Abstract
Background
Although microsatellite instability (MSI) is a powerful predictive biomarker for the efficacy of immunotherapy, the mechanism of MSI in sporadic gastrointestinal cancer is not fully understood. However, epigenetics, particularly microRNAs, has been suggested as one of the main regulators that contribute to the MSI formation.
Methods
We used microRNA expression data of 386 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database to identify differential microRNA expression profiles by different MSI status. We also obtained putative common target genes of the top differential microRNAs with miRanda online tools, and we analyzed these data by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment (KEGG).
Results
We found that 56 and 67 gastric adenocarcinoma samples were positive for low and high MSI, respectively, and that a high MSI status was associated with age, sex and subregion (P=0.049, 0.014 and 0.007, respectively). In the 67 samples with a high MSI status, expression levels of 14 microRNAs were upregulated but five microRNAs were downregulated as assessed by the fold change (FC), compared with that of the 56 samples with a low MSI status (P<0.05, |FC| >2). Further analysis suggested that the expression of miR-210-3p, miR-582-3p, miR-30a-3p and miR-105-5p predicted a high MSI status (P=4.93×10−10, 5.63×10−10, 3.23×10−9 and 7.64×10−4, respectively). Regulation of the transcription pathways ranked the top of lists from both GO and KEGG analyses, and these microRNAs might regulate DNA damage-repair genes that were also associated with a high MSI status.
Conclusions
MiR-30a-3p and miR-105-5p are potential biomarkers for the MSI-H gastric adenocarcinoma, possibly by altering expression of DNA damage-repair genes.
Keywords: DNA repair, epigenomics, stomach neoplasms, microsatellite instability (MSI), microRNAs
Introduction
More than one million patients suffered from gastric carcinoma (GCa) with an estimated 783,000 GCa-related deaths in 2018, making it the fifth most common and the third most deadly cancer worldwide (1). For advanced GCa, the palliative and systemic chemotherapies are the mainstay of treatments, and its median overall survival (OS) is only 10–12 months (2). Recently, the immune checkpoint inhibitors have been used to treat advanced GCa with a high-frequency microsatellite instability (MSI-H) or mismatch repair defects (dMMR) (3,4). The Food and Drug Administration (FDA) has granted an accelerated approval to pembrolizumab for pediatric and adult solid tumor patients with MSI-H or dMMR, and MSI-H has emerged as a key predictive biomarker for immunotherapy in GCa. Therefore, it is critical to identify the mechanism underlying the MSI-H formation in GCa.
Microsatellites are short tandem repeats of DNA, which are widely distributed in the eukaryotic genome, and they are mostly located in the non-coding regions of genes or near the telomere regions of chromosomes, likely caused by defects in mismatch repair (MMR) that plays important roles in maintaining genome stability. The gain or loss of tandem repeats resulting in the alteration of microsatellite length is called microsatellite instability (MSI) (5). It is generally considered that MSI arises from the impairment of MMR machinery and is associated with tumorigenesis (6), while dMMR originates from germline mutations in the MMR genes commonly seen in the Lynch syndrome (7), but the majority of sporadic MSI result from somatic mutational inactivation or epigenetic silencing of the MMR genes (8,9). Previous studies demonstrated that more than half of MSI-positive GCa manifested hypermethylation in the promoter of MLH1, a key member of the MMR genes, while another nearly 40% of MSI-positive GCa originated from unknown genetic or epigenetic alterations (10).
As an integral part of epigenetic regulators, non-coding RNAs, including microRNAs, play irreplaceable roles in RNA degradation and post-transcriptional regulation of gene expression. It has been shown that microRNAs are aberrantly expressed in various types of malignancies, functioning either as oncogenes or tumor suppressor genes (11,12). Therefore, whether microRNAs play a role in epigenetic regulation of MSI-H formation needs further exploration.
A previous study has explored the relationship between the expression of certain microRNAs and MSI-H in colorectal cancer with a small set of 39 samples (13), but the relationship between microRNAs and the MSI status in GCa has not been fully investigated yet. Therefore, additional studies on the relationship between microRNAs and microsatellite status in GCa may help elaborate the molecular mechanism underlying MSI formation and the efficacy of immunotherapy. Such a relationship also likely provides new biological markers for immunotherapy in GCa.
Because The Cancer Genome Atlas (TCGA) database provides a large number of microRNA sequencing dataset of GCa tissue samples (14), we evaluated differential expression of microRNAs in GCa with different microsatellite status by analyzing the available high-throughput microRNA data in the TCGA database. Furthermore, we used additional data from Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway enrichment (KEGG) databases to identify the pathways that may be regulated by differentially expressed microRNAs, which may provide possible molecular mechanisms underlying the MSI-H formation.
Methods
Data acquisition
The raw microRNA sequencing data and clinical information were downloaded from the FireBrowse database (http://www.firebrowse.org/). The inclusion criteria of GCa tissue samples were as follows: (I) the samples with pathologically confirmed diagnosis of GCa; (II) the samples with both microRNA sequencing data and clinical information; and (III) the samples with microsatellite status information. As a result, a total of 386 GCa samples were included in the analysis. The relationship between the microsatellite status and clinical features of the samples were assessed by the Chi square test, and P<0.05 was considered statistically significant.
