Renal cell carcinoma (RCC) incidence has increased over the past two decades. Recent studies reported microRNAs as promising biomarkers for early cancer detection, accurate prognosis, and molecular targets for future treatment. This study aimed to evaluate the expression levels of miR-34a and 11 of its bioinformatically selected target genes and proteins to test their potential dysregulation in RCC. Quantitative real-time PCR for miR-34a and its targets;
Renal cell carcinoma (RCC) accounts for approximately 3% of human malignancies, and its incidence appears to be increasing globally [
Over the past few years, emerging numerous bioinformatic tools have been developed to identify candidate disease-causing genes [
MicroRNA-34a gene (MIR-34A) that is located on chromosome 1p36 belongs to one of evolutionary-conserved miRNA families (MIR-34 family) that consists of three members: MIR-34A, MIR-34B, and MIR-34C [
Whether miR-34a or any one of its selected aforementioned 11 putative target genes or proteins could be related to RCC pathogenesis and/or progression in our population still lacks of solid evidence. Therefore, we aimed to investigate the expression level of miR-34a and a panel of selected putative targets in an attempt to better understand the molecular mechanisms that underlie the tumorigenesis and progression of RCC. This could represent potential future therapeutic targets in renal cell carcinoma.
Eighty-five archived formalin-fixed paraffin-embedded (FFPE) renal samples that have been taken from patients who underwent radical nephrectomy for a primary RCC and dating back for 3 years were collected from Pathology laboratory of Mansoura Oncology Center, Mansoura and Pathology laboratory of the Suez Canal University Hospital, Ismailia, Egypt. None of the patients received any neoadjuvant chemotherapy or radiotherapy. Complete clinicopathological data, including (patients’ age, sex, and tumor’s site and size), were obtained from patient medical records. Sections of cancer-free tissues adjacent to the tumor were cut, examined, and collected to serve as controls during the genetic profiling. Samples that were not homogeneous, histologically well-characterized primary renal cancer, nor had cancer-free adjacent tissues determined by an experienced pathologist have been excluded. The study was conducted in accordance with the guidelines in the Declaration of Helsinki and approved by the Medical Research Ethics Committee of Faculty of Medicine, Suez Canal University. Written informed consent was obtained from all participants before providing the archived tissue samples as part of their routine register in our University Teaching Hospitals.
Predicted and experimentally validated miRNAs that significantly target renal cell carcinoma KEGG pathway (hsa05211) were identified by DIANA-mirPath v3.0 web server via Reverse Search module and TarBase v7.0 pipeline [
Predicted target genes of miRNA-34a in renal cell carcinoma pathway [KEGG hsa05211]. Disease pathways for each pathological subtype are shown. Hsa-miR-34a-5p can target several genes in RCC pathway. They have complementary regions at their 3
The list of all experimentally validated target genes for miR-34a-5p was retrieved from miRTarBase v20 (
miR-34a target genes regulating the hallmarks of cancer. Eleven targets were investigated in the study. (a) List of targets analyzed by either immunohistochemistry (blue box) or quantitative real-time PCR (yellow box). (b) Classification of the miR-34a target genes and proteins according to their major role in cancer-related biology. They are enrolled in cellular differentiation, proliferation, apoptosis, and angiogenesis.
