 more , Viessmann N, Russmann C, Borchers CH
Expert Rev Proteomics · 2024 · PMID 39364775 · Publisher ↗
INTRODUCTION: Biomarker discovery is increasingly moving from single omics to multiomics, as well as from multi-cell omics to single-cell omics. These transitions have increasingly adopted digital transformation technolo...
INTRODUCTION: Biomarker discovery is increasingly moving from single omics to multiomics, as well as from multi-cell omics to single-cell omics. These transitions have increasingly adopted digital transformation technologies to accelerate the progression from data to insight. Here, we will discuss the concept of 'digitalomics' and how digital transformation directly impacts biomarker discovery. This will ultimately assist clinicians in personalized therapy and precision-medicine treatment decisions. AREAS COVERED: Genotype-to-phenotype-based insight generation involves integrating large amounts of complex multiomic data. This data integration and analysis is aided through digital transformation, leading to better clinical outcomes. We also highlight the challenges and opportunities of Digitalomics, and provide examples of the application of Artificial Intelligence, cloud- and high-performance computing, and use of tensors for multiomic analysis workflows. EXPERT OPINION: Biomarker discovery, aided by digital transformation, is having a significant impact on cancer, cardiovascular, infectious, immunological, and neurological diseases, among others. Data insights garnered from multiomic analyses, combined with patient meta data, aids patient stratification and targeted treatment across a broad spectrum of diseases. Digital transformation offers time and cost savings while leading to improved patent healthcare. Here, we highlight the impact of digital transformation on multiomics- based biomarker discovery with specific applications related to oncology.
Exploration of potential drug targets for Glaucoma by plasma proteome screening.
Wang Z, Zhou H, Wang F … +1 more , Huang H
J Proteomics · 2025 Jan · PMID 39342991 · Publisher ↗
BACKGROUND: Glaucoma is the leading cause of irreversible blindness. However, the current available treatment methods are still unsatisfactory. Therefore, the exploration of new drug targets for the treatment of glaucoma...
BACKGROUND: Glaucoma is the leading cause of irreversible blindness. However, the current available treatment methods are still unsatisfactory. Therefore, the exploration of new drug targets for the treatment of glaucoma is of paramount importance. METHODS: We conducted two-sample Mendelian randomization (MR) using plasma protein quantitative trait loci (pQTL) data from two datasets (n = 734, n = 4907) and their instrumental variables to investigate the causal relationship between plasma proteins and glaucoma. The analysis was validated by replacing the exposure and outcome cohorts. Additionally, we utilized protein-protein interaction networks to assess the associations between these potential drug targets and existing drug targets. RESULTS: Through two-sample Mendelian randomization analysis, we identified causal relationships between Glaucoma and the following proteins: AZU1, OBP2B, ENPP5, INPP5B, KREMEN1, LYPLAL1, and PTPRJ. External validation confirmed the protective effect of LYPLAL1 on Glaucoma, while ENPP5, KREMEN1, and PTPRJ increased the risk of Glaucoma. Reverse MR and Steiger filtering did not indicate any reverse causal associations of the aforementioned proteins with Glaucoma. CONCLUSION: Our study demonstrates a causal impact of ENPP5, KREMEN1, PTPRJ, and LYPLAL1 on the risk of Glaucoma. These findings suggest that these four proteins may serve as promising drug targets for Glaucoma treatment. SIGNIFICANCE: Currently, the pharmacological treatment of glaucoma primarily focuses on lowering intraocular pressure, which has its limitations. Targeted therapy is a personalized treatment approach that aims to inhibit or block the development and progression of diseases such as cancer and inflammation by selectively acting on specific biomolecules or signaling pathways. Our research employs a two-sample Mendelian randomization (MR) method, integrating a large amount of GWAS and pQTL data to perform MR analysis. This has enabled us to explore several plasma proteins as potential drug targets for glaucoma, providing direction and a research foundation for future investigations into glaucoma drug targets.
Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines.
Ferrara B, Bourgoin-Voillard S, Habert D … +10 more , Vallée B, Nicolas-Boluda A, Simanic I, Seve M, Vingert B, Gazeau F, Castellano F, Cohen J, Courty J, Cascone I
Proteomics · 2024 Dec · PMID 39279557 · Publisher ↗
The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this s...
