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ITRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer.

ABSTRACT: Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

SUBMITTER: Pathania S

PROVIDER: S-EPMC9124668 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer.

Pathania Sheetal S Khan Mohd Imran MI Bandyopadhyay Sabyasachi S Singh Suneet Shekhar SS Rani Komal K Parashar Tanvi Ramesh TR Jayaram Jnaneshwari J Mishra Piyush Ranjan PR Srivastava Anurag A Mathur Sandeep S Hari Smriti S Vanamail Perumal P Hariprasad Gururao G

Scientific reports 20220522 1

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was ...[more]

PMID: 35599267

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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.

Project description:IntroductionBreast cancer is the second most common cancer in women across the world. Some of the 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 its diagnosis is crucial for the staging of cancer thereby dictating the type of surgical therapy. Therefore, the sentinel lymph node status provides the most relevant information to the surgeon and patient prognosis. The expanded utilization of breast conservation surgery has declined the morbidity associated with mastectomy and axillary lymph node surgery. Recent interest is, therefore, centered on techniques that allow accurate assessment of the sentinel lymph node metastasis. A current procedure such as sentinel lymph node biopsy (SLNB) that is used to assess axillary lymph node metastasis is neither specific nor sensitive, and besides, it is time-consuming.ObjectiveTo compare the protein profiles between metastatic and non-metastatic lymph nodes to identify a biomarker that can flag lymph node metastasis.Materials and methodsWomen with early breast cancer were screened using mammography imaging and recruited to the study. Surgical resection was done to remove the breast tissue, and sentinel lymph node was identified using fluorescein and methylene blue tracer. Lymph node was sliced, and one set was sent for histopathology, which was considered the gold standard to assess the metastatic status of the lymph node. One set of slices was taken for proteomic experiments. Proteins were labelled with fluorescent cyanine tags and were subjected to difference gel electrophoresis experiment. Differentially expressed spots that had at least a twofold relative ratio and consistent pattern across three sets of biological replicate experiments were marked. Gel spots were trypsin digested and identified on mass spectrometry machine. Validation study was done by Western blot experiment on the same set of samples.ResultsThymidylate synthase has a twofold higher expression in the metastatic sentinel lymph nodes as compared to non-metastatic lymph nodes in early breast cancer patients.ConclusionDifferential in gel expression proteomics is an ideal platform for the identification of potential protein biomarker candidates that can differentiate metastatic from non-metastatic lymph nodes in early breast cancer. The identification of thymidylate synthase offers a scope to develop an on-table diagnostic kit to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical management of axillary lymph nodes in early breast cancer.

Project description:BackgroundIndividualized decisions are required in early-stage breast cancer patients. We aimed to establish a novel model for predicting non-sentinel lymph node (SLN) metastases in patients with positive SLNs, using preoperative and intraoperative characteristics and inflammatory indicators.MethodsThe data of 489 patients with invasive breast cancer were retrospectively collected from Xuanwu Hospital between 2014 and 2021. Among them, 96 patients with at least one positive SLN were used to build the predictive model. Univariate and multivariate analyses were performed to identify the risk factors of non-SLN metastases. A nomogram was developed using these risk factors and was validated by calibration curves. The area under the receiver operating characteristics curve (AUC) and decision curve analyses (DCA) were used to compare our novel nomogram with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram. Cross-validation was performed for further internal validation of the predictive model. External validation was conducted using another treatment group (n=46 patients) in Xuanwu Hospital.ResultsNon-SLN metastases occurred in 42 of the 83 patients with positive SLNs (50.6%). Multivariate stepwise logistic regression indicated that the risk factors were age (P=0.032), number of positive SLNs (P=0.020), number of negative SLNs (P=0.011), resected tumor size (P=0.038), and monocyte count (P=0.012). A predictive model was developed and virtualized by nomogram using these five risk factors. The AUC of our nomogram was 0.867, which was significantly higher than that of the MSKCC model. DCA also showed a superior clinical value for our novel nomogram. After 10-fold cross-validation with 400 times repetitions, the AUC of our model was still 0.830. External validation of our model showed an AUC of 0.727. The model was well-calibrated in the internal and external validation series.ConclusionsA five-factor nomogram was developed for predicting non-SLN metastases in early-stage breast cancer patients. This novel tool exhibited good accuracy and could assist clinicians with intraoperative decisions in breast cancer patients with positive SLNs.

Dataset Information

ITRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer.

Publications

iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer.

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