Total RNA, including the small RNAs, was isolated from FFPE tissue sections (5 to 8
Sections of 4
Immunohistochemical analysis for p53 protein, Bcl2 protein, Ki67, TGFb, and VEGF with a labelled streptavidin-biotin-peroxidase complex technique was performed on tumor sections. The primary antibodies were mouse monoclonal antibodies against p53 (clone BP-53-12, monoclonal mouse anti-human p53, c-Kit, Genemed, California, USA, diluted 1 : 50), Bcl2 (code 226M98, monoclonal mouse anti-human Bcl2, cell marque, prediluted), Ki67 (code number 1633, monoclonal mouse anti-human MIB1, DAKO corporation Carpinteria CA, USA, prediluted), TFGFB (ab9248, monoclonal mouse anti-TFGFB, abcam, USA, diluted 1 : 50), and VEGF (clone, GTX102643, monoclonal mouse anti-VEGFA, GeneTex, USA, diluted 1 : 50). A high sensitive kit has been used as a detection kit (DakoCytomation EnVision and dual link system peroxidase code K4061) using DAB as a chromogene. Antigen retrieval required pretreatment with 1 mM EDTA (at pH 8.0) for 20 minutes (p53, Bcl2, and VEGF) and 60 minutes (Ki67, and TGFb) in microwave oven. Proper positive and negative controls were performed. As a positive control, breast carcinoma has been run for p53, tonsils for Ki67, lymph node for Bcl2, and cells of proximal and distal convoluted tubules of nearby tumor-free kidney for TGFb. In addition, placental tissue was stained for VEGF as a positive control for VEGF antibody. As a negative control, sections were stained without the addition of a primary antibody.
For the immunohistochemistry assessment, examination of all prepared slides from each specimen was done with an Olympus CX31 light microscope. Photos were obtained from a PC-driven digital camera (Olympus E-620) and analyzed by Olympus Soft Imaging. Slides were scanned by ×40 magnification. Ten cellular areas were selected (i.e., the so-called hot spots) and evaluated at ×400 magnification. Positive p53 protein staining was defined as nuclear staining, and cytoplasmic staining was considered nonspecific and ignored. The percentage of tumor cell nuclei with positive staining was evaluated in relation to the total number of neoplastic nuclei in at least 10 fields observed at magnification ×400. Scoring of immunostained was categorized as mentioned in previous literature as follows: 3+ = high level (91–100% of positive cells), 2+ = medium level (11–90% of positive cells), 1+ = low level (up to 10% of positive cells), − = negative cells (0% of positive cells) [
Ki-67 antigen labeling was localized to the nucleus with a fine, strong, and homogenous brown granularity. Staining was considered positive if any nuclear staining was seen. Ki67 labeling index was done by calculating the ratio of positive nuclei in relation to the total number of neoplastic nuclei in 10 HPFs. Ki67 was considered to be abnormal when >10% tissue positivity was observed. The labeling index (number of positive tumor cells/total number of tumor cells expressed as a percentage) was calculated in every specimen. The Ki67 proliferation index was considered low if 0–30% of tumor cells was positive, moderate PI if 31–69% was positive, and high if ≥70% was positive. Unequivocal nuclear reactivity was considered positive [
The BCL2 positivity was determined by cytoplasmic staining (brown) of neoplastic cells which are deep colored. The percentage of positive cells at the whole section after exclusion of the areas of reactive T cells was determined. It was scored negative if 5% or less of neoplastic cells was stained. The value of BCL2 was considered weak positive if 6% to less than 50% was brown stained, and strong positive if ≥50% of tumor cells was brown stained [