The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this study was to investigate the influence of matrix stiffness on PDAC progression by analyzing the proteome of PDAC-derived extracellular vesicles (EVs). PDAC cell lines (mPDAC and KPC) were grown on synthetic supports with a stiffness close to non-tumor (NT) or tumor tissue (T), and the protein expression levels in cell-derived EVs were analyzed by a quantitative MS label-free mass spectrometry approach. Our analysis figured out 15 differentially expressed proteins (DEPs) in mPDAC-EVs and 20 DEPs in KPC-EVs in response to matrix rigidification. Up-regulated proteins participate to the processes of metabolism, matrix remodeling, and immune response, altogether hallmarks of PDAC progression. A multimodal network analysis revealed that the majority of DEPs are strongly related to pancreatic cancer. Interestingly, among DEPs, 11 related genes (ACTB/ANXA7/C3/IGSF8/LAMC1/LGALS3/PCD6IP/SFN/TPM3/VARS/YWHAZ) for mPDAC-EVs and 9 (ACTB/ALDH2/GAPDH/HNRNPA2B/ITGA2/NEXN/PKM/RPN1/S100A6) for KPC-EVs were significantly overexpressed in tumor tissues according to gene expression profiling interaction analysis (GEPIA). Concerning the potential clinical relevance of these data, the cluster of ACTB, ITGA2, GAPDH and PKM genes displayed an adverse effect (p < 0.05) on the overall survival of PDAC patients.
A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.
Guergues J, Wohlfahrt J, Koomen JM … +3 more , Krieger JR, Varma S, Stevens SM
Proteomics · 2025 Feb · PMID 39235396 · Full text
Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets...
Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.
Analysis of Unfolded Protein Response Activation in Colon Adenocarcinoma Epithelial Cells: A Proteomic Study.
Vivier S, Bray F, Flament S … +6 more , Guilbert L, Renaud F, Rolando C, Launay D, Dubucquoi S, Sobanski V
Proteomics Clin Appl · 2024 Nov · PMID 39226110 · Publisher ↗
PURPOSE: High throughput technologies have identified molecular patterns in colorectal cancer (CRC) cells, aiding in modeling responses to anti-cancer treatments. The different responses observed depend on the type of ca...
PURPOSE: High throughput technologies have identified molecular patterns in colorectal cancer (CRC) cells, aiding in modeling responses to anti-cancer treatments. The different responses observed depend on the type of cancer, the tumour grade and the functional programme of the cancer cells. Recent studies suggest that the unfolded protein response (UPR), autophagy and apoptosis could be involved in treatment resistance mechanisms by interacting with the tumour microenvironment (TME). EXPERIMENTAL DESIGN: We analysed by LC-MS/MS the proteome of two representative colon adenocarcinoma epithelial cell lines from different tumour grades (CCL-233 and CCL-221) at the basal state or after the UPR induction. RESULTS: Cell lines expressed a different proteome on about 10% of their total proteins identified, especially on UPR, autophagy and apoptosis pathways proteins at basal state. After UPR induction, the proteome of the cells was modified with a greater adaptive response to cellular stress in CCL-221 cells where the UPR was strongly activated at the basal state. CONCLUSIONS AND CLINICAL RELEVANCE: CRC cell lines at different tumour grades expressed different functional programmes at the proteomic level and were characterised by different responses to the UPR induction. This study suggests that baseline cancer cell stress status could have an impact on the efficiency of cancer therapies.
Combining proteomics and Phosphoproteomics to investigate radiation-induced rectal fibrosis in rats and the effects of pSTAT3 inhibitor S3I-201 on human intestinal fibroblasts.
Pan H, Zhao Z, Zhu Y … +5 more , Gao Y, Ruan H, Huang Y, Chi P, Huang S
J Proteomics · 2024 Sep · PMID 39173903 · Publisher ↗
OBJECTIVE: To investigate the regulatory mechanisms of radiation-induced rectal fibrosis (RIRF) and assess the therapeutic potential of S3I-201. METHODS: Sprague-Dawley rats were divided into control and radiation groups...
