C-KIT two mutation sites in patients with imatinib mesylate secondary resistance
All specimens were analyzed by RT-PCR amplification, DNA sequencing and analysis and then comparison with wild type c-KIT gene, C-KIT/PDGFR-α mutation were detection, secondary mutation were found in 3 GIST specimens with drug resistance. one case locus in the v654a of exon 13, one case locus in the T760I of exon 14, the other locus in the v654a of exon 17(Figure 1), which confirm the resistance of imatinib mesylate and offer a potential theoretical basic of the application probability of circRNAs.
Identification And Characteristics Of Circrnas
We performed ribosomal RNA-depleted RNA sequencing to explore circRNA expression profiles in three normal gastric tissue samples (N), three primary GIST samples (Y or YC) and three GIST samples secondarily resistant to IM (C). The number of circRNAs identified in each sample is shown in Figure 2A. Venn analysis for comparison of predicted circRNAs with the data published in the circBase, showing that 11935 circRNAs were found between predicted circRNAs and circBase (Figure 2B). According to the circular RNAs array, a total of 30,550 were detected in 9 samples, and the length mostly distribute in 201-400bp and >2000bp (Figure 2C). These circRNAs originated from all chromosomes, chr1, chr2, and chr3 were the three chromosomes to which the most circRNAs were mapped (Figure 2D). The number of exons per circRNA was less than six for most circRNAs (Figure 2E). Similarly, most of the identified circRNAs (27050,88.54%) were generated from sense-overlapping regions, indicating that the formation of circRNAs is closely associated with pre-mRNA splicing mechanism (Figure 1F). Approximately 3.82% (1167) and 5.41% (1652) of circRNAs arose from exons (exonic circRNA) and the intergenic regions. A small proportion of circRNAs were antisense circRNAs (383, 1.25%) and intronic circRNAs (298, 0.98%). General features of the circRNA sequencing data were list in Table 1.
Table 1
General features of the circRNA sequencing data
Sample | raw reads | raw bases | clean reads | clean bases | valid bases | Q30 | GC |
Sample_N1 Sample_N2 Sample_N3 Sample_C1 Sample_C2 Sample_C3 Sample_YC_1 Sample_YC_2 Sample_YC_3 | 84587074 91507150 91320298 84193988 82799646 85145886 84743526 83362440 82891684 | 10573384250 11438393750 11415037250 10524248500 10349955750 10643235750 10592940750 10420305000 10361460500 | 81651670 88469786 88647372 81676720 80243548 82621864 81602896 80906514 80622518 | 10201851969 11053620694 11076539842 10204694315 10025345565 10322885971 10186655571 10108276460 10073190258 | 96.48% 96.63% 97.03% 96.96% 96.86% 96.99% 96.16% 97.00% 97.21% | 93.56% 93.73% 94.29% 94.20% 93.93% 94.11% 93.57% 94.37% 94.35% | 55.50% 56.00% 57.00% 58.00% 58.00% 55.50% 57.00% 50.50% 55.50% |
The Potential Functions Identification
It has been confirmed that circRNAs possess tissue-specific expression characteristics. To screen dysregulated circRNAs in three different GIST samples, we used DEseq software to analyze circRNA expression profiles RPM (mapped back-splicing junction reads per million mapped reads), found that that no abnormal expression was observed in three different GIST samples (Figure 3A). PCA (Principal Component Analysis) was performed to analyze the circRNA expression profiles of the three groups samples. The distance between points represented the similarity between the two samples, and the repeatability of the three groups of samples was ideal in Figure 3B. Differential analysis was conducted among the three comparison groups by Volcano plots. The circRNA differentially expressed was screened using the criteria of "adjusted pvalue < 0.05 and absolute value of log2Foldchange >1". The red dot on the volcano map was significantly up-regulated circRNA, the green dot was significantly down-regulated circRNA, and the gray dot showed no obvious difference (Figure 3C).These were 159, 98, and 37 circRNAs up-regulated, 277, 284, and 23 circRNAs down-regulated in comparison C-vs-N, YC-vs-N and C-vs-YC, respectively(Figure 3D). Venn analysis of the three comparison groups was shown in Figure 3E. In general, the same kind of samples can be clustered in the same cluster, and the genes in the same cluster may have similar biological functions, our results show that all samples in paired groups have the co-regulated (up or down) genes (Figure 3F). The top ten different expression circRNA in the three comparison groups was shown in Table 2.