Analysis of differentially expressed microRNAs in GCa tissues by microsatellite status
We processed microRNA expression data by using R language packages (version 3.5.1) and analyzed the differentially expressed microRNAs in GCa tissues with a microsatellite status, i.e., MSI-H, MSI-low (MSI-L) and microsatellite stable (MSS), by the limma package in R. We calculated the fold changes (FC) of the expression levels of individual microRNAs, and the FCs in differentially expressed microRNAs with |FC| >1 and P<0.05 were considered statistically significant. Because MSI-H and MSS GCa had the most differentially expressed microRNAs (Table S1), we thus focused on MSI-H and MSS in the subsequent analyses. To identify more significantly differentially expressed microRNAs, we calculated the expression levels of microRNAs for both MSI-H and MSS GCa with |FC| >2 and P<0.05.
Table S1. Different expressed microRNAs in MSI-H and MSS gastric adenocarcinoma with P<0.05 and |fold change| >1.
| ID | |Fold change| | FDR |
|---|---|---|
| MIMAT0000267 | 4.264228785 | 1.19E-09 |
| MIMAT0000102 | 3.685301663 | 0.006835307 |
| MIMAT0001080 | 3.556060866 | 3.33E-06 |
| MIMAT0019814 | 2.958476637 | 7.36E-07 |
| MIMAT0000264 | 2.629836721 | 9.58E-07 |
| MIMAT0000097 | 2.2943782 | 1.57E-06 |
| MIMAT0001536 | 2.260993124 | 5.81E-06 |
| MIMAT0000682 | 2.253289919 | 1.75E-06 |
| MIMAT0000064 | 2.17596124 | 8.47E-08 |
| MIMAT0004797 | 2.175298156 | 5.12E-10 |
| MIMAT0004550 | 2.146435041 | 1.07E-13 |
| MIMAT0001620 | 2.110032652 | 1.95E-06 |
| MIMAT0000318 | 2.099751905 | 6.27E-07 |
| MIMAT0004514 | 2.065385362 | 1.99E-10 |
| MIMAT0000728 | 2.055748198 | 0.018643679 |
| MIMAT0000088 | 2.043643173 | 1.16E-08 |
| MIMAT0004571 | 2.042890454 | 3.33E-06 |
| MIMAT0000261 | 2.04123805 | 5.84E-05 |
| MIMAT0005920 | 2.041077668 | 9.58E-07 |
| MIMAT0003247 | 1.967459056 | 7.00E-12 |
| MIMAT0004978 | 1.958067971 | 0.000202137 |
| MIMAT0000416 | 1.9302329 | 0.006835307 |
| MIMAT0000087 | 1.888299921 | 1.51E-09 |
| MIMAT0004603 | 1.88693558 | 3.33E-06 |
| MIMAT0000262 | 1.886753228 | 0.009523598 |
| MIMAT0004569 | 1.886303163 | 4.28E-07 |
| MIMAT0000226 | 1.863228556 | 0.034900381 |
| MIMAT0000763 | 1.854717086 | 0.000168194 |
| MIMAT0000259 | 1.854088832 | 0.000152194 |
| MIMAT0000280 | 1.848938995 | 0.000436882 |
| MIMAT0023712 | 1.83850692 | 2.87E-05 |
| MIMAT0022727 | 1.817873973 | 0.000820333 |
| MIMAT0004928 | 1.814319928 | 1.57E-06 |
| MIMAT0004671 | 1.799173378 | 0.000918538 |
| MIMAT0026476 | 1.797700431 | 0.017216632 |
| MIMAT0000095 | 1.784378739 | 0.000144718 |
| MIMAT0000432 | 1.76175037 | 0.001486309 |
| MIMAT0004543 | 1.75685845 | 0.002155453 |
| MIMAT0000731 | 1.743121407 | 2.82E-07 |
| MIMAT0000646 | 1.736930564 | 3.72E-05 |
| MIMAT0000441 | 1.736859396 | 0.011953815 |
| MIMAT0000461 | 1.722576282 | 2.82E-07 |
| MIMAT0004985 | 1.704920565 | 1.92E-06 |
| MIMAT0002821 | 1.688341807 | 5.14E-08 |
| MIMAT0000274 | 1.687004101 | 0.001231438 |
| MIMAT0014990 | 1.684572501 | 1.95E-06 |
| MIMAT0000098 | 1.676111094 | 0.000716002 |
| MIMAT0003301 | 1.65950854 | 8.98E-05 |
| MIMAT0000423 | 1.656296737 | 0.000505055 |
| MIMAT0000460 | 1.651988139 | 0.00842623 |
| MIMAT0000222 | 1.645849461 | 0.012964121 |
| MIMAT0000434 | 1.63691306 | 0.007586202 |
| MIMAT0004503 | 1.634758825 | 1.60E-09 |
| MIMAT0004808 | 1.629740599 | 0.00046192 |
| MIMAT0000275 | 1.627004618 | 0.000238957 |
| MIMAT0002820 | 1.625678725 | 7.68E-07 |
| MIMAT0004552 | 1.612372117 | 6.72E-06 |
| MIMAT0003249 | 1.612048881 | 0.010417378 |
| MIMAT0004584 | 1.609889855 | 0.001992171 |
| MIMAT0000617 | 1.608859172 | 0.004202522 |
| MIMAT0000458 | 1.597347527 | 9.68E-07 |
| MIMAT0004701 | 1.587045803 | 0.000344391 |
| MIMAT0001635 | 1.582951142 | 0.003614507 |
| MIMAT0003321 | 1.578075864 | 2.14E-06 |
| MIMAT0000732 | 1.57312827 | 0.000202137 |
| MIMAT0000091 | 1.568779278 | 0.021909939 |
| MIMAT0005951 | 1.568437217 | 0.001091738 |
| MIMAT0003266 | 1.566948994 | 0.000858332 |
| MIMAT0004598 | 1.556933144 | 0.009084325 |
