Comprehensive Analysis and Validation of Solute Carrier Family 25 (SLC25) and Its Correlation with Immune Infiltration in Pan-Cancer.

As the largest gene family functioning in protein transport among human solute carriers, the SLC25 family (mitochondrial carrier family) can participate in development of cancer. However, a comprehensive exploration for the exactly roles of SLC family remains lacking. In the present study, a total of 15 functional SLC25 family genes were retrieved from all current publications. And multidimensional analyses were systematically performed based on the transcriptome and genome data of SLC25 family from a variety of online databases for their expression, immune cell infiltration, and cancer prognosis. Validation by qPCR and immunohistochemistry were further conducted for the expression of partial SLC25 family members in some tumor tissue. We found that the SLC25 family had strong correlation with immune cells, such as macrophages M2, CD8+ T cell, CD4+ T cell memory activated, and memory resting. Among them, SLC25A6 was most correlated with Macrophage M1 in uveal melanoma (r = -0.68, P = 1.9e - 0.5). Expression of mRNA level showed that SLC25A4 was downregulated in stomach adenocarcinoma and colon adenocarcinoma. SLC25A7 was highly expressed in stomach adenocarcinoma and colon adenocarcinoma. SLC25A23 was decreased in colon adenocarcinoma. qPCR and immunohistochemistry validation results were consistent with our bioinformatics prediction. SLC25A8 was associated with the prognosis of cancer. All these findings suggested that the SLC25 family might affects the immune microenvironment of the cancer and then had the potential to be predictive biomarkers for early diagnosis and prognosis as well as novel targets for individualized treatment of cancer.

Comprehensive Pan-Cancer Analysis of Heat Shock Protein 110, 90, 70, and 60 Families.

Background: Here we carried out a panoramic analysis of the expression and prognosis of HSP110, HSP90, HSP70, and HSP60 families in 33 types of cancer, with the aim of deepening the systematic understanding of heat shock proteins (HSPs) in cancer. Materials and Methods: Next-generation sequencing data of multiple tumors were downloaded from TCGA, CCLE and Oncomine databases. RStudio 3.6.1 was used to analyze HSP110, HSP90, HSP70 and HSP60 families based on their expression in 33 types of cancer. The validations in vivo (stomach adenocarcinoma and colon adenocarcinoma tissues) were performed by qRT-PCR. Results: HSPs were differentially expressed in different cancers. The results revealed mainly positive correlations among the expressions of HSPs in different cancers. Expressions of HSP family members were generally associated with poor prognosis in respiratory, digestive, urinary and reproductive system tumors and associated with good prognosis in cholangiocarcinoma, pheochromocytoma and paraganglioma. TCGA mutation analysis showed that HSP gene mutation rate in cancers was 0-23%. CCLE mutation analysis indicated that HSP gene mutation rate in 828 cell lines from 15 tumors was 0-17%. CNV analysis revealed that HSPs have different degrees of gene amplifications and deletions in cancers. Gene mutations of 15 HSPs influenced their protein expressions in different cancers. Copy number amplifications and deletions of 22 HSPs also impacted protein expression levels in pan-cancer. HSP gene mutation was generally a poor prognosis factor in cancers, except for uterine corpus endometrial carcinoma. CNVs in 14 HSPs showed varying influences on survival status in different cancers. HSPs may be involved in the activation and inhibition of multiple cancer-related pathways. HSP expressions were closely correlated with 22 immune cell infiltrations in different cancers. The qRT-PCR validation results in vivo showed that HSPA2 was down-regulated in stomach adenocarcinoma and colon adenocarcinoma; HSPA7 and HSPA1A also were down-regulated in colon adenocarcinoma. HSPA2-HSPA7 (r = 0.031, p = 0.009) and HSPA1A-HSPA7 (r = 0.516, p < 0.001) were positive correlation in colon adenocarcinoma. Conclusion: These analysis and validation results show that HSP families play an important role in the occurrence and development of various tumors and are potential tumor diagnostic and prognostic biomarkers as well as anti-cancer therapeutic targets.

Pepsinogen C expression-related lncRNA/circRNA/mRNA profile and its co-mediated ceRNA network in gastric cancer.

