Four microRNAs Signature for Survival Prognosis in Colon Cancer using TCGA Data

This study aims to develop microRNA expression signature for colon cancer survival prognosis based on the Cancer Genomic Common database. miRNAs levels between colon cancer and non-cancer tissues were screened by t-test (p < 0.05). Kaplan-Meier survival method was used to discriminate survival significant miRNAs, followed by miRNAs index accumulation to power the miRNAs-survival reliability. In the end, we test the selected miRNAs in HT126 colon cancer cells to validate its anti-cancer effect. The study identified a 84-miRNAs signature. Of the above 84 miRNAs, we got four miRNAs which were survival associated by using ROC curve method and Kaplan-Meier survival method (p < 0.001). The result showed that low risk group had quite a low death rate, the survival rate was over 80%. The high risk group had survival rate lower than 20%, which was also extremely lower than the overall survival rate. In the HT126 cells study, cell growth assay showed miR-130a sponge inhibited colon cancer cells growth and sensitized the anti-cancer drug effect of 5-FU to blocked cancer cell growth. We developed a prognostic 4-microRNA expression signature for colon cancer patient survival, and validated miR-130a sponge could sensitized 5-FU anti-cancer effect.


Results
Identification of a 84-miRNAs signature to discriminate colon cancer from non-cancer. Data of 268 COAD patients and 8 controls were downloaded from Harmonized Cancer Datasets (https://gdc-portal.nci.nih.gov/), including miRNAs expression profile, clinical follow-up information, et al. The overall information of patients were listed in Table 1. We compared all miRNAs expression level to non-cancer level, and got an 84-miRNAs signature cluster map using Multi-experimental viewer in Hierarchical Clustering method (Supplemental Figure s1). In the clustering analysis, 64 miRNAs were up regulated in cancer tissue, and 20 were down regulated in cancer tissue compared to non-cancer tissue (t test, p < 0.001).
Validation of 4 miRNAs were associated with patients survival. Of the above 84 miRNAs, we employed ROC curve method to set the cutoff point to classify 268 patients in two groups: high level group and low level group. If the ROC curve cutoff value was significant, patients were divided into two groups and carried out with Kaplan-Meier survival analysis. Upon the survival analysis, we got 4 miRNAs which were significantly related with patient survival (Fig. 1A, Log-rank method, *p < 0.05). These 4 miRNAs were miR-148a, miR-26a-2, miR-130a and miR-103-1. According to the result, high expression level of miR-148a, miR-26a-2 and miR-130a were regarded as poorer prognostic markers compared to the low level ( Fig. 1A-C). As to miR-103-1, contrarily, high expression might be a protection factor in patient survival, while low expression showed a shorter survival rate and time (Fig. 1D). We also performed validation of four miRNAs signature in stage 2 and stage 3 respectively. Data showed miRNAs signature-based risk index was also meaningful in stage 2 and stage 3 patients, indicating the robustness of miRNA signature prognostic biomarker (Supplemental Figure s2).
Four-miRNAs signature index for colon cancer prognosis. We scored the 4-miRNAs signature by value assignment for each miRNAs. For example, higher expression of miR-148a, miR-26a-2 and miR-130a got one score in each patient, and lower expression of miR-103-1 got one score in each patient. Furthermore, we summated the score for each patient. Accordingly, the highest score would be four, and the lowest would be zero (Supplemental Figure s2). We set index above three as high risk, and those below three as low risk. Therefore, all patients were divided into high risk or low risk group according to the miRNAs index score. We analyzed the two groups by Kaplan-Meier survival analysis in Log-rank method. The result showed that low risk group had quite a low death rate which the survival rate was over 80% (Fig. 2A). The high risk group had survival rate lower than 20%, which was also extremely lower than the overall survival rate in Table 1. KEGG signal pathway and GO annotation of 4-miRNAs predicted genes. In order to further explore the four miRNAs signature in biological function and mechanism. We analyzed those potential targets which might be regulated by the four miRNAs through KEGG signal pathway and GO annotation analysis. Firstly, we predicted target genes through online miRNAs prediction software (http://www.microrna.org/microrna/get-GeneForm.do), and selected the first 100 predicted targets (Supplemental Figure s3) as input genes for KEGG signal pathway and GO annotation. The results of KEGG pathway analysis were listed in Table 2. The results indicated that cancer related pathways are obviously activated, including glioma, endometrial cancer, thyroid cancer, prostate cancer and leukemia. Several key proteins appealed our interests, such as MDM4, TGFA, CDK19, SHC4 and PTEN. We hypothesized these proteins played vital panel joint in multiple cancers. GO annotation results have three parts: molecular function (Table 3), biological process (Supplemental Figure s4), and cellular component (Supplemental Figure s5). In the molecular function part, we found that many molecular functions were mainly associated with DNA binding and gene transcription. There four miRNAs might be tightly related with gene expression and the cellular and biological function.
Treatment of miR-130a sponge enhanced anti-cancer drug therapeutic effect in colon cancer cells. We used HT126 colon cancer cells in the study to explore the anti-cancer effects of miR-130a sponge.