| MIMAT0000279 | 1.539353915 | 0.000913669 |
| MIMAT0000100 | 1.535708318 | 3.72E-05 |
| MIMAT0005593 | 1.535395154 | 0.01027584 |
| MIMAT0019828 | 1.534879077 | 0.012964121 |
| MIMAT0003322 | 1.528267532 | 0.000152194 |
| MIMAT0004553 | 1.522662311 | 0.00069812 |
| MIMAT0004494 | 1.520974269 | 0.000153516 |
| MIMAT0003256 | 1.506753261 | 1.95E-06 |
| MIMAT0000250 | 1.505492791 | 0.000182247 |
| MIMAT0004657 | 1.50475595 | 0.006570749 |
| MIMAT0019927 | 1.487788526 | 0.002742594 |
| MIMAT0000066 | 1.485850578 | 0.000168194 |
| MIMAT0003241 | 1.485388014 | 0.000297465 |
| MIMAT0000440 | 1.462396455 | 0.004367022 |
| MIMAT0004484 | 1.457547295 | 0.000211644 |
| MIMAT0000070 | 1.457190008 | 0.020741236 |
| MIMAT0000258 | 1.456145364 | 5.02E-06 |
| MIMAT0004501 | 1.449910617 | 0.004769434 |
| MIMAT0004558 | 1.447237294 | 0.000246507 |
| MIMAT0019208 | 1.444843925 | 0.005494834 |
| MIMAT0004491 | 1.442718703 | 0.001672409 |
| MIMAT0003284 | 1.436431103 | 0.001878293 |
| MIMAT0019731 | 1.436293111 | 0.014194363 |
| MIMAT0003328 | 1.42749683 | 0.007706134 |
| MIMAT0000425 | 1.421126413 | 0.004043419 |
| MIMAT0000257 | 1.418223168 | 0.001649559 |
| MIMAT0004946 | 1.416993761 | 0.045261694 |
| MIMAT0004693 | 1.41325744 | 0.004769434 |
| MIMAT0003294 | 1.411728246 | 0.007355318 |
| MIMAT0004500 | 1.409612341 | 0.007706134 |
| MIMAT0003214 | 1.404498847 | 0.00012945 |
| MIMAT0000073 | 1.389784965 | 0.046751481 |
| MIMAT0017992 | 1.388505386 | 0.009810861 |
| MIMAT0000435 | 1.385016404 | 0.031244762 |
| MIMAT0018090 | 1.378677265 | 0.011942527 |
| MIMAT0004680 | 1.375526596 | 0.045473954 |
| MIMAT0004567 | 1.373418522 | 0.0002005 |
| MIMAT0004762 | 1.36682349 | 0.000324367 |
| MIMAT0004496 | 1.365947461 | 0.011296214 |
| MIMAT0002809 | 1.364319375 | 0.017142299 |
| MIMAT0015020 | 1.362157667 | 0.001405775 |
| MIMAT0019761 | 1.359728653 | 0.003082614 |
| MIMAT0004658 | 1.358847641 | 5.44E-05 |
| MIMAT0026738 | 1.355709859 | 0.01451574 |
| MIMAT0004485 | 1.355149568 | 0.004570055 |
| MIMAT0019940 | 1.353872523 | 0.016585451 |
| MIMAT0004559 | 1.351495552 | 0.000531265 |
| MIMAT0003298 | 1.344515815 | 0.030099922 |
| MIMAT0004766 | 1.340227545 | 0.013711544 |
| MIMAT0004511 | 1.334616141 | 0.007355318 |
| MIMAT0009451 | 1.33018041 | 0.003874558 |
| MIMAT0000227 | 1.329184638 | 0.015147391 |
| MIMAT0004570 | 1.329108637 | 0.049617671 |
| MIMAT0000761 | 1.322464512 | 0.04850475 |
| MIMAT0003880 | 1.320928375 | 0.010417378 |
| MIMAT0004489 | 1.319285996 | 0.006606604 |
| MIMAT0004615 | 1.316873881 | 0.001146656 |
| MIMAT0000263 | 1.307626663 | 0.047508536 |
| MIMAT0022977 | 1.302419895 | 0.049617671 |
| MIMAT0018968 | 1.300534423 | 0.012964121 |
| MIMAT0000071 | 1.298361538 | 0.049435248 |
| MIMAT0004562 | 1.297079857 | 0.002991261 |
| MIMAT0003218 | 1.295222184 | 0.037362735 |
| MIMAT0019957 | 1.295063209 | 5.57E-05 |
| MIMAT0004481 | 1.28407505 | 0.015092373 |
| MIMAT0003888 | 1.283997216 | 0.02830075 |
| MIMAT0016847 | 1.278806814 | 0.029834138 |
| MIMAT0000273 | 1.278561281 | 0.02097475 |
| MIMAT0000443 | 1.276801539 | 0.016908865 |
| MIMAT0004568 | 1.276610985 | 0.003938986 |
| MIMAT0019926 | 1.274212267 | 0.024043734 |
| MIMAT0027520 | 1.270893252 | 0.02599086 |
| MIMAT0000686 | 1.26864232 | 0.023253041 |
| MIMAT0004801 | 1.264646444 | 0.028512767 |
| MIMAT0017993 | 1.259293649 | 0.008591579 |
| MIMAT0026475 | 1.258239468 | 0.000108124 |
| MIMAT0018187 | 1.254531779 | 0.004861908 |
| MIMAT0019200 | 1.251418655 | 0.021063842 |
| MIMAT0027587 | 1.248703564 | 0.011942527 |
| MIMAT0000084 | 1.241918862 | 0.009981334 |
| MIMAT0005948 | 1.235974877 | 0.005387006 |
| MIMAT0000276 | 1.235392983 | 0.005452818 |
| MIMAT0000082 | 1.233482791 | 0.004079498 |
| MIMAT0004556 | 1.226711709 | 0.03676473 |
| MIMAT0004482 | 1.222780366 | 0.024043734 |
| MIMAT0004811 | 1.222701793 | 0.001520118 |
| MIMAT0004560 | 1.221800524 | 0.010558205 |
| MIMAT0004499 | 1.217676858 | 0.001986628 |
| MIMAT0030020 | 1.213847919 | 0.014766417 |
| MIMAT0004486 | 1.213506142 | 0.027241827 |
| MIMAT0026765 | 1.212785085 | 0.002877419 |