The expression of pepsinogen C (PGC) is considered an ideal negative biomarker of gastric cancer, but its pathological mechanisms remain unclear. This study aims to analyze competing endogenous RNA (ceRNA) networks related to PGC expression at a post-transcriptional level and build an experimental basis for studying the role of PGC in the progression of gastric cancer. RNA sequencing technology was used to detect the differential expression (DE) profiles of PGC-related long non-coding (lnc)RNAs, circular (circ)RNAs, and mRNAs. Ggcorrplot R package and online database were used to construct DElncRNAs/DEcircRNAs co-mediated PGC expression-related ceRNA networks. In vivo and in vitro validations were performed using quantitative reverse transcription-PCR (qRT-PCR). RNA sequencing found 637 DEmRNAs, 698 DElncRNAs, and 38 DEcircRNAs. The PPI network of PGC expression-related mRNAs consisted of 503 nodes and 1179 edges. CFH, PPARG, and MUC6 directly interacted with PGC. Enrichment analysis suggested that DEmRNAs were mainly enriched in cancer-related pathways. Eleven DElncRNAs, 13 circRNAs, and 35 miRNA-mRNA pairs were used to construct ceRNA networks co-mediated by DElncRNAs and DEcircRNAs that were PGC expression-related. The network directly related to PGC was as follows: SNHG16/hsa_circ_0008197-hsa-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p-PGC. qRT-PCR validation results showed that PGC, PPARG, SNHG16, and hsa_circ_0008197 were differentially expressed in gastric cancer cells and tissues: PGC positively correlated with PPARG (r = 0.276, P = 0.009), SNHG16 (r = 0.35, P = 0.002), and hsa_circ_0008197 (r = 0.346, P = 0.005). PGC-related DElncRNAs and DEcircRNAs co-mediated complicated ceRNA networks to regulate PGC expression, thus affecting the occurrence and development of gastric cancer at a post-transcriptional level. Of these, the network directly associated with PGC expression was a SNHG16/hsa_circ_0008197-mir-98-5p/hsa-let-7f-5p/hsa-let-7c-5p - PGC axis. This study may form a foundation for the subsequent exploration of the possible regulatory mechanisms of PGC in gastric cancer.

Identification of PGC-related ncRNAs and their relationship with the clinicopathological features of Gastric Cancer.

Pepsinogen C (PGC) is considered to be the final product of mature differentiated gastric mucosa. The expression level of PGC in gastric mucosa is clearly decreased upon the development of gastric cancer (GC). However, the mechanism behind PGC's down-regulation remains unclear and needs to be clarified. This study aimed to identify PGC-related ncRNAs with the potential to be PGC post-transcriptional regulators and to further explore the association between these ncRNAs and the clinicopathological parameters of GC. Bioinformatic software was used to predict miRNAs binding specifically to PGC and circRNAs binding specifically to these candidate miRNAs. Dual-luciferase reporter assay was performed to validate the completely complementary pairing of PGC and PGC-related ncRNAs. qRT-PCR was applied to determine the expression levels of PGC and PGC-related ncRNAs in GC tissue. hsa-let-7c was predicted to bind to the PGC gene, which was confirmed by dual-luciferase reporter assay. hsa_circ_0001483 and hsa_circ_0001324 were identified to bind to hsa-let-7c by bioinformatic analysis and dual-luciferase reporter assay. In addition, the hsa_circ_0001483/hsa_circ_0001324 -hsa-let-7c-PGC axis was confirmed in tissue by qRT-PCR. The expression level of hsa_circ_0001483 was correlated with peritumoral inflammatory cell infiltration and lymphatic metastasis. hsa_circ_0001483, hsa_circ_0001324, and let-7c were newly identified and validated as PGC-related ncRNAs and showed associations with the clinicopathological features of GC. The hsa_circ_0001483/hsa_circ_0001324-hsa-let-7c-PGC axis in GC may account for the down-regulation of PGC in GC tissue.

Interaction of HULC polymorphisms with Helicobacter pylori infection plays a strong role for the prediction of gastric cancer risk.

Aim: Gene-environment interactions have better efficacy in predicting cancer susceptibility than a single gene. Materials & methods: Eight tag single nucleotide polymorphisms encompassing the whole HULC gene were detected by KASP platform (LGC Genomics, Hoddesdon, UK) in 631 gastric cancer (GC) cases and 953 controls. Results: The HULC gene rs7770772 polymorphism could increase GC risk (recessive model: odds ratio = 1.95). The multifactor dimensionality reduction (MDR) analysis suggested that the 2D model HULC rs7770772-Helicobacter pylori had better effect on GC risk prediction (maximum testing accuracy = 0.7005). No significant result was observed in our experimental expression quantitative trait loci analysis. Conclusion: 2D model HULC rs7770772-H. pylori might have superior efficacy for GC risk than a single factor.

