Quantitative proteomic analysis reveals potential diagnostic markers and pathways involved in pathogenesis of renal cell carcinoma

Quantitative score modulation of HSP90 and HSP27 in clear cell renal cell carcinoma

We sought to evaluate the expression of HSP27 and HSP90 chaperones in renal cell carcinomas as a target for cancer therapeutics.A total of 127 clear cell renal cell carcinomas stratified according to the Mayo Clinic SSIGN (size, staging, grading, and necrosis) risk groups (good, 1; poor, 5) and 20 cases with metastases, were available. Immunostaining for both HSP27 and HSP90 was performed on tissue microarrays. Results were detailed per scorable arrays per SSIGN risk groups.Immunolabelling for HSP90 and HSP27 was seen in 109 of 127 (86%) and 114 of 127 (89%) cases, respectively. HSP90 scored 4.9 in 32 cases risked SSIGN 1, 3.5 in 41 cases SSIGN 2, 4.8 in 11 cases SSIGN 3, 4.2 in 22 cases SSIGN 4, and 5.0 in three cases SSIGN 5. HSP27 scored 4.6 in 33 risked SSIGN 1, 3.1 in 43 SSIGN 2, 2.6 in 11 SSIGN 3, 3.6 in 24 SSIGN 4, and 2.7 in three SSIGN 5. Metastases ranged from 2.9-5.0. A trend of increasing value for HSP90 was observed when comparing SSIGN 1-2 versus SSIGN 3-5 risk groups (4.2 versus 4.6 mean values; p = 0.06); no difference has been observed for HSP27 (3.8 to 3.9; p = 0.08).A score modulation of HSPs is observed in renal cell carcinoma and may affect the efficacy of targeted therapy.

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.

Comparative proteomic profiling identifies potential prognostic factors for human clear cell renal cell carcinoma

The identification of markers for disease diagnostic, prognostic, or predictive purposes will have a great effect in improving patient management. Proteomic‑based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on four patients including clear cell renal cell carcinoma (ccRCC) and paired adjacent non‑cancerous renal tissues using label‑free quantitative proteomics and liquid chromatography‑tandem mass spectrometry (LC‑MS/MS) to identify differentially expressed proteins. Among 3,061 identified non‑redundant proteins, we found that 210 proteins were differentially expressed (83 overexpressed and 127 underexpressed) in ccRCC tissue when compared with normal kidney tissues. Two most significantly dysregulated proteins (PCK1 and SNRPF) were chosen to be confirmed by western blotting. Pathway analysis of 210 differentially expressed proteins showed that dysregulated proteins are related to many cancer‑related biological processes such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Online survival analysis indicated the prognostic value of these dysregulated proteins. In conclusion, we identified some potential diagnostic biomarkers for ccRCC and an in‑depth understanding of their involved biological pathways may help pave the way to discover new therapeutic strategies for ccRCC.

Integrative analysis to select cancer candidate biomarkers to targeted validation

Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS.

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.

Prognostic significance of two lipid metabolism enzymes, HADHA and ACAT2, in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is one of the leading causes of cancer mortality in adults, but there is still no acknowledged biomarker for its prognostic evaluation. Our previous proteomic data had demonstrated the dysregulation of some lipid metabolism enzymes in clear cell RCC (ccRCC). In the present study, we elucidated the expression of two lipid metabolism enzymes, hydroxyl-coenzyme A dehydrogenase, alpha subunit (HADHA) and acetyl-coenzyme A acetyltransferase 2 (ACAT2), using Western blotting analysis, then assessed the prognostic potential of HADHA and ACAT2 using immunohistochemistry (IHC) on a tissue microarray of 145 ccRCC tissues. HADHA and ACAT2 were downregulated in ccRCC (P < 0.05); further IHC analysis revealed that HADHA expression was significantly associated with tumor grade, stage, size, metastasis, and cancer-specific survival (P = 0.004, P < 0.001, P < 0.001, P = 0.049, P < 0.001, respectively) and ACAT2 expression was significantly associated with tumor stage, size, and cancer-specific survival (P < 0.001, P = 0.001, P < 0.001, respectively). In addition, a strong correlation was found between HADHA and ACAT2 expression (R = 0.655, P < 0.001). Further univariate survival analysis demonstrated that high stage, big tumor size, metastasis, and HADHA and ACAT2 down-expression were associated with poorer prognosis on cancer-specific survival (P = 0.007, P = 0.005, P = 0.006, P < 0.001, P = 0.001, respectively), and multivariate analysis revealed that HADHA, stage, and metastasis were identified as independent prognostic factors for cancer-specific survival in patients with ccRCC (P = 0.018, P = 0.046, P = 0.001, respectively). Collectively, these findings indicated that HADHA could serve as a promising prognostic marker in ccRCC, which indicated lipid metabolism abnormality might be involved in ccRCC tumorigenesis.