TGFB immunohistochemistry specimens were classified based on the intensity of staining as follows: weak or absent staining (< 10% of cells), intermediate (10–25%), focally strong (25–50%), and strong (> 50% of cells) [
Data were managed using the R package (version 3.3.2). Categorical variables were compared using the chi-square (χ2) or Fisher’s exact tests where appropriate, while Mann–Whitney
In the current study, 85 patients (32 females and 53 males) were enrolled in the study. Their age ranged from 20 to 79 years old with mean ± SD of 52.23 ± 11.12. Renal cancer samples were compared to normal tissues. There was no significant difference in age and gender between FFPE tumor samples and normal renal tissues (
Clinicopathological characteristics of renal cell carcinoma patients (
Variables |
|
% |
---|---|---|
Age | ||
20 y | 5 | 5.9 |
40 y | 47 | 55.3 |
60 y | 33 | 38.8 |
Gender | ||
Females | 34 | 40.0 |
Males | 51 | 60.0 |
Affected side | ||
Right | 47 | 44.7 |
Left | 38 | 55.3 |
Histological type | ||
Clear cell RCC | 47 | 55.3 |
Papillary RCC | 15 | 17.6 |
Chromophobic RCC | 13 | 15.3 |
Unclassified | 10 | 11.8 |
Pathological grade | ||
Grade 1 | 11 | 12.9 |
Grade 2 | 51 | 60.0 |
Grade 3 | 23 | 27.1 |
Tumor size | ||
T1 | 25 | 29.4 |
T2 | 42 | 49.4 |
T3 | 18 | 21.2 |
LN involvement | ||
Negative | 77 | 90.6 |
Positive | 8 | 9.4 |
Capsular infiltration | ||
Negative | 60 | 70.6 |
Positive | 25 | 29.4 |
Vascular infiltration | ||
Negative | 71 | 83.5 |
Positive | 14 | 16.5 |
Renal pelvis infiltration | ||
Negative | 79 | 92.9 |
Positive | 6 | 7.1 |
Data are presented as
Using qRT-PCR technology and immunohistochemistry, gene and protein expression analyses were used to identify differential molecular changes between tumor and normal renal tissues. Gene expression profiling revealed a significant overexpression of miR-34a in almost all RCC patients (91.7%) with an overall median and quartile values of 7.97 (2.37–29.54). In addition, among the 6 genes that have been predicted to be targeted by miR-34a via the in silico computational tools, two genes were significantly upregulated (
Gene expression profiling in cancer and normal renal tissues. Data are represented as medians. The box defines upper and lower quartiles (25% and 75%, resp.), and the error bars indicate upper and lower adjacent limits. Expression levels of miR-34a and targets in cancer and normal tissues were normalized to RNU6B and GAPDH, respectively. Fold change was calculated using the delta-delta CT method (2−ΔΔCT) in comparison to normal renal tissues. The gray dash line represents the expression level of normal renal tissues (equivalent to 1.0).
Immunohistochemistry of renal tissue samples demonstrated variable staining patterns (Figure
Frequency of Immunohistochemistry markers of miR-34a putative target proteins in RCC specimens. Five protein markers were examined, Bcl2, Tp53, TGFB1, VEGFA, and Ki67.
ROC curve analysis of all genes and proteins showed significant high diagnostic performance of miR-34a (AUC = 0.854),
ROC curve of miRNA-34a and target genes in renal cancer and normal tissues.
Variable(s) | Area | Standard error |
|
95% confidence interval | |
---|---|---|---|---|---|
Lower bound | Upper bound | ||||
miR-34a |
|
0.051 | <0.001 | 0.754 | 0.954 |
MET |
|
0.059 | 0.005 | 0.648 | 0.881 |
E2F3 |
|
0.063 | 0.006 | 0.638 | 0.884 |
SOX2 | 0.571 | 0.094 | 0.479 | 0.388 | 0.755 |
TGFB3 | 0.553 | 0.081 | 0.586 | 0.395 | 0.711 |
DFFA | 0.118 | 0.053 | 0.068 | 0.014 | 0.222 |
TP53INP2 | 0.587 | 0.062 | 0.173 | 0.466 | 0.709 |
Combined first three markers |
|
0.034 | <0.001 | 0.727 | 0.859 |
All combined markers |
|
0.030 | 0.014 | 0.530 | 0.648 |
Bold values are statistically significant at