| MIMAT0003323 | 1.205382345 | 0.010834503 |
| MIMAT0019918 | 1.19835748 | 0.009810861 |
| MIMAT0000418 | 1.197773473 | 0.042862387 |
| MIMAT0018936 | 1.18811845 | 0.039064377 |
| MIMAT0019696 | 1.183583085 | 0.037227484 |
| MIMAT0018360 | 1.181985012 | 0.045261694 |
| MIMAT0015070 | 1.16721465 | 0.040369259 |
| MIMAT0022710 | 1.15590751 | 0.02229369 |
| MIMAT0027608 | 1.153721284 | 0.029834138 |
| MIMAT0005936 | 1.151194014 | 0.028512767 |
| MIMAT0022500 | 1.146345252 | 0.023666317 |
| MIMAT0022483 | 1.142537625 | 0.024583611 |
| MIMAT0019751 | 1.141954821 | 0.034214514 |
| MIMAT0022280 | 1.122611782 | 0.013711544 |
To distinguish of MSI-H subtypes from MSS using microRNAs expression profiles
We also used microRNA expression data to distinguish MSI-H from MSS subtype by a stepwise logistic regression analysis, and P<0.05 was considered statistically significant. We then constructed the receiver operating characteristic (ROC) curves to illustrate prediction accuracy of the models containing each of the microRNAs, respectively. We also used ROCs from the models that included all of the microRNAs with P<0.05 using the pROC package of R.
Prediction of genes targeted by MSI-H-related microRNAs and mapping of the target signaling pathway genes
We divided the MSI-H-related microRNAs into two groups of either upregulated or downregulated expression levels and compared their MSS. We selected the top six upregulated and three downregulated microRNAs for the two groups, respectively, by using more stringent criteria (P<0.01 and |FC| >2.175). The genes targeted by upregulated and downregulated microRNAs in GCa with MSI-H were predicted, respectively, according to miRanda (http://www.microrna.org/microrna/home.do) online analytic tools, and the putative genes with a short variable region (SVR) score less than −0.5 were included for further analysis. We further explored the signaling pathways and processes of the predicted genes by using the Annotation, Visualization and Integrated Discovery (DAVID) database (v6.8, https://david.ncifcrf.gov/summary.jsp). Finally, we performed GO and KEGG pathway enrichment analyses for the target genes with P<0.05 and gene counts ≥3 sets as the cut-off criteria for the comparisons.
Statistical analysis
The expression levels of microRNAs in GCa tissues were analyzed and compared by the unpaired t-test. The statistical analyses were performed by using the IBM SPSS statistics software program version 20.0 (IBM Corp., NY, USA) and R language (version 3.5.1). P values were two-sided with a significance level of 0.05.
Results
Different clinicopathological traits of GCa with different MSI status
In the present study, we included the data for 386 GCa samples from the TCGA database, and the number of the samples with MSS, MSI-L and MSI-H was 263, 56 and 67, respectively. Their general clinical traits are presented in Table 1. The associations between the MSI status and detailed clinical traits, including age at diagnosis, sex, family history, helicobacter pylori infection, gastric subregion, histologic type, histologic grade and TNM pathological stage are presented in Table 2. We found that the MSI status was significantly associated with age at diagnosis (P=0.049), sex (P=0.014) and gastric subregion (P=0.007). Overall, the proportion of MSI-H positive tumors increased as age increased, while the proportion of MSS tumors decreased as age increased, but no obvious trend was seen for MSI-L tumors. Specifically, 33 of 129 (25.6%) patients with age >70 years had MSI-H positive tumors, 23 of 128 (18.0%) patients with age of 61–70 years had MSI-H positive tumors, and 11 of 129 (8.5%) patients with age ≤61 years had MSI-H positive tumors; female GCa patients (25.2%) were more likely to develop MSI-H tumors than male GCa patients (13.3%); and the MSI-H was more likely found in distal (37.1%) and body (35.5%) GCa than in proximal (13.7%) and junction (11.4%) GCa (Figure 1). No differences were observed for other patients’ traits (Table 2).