Lactate dehydrogenase A negatively regulated by miRNAs promotes aerobic glycolysis and is increased in colorectal cancer

Reprogramming metabolism of tumor cells is a hallmark of cancer. Lactate dehydrogenase A (LDHA) is frequently overexpressed in tumor cells. Previous studies has shown higher levels of LDHA is related with colorectal cancer (CRC), but its role in tumor maintenance and underlying molecular mechanisms has not been established. Here, we investigated miRNAs-induced changes in LDHA expression. We reported that colorectal cancer express higher levels of LDHA compared with adjacent normal tissue. Knockdown of LDHA resulted in decreased lactate and ATP production, and glucose uptake. Colorectal cancer cells with knockdown of LDHA had much slower growth rate than control cells. Furthermore, we found that miR-34a, miR-34c, miR-369-3p, miR-374a, and miR-4524a/b target LDHA and regulate glycolysis in cancer cells. There is a negative correlation between these miRNAs and LDHA expression in colorectal cancer tissues. More importantly, we identified a genetic loci newly associated with increased colorectal cancer progression, rs18407893 at 11p15.4 (in 3′-UTR of LDHA), which maps to the seed sequence recognized by miR-374a. Cancer cells overexpressed miR-374a has decreased levels of LDHA compared with miR-374a-MUT (rs18407893 at 11p15.4). Taken together, these novel findings provide more therapeutic approaches to the Warburg effect and therapeutic targets of cancer energy metabolism.

Proteotranscriptomic Analysis Reveals Stage Specific Changes in the Molecular Landscape of Clear-Cell Renal Cell Carcinoma

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.)

Reduced cytosolic carboxypeptidase 6 (CCP6) level leads to accumulation of serum polyglutamylated DNAJC7 protein: A potential biomarker for renal cell carcinoma early detection

Renal cell carcinoma (RCC) is frequently diagnosed at advanced stages of disease, although early diagnosis has much favorable prognosis. This study assessed aberrant expression of cytosolic carboxypeptidase 6 (CCP6) leading to accumulation of serum polyglutamylated DNAJC7 as a biomarker for early RCC detection. A total of 835 RCCs, 143 chronic nephritis, 170 kidney stones and 415 health controls were collected for qRT-PCR, immunohistochemistry and Western blot analysis of CCP6 expression and mass spectrometry of DNAJC7 and polyglutamylated DNAJC7. The data showed that CCP6 expression was significantly decreased in 30 RCC tissues and that mass spectrometric and pull-down analysis identified DNAJC7 as a substrate of CCP6 and showed upregulated polyglutamylated-DNAJC7 (polyE-DNAJC7) in sera of RCC patients. The electrochemiluminescence immunoassay of large-scale serum samples from multi-institutes further confirmed the remarkable increase of polyE-DNAJC7 in 805 RCCs compared to that of 385 healthy controls (p < 0.001), 128 patients with chronic nephritis (p < 0.001), and 153 with kidney stone (p < 0.001). Serum level of DNAJC7-polyE protein was also associated with advanced RCC stage and grade in 805 patients. The data from the current study for the first time demonstrated increased serum polyglutamylated DNAJC7 as a potential biomarker for RCC early detection and association with advanced tumor stages and grade, which provides support of further polyglutamylation research in RCC.

