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

There are no serum biomarkers for the accurate diagnosis of clear cell renal cell carcinoma (ccRCC). Diagnosis and decision of nephrectomy rely on imaging which is not always accurate. Non-invasive diagnostic biomarkers are urgently required. In this study, we preformed quantitative proteomics analysis on a total of 199 patients including 30 matched pairs of normal kidney and ccRCC using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify differentially expressed proteins. We found 55 proteins significantly dysregulated in ccRCC compared to normal kidney tissue. 54 were previously reported to play a role in carcinogenesis, and 39 are secreted proteins. Dysregulation of alpha-enolase (ENO1), L-lactate dehydrogenase A chain (LDHA), heat shock protein beta-1 (HSPB1/Hsp27), and 10 kDa heat shock protein, mitochondrial (HSPE1) was confirmed in two independent sets of patients by western blot and immunohistochemistry. Pathway analysis, validated by PCR, showed glucose metabolism is altered in ccRCC compared to normal kidney tissue. In addition, we examined the utility of Hsp27 as biomarker in serum and urine. In ccRCC patients, Hsp27 was elevated in the urine and serum and high serum Hsp27 was associated with high grade (Grade 3-4) tumors. These data together identify potential diagnostic biomarkers for ccRCC and shed new light on the molecular mechanisms that are dysregulated and contribute to the pathogenesis of ccRCC. Hsp27 is a promising diagnostic marker for ccRCC although further large-scale studies are required. Also, molecular profiling may help pave the road to the discovery of new therapies.

Digital pathology: Attitudes and practices in the Canadian pathology community.

Digital pathology is a rapidly evolving niche in the world of pathology and is likely to increase in popularity as technology improves. We performed a questionnaire for pathologists and pathology residents across Canada, in order to determine their current experiences and attitudes towards digital pathology; which modalities digital pathology is best suited for; and to assess the need for training in digital pathology amongst pathology residents and staff. An online survey consisting of 24 yes/no, multiple choice and free text questions regarding digital pathology was sent out via E-mail to all members of the Canadian Association of Pathologists and pathology residents across Canada. Survey results showed that telepathology (TP) is used in approximately 43% of institutions, primarily for teaching purposes (65%), followed by operating room consults (46%). Seventy-one percent of respondents believe there is a need for TP in their practice; 85% use digital images in their practice. The top two favored applications for digital pathology are teaching and consultation services, with the main advantage being easier access to cases. The main limitations of using digital pathology are cost and image/diagnostic quality. Sixty-two percent of respondents would attend training courses in pathology informatics and 91% think informatics should be part of residency training. The results of the survey indicate that Pathologists and residents across Canada do see a need for TP and the use of digital images in their daily practice. Integration of an informatics component into resident training programs and courses for staff Pathologists would be welcomed.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

Microvascular density as an independent predictor of clinical outcome in renal cell carcinoma: an automated image analysis study.

Tumor microvascular density (MVD) has been shown to correlate with the aggressiveness of several cancers. With the introduction of targeted anti-angiogenic therapy, assessment of MVD has the potential not only as a prognostic but also as a therapeutic marker. The significance of tumor vascularity in clear cell renal cell carcinoma (ccRCC) has been debated, with studies showing contradictory results. Previous studies were limited by manual quantification of MVD within a small area of tumor. Since then, the validity of this method has been questioned. To avoid the inaccuracies of manual quantification, we employed a computerized image analysis, which allowed assessment of large areas of tumor and adjacent normal tissue. The latter was used as an internal reference for normalization. MVD and vascular endothelial growth factor (VEGF) were assessed in 57 cases of ccRCC. Sections were immunostained for CD34 and VEGF. Areas of ccRCC and normal kidney medulla were analyzed within scanned images using software that counted CD34-positive vessels and measured the intensity of VEGF staining. We obtained unadjusted values from tumoral areas and calculated adjusted values as tumor/normal ratios. Unadjusted MVD had no association with clinical outcome. However, similarly to tumor stage, higher adjusted MVD was associated with shorter disease-free survival (log-rank P=0.037, Cox P=0.02). This was significant in univariate and multivariate analyses. MVD did not correlate with tumor stage, pointing to its independent prognostic value. As expected due to the known molecular abnormalities in ccRCC, most tumors showed higher VEGF expression than normal tissue. Higher adjusted VEGF was associated with high tumor grade (P=0.049). The finding of increased MVD as an independent marker of tumor aggressiveness may prove useful in the development of new tests for prognostic and therapeutic guidance. Digital techniques can provide more accurate assessment of immunomarkers and may reveal less obvious associations.

Assessment of the prognostic significance of endoglin (CD105) in clear cell renal cell carcinoma using automated image analysis.