OBJECTIVE: To investigate the regulatory mechanisms of radiation-induced rectal fibrosis (RIRF) and assess the therapeutic potential of S3I-201. METHODS: Sprague-Dawley rats were divided into control and radiation groups, with the latter exposed to 20 Gray pelvic X-rays. After 10 weeks, rectal tissues were analyzed using tandem mass tag (TMT) proteomics and phosphoproteomics. Pathway enrichment was performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, with secondary annotation using Cluego. Representative proteins and their phosphorylated counterparts were validated through immunoblotting in another cohort. STAT3 levels in rectal tissues from irradiated and non-irradiated colorectal cancer patients were examined, and the effects of S3I-201 on human rectal fibroblasts were evaluated. RESULTS: The radiation group showed significant inflammatory responses and collagen deposition in the rat rectal walls. Enrichment analysis revealed that radiation-induced proteins and phosphoproteins were primarily involved in extracellular matrix-receptor interaction and the MAPK signaling pathway. Immunoblotting indicated increased expression of p-CAMKII, p-MRACKS, p-Cfl1, p-Myl9, and p-STAT3 in the radiation group compared to the control, while p-AKT1 expression decreased. Elevated phosphorylation of STAT3 was observed in submucosal fibroblasts of the post-radiation human rectum. S3I-201 specifically inhibited STAT3 phosphorylation and suppressed activation of human rectal fibroblasts, also inhibiting the pro-fibrotic effects of the classical TGF-β/Smad/CTGF pathway. CONCLUSION: By integrating phosphoproteomics and proteomics, this study elucidated the protein regulatory network of RIRF and identified the potential therapeutic targets, including phosphoproteins such as STAT3 in managing RIRF. SIGNIFICANCE: In our research, we employed TMT labeling alongside LC-MS/MS techniques to comprehensively explore the proteomic and phosphoproteomic landscapes in rat models of radiation-induced intestinal fibrosis (RIRF). Our analysis revealed the function and pathways of proteins and phosphorylated proteins triggered by radiation, as well as those with protective roles. We mapped a network of interactions among these proteins and validated key protein expression levels using quantitative methods. Furthermore, we investigated STAT3 as a potential therapeutic target, assessing the efficacy of the inhibitor S3I-201 in laboratory settings, and highlighting its potential for RIRF treatment. Overall, our findings provide groundbreaking insights into the mechanisms underlying RIRF, paving the way for the development of future antifibrotic therapies.
Plasma proteomics implicate glutamic oxaloacetic transaminases as potential markers for acute myocardial infarction.
Wei Q, Li K, Su L … +5 more , Cen T, Sooranna SR, Pan X, Huang Z, Liu Y
J Proteomics · 2024 Sep · PMID 39173902 · Publisher ↗
AIM: To provide a novel perspective on the pathogenesis of acute myocardial infarction (AMI) patients with respect to glutamic oxaloacetic transaminase (GOT). METHODS: The plasma proteome of 20 patients with AMI were mat...
AIM: To provide a novel perspective on the pathogenesis of acute myocardial infarction (AMI) patients with respect to glutamic oxaloacetic transaminase (GOT). METHODS: The plasma proteome of 20 patients with AMI were matched for age and sex and compared with 10 healthy individuals. We analyzed the mass spectrum data and compared the signal intensity of the corresponding peptides which related to their corresponding proteins. A sample-specific protein database was constructed and a quality control analysis was conducted to screen out the key regulatory proteins under specific experimental conditions. The data from 37 new AMI patients and 13 healthy adults were subjected to parallel reaction monitoring (PRM) to verify the target proteins found. Finally, the survival status of the key genes (> 1.5-fold) in the PPI were analyzed. RESULTS: 2589 and 2162 proteins were identified and quantified, respectively, and 143 differentially expressed proteins (DEPs) (≥1.5-fold) were found between the AMI and control groups. Of these 90 and 53 were significantly up-regulated and down-regulated, respectively. Gene ontology, KEGG enrichment, protein domain and cluster analysis as well as PPI networks of the DEPs revealed a central role of acute inflammatory response processes in patients with AMI. A cluster of proteins were found to be related to cysteine, methionine, arginine, proline, phenylalanine and propanoate metabolism as well as the cAMP signaling pathway. PPI network analysis showed CHI3L1, COPB2, GOT2, MB, CYCS, GOT1, CKM, SAA1 and PRKCD and RPS3 were in key positions, but only MB, CKM, GOT1, PRKCD, CYCS and GOT2 were found in a cluster. PRM verified the high levels of MB, CKM, GOT1 and GOT2 in 37 AMI patients but there was no statistical difference in the survival status for patients with either high or low expression levels of these proteins. CONCLUSIONS: Our findings showed that acute inflammatory response processes play a central role in patients with AMI. Cysteine and methionine metabolism was also activated, in which GOT1 and GOT2 were key proteins. These pathways might be potential targets for diagnosis and novel therapies to improve the poor outcomes observed in patients with heart failure.
