Dataset Information

Clinical proteomics analysis using Data Independent Acquisition-Mass Spectrometry (DIA-MS) identified classifiers for molecular characterization of Lymphoma

ABSTRACT: In this study, we conducted a proteomics analysis on 109 fresh-frozen lymph node samples from clinical patients, covering a comprehensive suite of lymphoma subtypes including B-NHL, T-NHL, HL, Lymphadenitis, Tumor metastatic lymph node (TLN), and Non-neoplastic lymph node (TNM: N0).

ORGANISM(S): Homo Sapiens

SUBMITTER: Wei Yan

PROVIDER: PXD017096 | iProX | Wed Jan 15 00:00:00 GMT 2020

REPOSITORIES: iProX

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Publications

Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression.

Ku Xin X Wang Jinghan J Li Haikuo H Meng Chen C Yu Fang F Yu Wenjuan W Li Zhongqi Z Zhou Ziqi Z Zhang Can C Hua Ying Y Yan Wei W Jin Jie J

Phenomics (Cham, Switzerland) 20221212 2

An altered proteome in lymph nodes often suggests abnormal signaling pathways that may be associated with diverse lymphatic disorders. Current clinical biomarkers for histological classification of lymphomas have encountered many discrepancies, particularly for borderline cases. Therefore, we launched a comprehensive proteomic study aimed to establish a proteomic landscape of patients with various lymphatic disorders and identify proteomic variations associated with different disease subgroups. ...[more]

PMID: 37197640

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Project description:Background Breast cancer patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and metastasis to this lymph node is crucial for the staging of cancer and the quality of surgical intervention. Sentinel Lymph Node Biopsy (SLNB) that is currently used to assess lymph node metastasis is neither sensitive, nor specific, is time-consuming, thereby necessitating the identification of novel biomarkers that can flag sentinel lymph node metastasis. Methods Breast cancer patients were screened, and those with early stage were recruited in the study. Surgical resection of the breast was followed by identification of sentinel lymph nodes by methylene fluorescent technique. Histo-pathology of fresh frozen section biopsy was used as the gold standard to assign the clinical phenotypes of metastatic (SLNM+) and non-metastatic sentinel lymph nodes (SLNM-). Discovery phase of the experiment included isobaric Tags for Relative and Absolute Quantitation (iTRAQ) technique comprising of six comparative experiments coupled with mass spectrometric analysis on Orbitrap Fusion to identify differentially expressed proteins on Proteome Discoverer 2.4. Functional enrichment and pathway analyses of differentially regulated genes was carried out in DAVID functional annotation tool. Validation was done by ELISA and protein concentrations were used to estimate the ROC for computing diagnostic parameters. Results Based on MS/MS spectra there were 2396 unique protein groups and 81 differentially expressed proteins comparing SLNB + and SLNB -. Nineteen proteins up-regulated, and eight proteins that were down regulated in SLNB+ as compared to SLNB-. Bioinformatic analysis showed the implication of extra cellular matrix proteins and ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed the up-regulation of caveolin 1, collagen α-1, desmin, fibrillin-1, and microfibrillar associated glycoprotein 4 in metastatic, as compared to non-metastatic lymph nodes. These proteins are known to be integral in tumorogenesis, cell proliferation, invasion, cell survival and anti-apoptosis. These proteins have 80%-100%, of sensitivity and specificity to differentiate the two clinical phenotypes. Conclusion Identified extra cellular matrix protein biomarkers have requisite diagnostic parameters to be developed as a translational tool to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical therapy of axillary lymph nodes in early breast oncology.

Dataset Information

Clinical proteomics analysis using Data Independent Acquisition-Mass Spectrometry (DIA-MS) identified classifiers for molecular characterization of Lymphoma

Publications

Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression.

Similar Datasets

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