Table 1. Clinicopathological characteristics of gastric adenocarcinoma cases in the TCGA database.
| Traits | No. of cases (%) |
|---|---|
| All subjects | 386 (100.0) |
| Age at diagnosis | |
| <50 | 32(8.3) |
| 51–60 | 97 (25.1) |
| 61–70 | 128 (33.2) |
| 71–80 | 103 (26.7) |
| >80 | 22 (5.7) |
| NA | 4 (1.0) |
| Sex | |
| Female | 131 (33.9) |
| Male | 255 (66.1) |
| Microsatellite status | |
| MSS | 263 (68.1) |
| MSI-L | 56 (14.5) |
| MSI-H | 67 (17.4) |
| Gastric subregion | |
| Antrum/distal | 143 (37.1) |
| Cardia/proximal | 53 (13.7) |
| Fundus/body | 137 (35.5) |
| Gastroesophageal junction | 44 (11.4) |
| NA | 9 (2.3) |
| Family history | |
| Yes | 18 (4.6) |
| No | 315 (81.6) |
| NA | 53 (13.8) |
| HP infection | |
| Yes | 19 (5.1) |
| No | 162 (41.7) |
| NA | 205 (53.2) |
| Stage | |
| Stage I | 50 (13.0) |
| Stage II | 123 (31.9) |
| Stage III | 174 (45.1) |
| Stage IV | 31 (8.0) |
| NA | 8 (2.1) |
TCGA, The Cancer Genome Atlas; MSS, microsatellite stable; MSI-L, microsatellite instability low; MSI-H, microsatellite instability high; NA, not available; HP, Helicobacter pylori.
Table 2. Differences in the frequencies of MSI status by clinicopathological features in gastric adenocarcinoma cases in TCGA database.
| Variables | MSI-H (n=67) | MSI-L (n=56) | MSS (n=263) | P (group) | P (subgroup) |
|---|---|---|---|---|---|
| Mean of age ± SD (years) | 69.08±9.54 | 64.51±10.83 | 64.23±10.71 | 0.004* | |
| Neoplasm subdivision (%) | 0.002* | ||||
| Antrum/distal | 37 (56.9) | 20 (37.0) | 86 (33.3) | 1.000 | |
| Cardia/proximal | 3 (4.6) | 10 (18.5) | 40 (15.5) | 0.007# | |
| Fundus/body | 24 (36.9) | 18 (33.3) | 95 (36.8) | 0.202 | |
| Gastroesophageal junction | 1 (1.5) | 6 (11.1) | 37 (14.3) | 0.002# | |
| Sex | |||||
| Male | 34 (50.7) | 39 (69.6) | 182 (69.2) | 0.014* | |
| Female | 33 (25.2) | 17 (13.0) | 81 (61.8) | ||
| Histological type (%) | 0.965 | ||||
| STAD, signet ring type | 2 (3.0) | 0 (0.0) | 9 (3.4) | 1.000 | |
| STAD, diffuse type | 11 (16.4) | 9 (16.4) | 47 (17.9) | 0.512 | |
| STAD, NOS | 21 (31.3) | 22 (40.0) | 89 (33.8) | 0.399 | |
| SIAD, mucinous type | 4 (6.0) | 2 (3.6) | 15 (5.7) | 0.829 | |
| SIAD, NOS | 14 (20.9) | 12 (21.8) | 44 (16.7) | 0.396 | |
| SIAD, papillary type | 2 (3.0) | 1 (1.8) | 5 (1.9) | 0.580 | |
| SIAD, tubular type | 13 (19.4) | 9 (16.4) | 54 (20.5) | 0.755 | |
| Neoplasm histologic grade (%) | 0.717 | ||||
| G1 | 2 (3.0) | 1 (1.8) | 4 (1.6) | 1.000 | |
| G2 | 20 (30.3) | 20 (35.7) | 99 (38.8) | 0.579 | |
| G3 | 44 (66.7) | 35 (62.5) | 152 (59.6) | 0.848 | |
| Pathologic T stage (%) | 0.168 | ||||
| T1 | 6 (9.0) | 3 (5.4) | 12 (4.6) | 1.000 | |
| T2 | 13 (19.4) | 15 (26.8) | 49 (18.6) | 0.503 | |
| T3 | 23 (34.3) | 25 (44.6) | 132 (50.2) | 0.164 | |
| T4 | 25 (37.3) | 13 (23.2) | 70 (26.6) | 0.724 | |
| Pathologic N stage (%) | 0.030* | ||||
| N0 | 30 (45.5) | 19 (33.9) | 70 (27.2) | 1.000 | |
| N1 | 17 (25.8) | 14 (25.0) | 69 (26.8) | 0.255 | |
| N2 | 8 (12.1) | 16 (28.6) | 54 (21.0) | 0.033# | |
| N3 | 11 (16.7) | 7 (12.5) | 64 (24.9) | 0.017# | |
| Pathologic M stage (%) | 0.142 | ||||
| M1 | 1 (1.5) | 2 (3.8) | 19 (7.6) | – | |
| M0 | 64(98.4) | 51(96.2) | 231(92.4) | – | |
| Pathologic TNM stage (%) | 0.153 | ||||
| Stage I | 14 (20.9) | 8 (14.8) | 28 (10.9) | 1.000 | |
| Stage II | 25 (37.3) | 20 (37.0) | 78 (30.4) | 0.535 | |
| Stage III | 25 (37.3) | 23 (42.6) | 126 (49.0) | 0.053 | |
| Stage IV | 3 (4.5) | 3 (5.6) | 25 (9.7) | 0.064 | |
*, P value was less than 0.05; #, the subgroup contributed the difference within the groups. TCGA, The Cancer Genome Atlas; GA, gastric adenocarcinoma; MSS, microsatellite stable; MSI-L, microsatellite instability low; MSI-H, microsatellite instability high; NA, not available; SD, standard deviation; GE, gastroesophageal; STAD, stomach adenocarcinoma; NOS, not other specified; SIAD, stomach intestinal adenocarcinoma.