Proteomic characterization of the medial prefrontal cortex in chronic restraint stress mice.
Fu Y, Gu Z, Cao H … +6 more , Zuo C, Huang Y, Song Y, Miao J, Jiang Y, Wang F
J Proteomics · 2024 Sep · PMID 39142625 · Publisher ↗
Depression is a prominent contributor to global disability. A growing body of data suggests that depression is associated with the pathophysiology of the medial prefrontal cortex (mPFC), but the underlying mechanisms rem...
Depression is a prominent contributor to global disability. A growing body of data suggests that depression is associated with the pathophysiology of the medial prefrontal cortex (mPFC), but the underlying mechanisms remain poorly understood. Mice were subjected to chronic restraint stress (CRS) for 3 weeks to create depression models during this investigation. Protein tandem mass tag (TMT) quantification and LC-MS/MS analysis were conducted to examine proteome patterns. Afterwards, to further explore the enrichment of differential proteins and the signaling pathways involved, we annotated these differentially expressed proteins. We confirmed that CRS mice developed depression-like and anxiety-like behaviors. Among the 8081 measured proteins, a total of 15 proteins were found to be differentially expressed. These proteins exhibited functional enrichment in a variety of biological functions, and among these pathways, alterations in synaptic function and autophagy are noteworthy. In addition, we identified a differentially expressed protein called Wnt2b and found that CRS may disrupt synaptic plasticity by affecting the activation of the Wnt2b/β-catenin pathway. Our findings showed depression-like behaviors in the CRS mouse model and molecular alterations in the mPFC, which may help explain the pathogenesis of depression and identify novel antidepressant medication targets. SIGNIFICANCE: Depression is a prevalent and frequent chronic mental illness and is now a significant contributor to global disability. In this study, we used chronic restraint stress to establish a mouse model of depression, and differentially expressed proteins in the medial prefrontal cortex of depressed model mice were detected by TMT proteomics. Our study verified the presence of altered synaptic function and excessive autophagy in the mPFC of CRS-induced mice from a proteomic perspective. Furthermore, we demonstrated that CRS may disrupt synaptic plasticity by affecting the activation of the Wnt2b/β-catenin pathway, which may be a key link in the pathogenesis of depression and may provide new insights for identifying new antidepressant drug targets.
TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data.
Cosenza-Contreras M, Seredynska A, Vogele D … +14 more , Pinter N, Brombacher E, Cueto RF, Dinh TJ, Bernhard P, Rogg M, Liu J, Willems P, Stael S, Huesgen PF, Kuehn EW, Kreutz C, Schell C, Schilling O
Proteomics · 2024 Oct · PMID 39126236 · Publisher ↗
State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modific...
State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "neo-N-termini" analysis or "N-terminomics"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.
"Phosphoproteomic quantification based on phosphopeptide intensity or occupancy? An evaluation based on casein kinase 2 downstream effects".
Rodríguez-Ulloa A, Rosales M, Ramos Y … +6 more , Guirola O, González LJ, Wiśniewski JR, Perera Y, Perea SE, Besada V
J Proteomics · 2024 Sep · PMID 39098729 · Publisher ↗
Quantitative phosphoproteomic data has mostly been reported from experiments comparing relative phosphopeptides intensities in two or more different conditions, while the ideal parameter to compare is phosphopeptides occ...