Metabolomic profile of glycolysis and the pentose phosphate pathway identifies the central role of glucose-6-phosphate dehydrogenase in clear cell-renal cell carcinoma

The analysis of cancer metabolome has shown that proliferating tumor cells require a large quantities of different nutrients in order to support their high rate of proliferation. In this study we analyzed the metabolic profile of glycolysis and the pentose phosphate pathway (PPP) in human clear cell-renal cell carcinoma (ccRCC) and evaluate the role of these pathways in sustaining cell proliferation, maintenance of NADPH levels, and production of reactive oxygen species (ROS). Metabolomic analysis showed a clear signature of increased glucose uptake and utilization in ccRCC tumor samples. Elevated levels of glucose-6-phosphate dehydrogenase (G6PDH) in association with higher levels of PPP-derived metabolites, suggested a prominent role of this pathway in RCC-associated metabolic alterations. G6PDH inhibition, caused a significant decrease in cancer cell survival, a decrease in NADPH levels, and an increased production of ROS, suggesting that the PPP plays an important role in the regulation of ccRCC redox homeostasis. Patients with high levels of glycolytic enzymes had reduced progression-free and cancer-specific survivals as compared to subjects with low levels. Our data suggest that oncogenic signaling pathways may promote ccRCC through rerouting the sugar metabolism. Blocking the flux through this pathway may serve as a novel therapeutic target.

The miR-34a-LDHA axis regulates glucose metabolism and tumor growth in breast cancer

Lactate dehydrogenase A (LDHA) is involved in a variety of cancers. The purpose of this study was to investigate the expression, prognostic roles and function of LDHA in breast cancer. We found that LDHA was upregulated in both breast cancer cell lines and clinical specimens using quantitative real-time PCR (qRT-PCR). Immunohistochemistry (IHC) analysis of tissue microarrays (TMAs) showed that high LDHA expression was associated with cell proliferation, metastasis and poor patient overall survival (OS) and disease free survival (DFS). Furthermore, we found that LDHA promoted glycolysis and cell proliferation in vitro and in vivo. We also performed luciferase reporter assays and found that LDHA was a direct target of miR-34a. Repression of LDHA by miR-34a suppressed glycolysis and cell proliferation in breast cancer cells in vitro. Our findings provide clues regarding the role of miR-34a as a tumor suppressor in breast cancer through the inhibition of LDHA both in vitro and in vivo. Targeting LDHA through miR-34a could be a potential therapeutic strategy in breast cancer.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Increased Expression of the Autocrine Motility Factor is Associated With Poor Prognosis in Patients With Clear Cell-Renal Cell Carcinoma

Glucose-6-phosphate isomerase (GPI), also known as phosphoglucose isomerase, was initially identified as the second glycolytic enzyme that catalyzes the interconversion of glucose-6-phosphate to fructose-6-phosphate. Later studies demonstrated that GPI was the same as the autocrine motility factor (AMF), and that it mediates its biological effects through the interaction with its surface receptor (AMFR/gp78). In this study, we assessed the role of GPI/AMF as a prognostic factor for clear cell renal cell carcinoma (ccRCC) cancer-specific (CSS) and progression-free survival (PFS). In addition, we evaluated the expression and localization of GPI/AMF and AMFR, using tissue microarray-based immunohistochemistry (TMA-IHC), indirect immunofluorescence (IF), and confocal microscopy analysis.Primary renal tumor and nonneoplastic tissues were collected from 180 patients who underwent nephrectomy for ccRCC. TMA-IHC and IF staining showed an increased signal for both GPI and AMFR in cancer cells, and their colocalization on plasma membrane. Kaplan-Meier curves showed significant differences in CSS and PFS among groups of patients with high versus low GPI expression. In particular, patients with high tissue levels of GPI had a 5-year survival rate of 58.8%, as compared to 92.1% for subjects with low levels (P < 0.0001). Similar findings were observed for PFS (56.8% vs 93.3% at 5 years). At multivariate analysis, GPI was an independent adverse prognostic factor for CSS (HR = 1.26; P = 0.001), and PFS (HR = 1.16; P = 0.01).In conclusion, our data suggest that GPI could serve as a marker of ccRCC aggressiveness and a prognostic factor for CSS and PFS.