Figure 1.
The proportion of GCa patients with different MSI status grouped by (A) age, (B) sex, and (C) gastric subregion.
MicroRNA expression profiles by MSI status
To explore the differences in the frequencies of MSI-H, MSI-L and MSS in the microRNA expression profiles, all the differentially expressed microRNAs (defined as P<0.05 with |FC| >1) among these three groups were assessed and compared with each other (Tables S1-S3). We found that MSI-L and MSS tumors had similar microRNA expression profiles, but MSI-H tumors had the most different expression profiles in comparison with MSS (Figure 2).
Table S2. Different expressed microRNAs in MSI-H and MSI-L gastric adenocarcinoma with P<0.05 and |fold change| >1.
| ID | |Fold change| | FDR |
|---|---|---|
| MIMAT0000267 | 2.468875448 | 0.010219 |
| MIMAT0019814 | 2.300115342 | 2.11E-02 |
| MIMAT0000763 | 2.112081476 | 0.009511 |
| MIMAT0000682 | 2.111826398 | 0.000405 |
| MIMAT0000318 | 1.910117734 | 0.000405 |
| MIMAT0001536 | 1.880922659 | 0.013484 |
| MIMAT0005920 | 1.823869638 | 0.010219 |
| MIMAT0001620 | 1.790420257 | 0.002833 |
| MIMAT0003247 | 1.713692493 | 0.009511 |
| MIMAT0000088 | 1.697596859 | 0.034798 |
| MIMAT0004558 | 1.68404046 | 4.05E-04 |
| MIMAT0004514 | 1.666236563 | 0.012608 |
| MIMAT0004571 | 1.658890595 | 0.023278 |
| MIMAT0004701 | 1.64181437 | 0.013933 |
| MIMAT0003328 | 1.614420354 | 0.040287 |
| MIMAT0000646 | 1.583097336 | 0.029688 |
| MIMAT0000257 | 1.571716635 | 0.009511 |
| MIMAT0004550 | 1.556305761 | 0.024059 |
| MIMAT0002809 | 1.555288061 | 0.009511 |
| MIMAT0000458 | 1.549880272 | 1.26E-02 |
| MIMAT0000100 | 1.546333728 | 0.01603 |
| MIMAT0014990 | 1.533451709 | 0.021695 |
| MIMAT0002821 | 1.522236606 | 0.007251 |
| MIMAT0000731 | 1.507560293 | 0.040287 |
| MIMAT0002820 | 1.498727252 | 0.034798 |
| MIMAT0000066 | 1.471321879 | 0.049187 |
| MIMAT0003321 | 1.469350506 | 0.034169 |
| MIMAT0004559 | 1.424003999 | 0.009511 |
| MIMAT0004503 | 1.401724895 | 3.99E-02 |
| MIMAT0017993 | 1.385063909 | 0.007251 |
| MIMAT0005948 | 1.32884243 | 0.044563 |
Table S3. Different expressed microRNAs in MSI-L and MSS gastric adenocarcinoma with P<0.05 and |fold change| >1.
| ID | |Fold change| | FDR |
|---|---|---|
| MIMAT0002830 | 17.76279758 | 0.026251 |
| MIMAT0027459 | 2.815585575 | 1.32E-05 |
| MIMAT0014998 | 1.821807692 | 0.026251 |
| MIMAT0015050 | 1.635801689 | 0.0118073 |
| MIMAT0019958 | 1.423560534 | 0.0421419 |
| MIMAT0000084 | 1.302644305 | 0.0303131 |
| MIMAT0000078 | 1.292059736 | 0.0118073 |
Figure 2.
The number of commonly expressed microRNAs and differentially expressed microRNAs between MSI-H vs. MSI-L, MSI-H vs. MSS, and MSI-L vs. MSS. “Total miRNAs” means all the microRNAs investigated in the present study.
