Locked Nucleic Acids-In Situ Hybridization (LNA-ISH).

<p>LNA-ISH for miR-25-5p in ccRCC (A), papRCC (B), chRCC (C) and UT-UC (D). miR-25-5p was confined to the cytoplasm both in normal and tumour sections. The nuclear expression of U6 snRNA (positive control) was confirmed in all the patient samples, whereas the scrambled oligonucleotide was negative in all samples. miR-25-5p high expression was confirmed in all ccRCC sections by LNA-ISH. ccRCCs of high stage and grade stained stronger miR-25-5p compared to lower stage and grade ccRCCs. Each ccRCC section was compared against its corresponding normal kidney section (A). papRCCs of type II stained stronger for miR-25-5p compared to type I papRCCs (B). Validating the qRT-PCR results, miR-25-5p did not stain stronger in chRCC sections vs. the normal tissue ones. This was also confirmed for chRCCs with focal sarcomatoid differentiation, suggesting that miR-25-5p does not play any role in the metastatic behavior of the tumour (C). Verifying the qRT-PCR results, miR-25-5p was not significantly stronger in UT-UC vs. the normal tissue sections (D).</p

Correlation between microarrays and qRT-PCR.

<p>Median log₂ fold change expression levels of the 14 most up-regulated and 11 most down-regulated miRNAs between ccRCC, papRCC, chRCC and UT-UC and the normal kidney tissue, as determined by both qRT-PCR and microarray analysis. As shown in the figure, qRT-PCR and microarray results were highly compatible. The most identical results between the two techniques were those for ccRCC, which was expected due to the high sample number (Pearson’s CC = 0.778, p<0.001). The qRT-PCR results for papRCC, chRCC and UT-UC also revealed similar deregulation patterns with those of the microarray experimentation, however the correlation coefficients were lower, apparently due to small sample number (in papRCC, CC = 0.596, p = 0.002; in chRCC CC = 0.570, p = 0.003; in UT-UC, CC = 0.517, p = 0.009).</p

Overlapping relationship of the deregulated miRNAs.

<p>Venn diagrams illustrate the overlapping relationship of the number of up-regulated miRNAs among RCC subtypes (A), down-regulated miRNAs among RCC subtypes (B), up-regulated miRNAs among RCC subtypes and UT-UCs (C), down-regulated miRNAs between RCC subtypes and UT-UCs (D). Ninety-four miRNAs were co-upregulated among ccRCC, papRCC and chRCC; and 11, 44 and 24 miRNAs were specifically up-regulated in each one of the three RCC subtypes (ccRCC, chRCC and papRCC), respectively. On the other hand, 222 miRNAs were co-down-regulated in the three RCC subtypes, whereas 16, 18 and 5 miRNAs were specifically down-regulated in ccRCC, chRCC and papRCC, respectively. When the DE miRNAs in each RCC subtype were combined with those in UT-UC, we identified 89 and 206 miRNAs that were up- and down-regulated, respectively in all tumor types.</p

ROC analysis using qRT-PCR data.

<p>ROC curves of the significantly deregulated miRNAs, using the expression data from qRT-PCR analysis. Of them, the miRNAs with a p<0.01 and an AUC>0.8 were selected as successful distinguishing markers between cancerous and normal kidney tissues. The median area under the curve (AUC) for ccRCC was 0.802 (A); for papRCC, median AUC = 0.756 (B); for chRCC, median AUC = 0.926 (C) and for UT-UC, median AUC = 0.955 (D).</p

Clinicopathological information of the patients.

<p>Clinicopathological information of the patients.</p

Ingenuity pathway analysis (IPA).