Quantitative proteomic analysis of formalin-fixed, paraffin-embedded clear cell renal cell carcinoma tissue using stable isotopic dimethylation of primary amines

Background

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most abundant resource of archived human specimens in pathology. Such tissue specimens are emerging as a highly valuable resource for translational proteomic studies. In quantitative proteomic analysis, reductive di-methylation of primary amines using stable isotopic formaldehyde variants is increasingly used due to its robustness and cost-effectiveness.

Results

In the present study we show for the first time that isotopic amine dimethylation can be used in a straightforward manner for the quantitative proteomic analysis of FFPE specimens without interference from formalin employed in the FFPE process. Isotopic amine dimethylation of FFPE specimens showed equal labeling efficiency as for cryopreserved specimens. For both FFPE and cryopreserved specimens, differential labeling of identical samples yielded highly similar ratio distributions within the expected range for dimethyl labeling. In an initial application, we profiled proteome changes in clear cell renal cell carcinoma (ccRCC) FFPE tissue specimens compared to adjacent non–malignant renal tissue. Our findings highlight increased levels of glyocolytic enzymes, annexins as well as ribosomal and proteasomal proteins.

Conclusion

Our study establishes isotopic amine dimethylation as a versatile tool for quantitative proteomic analysis of FFPE specimens and underlines proteome alterations in ccRCC.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1768-x) contains supplementary material, which is available to authorized users.

Serum and urine biomarkers for human renal cell carcinoma

Renal cell carcinoma (RCC) diagnosis is mostly achieved incidentally by imaging provided for unrelated clinical reasons. The surgical management of localized tumors has reported excellent results. The therapy of advanced RCC has evolved considerably over recent years with the widespread use of the so-called “targeted therapies.” The identification of molecular markers in body fluids (e.g., sera and urine), which can be used for screening, diagnosis, follow-up, and monitoring of drug-based therapy in RCC patients, is one of the most ambitious challenges in oncologic research. Although there are some promising reports about potential biomarkers in sera, there is limited available data regarding urine markers for RCC. The following review reports some of the most promising biomarkers identified in the biological fluids of RCC patients.

Analysis and interpretation of transcriptomic data obtained from extended Warburg effect genes in patients with clear cell renal cell carcinoma

Background

Many cancers adopt a metabolism that is characterized by the well-known Warburg effect (aerobic glycolysis). Recently, numerous attempts have been made to treat cancer by targeting one or more gene products involved in this pathway without notable success. This work outlines a transcriptomic approach to identify genes that are highly perturbed in clear cell renal cell carcinoma (CCRCC).

Methods

We developed a model of the extended Warburg effect and outlined the model using Cytoscape. Following this, gene expression fold changes (FCs) for tumor and adjacent normal tissue from patients with CCRCC (GSE6344) were mapped on to the network. Gene expression values with FCs of greater than two were considered as potential targets for treatment of CCRCC.

Results

The Cytoscape network includes glycolysis, gluconeogenesis, the pentose phosphate pathway (PPP), the TCA cycle, the serine/glycine pathway, and partial glutaminolysis and fatty acid synthesis pathways. Gene expression FCs for nine of the 10 CCRCC patients in the GSE6344 data set were consistent with a shift to aerobic glycolysis. Genes involved in glycolysis and the synthesis and transport of lactate were over-expressed, as was the gene that codes for the kinase that inhibits the conversion of pyruvate to acetyl-CoA. Interestingly, genes that code for unique proteins involved in gluconeogenesis were strongly under-expressed as was also the case for the serine/glycine pathway. These latter two results suggest that the role attributed to the M2 isoform of pyruvate kinase (PKM2), frequently the principal isoform of PK present in cancer: i.e. causing a buildup of glucose metabolites that are shunted into branch pathways for synthesis of key biomolecules, may not be operative in CCRCC. The fact that there was no increase in the expression FC of any gene in the PPP is consistent with this hypothesis. Literature protein data generally support the transcriptomic findings.

Conclusions

A number of key genes have been identified that could serve as valid targets for anti-cancer pharmaceutical agents. Genes that are highly over-expressed include ENO2, HK2, PFKP, SLC2A3, PDK1, and SLC16A1. Genes that are highly under-expressed include ALDOB, PKLR, PFKFB2, G6PC, PCK1, FBP1, PC, and SUCLG1.