Correlation Between TNFAIP2 Gene Polymorphism and Prediction/Prognosis for Gastric Cancer and Its Effect on TNFAIP2 Protein Expression.

Objective: TNFAIP2 is a novel gene induced by TNF-α and participates in inflammatory reaction and tumor angiogenesis. This study aims to understand the correlation between TNFAIP2 gene polymorphism and prediction as well as prognosis of gastric cancer (GC) in a Chinese population. Methods: One thousand two hundred seventy-nine cases were enrolled, including 640 GC and 639 non-cancer cases. The functional tagSNPs of the TNFAIP2 gene were screened by Haploview software and NIH Snpinfo website. Human whole-blood genomic DNA was extracted by phenol chloroform method and analyzed by KASP SNP typing and sequencing method. ELISA was used to determine the expression of TNFAIP2 protein in serum samples. The miRNAs bound to TNFAIP2 3' UTR rs8126 were predicted by MirSNP and TargetScan database. SPSS 22.0 software was used for statistical analysis, and P < 0.05 showed statistical difference. Results: Four functional TNFAIP2 tagSNPs were found by bioinformatics analysis. TNFAIP2 rs8126 T>C polymorphism increased GC risk, and the risk in TC genotype cases was higher than that in TT genotype cases (P = 0.001, OR = 1.557). In the dominant model, the TNFAIP2 rs8126 polymorphic carrier was 1.419 times higher (P = 0.007). TNFAIP2 rs710100 C>T polymorphism, TNFAIP2 rs3759571 G>A polymorphism, and TNFAIP2 rs3759573 A>G polymorphism were not correlated with GC risk. In the subgroup analysis, TNFAIP2 rs8126 TC genotype cases had a higher GC risk in male, aged 60 years or older, Helicobacter pylori-negative, non-smoking, and non-drinking. However, there was no correlation between TNFAIP2 SNPs and GC prognosis. The TNFAIP2 protein concentration in GC patients was significantly different from that in healthy persons (P = 0.029), but it was not associated with GC prognosis. The high or low expression of TNFAIP2 protein had no significant difference with gender, age, H. pylori infection, smoking, and drinking in GC patients. The serum TNFAIP2 protein expression in rs8126 TT genotype carriers was significantly higher than that in rs8126 CC genotype carriers (P < 0.001). Conclusion: TNFAIP2 3' UTR rs8126 T>C polymorphism was associated with GC risk in a Chinese population, especially in cases with males aged 60 years or older, H. pylori negative, non-smoking and non-drinking. Compared with healthy persons, serum TNFAIP2 protein expression was higher in Chinese GC patients, and TNFAIP2 3' UTR rs8126 T>C polymorphism might affect TNFAIP2 protein expression.

HOTTIP polymorphism may affect gastric cancer susceptibility by altering HOTTIP expression.

BACKGROUND: Non-coding RNA polymorphisms can affect disease risk and prognosis by influencing gene expression. Here, we first investigated the association between single nucleotide polymorphisms (SNPs) of long non-coding RNA (lncRNA) HOTTIP and gastric cancer risk/prognosis. METHODS: A total of five HOTTIP SNPs among 627 gastric cancer cases and 935 controls were tested by Kompetitive Allele Specific PCR (KASP) assay. The functional SNPs underwent eQTL analysis and the expression of HOTTIP was assessed by quantitative RT-PCR. RESULTS: The rs2067087 and rs3807598 SNPs of HOTTIP increased susceptibility to gastric cancer (rs2067087: dominant model, P=0.008, odds ratio (OR) = 1.35; rs3807598: recessive model, P=0.037, OR = 1.29). Both HOTTIP rs2067087 and rs3807598 could affect the expression of mature lncRNA (P=0.003 and P=0.032, respectively). CONCLUSION: The rs2067087 and rs3807598 SNPs of HOTTIP are associated with gastric cancer risk, possibly by affecting the expression of mature HOTTIP.

