iTRAQ-Based Quantitative Proteomic Analysis Identified HSC71 as a Novel Serum Biomarker for Renal Cell Carcinoma

Screening of autoantibodies as biomarkers in the serum of renal cancer patients based on human proteome microarray

The autoantibody in patients' serum can act as a biomarker for diagnosing cancer, and the differences in autoantibodies are significantly correlated with the changes in their target proteins. In this study, 16 renal cancer (RC) patients were assigned to the disease group, and 16 healthy people were assigned to the healthy control (HC) group. The human proteome microarray consisting of>19,500 proteins was used to examine the differences in IgG and IgM autoantibodies in sera between RC and HC. The comparative analysis of the microarray results shows that 101 types of IgG and 25 types of IgM autoantibodies are significantly higher in RC than in HC. Highly responsive autoantibodies can be candidate biomarkers (e.g., anti-KCNAB2 IgG and anti-RCN1 IgM). Extensive enzyme-linked immunosorbent assay (ELISA) was performed to screen sera in 72 RC patients and 66 healthy volunteers to verify the effectiveness of the new autoantibodies. The AUCs of anti-KCNAB2 IgG and anti-GAPDH IgG were 0.833 and 0.753, respectively. KCNAB2 achieves high protein expression, and its high mRNA level is confirmed to be an unfavorable prognostic marker in clear cell renal cell carcinoma (ccRCC) tissues. This study suggests that the high-throughput human proteome microarray can effectively screen autoantibodies in serum as candidate biomarkers, and their corresponding target proteins can lay a basis for the in-depth investigation into renal cancer.

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.

HSPA1A, HSPA2, and HSPA8 Are Potential Molecular Biomarkers for Prognosis among HSP70 Family in Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disease, which leads to impairment of cognition and memory. The heat shock protein 70 (HSP70) family plays an important role in the pathogenesis of AD. It is known to regulate protein misfolding in a variety of diseases, including inhibition of Aβ aggregation and NFT formation in AD. As yet, the diagnostic molecular markers of AD remain unclear. Herein, we sought to investigate molecular markers of HSP70 family that can affect diagnosis and treatment in AD through computational analysis. In this study, the intersection between HSP70 family members and immune molecules was taken to screen immune-related HSP70 family genes. Based on the datasets from the NCBI-Gene Expression Omnibus (GEO) database, we found that the expression levels of HSPA1A and HSPA2 were significantly increased in AD samples, while HSPA8 significantly decreased. Surprisingly, the combination of the 3 hub genes had a good diagnosis of AD via receiver operating characteristic curve (ROC). Moreover, the clinical value of the 3 hub genes was further assessed by the Spearman correlation analysis with AD-related genes, β-secretase activity, and γ-secretase activity. In terms of immune cell infiltration, we showed that the distribution of seven immune cell types (macrophages M2, neutrophils, T cells CD4 memory activated, macrophages M0, NK cells activated, plasma cells, and T cells follicular helper) was associated with the occurrence of AD by CIBERSORT. Furthermore, our data suggested that EP300, MYC, TP53, JUN, CREBBP, and ESR1 might be key transcription factors (TFs) for the 3 hub genes. In general, these findings suggest that HSPA1A, HSPA2, and HSPA8 are potential molecular biomarkers for prognosis among HSP70 family in AD, and it provides a new perspective on diagnostic and therapeutic targets for AD.

The Role of Circulating Biomarkers in the Oncological Management of Metastatic Renal Cell Carcinoma: Where Do We Stand Now?

Renal cell carcinoma (RCC) is an increasingly common malignancy that can progress to metastatic renal cell carcinoma (mRCC) in approximately one-third of RCC patients. The 5-year survival rate for mRCC is abysmally low, and, at the present time, there are sparingly few if any effective treatments. Current surgical and pharmacological treatments can have a long-lasting impact on renal function, as well. Thus, there is a compelling unmet need to discover novel biomarkers and surveillance methods to improve patient outcomes with more targeted therapies earlier in the course of the disease. Circulating biomarkers, such as circulating tumor DNA, noncoding RNA, proteins, extracellular vesicles, or cancer cells themselves potentially represent a minimally invasive tool to fill this gap and accelerate both diagnosis and treatment. Here, we discuss the clinical relevance of different circulating biomarkers in metastatic renal cell carcinoma by clarifying their potential role as novel biomarkers of response or resistance to treatments but also by guiding clinicians in novel therapeutic approaches.

Quantitative Proteomics Analysis of Differentially Expressed Proteins in Serum of Former Uranium Miners by Isobaric Tags for the Relative and Absolute Quantitation

The carcinogenicity of radon has been convincingly documented through epidemiological studies of underground miners. However, there is a lack of early warning indicators for radon radiation damage. In this study, mixed serum samples of 3 groups were collected from 27 underground uranium miners and seven aboveground miners according to the radiation exposure dose. The differentially expressed proteins in the serum were identified using the isobaric tags for the relative and absolute quantitation (iTRAQ)-based method. Some differentially expressed proteins were validated by enzyme-linked immunosorbent assay (ELISA) in 84 underground and 32 aboveground miners. A total of 25 co-differentially expressed proteins in 2 underground miner groups were screened, of which 9 were downregulated and 13 were upregulated. Biological process analysis of these proteins using Metascape showed that 5 GO terms were enriched, such as negative regulation of very-low-density lipoprotein particle clearance, endocytosis, and regulated exocytosis. The results of the ELISA for the expression levels of GCN1, CIP2A, and IGHV1-24 in the serum of 116 miners’ serum showed that the levels of GCN1 and CIP2A were consistent with the iTRAQ results. In conclusion, APOC1, APOC2, APOC3, ORM1, ORM2, ANTXR1, GCN1, and CIP2A may be potential early markers of radon radiation damage.