A versatile reversed phase-strong cation exchange-reversed phase (RP–SCX–RP) multidimensional liquid chromatography platform for qualitative and quantitative shotgun proteomics

We developed a novel online MDLC platform that integrates a dual-trap configuration and two separation technologies into a single automated commercial platform.

Identification of potential serum proteomic biomarkers for clear cell renal cell carcinoma

Objective

To investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients.

Methods

We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients.

Results

Patients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively.

Conclusion

MB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.

Paraoxonase 1 deficiency and hyperhomocysteinemia alter the expression of mouse kidney proteins involved in renal disease

SCOPE

Hyperhomocysteinemia (HHcy) is associated with kidney disease and leads to atherosclerosis and thrombosis. Paraoxonase 1 (Pon1), a hydrolase that participates in homocysteine (Hcy) metabolism and is carried in the circulation on high-density lipoprotein, has also been linked to kidney disease and atherothrombosis. Pon1-knockout mice are susceptible to atherosclerosis and exhibit a kidney-associated phenotype, polyuria or urine dilution. We hypothesize that HHcy and Pon1 deficiency are toxic to kidney function because they impair metabolic pathways important for normal kidney homeostasis.

METHODS AND RESULTS

We examined changes in the mouse kidney proteome induced by Pon1 gene deletion and dietary HHcy, using 2D IEF/SDS-PAGE gel electrophoresis and MALDI-TOF mass spectrometry. We found that the expression of ten mouse kidney proteins was altered by the Pon1(-/-) genotype or HHcy. Proteins involved in metabolism of lipid (ApoA-I), protein (Hspd1), carbohydrate (Pdhb, Fbp1-isoform2, Eno1), and energy (Ndufs8, Ldhd) were down-regulated. Proteins involved in lipid transport (Pebp1), oxidative stress response (Prdx2), and cellular detoxification (Glo1) were up-regulated. The kidney proteins altered by HHcy or Pon1 are also altered in renal disease.

CONCLUSION

Our findings suggest that excess Hcy is toxic because it deregulates the expression of proteins involved in diverse cellular processes-from lipid, protein, carbohydrate, and energy metabolisms to detoxification and antioxidant defenses-that are essential for normal kidney homeostasis. Dysregulation of these processes can account for the involvement of HHcy and reduced Pon1 in kidney disease. Our findings also show that Pon1 plays an important role in maintaining normal kidney homeostasis.

Label-free quantitative proteomic analysis reveals potential biomarkers and pathways in renal cell carcinoma

Renal cell carcinoma (RCC) is one of the most common malignancies in adults, and there is still no acknowledged biomarker for its diagnosis, prognosis, recurrence monitoring, and treatment stratification. Besides, little is known about the post-translational modification (PTM) of proteins in RCC. Here, we performed quantitative proteomic analysis on 12 matched pairs of clear cell RCC (ccRCC) and adjacent kidney tissues using liquid chromatography-tandem mass spectrometry (nanoLCMS/MS) and Progenesis LC-MS software (label-free) to identify and quantify the dysregulated proteins. A total of 1872 and 1927 proteins were identified in ccRCC and adjacent kidney tissues, respectively. Among these proteins, 1037 proteins were quantified by Progenesis LC-MS, and 213 proteins were identified as dysregulated proteins between ccRCC and adjacent tissues. Pathway analysis using IPA, STRING, and David tools was performed, which demonstrated the enrichment of cancer-related signaling pathways and biological processes such as mitochondrial dysfunction, metabolic pathway, cell death, and acetylation. Dysregulation of two mitochondrial proteins, acetyl-CoA acetyltransferase 1 (ACAT1) and manganese superoxide dismutase (MnSOD) were selected and confirmed by Western blotting and immunohistochemistry assays using another 6 pairs of ccRCC and adjacent tissues. Further mass spectrometry analysis indicated that both ACAT1 and MnSOD had characterized acetylation at lysine residues, which is the first time to identify acetylation of ACAT1 and MnSOD in ccRCC. Collectively, these data revealed a number of dysregulated proteins and signaling pathways by label-free quantitative proteomic approach in RCC, which shed light on potential diagnostic or prognostic biomarkers and therapeutic molecular targets for clinical intervention of RCC.