Relationship between Long Noncoding RNA H19 Polymorphisms and Risk of Coronary Artery Disease in a Chinese Population: A Case-Control Study.

METHODS: We collected 732 samples from Liaoning Province, China, and three polymorphisms in long noncoding RNA H19 were genotyped using the KASP platform. RESULTS: Our data showed that H19 rs2735971 and rs3024270 variant genotypes were associated with a decreased risk of CAD (rs2735971, P = 0.003, odds ratio (OR) = 0.6195, 95% confidence interval = 0.44 - 0.84; rs3024270, P = 0.030, OR = 0.65, 95% confidence interval = 0.44 - 0.96). No significant association with the risk of CAD was found for H19 rs2839698 polymorphism (P > 0.05). In haplotype analysis, H19 polymorphisms of rs2735971-rs2839698-rs3024270 A-C-C haplotype reduced the risk of CAD by 0.61-fold (P = 0.004, OR = 0.61, 95% confidence interval = 0.43-0.86). In addition, we found that rs2839698 interacted with smoking (P interaction = 0.027), and according to multifactor dimensionality reduction analysis, the three-factor model including H19 rs2839698-smoking-drinking was the best model for the risk of CAD (testing balanced accuracy = 0.6979). CONCLUSION: Our study demonstrated that some genotypes of H19 rs2735971 and rs3024270 polymorphisms, as well as rs2735971-rs2839698-rs3024270 A-C-C haplotype, were associated with the risk of CAD in a Chinese population, and these genotypes have the potential to be biomarkers for predicting CAD risk. We also found that rs2735971-rs2839698-rs3024270 A-C-C may have a significantly lower risk of CAD. The recessive genetic model of rs3024270 could predict the severity of CAD.

LncRNAs adjacent to pepsinogen C in gastric diseases and diagnostic efficiencies of joint detection in gastric diseases.

Aims: We aimed to explore diagnostic efficiencies of long noncoding RNAs (lncRNAs) adjacent to PGC combining with sPGC and anti-Helicobacter pylori IgG in identifying GC (gastric cancer) and precancerous disease. Patients & methods: A total of 265 patients with different gastric diseases were collected. ELISA was to detect sPGC and anti-H. pylori IgG. LncRNAs was determined by qRT-PCR. Results: The area under receiver operating characteristic curve of lncRNAs in discriminating GC+AG (atrophic gastritis) and superficial gastritis (SG) were 79.0, 68.1 and 75.9%. The diagnostic performance of lncRNAs with sPGC had increasing trends in distinguishing GC from non-GC, SG from GC+AG comparing with lncRNAs, with no statistic difference. Diagnosis efficacies of lncRNAs with anti-H. pylori IgG improved dramatically. Conclusions: Serum lncRNAs could distinguish GC, AG and SG. Diagnosis efficiencies of lncRNAs with sPGC and anti-H. pylori-IgG could be improved.

MetaDE-Based Analysis of circRNA Expression Profiles Involved in Gastric Cancer.

BACKGROUND: Circular RNAs (circRNAs) could play carcinogenic roles in gastric cancer (GC) and have potential to be biomarkers for GC early diagnosis, which needs to be further excavated and supported by more evidence. AIMS: The study aims to identify more authentic circRNA expression profiles that could function as potential biomarkers in GC. METHODS: circRNA expression data in three microarrays were downloaded from Gene Expression Omnibus datasets. A systematic meta-analysis based on an integrated dataset pre-processed from the three microarrays was conducted to identify a panel of differentially expressed circRNAs (DEcircs) by using the metaDE package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes term enrichment were used to note the corresponding functions of DEcircs. Quantitative real-time polymerase chain reaction was applied to verify the DEcircs expression in cancer tissues and adjacent paracancerous tissues. A GC risk-related circRNAs-miRNAs-mRNAs network was further constructed and analyzed. RESULTS: MetaDE analysis suggested 64 DEcircs between cancer tissues and adjacent normal tissues. GO and KEGG analysis showed that the parental genes of these DEcircs were mainly associated with histone methylation, Wnt signalosome and histone methylation activity. Hsa_circ_0005927 and hsa_circ_0067934 were verified in GC tissues, and a GC risk-related network was constructed. CONCLUSION: MetaDE-based circRNA expression profiles revealed a series of potential biomarkers involved in GC. Two circRNAs, hsa_circ_0005927 and hsa_circ_0067934, could be more authentic biomarkers for GC screening. The GC risk-related network of hsa_circ_0005927/hsa_circ_0067934 and their downstream targets will provide new genetic insights for GC research.

lncRNA-PCAT1 rs2632159 polymorphism could be a biomarker for colorectal cancer susceptibility.