To analyze the association between microRNA expression and MSI, we further analyzed the difference in microRNA expression between the MSI-H and MSS groups. By using a more stringent criterion (P<0.05 and |FC| >2), we found that a total of 19 differentially expressed microRNAs were identified between MSI-H and MSS samples, of which 14 were upregulated and five were downregulated in MSI-H samples, compared with those in MSS samples (Table 3). The Volcano plot is presented to show microRNA expression levels with P<0.05 and |FC| >2 (Figure 3).
Table 3. Differentially expressed microRNAs between MSI-H and MSS gastric adenocarcinoma in the TCGA database.
| ID | Accession number | Fold Change | FDR |
|---|---|---|---|
| miR-210-3p | MIMAT0000267 | 4.264228785 | 1.19E-09 |
| miR-196b-5p | MIMAT0001080 | 3.556060866 | 3.33E-06 |
| miR-203b-3p | MIMAT0019814 | 2.958476597 | 7.36E-07 |
| miR-203a-3p | MIMAT0000264 | 2.629836721 | 9.58E-07 |
| miR-429 | MIMAT0001536 | 2.260993124 | 5.81E-06 |
| miR-200a-3p | MIMAT0000682 | 2.253289919 | 1.75E-06 |
| miR-582-3p | MIMAT0004797 | 2.175298156 | 5.12E-10 |
| miR-200a-5p | MIMAT0001620 | 2.110032652 | 1.95E-06 |
| miR-200b-3p | MIMAT0000318 | 2.099751905 | 6.27E-07 |
| miR-29b-1-5p | MIMAT0004514 | 2.065385362 | 1.99E-10 |
| miR-375-3p | MIMAT0000728 | 2.055748198 | 0.01864 |
| miR-200b-5p | MIMAT0004571 | 2.042890454 | 3.33E-06 |
| miR-183-5p | MIMAT0000261 | 2.04123805 | 5.84E-05 |
| miR-1266-5p | MIMAT0005920 | 2.041077668 | 9.58E-07 |
| miR-30a-3p | MIMAT0000088 | -2.04364317 | 1.16E-08 |
| miR-30c-2-3p | MIMAT0004550 | -2.14643504 | 1.07E-13 |
| has-let-7c-5p | MIMAT0000064 | -2.17596124 | 8.47E-08 |
| miR-99a-5p | MIMAT0000097 | -2.2943782 | 1.57E-06 |
| miR-105-5p | MIMAT0000102 | -3.68530166 | 0.00684 |
TCGA, The Cancer Genome Atlas; GA, gastric adenocarcinoma; MSS, microsatellite stable; MSI-L, microsatellite instability low; MSI-H, microsatellite instability high; FDR, false discovery rate.
Figure 3.
Volcano plot of differentially expressed microRNAs between MSI-H and MSS GCa samples. The red dots represent upregulated microRNAs with a P value <0.05 and |FC| >2, and the blue dots represent downregulated microRNAs with a P value <0.05 and |FC| <2.
MicroRNAs that predicted the MSI-H status
By the microRNA expression profiles from the TCGA database, we found that four microRNAs (miR-210-3p, miR-582-3p, miR-30a-3p and miR-105-5p) could accurately distinguish the MSI-H tumors from the MSS tumors (P=4.93×10−10, 5.63×10−10, 3.23×10−9 and 7.64×10−4, respectively). To further validate the accuracy of the prediction models, ROCs of the miR-210-3p, miR-582-3p and miR-30a-3p were constructed, and the area under the curve (AUC) was 0.784, 0.757 and 0.738 for these three microRNAs, respectively, and the increase in these AUCs was statistically significant (P<0.01 for all), while the ROC of miR-105-5p could not be performed due to the missing expression data of some samples. When the three microRNAs were combined, the AUC of the combined prediction model increased to 0.886 (P=0.0004), indicating that the MSI-H subtype could be accurately distinguished from the MSS subtype by this combined prediction model (Figure 4).
Figure 4.
ROC curves showed that three microRNAs could accurately distinguish the MSI-H status from MSS alone or combined together. A: miR-210-3p; B: miR-30a-5p; C: miR-582-3p; D: miR-210-3p, miR-582-3p and miR-30a-5p combined together.
Biological signaling pathway enrichment for MSI-H related microRNAs
According to the cut-off criteria (P<0.01 and |FC| >2.175), we considered the top six microRNAs of the 14 upregulated microRNAs and the top three microRNAs of the five downregulated microRNAs as the MSI-H-related microRNAs. By using the miRanda online analysis tools, we identified a total of 171 genes of upregulated microRNAs and 119 genes of downregulated microRNAs. Then, we performed an enrichment analysis to elucidate biological functions of these target genes. We found that the GO biological process (BP) terms were mainly enriched in the regulation of transcription (DNA templated); positive regulation of transcription (DNA templated); positive regulation of transcription from RNA polymerase II promoter, and negative regulation of transcription from polymerase II promoter (Figure 5A). In addition, the KEGG pathways were significantly enriched in those for transcription mis-regulation in cancer (Figure 5B).
Figure 5.
The significantly enriched GO biological processes and KEGG pathways of putative genes targeted by the selected microRNAs. (A) GO biological processes; (B) KEGG pathways.
Discussion
Current choice of therapies for the advanced GCa are limited, and the prognosis is still relatively poor. For GCa patients with MSI-H or dMMR, however, recent therapeutic regimes of using PD-1/PD-L1 inhibitors alone or a combination with chemotherapy have achieved a remarkable progress (15-17). Based on the findings from the present study, 17.1% of the GCa patients had MSI-H tumors (18), which means nearly 1/6 of the GCa patients may benefit from the PD-1/PD-L1 mono-antibody therapy.