Quantitative proteomic analysis reveals sophisticated metabolic alteration and identifies FMNL1 as a prognostic marker in clear cell renal cell carcinoma

Purpose: In this study, we have undertaken the whole proteomic analysis and got a better understanding of biological processes involved in the development and progression of ccRCC. We hope promising biomarkers can be uncovered to facilitate early diagnosis, predict the prognosis and progression, more importantly, to be applied as potential therapeutic targets.

Experimental design: Fresh frozen tissue samples were surgically resected from patients with local or locally advanced ccRCC. Trypsin digested proteins were analyzed using TMT-based LC-MS/MS proteomic approach, followed by bioinformatic analysis. A potential prognostic marker FMNL1 was chosen to be validated in TCGA_KIRC datasets (n=525 and 72), further validation sets (n=10 and 10) and expanded validation sets (n=81 and 16). The effects of FMNL1 on proliferation, migration and invasion were determined by colony formation, wound healing, and transwell assays in 786-O and Caki-1 cells in vitro study.

Results: A total of 657 differentially expressed proteins were identified and quantified between ccRCC and adjacent normal tissues (p-value<0.05, FC>2 or<1/2), of which 186 proteins were up-regulated and 471 proteins were down-regulated. Bioinformatic analysis showed enriched metabolic biological processes and pathways. Univariate and multivariate analysis defined FMNL1 as an independent negative prognostic marker in the TCGA datasets. High expression of FMNL1 correlated significantly with tumor stage and distant metastasis (P<0.05) both in the TCGA-KIRC datasets and expanded validation sets. Kaplan-Meier survival curve illustrated that the patients with high FMNL1 protein level had shorter OS time in the expanded validation sets (p=0.0273). In vitro experiments presented the functional effects of FMNL1 knockdown on the inhibition of proliferation, migration and invasion in cancer cell lines.

Conclusion and clinical relevance: The proteomic results uncovered sophisticated metabolic reprogramming of ccRCC and indicated that the upregulation of rate-limiting enzymes in glycolysis and mitochondrial impairment may be the cause of metabolic reprogramming in ccRCC. Moreover, FMNL1 has been identified as a promising prognostic marker, and knockdown of FMNL1 could inhibit ccRCC cell proliferation, migration and invasion, which might be used as a new effective therapeutic strategy to inhibit the progression of ccRCC.

Liquid Biopsies in Renal Cell Carcinoma-Recent Advances and Promising New Technologies for the Early Detection of Metastatic Disease

Clear cell renal cell carcinoma (ccRCC) displays a highly varying clinical progression, from slow growing localized tumors to very aggressive metastatic disease (mRCC). Almost a third of all patients with ccRCC show metastatic dissemination at presentation while another third develop metastasis during the course of the disease. Survival rates of mRCC patients remain low despite the development of novel targeted treatment regimens. Biomarkers indicating disease progression could help to define its aggressive potential and thus guide patient management. However, molecular markers that can reliably assess metastatic dissemination and disease recurrence in ccRCC have not been recommended for clinical practice to date. Liquid biopsies could provide an attractive and non-invasive method to determine the risk of recurrence or metastatic dissemination during follow-up and thus assist the search for surveillance biomarkers in ccRCC tumors. A wide spectrum of circulating molecules have already shown considerable potential for ccRCC diagnosis and prognostication. In this review, we outline state of the art of the key circulating analytes such as cfDNA, cfRNA, proteins, and exosomes that may serve as biomarkers for the longitudinal monitoring of ccRCC progression to metastasis. Moreover, we address some of the prevailing limitations in the past approaches and present promising adoptable technologies that could help to pursue the implementation of liquid biopsies as a prognostic tool for mRCC.

Proteomic approaches for characterizing renal cell carcinoma

Renal cell carcinoma is among the top 15 most commonly diagnosed cancers worldwide, comprising multiple sub-histologies with distinct genomic, proteomic, and clinicopathological features. Proteomic methodologies enable the detection and quantitation of protein profiles associated with the disease state and have been explored to delineate the dysregulated cellular processes associated with renal cell carcinoma. In this review we highlight the reports that employed proteomic technologies to characterize tissue, blood, and urine samples obtained from renal cell carcinoma patients. We describe the proteomic approaches utilized and relate the results of studies in the larger context of renal cell carcinoma biology. Moreover, we discuss some unmet clinical needs and how emerging proteomic approaches can seek to address them. There has been significant progress to characterize the molecular features of renal cell carcinoma; however, despite the large-scale studies that have characterized the genomic and transcriptomic profiles, curative treatments are still elusive. Proteomics facilitates a direct evaluation of the functional modules that drive pathobiology, and the resulting protein profiles would have applications in diagnostics, patient stratification, and identification of novel therapeutic interventions.

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.

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.