The behavior of clear cell renal cell carcinoma can be difficult to predict. Angiogenesis has proven to be a useful prognostic indicator in different malignancies. Endoglin (CD105) is a new marker of angiogenesis found to have prognostic utility in various tumors. Here, we provide the first automated digital assessment of intratumoral microvascular density in clear cell renal cell carcinoma using endoglin and CD31 and assess their utility as predictors of clinical outcome. Both endoglin and CD31 expression showed association with advanced tumor stage (P = .025 and P = .011, respectively). There was a significant correlation between CD31 and tumor grade (P = .034). Kaplan-Meier survival curves showed that patients with higher endoglin expression had significantly shorter progression-free survival (P = .010). Patients with higher CD31 expression tended to have a worse prognosis, although this was not statistically significant (P = .082). In univariate analysis using endoglin as a continuous variable, increased endoglin was strongly associated with reduced survival (hazard ratio, 1.74; 95% CI, 1.39-2.18; P = <.001). CD31 also correlated with poor outcomes (hazard ratio, 1.52; 95% CI, 1.24-1.86; P = .001). There was no correlation between CD31 and endoglin expression (r = -0.090, P = .541). Receiver operating characteristic analysis showed the area under the curve to be 0.749 for endoglin and 0.550 for CD31. In conclusion, increased endoglin and CD31 expression are associated with a higher tumor stage and decreased progression-free survival. Our automated approach overcomes many limitations of manual quantification. Advances in digital assessment of immunohistochemical markers can be helpful in standardizing the evaluation of tumor biomarkers.

Immunohistochemical analysis of kallikrein-related peptidases in the normal kidney and renal tumors: potential clinical implications.

Kallikrein-related peptidases (KLKs) have been shown to be differentially expressed in various malignancies and shown to be useful tumor markers. Previous immunohistochemistry (IHC) analysis demonstrated that KLKs 5, 6, 10, and 11 have a potential prognostic significance in renal cell carcinoma (RCC). To further explore the significance of KLKs, we examined KLKs 1, 6, 7, and 15 in different subtypes of renal tumors. KLK1 has stronger expression in high grade compared to low grade clear cell RCC. However, KLK6 and KLK7 show strong expression in low grade in contrast to high grade clear cell RCC. Furthermore, the expression of KLK7 can distinguish between oncocytoma and chromophobe RCC. Oncocytoma showed diffuse, strong granular cytoplasmic staining, but chromophobe RCC showed focal weak homogeneous cytoplasmic stain. The pattern of staining of different KLKs can also be helpful in differentiating some of the subtypes of renal tumors. Our results show the potential ability of KLKs to serve as diagnostic markers and expand previous data about the prognostic significance of KLKs in kidney cancer. In addition, our study is the first to show the ability of KLK staining to distinguish various types of kidney cancers when morphology is similar.

The miR-17-92 cluster is over expressed in and has an oncogenic effect on renal cell carcinoma.

PURPOSE: miRNAs are small, nonprotein coding RNAs that are differentially expressed in many malignancies. We previously identified 80 miRNAs that are dysregulated in clear cell renal cell carcinoma. In this study we validated over expression of the miR-17-92 cluster in clear cell renal cell carcinoma and tested the effect of 2 members of this cluster (miR-17-5p and miR-20a) on tumor proliferation. We also elucidated the role of miRNA in clear cell renal cell carcinoma pathogenesis with bioinformatics. MATERIALS AND METHODS: miRNA expression was validated by quantitative reverse transcriptase-polymerase chain reaction. The cell proliferation effect of miR-17-5p and miR-20a was tested in a renal adenocarcinoma cell line model. Multiple in silico analyses were done of dysregulated miRNAs. RESULTS: We validated miR-71-92 cluster over expression in clear cell renal cell carcinoma by quantitative reverse transcriptase-polymerase chain reaction. Transfection of miR-20a inhibitor significantly decreased cell proliferation in a dose dependent manner. Transfection of miR-17-5p, which is not endogenously expressed in the ACHN cell line, led to increased cell proliferation compared to control values. This effect was suppressed by miR-17-5p inhibitor. Bioinformatics analysis identified 10 clusters of miRNAs dysregulated in clear cell renal cell carcinoma that followed the same expression patterns. We also identified matching patterns between reported chromosomal aberration in clear cell renal cell carcinoma and miRNA dysregulation for 37.5% of the miRNAs. Target prediction analysis was done using multiple algorithms. Many key molecules in clear cell renal cell carcinoma pathogenesis, including HIFs, mTOR, VEGF and VHL, were potential targets for dysregulated miRNAs. CONCLUSIONS: A significant number of dysregulated proteins in clear cell renal cell carcinoma are potential miRNA targets. Also, many clear cell renal cell carcinoma dysregulated miRNAs are phylogenetically conserved.