Background: Single-nucleotide polymorphisms (SNPs) in lncRNAs could be biomarkers for susceptibility to colorectal cancer (CRC), but the association of PCAT1 polymorphisms and CRC susceptibility is yet to be studied. Methods: Five tagSNPs covering the PCAT1 gene were detected through Kompetitive Allele-Specific PCR among 436 CRC patients and 510 controls. An expression quantitative trait locus (eQTL) bioinformatic analysis was then performed. Results: In the present study, PCAT1 rs2632159 polymorphism increased CRC risk by 1.37-fold and 2.19-fold in the dominant and recessive models, respectively (P=0.040 and 0.041). When the CRC cases were divided into colon cancer and rectal cancer, we found that this polymorphism affected colon cancer risk under the dominant model (P=0.022, OR = 1.51) and affected rectal cancer susceptibility under the recessive model (P=0.009, OR = 3.03). A more pronounced effect was observed in the male subgroup in that PCAT1 rs2632159 SNP increased rectal cancer risk by 3.97-fold (P=0.017). When PCAT1 rs2632159 was present, epistatic effects were observed with rs1902432 and rs785005 (P=0.011 and 0.008, respectively). eQTL analysis showed that rs2632159 could influence binding with the transcription factors EBF, LUN-1, and TCF12. Conclusion:PCAT1 rs2632159 SNP could be a biomarker for CRC risk. And the rs1902432 SNP might only have potential to be a biomarker for colon cancer risk.

Association of twelve polymorphisms in three onco-lncRNA genes with hepatocellular cancer risk and prognosis: A case-control study.

AIM: To evaluate the association of 12 tag single nucleotide polymorphisms (tagSNPs) in three onco-long non-coding RNA (lncRNA) genes (HOTTIP, CCAT2, MALAT1) with the risk and prognosis of hepatocellular cancer (HCC). METHODS: Twelve tagSNPs covering the three onco-lncRNAs were genotyped by the KASP method in a total of 1338 samples, including 521 HCC patients and frequency-matched 817 controls. The samples were obtained from an unrelated Chinese population at the First Hospital of China Medical University from 2012-2015. The expression quantitative trait loci (eQTL) analyses were conducted to explore further the potential function of the promising SNPs. RESULTS: Three SNPs in HOTTIP, one promoter SNP in MALAT1, and one haplotype of HOTTIP were associated with HCC risk. The HOTTIP rs17501292, rs2067087, and rs17427960 SNPs were increased to 1.55-, 1.20-, and 1.18-fold HCC risk under allelic models (P = 0.012, 0.017 and 0.049, respectively). MALAT1 rs4102217 SNP was increased to a 1.32-fold HCC risk under dominant models (P = 0.028). In addition, the two-way interaction of HOTTIP rs17501292-MALAT1 rs619586 polymorphisms showed a decreased effect on HCC risk (Pinteraction = 0.028, OR = 0.30) and epistasis with each other. HOTTIP rs3807598 variant genotype showed significantly longer survival time in HBV negative subgroup (P = 0.049, HR = 0.12), and MALAT1 rs591291 showed significantly better prognosis in female and HBV negative subgroups (P = 0.022, HR = 0.37; P = 0.042, HR = 0.25, respectively). In the study, no significant effect was observed in eQTL analysis. CONCLUSION: Specific lncRNA (HOTTIP and MALAT1) SNPs have potential to be biomarkers for HCC risk and prognosis.

The association of lncRNA-HULC polymorphisms with hepatocellular cancer risk and prognosis.