The expression of miR-34a was markedly higher in RCC samples with chromophobic renal cell carcinoma and lower in clear cell type (
Association of miR-34a and target genes with the clinicopathological features in RCC patients. (a) Higher expression of miR-34a was significantly associated with chromophobic RCC subtype. (b) Lower levels of
Immunohistochemistry photos of the target proteins in renal tissues in relation with pathological parameters are illustrated in Figure
Immunohistochemistry images according to type and grade of RCC. Clear cell RCC (Ng1) weakly expresses bcl2 (x100), (photo 1), clear cell RCC (Ng2) with focal strong cytoplasmic bcl2 (x100) (photo 2), chromophobe RCC (Ng2) with diffuse moderate expression of bcl2 (x400) (photo 3), and papillary RCC (Ng2) with diffuse strong expression of bcl2 (x200) (photo 4). Clear cell RCC (Ng1/2) with diffuse strong nuclear expression of P53 (x100) (photo 5), clear cell RCC clear cell RCC (Ng3) showed scarce cell nuclei express P53 (X200) (photo 6), chromophobe RCC (Ng2) diffusely and strongly express P53 (X100) (photo 7), and papillary RCC do not express p53 (x100) (photo 8). Clear cell RCC (Ng2) with weak expression of TGFB1 (x100) (photo 9), RCC (Ng3) with strong expression of TGFB1 (x200) (photo 10), chromophobe RCC with focal strong expression of TGFB1 (X200) (photo 11), and papillary with focal strong expression of TGFB1 (X200) (photo 12). Clear cell RCC (Ng1) with diffuse weak expression of VEGFR (X100) (photo 13), clear RCC (Ng3) with diffuse moderate expression of VEGFR (X200) (photo 14), chromophobe RCC with weak expression of VEGF (X100) (photo 15), papillary RCC with intermediate expression of VEGFR (X200) (photo 16). RCC (Ng2) with low expression of Ki67 (X100) (photo 17), RCC (Ng3) with high expression of Ki67 (X200) (photo 18), and papillary RCC does not express Ki 67 (x100) (photo 19), and chromophobe RCC do not express Ki67 (x200) (photo 20).
Association of immunohistochemistry markers with the clinicopathological features in RCC patients. The figures illustrated higher intensity of Ki67, TGFB1, VEGFA, and Tp53 in RCC tumors with advanced pathological grade (a–d), extensive staining of Ki67 antibodies in T3 samples and capsular infiltration (e-f), and differential expression of Tp53 and TGFB1 in various histopathological subtypes (g-h).
Hsa-miR-34a is encoded by MIR-34A gene (ENSG00000284357), mapped at 1p36.22. The gene has a single exon which contains a p53-binding site within a CpG island about 30 kb upstream of the mature MIR-34A sequence and encodes for a transcript of 110 bp in length. The precursor miRNA stem-loop is processed in the cytoplasm of the cell, with the predominant miR-34a mature sequence excised from the 5
Structural analysis of MIR-34A gene locus and transcripts. (a)
Interaction of mature miR-34a-5p with complementary sites of selected experimentally validated targets is shown in Supplementary Figure S
A key goal in clinical oncology is the development of therapeutic strategies that impede specific deregulated biological pathways in cancer. Understanding these pathways which involve candidate disease-causing genes will provide new therapeutic modalities for renal cancer.
In the current study, upregulation of miR-34a was observed in more than 90% of RCC patients, with median fold change of 7.97 in RCC FFPE tissues compared to noncancer tissues. ROC analysis revealed a high diagnostic performance of miR-34a in discriminating between cancer and noncancer tissues. However, higher levels showed a better prognosis (i.e., it was moderately correlated with well differentiated tumors). In addition, expression profiles in chromophobic RCC samples were markedly greater than that of clear cell and papillary subtypes.
