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In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers.

ABSTRACT: Liver metastasis is the most common form of metastatic colorectal cancers during the course of the disease. The global change in protein abundance in liver metastatic colorectal cancers and its role in metastasis establishment have not been comprehensively analyzed. In the present study, fresh-frozen tissue samples including normal colon/localized/liver metastatic CRCs from each recruited patient were analyzed by quantitative proteomics using a multiplexed TMT labeling strategy. Around 5000 protein groups were quantified from all samples. The proteomic profile of localized/metastatic CRCs varied greatly from that of normal colon tissues; differential proteins were mainly from extracellular regions and participate in immune activities, which is crucial for the chronic inflammation signaling pathways in the tumor microenvironment. Further statistical analysis revealed 47 proteins exhibiting statistical significance between localized and metastatic CRCs, of which FILI1P1 and PLG were identified for the first time in proteomic data, which were highly associated with liver metastasis in CRCs.

SUBMITTER: Ku X

PROVIDER: S-EPMC6875276 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers.

Ku Xin X Xu Yan Y Cai Chunlin C Yang Yili Y Cui Long L Yan Wei W

Analytical cellular pathology (Amsterdam) 20191104

Liver metastasis is the most common form of metastatic colorectal cancers during the course of the disease. The global change in protein abundance in liver metastatic colorectal cancers and its role in metastasis establishment have not been comprehensively analyzed. In the present study, fresh-frozen tissue samples including normal colon/localized/liver metastatic CRCs from each recruited patient were analyzed by quantitative proteomics using a multiplexed TMT labeling strategy. Around 5000 prot ...[more]

PMID: 31781478

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Project description:BackgroundHalting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking.MethodsPlasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses.ResultsThe resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched.ConclusionsThe in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

Project description:BackgroundFeline mammary carcinoma (FMC) is a common aggressive and highly metastatic cancer affecting female cats. Early detection is essential for preventing local and distant metastasis, thereby improving overall survival rates. While acquiring molecular data before surgery offers significant potential benefits, the current protein biomarkers for monitoring disease progression in non-metastatic FMC (NmFMC) and metastatic FMC (mFMC) are limited. The objective of this study was to investigate the serum peptidome profiles of NmFMC and mFMC using liquid chromatography-tandem mass spectrometry. A cross-sectional study was conducted to compare serum peptidome profiles in 13 NmFMC, 23 mFMC and 18 healthy cats. The liquid chromatography-tandem mass spectrometry analysis was performed on non-trypsinized samples.ResultsOut of a total of 8284 expressed proteins observed, several proteins were found to be associated with human breast cancer. In NmFMC, distinctive protein expressions encompassed double-stranded RNA-binding protein Staufen homolog 2 (STAU2), associated with cell proliferation, along with bromodomain adjacent to zinc finger domain 2A (BAZ2A) and gamma-aminobutyric acid type A receptor subunit epsilon (GABRE), identified as potential treatment targets. Paradoxically, positive prognostic markers emerged, such as complement C1q like 3 (C1QL3) and erythrocyte membrane protein band 4.1 (EPB41 or 4.1R). Within the mFMC group, overexpressed proteins associated with poor prognosis were exhibited, including B-cell lymphoma 6 transcription repressor (BCL6), thioredoxin reductase 3 (TXNRD3) and ceruloplasmin (CP). Meanwhile, the presence of POU class 5 homeobox (POU5F1 or OCT4) and laminin subunit alpha 1 (LAMA1), reported as metastatic biomarkers, was noted.ConclusionThe presence of both pro- and anti-proliferative proteins was observed, potentially indicating a distinctive characteristic of NmFMC. Conversely, proteins associated with poor prognosis and metastasis were noted in the mFMC group.

Dataset Information

In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers.

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In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers.

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