Dataset Information

Proteomic analysis identifies HMGA2 as a novel biomarker of overall survival in papillary renal cell carcinoma.

ABSTRACT:

Purpose

Although papillary renal cell carcinoma (PRCC) has a relatively favorable prognosis, a small number of patients with lymph node or distant metastasis have a poor prognosis. Owing to the complex typing and heterogeneity of PRCC, it remains difficult to provide risk stratification. The objective of our research was to identify potential markers of PRCC prognosis.

Methods

We performed proteomics and bioinformatics analyses on six pairs of formalin-fixed paraffin-embedded tumor and paired normal tissue samples. The Cancer Genome Atlas (TCGA) data were used to analyze the prognostic value of differentially expressed proteins (DEPs) in PRCC. We verified the expression of the major biomarker through immunohistochemistry (IHC) in 91 PRCC tumor specimens.

Results

Proteomic analysis revealed 1544 DEPs between tumor and paired normal tissues. PRCC transcriptomic data from the TCGA database revealed that compared to non-tumor tissues, the expression of high-mobility group protein A2 (HMGA2) was upregulated in tumor tissues, and patients with high HMGA2 expression exhibited shorter overall survival times. HMGA2 was associated with PRCC tissue subtype and higher cell pleomorphism. Both TCGA and IHC results showed that HMGA2 expression was associated with lymph node metastasis and clinical stage.

Conclusion

HMGA2 was positively correlated with malignant progression and could be a valuable novel prognostic biomarker for PRCC risk stratification.

SUBMITTER: Wei T

PROVIDER: S-EPMC10358203 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Proteomic analysis identifies HMGA2 as a novel biomarker of overall survival in papillary renal cell carcinoma.

Wei Tian T Xu Huiya H Liang Huishan H Lian Yating Y Chen Huiyu H Zheng Zhangyi Z Zhong Minghui M Liu Junfeng J Wang Ran R Wang Fen F

Cancer medicine 20230607 13

<h4>Purpose</h4>Although papillary renal cell carcinoma (PRCC) has a relatively favorable prognosis, a small number of patients with lymph node or distant metastasis have a poor prognosis. Owing to the complex typing and heterogeneity of PRCC, it remains difficult to provide risk stratification. The objective of our research was to identify potential markers of PRCC prognosis.<h4>Methods</h4>We performed proteomics and bioinformatics analyses on six pairs of formalin-fixed paraffin-embedded tumo ...[more]

PMID: 37283291

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Project description:BackgroundPapillary renal cell carcinoma (pRCC) is the largest histologic subtype of non-clear-cell RCC. To date, there is no reliable nomogram to predict the prognosis of patients with pRCC after nephrectomy. We aimed to first establish an effective nomogram to predict the overall survival (OS) of patients with pRCC after nephrectomy.MethodsA total of 3,528 eligible patients with pRCC after nephrectomy were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The patients were randomized into the training cohort (n = 2,472) and the validation cohort (n = 1,056) at a 7:3 ratio. In total, 122 real-world samples from our institute (titled the AHMU-pRCC cohort) were used as the external validation cohort. Univariate and subsequent multivariate Cox regression analyses were conducted to identify OS-related prognostic factors, which were further used to establish a prognostic nomogram for predicting 1-, 3-, and 5-year OS probabilities. The performance of the nomogram was evaluated by using the concordance index (C-index), receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA).ResultsMultivariate Cox analysis showed that age, race, marital status, TNM stage, tumor size, and surgery were significant OS-related prognostic factors. A prognostic model consisting of these clinical parameters was developed and virtualized by a nomogram. High C-index and area under the ROC curve (AUC) values of the nomogram at 1, 3, and 5 years were found in the training, validation, and AHMU-pRCC cohorts. The calibration plot and DCA also showed that the nomogram had a satisfactory clinical application value. A risk classification system was established to risk-stratify patients with pRCC.ConclusionBased on a large cohort from the public SEER database, a reliable nomogram predicting the OS of patients with pRCC after nephrectomy was constructed, which could optimize the survival assessment and clinical treatment.

Dataset Information

Proteomic analysis identifies HMGA2 as a novel biomarker of overall survival in papillary renal cell carcinoma.

Purpose

Methods

Results

Conclusion

Publications

Proteomic analysis identifies HMGA2 as a novel biomarker of overall survival in papillary renal cell carcinoma.

Similar Datasets

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