Differential expression and clinical significance of serum protein among patients with clear-cell renal cell carcinoma

Identification of potential biomarkers for progression and prognosis of renal clear cell carcinoma by comprehensive bioinformatics analysis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma (RCC), and effective biomarkers will improve diagnosis and treatment.

OBJECTIVE

This study investigated NPEPL1 expression in ccRCC through public databases and clinical samples and assessed its correlation with clinicopathological features and patient prognosis.

METHOD

Data from The Cancer Genome Atlas and clinical specimens were gathered, NPEPL1 expression levels were analyzed; a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of NPEPL1; and clinicopathological data was used to study the correlations between expression and clinical parameters. NPEPL1's prognostic value was appraised using a Kaplan-Meier (K-M) survival curve, Cox regression analysis, and a nomogram model; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differently expressed genes between tissues with high and low NPEPL1 expression were used to estimate the underlying mechanisms involved.

RESULTS

NPEPL1 was significantly higher-expressed in ccRCC tissue. ROC analysis showed that NPEPL1 had noteworthy diagnostic efficacy. NPEPL1 expression was closely related to clinicopathological parameters, such as T and M stage. K-M analysis showed that overall survival was significantly shortened with high NPEPL1 expression. Cox regression analysis showed that NPEPL1 expression was an independent risk factor predicting overall survival. The nomogram showed a significantly high clinical value in predicting the 1-, 3-, and 5-year survival probabilities in ccRCC. GO and KEGG enrichment analysis suggested that NPEPL1 may promote the occurrence and development of ccRCC via the Ras signaling and other pathways.

CONCLUSION

NPEPL1 expression in ccRCC was higher than that in normal kidney tissues and was significantly associated with advanced clinical stage and poor prognosis. Therefore, NPEPL1 is a promising prognostic biomarker.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Serum tumour associated trypsin inhibitor, as a biomarker for survival in renal cell carcinoma

OBJECTIVE

Tumour associated trypsin inhibitor (TATI) is a peptide that is a marker for several tumours. TATI may also behave as an acute phase reactant in severe inflammatory disease. Overexpression of TATI predicts an unfavourable outcome for many cancers. This study aimed to evaluate the prognostic value of pre- and postoperative concentration of TATI in serum (S-TATI) of patients with renal cell carcinoma (RCC).

MATERIALS AND METHODS

S-TATI was determined by time resolved immunofluorometric assay in preoperative and postoperative samples that were collected from 132 RCC patients, who underwent partial or complete nephrectomy in Helsinki University Hospital from May 2005 to July 2010.

RESULTS

Preoperative S-TATI was significantly associated with tumour stage, lymph-node involvement, metastatic stage, Chronic Kidney Disease Stage (CKD grade), and preoperative C-reactive protein level (p < 0.05). Postoperative S-TATI was significantly associated only with CKD grade (p < 0.001). Multivariate Cox regression analysis of postoperative S-TATI, as a continuous variable, was an independent prognostic factor for overall survival (HR = 1.01, 95% CI = 1.00-1.01, p = 0.03) and cancer-specific survival (CSS) (HR = 1.01, 95% CI = 1.00-1.02, p = 0.004).

CONCLUSIONS

Our data suggest that elevated postoperative S-TATI may be associated with adverse prognosis in RCC patients.

Challenges and opportunities in the proteomic characterization of clear cell renal cell carcinoma (ccRCC): A critical step towards the personalized care of renal cancers

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, comprising approximately 75% of all kidney tumors. Recent the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) studies have significantly advanced the molecular characterization of RCC and facilitated the development of targeted therapies. Such advances have improved the median survival of patients with advanced disease from less than 10 months prior to 2004 to 30 months by 2011. However, approximately 30% of localized ccRCC patients will nevertheless develop recurrence or metastasis after surgical resection of their tumor. Therefore, it is critical to further analyze potential tumor-associated proteins and their profiles during disease progression. Over the past decade, tremendous effort has been focused on the study of molecular pathways, including genomics, transcriptomics, and proteomics in order to identify potential molecular biomarkers, as well as to facilitate early detection, monitor tumor progression and uncover potentially therapeutic targets. In this review, we focus on recent advances in the proteomic analysis of ccRCC, current strategies and challenges, and perspectives in the field. This insight will highlight the discovery of tumor-associated proteins, and their potential clinical impact on personalized precision-based care in ccRCC.

Expression of microRNA-30c via lentivirus vector inhibits the proliferation and enhances the sensitivity of highly aggressive ccRCC Caki-1 cells to anticancer agents

The clear cell renal cell carcinoma (ccRCC) is one of the most fatal urologic tumors, and the prognosis remains very poor for advanced or metastatic ccRCC. This study reveals the roles of microRNA (miR)-30c in regulating a highly aggressive ccRCC cell line proliferation by targeting MTA-1, which is a key mediator for human cancer metastasis. Results from quantitative real-time polymerase chain reaction showed that the expression of MTA-1, the target of miR-30c, was significantly higher in metastatic ccRCC specimens than in nonmetastatic ccRCC or nontumor specimens. Accordingly, endogenous miR-30c is at a much lower level in highly aggressive ccRCC Caki-1 cells than nontumor or ccRCC cell lines. Expression of miR-30c via lentivirus vector inhibits the proliferation, anchorage-independent growth, in vitro invasion or migration, or in vivo growth of Caki-1 cells by repressing MTA-1 protein expression. miR-30c also enhances the sensitivity of Caki-1 cells to anticancer agents, including sorafenib and paclitaxel. These data reveal the potential application of miR-30c and that its targeting gene, MTA-1, would be a potential target in metastatic ccRCC treatment.

The proteomic landscape of renal tumors

INTRODUCTION

Renal cell carcinoma (RCC) is the most fatal of the common urologic cancers, with approximately 35% of patients dying within 5 years following diagnosis. Therefore, there is a need for non-invasive markers that are capable of detecting and determining the severity of small renal masses at an early stage in order to tailor treatment and follow-up. Proteomic studies have proved to be very useful in the study of tumors. Areas covered: In this review, we will detail the current knowledge obtained by the different proteomic approaches, focusing on MS-based strategies, used to investigate RCC biology in order to identify diagnostic, prognostic and predictive biomarkers on tissue, cultured cells and biological fluids. Expert commentary: Currently, no reliable biomarkers or targets for RCC have been translated into the clinical setting. Moreover, despite the efforts of proteomics and other -omics disciplines, only a small number of them have been observed as shared targets between the different analytical platforms and biological specimens. The difficulty to define a specific molecular pattern for RCC and its subtypes highlights a peculiar profile and a heterogeneity that must be taken into account in future studies.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.