Quantitative phosphoproteomic data has mostly been reported from experiments comparing relative phosphopeptides intensities in two or more different conditions, while the ideal parameter to compare is phosphopeptides occupancies. This term is scarcely used and therefore barely implemented in phosphoproteomics studies, and this should be of concern for the scientific journals. In order to demonstrate the relevance of this issue, here we show how the method of choice affects the interpretation of the data. The phosphoproteomic profile modulated in two AML cell lines after CK2 inhibition with CIGB-300 or CX-4945 is shown. Following the downstream action of CK2 the phosphosite intensity and occupancy results were compared to validate the best approach for quantitative phosphoproteomic studies. Even when the total number of quantified phosphopeptides was higher by using the intensity calculation, in all the cases the percent of CK2 consensus sequences which were down-regulated in response to CK2 inhibition was higher using the phosphosite occupancy quantification. To note, a high number of CK2 consensus sequences was found down-regulated with at least a 10% or 15% of phosphosite occupancy variation illustrating that low thresholds of occupancy modulation might be indicative of biological effect. Additionally, several biological processes only appear significantly over-represented in the phosphoproteome quantified by occupancy. The functional enrichment analysis per ranges of occupancy variations also illustrated clear differences among AML cell lines subjected to CK2 inhibition by CX-4945. A low overlap between the phosphoproteomes quantified by intensity and occupancy was obtained illustrating that new developments in proteomics techniques are needed to improve the performance of the occupancy approach. Even in such context, results indicate that occupancy quantification performs better than phosphorylation quantification based on intensity reinforcing the importance of such quantification approach to describe phosphoproteomic data.
Data acquisition approaches for single cell proteomics.
Ghosh G, Shannon AE, Searle BC
Proteomics · 2025 Jan · PMID 39088833 · Full text
Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome an...
Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.
Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications.
Ramesh P, Nisar M, Neha … +7 more , Ammankallu S, Babu S, Nandakumar R, Abhinand CS, Prasad TSK, Codi JAK, Raju R
J Proteomics · 2024 Aug · PMID 39047941 · Publisher ↗
Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility...
Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument. Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.
SWATH-proteomics reveals Mathurameha, a traditional anti-diabetic herbal formula, attenuates high glucose-induced endothelial dysfunction through the EGF/NO/IL-1β regulatory axis.
Aluksanasuwan S, Somsuan K, Chiangjong W … +6 more , Rongjumnong A, Jaidee W, Rujanapun N, Chutipongtanate S, Laphookhieo S, Charoensup R
J Proteomics · 2024 Aug · PMID 39047940 · Publisher ↗
Mathurameha is a traditional Thai herbal formula with a clinically proven effect of blood sugar reduction in patients with diabetes mellitus, but its anti-diabetic complication potential is largely unknown. This study ai...
Mathurameha is a traditional Thai herbal formula with a clinically proven effect of blood sugar reduction in patients with diabetes mellitus, but its anti-diabetic complication potential is largely unknown. This study aimed to elucidate the effects of Mathurameha and its underlying mechanisms against high glucose-induced endothelial dysfunction in human endothelial EA.hy926 cells. After confirming no cytotoxic effects, the cells were treated with normal glucose (NG), high glucose (HG), or high glucose plus Mathurameha (HG + M) for 24 h. A quantitative label-free proteomic analysis using the sequential window acquisition of all theoretical mass spectra (SWATH-MS) approach identified 24 differentially altered proteins among the three groups: 7 between HG and NG, 9 between HG + M and NG, and 13 between HG + M and HG. Bioinformatic analyses suggested a potential anti-diabetic action through the epidermal growth factor (EGF) pathway. Subsequent functional validations demonstrated that Mathurameha reduced the EGF secretion and the intracellular reactive oxygen species (ROS) level in high glucose-treated cells. Mathurameha also exhibited a stimulatory effect on nitric oxide (NO) production while significantly reducing the secretion of endothelin-1 (ET-1) and interleukin-1β (IL-1β) in high glucose-treated cells. In conclusion, our findings demonstrated that Mathurameha attenuated high glucose-induced endothelial dysfunction through the EGF/NO/IL-1β regulatory axis. SIGNIFICANCE: This study reveals the potential of Mathurameha, a traditional Thai herbal formula, in mitigating high glucose-induced endothelial dysfunction, a common complication in diabetes mellitus. Using proteomics and bioinformatic analyses followed by functional validations, the present study highlights the protective effects of Mathurameha through the EGF/NO/IL-1β regulatory axis. These findings support its potential use as a therapeutic intervention for diabetic vascular complications and provide valuable information for developing more effective anti-diabetic drugs.
About
- Frequency
- Sun
- Papers found
- 200
- RSS feed
- Subscribe