AHNAK: the giant jack of all trades

The nucleoprotein AHNAK is an unusual and somewhat mysterious scaffolding protein characterised by its large size of approximately 700 kDa. Several aspects of this protein remain uncertain, including its exact molecular function and regulation on both the gene and protein levels. Various studies have attempted to annotate AHNAK and, notably, protein interaction and expression analyses have contributed greatly to our current understanding of the protein. The implicated biological processes are, however, very diverse, ranging from a role in the formation of the blood-brain barrier, cell architecture and migration, to the regulation of cardiac calcium channels and muscle membrane repair. In addition, recent evidence suggests that AHNAK might be yet another accomplice in the development of tumour metastasis. This review will discuss the different functional roles of AHNAK, highlighting recent advancements that have added foundation to the proposed roles while identifying ties between them. Implications for related fields of research are noted and suggestions for future research that will assist in unravelling the function of AHNAK are offered.

SET-mediated NDRG1 inhibition is involved in acquisition of epithelial-to-mesenchymal transition phenotype and cisplatin resistance in human lung cancer cell

Development of resistance to therapy continues to be a serious clinical problem in lung cancer management. Cancer cells undergoing epithelial-to-mesenchymal transition (EMT) have been shown to play roles in resistance to chemotherapy. Here, we utilized a proteomics-based method and identified a significant downregulation of the metastasis suppressor NDRG1 in drug resistant lung cancer cells. We showed that downregulation of DNRG1 constitutes a mechanism for acquisition of EMT phenotype and endows lung cancer cells with an increased resistance to cisplatin. We also identified a signal cascade, namely, SET--| PP2A--| c-myc--| NDRG1, in which upregulation of SET is critical for inhibition of NDRG1. We also found that blockade of SET (or reactivation of PP2A) by FTY720 reverted EMT, restored drug sensitivity, and inhibited invasiveness and growth of lung tumor xenografts. Together, our results indicated a functional link between SET-mediated NDRG1 regulation and acquisition of EMT phenotype and drug resistance, and provided an evidence that blockade of SET-driven EMT can overcome drug resistance and inhibit tumor progression.

Methionine-induced hyperhomocysteinemia and bleomycin hydrolase deficiency alter the expression of mouse kidney proteins involved in renal disease

SCOPE

Hyperhomocysteinemia (HHcy) induced by dietary or genetic factors is linked to kidney disease. Bleomycin hydrolase (Blmh) metabolizes Hcy-thiolactone to Hcy. We aimed to explain the role of dietary HHcy in kidney disease.

METHODS AND RESULTS

We examined kidney proteome in dietary HHcy and Blmh-knockout mouse models using 2D IEF/SDS-PAGE gel electrophoresis and MALDI-TOF mass spectrometry. We found that the kidney proteome was altered by dietary HHcy and the Blmh(-/-) genotype. Proteins involved in metabolism of lipoprotein (ApoA1), amino acid and protein (Acy1, Hspd1), carbohydrate (Pdhb, Fbp1-isoform 1, Eno1), and energy metabolism (Ndufs8, Ldhd) were down-regulated. Proteins involved in carbohydrate metabolism (Fbp1-isoform 2), oxidative stress response (Prdx2), and detoxification (Glod4) were up-regulated. The Blmh(-/-) genotype down-regulated Glod4 isoform 3 mRNA but did not affect isoform 1 mRNA expression in mouse kidneys, suggesting post-transcriptional regulation of the Glod4 protein by the Blmh(+/+) genotype. Responses of ApoA1, Acy1, Hspd1, Ndufs8, Fbp1, Eno1, and Prdx2 to HHcy and/or Blmh deficiency mimic their responses to renal disease.

CONCLUSION

Our findings indicate that Blmh interacts with diverse cellular processes--lipoprotein, amino acid and protein, carbohydrate, and energy metabolisms, detoxification, antioxidant defenses--that are essential for normal kidney homeostasis and that deregulation of these processes can account for the involvement of HHcy in kidney disease.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.