Only a small proportion of MSI-H GCa arises from germline mutations of the MMR genes (19). It is known that microRNAs play important roles in epigenetic regulation and that among the sporadic GCa, MSI-H is associated with epigenetic regulation, but the mechanism of MSI-H formation remains ambiguous (10,20,21). Previous studies have revealed that some microRNAs had a consistent expression pattern in both tumor tissues and circulatory plasma, serving as important predictive biomarkers for various types of malignant tumors (22,23). Therefore, the present study focused on the relationship between microRNA expression profiles and the MSI status in GCa, aiming at revealing the mechanism underlying the MSI-H formation.
Firstly, we found that the MSI-H status in 386 GCa patients was correlated with some clinicopathological features, e.g., the MSI-H status increased as age increased, with a higher frequency in female patients and patients with distal GCa located in the pylorus or body of stomach. These findings are consistent with those described in a review of other previously published results from fewer tumor samples (24).
Secondly, the present study also suggests that the microRNA expression profiles of MSS, MSI-L and MSI-H showed a trend change in GCa tumor samples. Although the difference between MSS and MSI-L was rather small, the difference between MSI-H and MSI-L was relatively remarkable and associated with aging. These trends indicate that it is a continuous change from MSS to MSI-H, consistent with the dividing method of MSI in colon cancer (25). Furthermore, we found that both MSI-H and MSS were significantly associated with microRNA expression levels.
MiR-210, which ranks the top of the most significantly differentially expressed microRNAs, has been reported to impair the functions of DNA damage-repair genes, possibly causing DNA replication errors (26,27), which may lead to the MSI formation (28). As for miR-196b, there are a few reports on the role of miR-196b in GCa. For example, a couple of studies have suggested that miR-196b promotes the metastasis and invasion of GCa cells (29,30). Other studies had shown that the high expression of miR-196b significantly impaired DNA damage-repair functions (31). Hence, we speculate that the high expression levels of miR-196b in the MSI-H-related GCa may affect the stability of the genome through the impairment of DNA damage-repair functions.
Studies have revealed that miR-203 also inhibits invasion and metastasis of GCa cells. For example, one study found that the expression of miR-203 was negatively correlated with expression of ataxia-telangiectasia mutated (ATM) protein (32), while another study demonstrated that the ATM gene was highly mutated and that the expression of the ATM protein was downregulated in MSI-H-related GCa tissues (33). Since ATM plays a critical role in DNA damage-induced signaling and initiation of cell cycle checkpoint signaling, it is reasonable to assume that miR-203 may contribute to MSI-H by targeting the ATM gene.
miR-429 and miR-200a, as the members of the miR-200 family, were significantly upregulated in MSI-H GCa tissues than in the MSS subtype. One study demonstrated that expression levels of the miR-200 family increased substantially in GCa tumor tissues, compared with that of normal tissues, indicating that the miR-200 family may play an important role in promoting GCa cell growth (34).
The miR-105, miR-99a and hsa-let-7c were the three microRNAs downregulated the most in MSI-H GCa, compared with the MSS subtype. Few studies reported the roles of miR-105 and has-let-7c in GCa. One study reported, however, that the miR-99 family of microRNAs could regulate DNA damage response by targeting SNF2H (35), while other studies showed that overexpression of the miR-99 family in prostatic cancer cells could inhibit the expression of SNF2H and reduce DNA damage-repair rate and overall repair efficiency (36,37), although the role of miR-99 in GCa has not been reported yet.
To further explore the functions of the above-mentioned nine microRNAs, we searched for the predicted target genes of these microRNAs and analyzed their related pathways and GO annotations by using bioinformatics online tools. We found that these nine microRNAs could regulate a variety of genes in several key signaling pathways, including regulation of transcription (DNA templated), positive regulation of transcription from RNA polymerase II promoter, positive regulation of transcription (DNA templated) and negative regulation of transcription from polymerase II promoter. It has been suggested that abnormal signaling pathways, such as the KRAS signaling pathway and the base-excision repair pathway, may contribute to the formation of MSI-H in gastrointestinal and endometrial cancers (38-40). Therefore, we assume that other DNA damage repair pathways may also play important roles in the formation of MSI-H, in addition to the impairment of the MMR pathway; however, further investigations are needed to test this hypothesis and unravel the underlying molecular mechanisms.
Conclusions
In the present study, we identified nine significantly differentially expressed microRNAs in GCa tumor tissues, and the results suggested that the pathways related to DNA damage-repair functions, other than MMR, were associated with MSI formation in GCa. Because of limited sample size and the limitations in bioinformatics analysis, further rigorous laboratory experiments in molecular and functional investigations are needed to substantiate these results.
Supplementary
The article’s supplementary files as
Acknowledgments
Funding: This work was supported by the Natural Science Foundation of China (No. 81871948).
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Ethics Approval was exempt, because all the raw data were from the TCGA database that is publicly available for all interested researchers, and the patients’ privacy was strictly protected due to deidentification in the TCGA database.
Footnotes
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm.2020.03.54). The authors have no conflicts of interest to declare.
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