<p>A. In ccRCC, the most important biological functions of the top deregulated miRNAs were: 1) Cancer (p = 8.71E-11-4.91E-02); 2) Renal and Urological Disease (p = 8.71E-11-2.12E-09); 3) Inflammatory Disease (p = 2.12E-09-2.14E-03); 4) Inflammatory Response (p = 2.12E-09-2.4E-04) and 5) Reproductive System Disease (p = 3.37E-05-2.58E-02). The associated functions of the major miRNA network (score = 30) were: Inflammatory disease, inflammatory response, renal inflammation. Argonaute RISC catalytic component 2 (EIF2C2), tumour protein p53 (TP53), v-myc myelocytomatosis viral oncogene homolog (MYC) and EPH receptor B6 (EPHB6) constituted some of the major central nodes in this network. B. In papRCC, the most important biological functions of the top deregulated miRNAs were: 1) Cancer (p = 9.4E-09-4.15E-02); 2) Endocrine System Disorders (p = 9.4E-09-4.54E-02); 3) Reproductive System Disease (p = 9.4E-09-5.11E-03); 4) Inflammatory Disease (p = 2.17E-06-2.17E-06) and 5) Inflammatory Response (p = 2.17E-06-1.65E-03). The associated functions of the major miRNA network (score = 22) were: Endocrine System Disorders, Reproductive System Disease, Cellular Development. Tumour protein p53 (TP53) and EPH receptor B6 (EPHB6) constituted some of the major central nodes in this network. C. In chRCC, the most important biological functions of the top deregulated miRNAs were: 1) Cancer (p = 8.99E-07-4.73E-02); 2) Inflammatory Disease (p = 1.64E-06-1.64E-06); 3) Inflammatory Response (p = 1.64E-06-1.19E-03); 4) Renal and Urological Disease (p = 1.64E-06-7.96E-03) and 5) Reproductive System Disease (p = 3.02E-04-2.39E-02). The associated functions of the major miRNA network (score = 22) were: Hereditary Disorder, Skeletal and Muscular Disorders, Developmental Disorder. Tumour protein p53 (TP53), B-cell CLL/lymphoma 2 (BCL2) vascular endothelial growth factor A (VEGFA) and v-myc myelocytomatosis viral oncogene homolog (MYC) constituted some of the major central nodes in this network. D. In UT-UC, the most important biological functions of the top deregulated miRNAs were: 1) Inflammatory Disease (p = 2.7E-12-3.42E-02); 2) Inflammatory Response (p = 2.7E-12-1.75E-05); 3) Renal and Urological Disease (p = 2.7E-12-3.35E-09); 4) Cancer (p = 4.67E-10-4.53E-02) and 5) Reproductive System Disease (p = 3.82E-06-4.96E-02). The associated functions of the 2 major miRNA networks were: 1) Connective Tissue Disorders, Inflammatory Disease, Inflammatory Response (score = 25); and 2) Cancer, Reproductive System Disease, Renal and Urological Disease (score = 24). Insulin, hydrogen peroxide and ribosomal protein S15 (RPS15) constituted some of the major central nodes in the first network; whereas tumour protein p53 (TP53) constituted a central node in the second network.</p

microRNA profiling.

<p>Four-hundred and thirty-four miRNAs were statistically significantly deregulated in all RCC subtypes and UT-UC versus the normal kidney. (A) Q-Q (quantile-quantile) plot. Red circles indicate the significantly deregulated miRNAs. (B) Frequencies of the t-scores and p-values. The deregulated miRNAs had a p<0.05. (C) The volcano-plot depicts the 434 statistically significantly deregulated miRNAs in ccRCC, papRCC, chRCC and UT-UC versus the normal kidney, of which the majority was significantly down-regulated in the cancerous tissue compared to the latter. (D) FDR diagram depicting the percentage of FDR with respect to p-value along with a plot of the estimated a priori probability that the null hypothesis π(0), is true versus the tuning parameter, lambda, λ, with a cubic polynomial fitting curve.</p

ROC statistics of the miRNAs that exhibited the best discriminatory ability in ccRCC (A), papRCC (B), chRCC (C), and UT-UC (D) vs. the normal kidney tissue, respectively.

<p>AUC, area under the curve; S.E., standard error; 95% C.I., 95% confidence interval.</p

Haematoxylin and eosin (H&E) staining and immunohistochemistry (IHC).

<p><i>Upper pannel:</i> Representative H&E staining from ccRCC, papRCC, chRCC and normal kidney tissue. About 5–10 serial tissue sections of 10 μm were cut from each FFPE block, deparaffinized with xylene, hydrated and stained with H&E before microscopic examination. When the proportion of tumour cells was >70% the FFPE block was subjected to total RNA extraction. <i>Lower pannel:</i> IHC of FFPE tissue sections using anti-vimentin as primary antibody. Vimentin was predominantly seen in ccRCC and papRCC (∼70% and ∼50%, respectively), but only rarely in chRCC (4%) and absent in the normal kidney. Vimentin was also down-regulated in the majority of UT-UC cases.</p

Hierarchical Clustering (HCl).

<p>The unsupervised two-way HCl with Euclidian distance depicts differential miRNA expression in ccRCC, papRCC, chRCC and UT-UC. The log₂ fold change in each RCC subtype and UT-UC versus the normal kidney tissue was used to construct the heat map. miRNA profiling accurately discriminated between RCC and UT-UC, as well as among ccRCC, papRCC and chRCC. ccRCC, clear cell renal cell carcinoma; papRCC, papillary renal cell carcinoma; chRCC, chromophobe renal cell carcinoma; UT-UC, upper tract urothelial carcinoma. Red and blue colours show significant up- or down-regulation of each miRNA in the tumour versus the normal kidney, respectively.</p