According to a survey across diverse normal human tissues, miR-34a was downregulated in most human normal tissues, including renal cortex and medulla (data source: U133plus2 Affymetrix microarray from
Taken our results with the findings of prior studies, we could support the hypothesis that miR-34a overexpression in the current study is a secondary consequence in cancer cells elucidated to compete the DNA damage and uncontrolled growth proliferation. Accumulation of further mutations in higher pathological grade tumors, especially those related to Tp53 gene activity or 1p36 locus itself, could account for the fall of miR-34a expression profile in those patients. Further functional studies are recommended to unravel the molecular mechanisms underlying the chromophobic RCC which has the best prognosis among all other subtypes in our cases [
In silico analysis of miR-34a targets in databases revealed numerous candidate gene targets. Functional annotation and enrichment analysis showed high linkage of miR-34a with cancer-related pathways. It can influence several pathways involved in all cancer hallmarks acquired during the multistep development of human tumors, by sustaining proliferative cell signaling, evading growth suppressors, resisting apoptosis, inducing angiogenesis, and activating invasion and metastasis. In the current study, we identified predicted putative miR-34a binding sites within the 3
Of the deregulated target genes expressed significantly in the current renal cancer specimens,
The second upregulated gene in most of the current RCC samples was the transcription factor
As an excellent marker to determine the growth fraction of a given cell population, the expression of proliferation-related Ki67 antigen was investigated in the current study. The fraction of Ki67 positive cells is often correlated with the clinical course of the tumors. Currently, this marker of proliferation was detected in all cases of RCC, but with variable levels of expression. High expression of Ki67 was associated with advanced pathological grade, large tumor size, lymphatic invasion, and capsular infiltration. In addition, strong staining was correlated with chromophobic RCC subtype. Antigen Ki67 is a nuclear protein, encoded by
Regarding the TGFB superfamily proteins, they were known to be implicated in cell growth and differentiation. These growth factors bind various TGF-beta receptors, leading to recruitment and activation of SMAD family transcription factors which regulate the expression of the downstream genes, including interferon gamma and tumor necrosis factor alpha [
SOX2 is a critical transcription factor for self-renewal and maintenance of undifferentiated embryonic stem cells [
In the current study, one antiapoptotic and three proapoptotic miR-34a targets regulating essential cancer-related pathways were examined. The apoptotic regulator
The tumor suppressor protein Tp53, the guardian of the genome, is essential for the carcinogenesis prevention. In the current study, it was not detected by immunohistochemistry in less than one half of the specimens. Absent staining of Tp53 protein in tumor cell nuclei was significantly associated with advanced pathological grade, while positive staining was observed in the chromophobic RCC, known to have the best prognosis. The transcription factor Tp53 is encoded by
Another apoptotic gene,
Low levels of the apoptotic gene,
As angiogenesis is of central importance in the growth and metastasis of tumors [
The current study does confirm the association of miR-34a overexpression with RCC in our population, suggesting its potential role in pathogenesis and progression of this type of cancer. Furthermore, chromophobic RCC subtype has been postulated to attain different transcriptomics and proteomics characteristics compared to other subtypes. It has been found to have higher
Area under curve
B-cell lymphoma 2
Cyclin dependent kinase inhibitor 1A
Chromophobe renal cell carcinomas
Clear cell renal cell carcinomas
DNA fragmentation factor subunit alpha
Formalin-fixed paraffin embedded
Hepatocyte growth factor
International society of urological pathology
Kyoto encyclopedia of genes and genomes
Mouse double minute 2 homolog
MicroRNA-34a
MicroRNAs
Nuclear grade
Non-small-cell lung cancer
Papillary renal cell carcinomas
Phosphatidylinositol 3-kinase
Quantitative polymerase chain reaction
Quantitative cycle
Receiver operating characteristic
Renal cell carcinoma
Retinoblastoma protein
Reverse transcription
Secreted frizzled-related protein 1
Signal transducer and activator of transcription
Sex-determining region Y-box 2
Transforming growth factor-beta
Tumor protein p53 inducible nuclear protein
Untranslated region
Vascular endothelial growth factor
Vitamin D receptor
Vacuole membrane protein 1.
The authors declare that they have no competing interests.
The authors thank the Oncology Diagnostic Unit and the Center of Excellence in Molecular and Cellular Medicine, Suez Canal University, Ismailia, Egypt for providing the facilities for performing the research work.