In the study, cell growth assay showed miR-130a sponge inhibited colon cancer cells growth in a dose dependent manner in 96 h ( Fig. 3A and B). When it combined with anti-cancer drug 5-FU, the miR-130a sponge sensitized the anti-cancer drug effect of 5-FU to block cancer cell growth in 96 h (Fig. 3C). Discussion miRNAs regulation as a key epigenetic issue, as well as DNA methylation, histone acetylation and methylation, protein modification, would be no doubt becoming important markers in disease diagnosis and prognosis.     mechanism is quite complicated. The survival prognostic miRNAs signature meets many crucial standards. Firstly, the signature must be specific in cancer and non-cancer; secondly, the signature is correlated with patient survival; last, the signature has synergized effect in patient survival prognosis. Several diagnostic and predicted miRNAs signature have revealed by scientists worldwide. It was reported that several miRNAs markers were identified for cancer prediction and prognosis, such as head and neck squamous cell carcinomas 7 , bile duct cancer prediction 8 , and glioma 9 . However, up to date, the miRNAs expression patterns in the survival prognosis of colon cancer have not been investigated systematically. In the present study, we got four miRNAs which were survival associated by using ROC curve method and Kaplan-Meier survival method (p < 0.001) from 467 colon cancer database. We scored the miRNAs signature to form an index by assignment value for each miRNAs. The result showed that low risk group had quite a low death rate, the survival rate of which was over 80%. The high risk group had a survival rate lower than 20%, which was also extremely lower than the overall survival rate. Recently, Gao et al. developed 8 cancer hallmark-based gene signature sets which in combination can predict prognostic of recurrence for patient receiving fluorouracil-based chemotherapy of stage 2 colon cancer 12 . In agreement with their study, and enlightening by their idea, we performed validation of four miRNAs signature for stage 2 and stage 3 prognostic analysis, due to the heterogeneous of cancers. To our surprise, not all single miRNA expression level works well for stage 2 and stage 3 patients (data not shown). The combined miRNAs expression level -based index showed association of risk factor with patient survival rate in stage 2 and stage 3 colon cancer patients. The reason might be related with the different potential targets with different weighting effects on cancer hallmark of stage 2 and stage 3, additionally, discrepant regulation on genes expression of each miRNA in different cancer stage. Wang et al. reported that cancer hallmark network framework play important roles in predicting tumor clinical phenotypes 13 . Therefore, we performed GO Terms and KEGG pathway analysis. We also found many predicted genes participated in cancer related pathway and acted oncogene functions. Many genes were involved in the cancer hallmarks 14 , such as cell death (more than 25 genes, p < 0.004, Supplemental Tables s4 and s5), sustained angiogenesis and vessel morphogenesis (more than 12 genes, p < 0.001, Supplemental Table s4), and cellular metabolic processes (more than 47 genes, p = 0.018, Supplemental Table s4). Furthermore, many genes participated in transcription activity (more than 50 genes, Table 3), mRNA processing (more than 5 genes, Table s5), RNA polymerase II transcription factor activity (more than 10 genes, Table 3). These genes were associated with limitless replicative potential, inflammation cytokines release, and immune system [15][16][17][18] . Additionally, we performed KEGG pathway analysis, and found that all pathways were associated with cancer, such as p53 pathway (7 genes, p = 0.002, Table 2), glioma pathway (8 genes, p = 0.001, Table 2), pathway in cancer (14 genes, p = 0.009 Table 2), et al. Taken together, the four miRNAs signature potentially regulated cancer related genes, and influenced cancer hallmarks. The vital impacts of these four miRNAs on cancer still need further exploration in the future.
Our observations indicated that the four miRNAs signature may play a critical role in cancer cell growth after anti-cancer drug treatment. To further testify such hypothesis, we constructed miR-130 sponge expression vector and treated cancer cells with anti-cancer drug 5-FU. Results showed miR-130a sponge inhibited HT126 cells growth and sensitized the anti-cancer drug effect of 5-FU to block cancer cell growth. The latest study about gastric cancer reported that miR-130 was an oncogene by directly targeting TGFbetaR2, and as a result, it promotes cancer growth 19 . Egawa H. et al. also indicated that the miR-130 family has a crucial role in malignant progression of bladder cancer 20 . The authors suggested the miR-130 family could be a promising therapeutic target for invasive bladder cancer. Some other studies revealed miR-130 also participated in cardiac development and pulmonary hypertension 21,22 . So far, rare study focused on miR-130a in colon cancer. In agreement with the previous study of miR-130 as an oncogene, our study further revealed that miR-130a sponge vector could suppressed colon cancer cell growth. The miR-130a sponge also sensitized 5-FU drug anti-cancer effect. The influence of miR-130a expression on regulation of cell growth and anti-cancer drug efficacy might be through targeting some vital signal pathway members. In the miR-130a targets prediction, many potential genes play important roles in cell growth (MDM4, KLF7 . Therefore, we hypothesized that miR-130a might act as a anti-cancer target, as well as a prognostic biomarker for colon cancer.
Our results demonstrated that the four-miRNAs signature is a potential marker for colon cancer patient survival prognosis. The suppressing effect of colon cancer cell growth of miR-130a sponge vector supplies a brand new insight into the therapeutic strategy against colon cancer, especially for those patients with poor predicted survival rate.