BACKGROUND: Genetic polymorphisms in lncRNA HULC may affect the susceptibility and clinical outcome of cancer. We aimed to investigate the association of HULC tagSNPs with the risk and prognosis of hepatocellular cancer, as well as the influence of the SNPs on lncRNA expression level. METHODS: A total of 1338 samples were recruited in the risk study. Among them, 351 HCC patients were involved in the prognosis study. SNP genotyping was performed using KASP method and lncRNA expression was detected by Real-time PCR. RESULTS: We found a promoter SNP, rs1041279, was associated with a 1.41-fold increased HCC risk (P = 0.032). In the stratified analysis, rs1041279 had greater ORs for the increased HCC risk in the male subgroup (P = 0.014, OR = 1.54). Furthermore, multi-logistic regression analysis revealed a two-way interaction effect of smoking-rs2038540 SNP on HCC risk (OR = 4.20). And MDR analysis consistently demonstrated a SNP-environmental interaction among smoking-drinking-rs2038540 SNP as the best model for predicting HCC risk (P = 0.0107). In our study, no significant association was found between HULC SNPs and the overall survival (P > 0.05), and no significant effect was observed of rs1041279 SNP on lncRNA-HULC expression (P > 0.05). CONCLUSION: lncRNA-HULC rs1041279 SNP and the interaction of rs2038540 SNP with environmental factors could enhance HCC risk.

The expression of circRNAs as a promising biomarker in the diagnosis and prognosis of human cancers: a systematic review and meta-analysis.

BACKGROUND: CircRNAs, a type of non-coding RNAs with special loop structure, of which the aberrant expression is closely related to tumor growth, proliferation, metastasis and recurrence. It remains unclear whether they have the potential to be biomarkers for diagnosis and prognosis of cancers. The study aims to clarify the relationship of circRNAs expression with cancers diagnosis and prognosis. MATERIALS AND METHODS: Sensitivity, specificity, area under curve (AUC) and receiver operating characteristic curve (ROC) were calculated to evaluate the diagnostic efficacy; Hazard ratio (HR) of overall survival (OS), disease free survival (DFS) and recurrence free survival (RFS) were calculated to evaluate the association between circRNAs expression and survival of cancer patients. RESULTS: A total of 27 studies were involved in the meta-analysis, including 16 diagnostic and 11 prognostic articles. Among the diagnostic studies, 18 kinds of circRNAs had been investigated, in which 3 were up regulated and 15 were down regulated. Their pooled sensitivity, specificity and AUC were 0.71(0.65-0.77), 0.77(0.72-0.81) and 0.81(0.77-0.84), respectively. In stratified analysis, a higher specificity was shown in circRNAs for diagnosing gastric cancer and hepatocellular cancer. 12 circRNAs were involved in the prognostic studies, including 6 up-regulated and 6 down-regulated circRNAs. Their overall HR of OS and DFS/RFS were 1.37(0.98-1.75) and 2.28 (0.77-3.79), respectively. CONCLUSIONS: CircRNAs have the potential to be biomarkers for diagnosis and prognosis of cancers. Further investigations are still needed to explore the clinical value of circRNAs as tumor markers.

MiRNA Polymorphisms and Cancer Prognosis: A Systematic Review and Meta-Analysis.

Background: Accumulating studies have focused on the relationship between miRNAs polymorphisms and cancer prognosis. However, the results are conflicting and unconvincing. This systematic review and meta-analysis was conducted to explore the relationship between miRNAs polymorphisms and cancer prognosis, aiming to seek for markers with cancer prognostic function. Methods: Hazard ratio of overall survival, disease-free survival (DFS) and recurrence-free survival were calculated to evaluate the association between miRNAs polymorphisms and cancer prognosis by using Stata software 11.0. Results: We systematically reviewed the association of 17 miRNAs SNPs with cancer prognosis including 24,721 samples. It was shown that 6 miRNAs SNPs (miR-608 rs4919510, miR-492 rs2289030, miR-378 rs1076064, miR-499 rs4919510, miR-149 rs2292832, miR-196a2 rs11614913) were associated with better cancer overall survival (OS) while let-7i rs10877887 was associated with poor OS; the homozygous and heterozygote genotype of miR-423 were related to poor cancer relapse-free survival (RFS) when compared with the wild genotype; miR-146 rs2910164 was linked to favorable cancer DFS while miR-196a2 rs11614913 was associated with poor DFS. Conclusions: In summary, let-7i rs10877887, miR-608 rs4919510, miR-492 rs2289030, miR-378 rs1076064, miR-423 rs6505162, miR-499 rs4919510, miR-149 rs2292832, miR-146 rs2910164, and miR-196a2 rs11614913 might serve as potential biomarkers for cancer prognosis.