Table 2
Top 10 differentially expressed circRNAs in the three comparison groups
circRNA_id | circBase_id | log2FoldChange | P-value | Adjusted P-value | Regulation | Host genes |
C-vs-N | | | | | | |
circRNA_09533 | hsa_circ_0006867 | -8.62 | 9.25E-90 | 2.61E-85 | Down | LRBA |
circRNA_17427 | hsa_circ_0018064 | -inf | 3.05E-64 | 4.30E-60 | Down | SVIL |
circRNA_20776 | hsa_circ_0026782 | -9.86 | 7.21E-53 | 6.78E-49 | Down | ITGA7 |
circRNA_09530 | - | -inf | 2.72E-46 | 1.92E-42 | Down | LRBA |
circRNA_13055 | hsa_circ_0079284 | -5.41 | 2.84E-43 | 1.60E-39 | Down | RNF216 |
circRNA_11884 | hsa_circ_0004119 | -5.40 | 1.63E-41 | 7.69E-38 | Down | RAB23 |
circRNA_01991 | hsa_circ_0005230 | 5.26 | 1.57E-35 | 6.32E-32 | Up | DNM3 |
circRNA_13811 | hsa_circ_0004365 | -inf | 7.44E-35 | 2.62E-31 | Down | SEMA3C |
circRNA_03576 | hsa_circ_0000994 | -4.03 | 2.99E-30 | 8.43E-27 | Down | SLC8A1 |
circRNA_26953 | hsa_circ_0000825 | -5.70 | 2.70E-30 | 8.43E-27 | Down | MTCL1 |
C-vs-YC | | | | | | |
circRNA_01991 | hsa_circ_0005230 | 3.92 | 1.33E-19 | 2.49E-15 | Up | DNM3 |
circRNA_03862 | hsa_circ_0004435 | -2.74 | 1.07E-12 | 6.67E-09 | Down | FANCL |
circRNA_15734 | - | Inf | 9.93E-13 | 6.67E-09 | Up | - |
circRNA_11269 | hsa_circ_0003718 | -4.00 | 6.83E-12 | 3.20E-08 | Down | RANBP17 |
circRNA_02957 | hsa_circ_0002922 | -2.17 | 2.05E-11 | 7.68E-08 | Down | ZNF124 |
circRNA_30179 | - | -inf | 3.18E-11 | 9.95E-08 | Down | DIAPH2 |
circRNA_30540 | hsa_circ_0009024 | -inf | 7.27E-11 | 1.95E-07 | Down | - |
circRNA_03489 | hsa_circ_0000992 | 3.91 | 4.07E-10 | 9.55E-07 | Up | PRKD3 |
circRNA_04497 | - | -2.60 | 5.75E-10 | 1.20E-06 | Down | DPP10 |
circRNA_25651 | - | Inf | 9.34E-10 | 1.75E-06 | Up | ZC3H18 |
YC-vs-N | | | | | | |
circRNA_09533 | hsa_circ_0006867 | -8.15 | 1.75E-86 | 4.41E-82 | Down | LRBA |
circRNA_17427 | hsa_circ_0018064 | -inf | 1.81E-67 | 2.28E-63 | Down | SVIL |
circRNA_13055 | hsa_circ_0079284 | -7.80 | 8.02E-60 | 6.75E-56 | Down | RNF216 |
circRNA_04497 | - | Inf | 5.19E-58 | 3.27E-54 | Up | DPP10 |
circRNA_09530 | - | -inf | 4.50E-47 | 2.27E-43 | Down | LRBA |
circRNA_11884 | hsa_circ_0004119 | -4.77 | 1.01E-39 | 4.26E-36 | Down | RAB23 |
circRNA_20776 | hsa_circ_0026782 | -6.94 | 1.03E-33 | 3.70E-30 | Down | ITGA7 |
circRNA_26999 | hsa_circ_0008821 | -inf | 5.42E-32 | 1.71E-28 | Down | RAB31 |
circRNA_13811 | hsa_circ_0004365 | -6.68 | 1.69E-29 | 4.74E-26 | Down | SEMA3C |
circRNA_18913 | hsa_circ_0000277 | 6.50 | 1.12E-27 | 2.82E-24 | Up | PDE3B |
GO enrichment analysis for the host genes of differentially expressed circRNAs
After get the differentially expressed genes, we selected the top10 functional enrichment analysis. The enriched functional terms were used as the predicted functional term of given circRNAs. Analysis the difference gene expression with GO analysis, to describe its function (with GO annotation). GO analyses covered three subgroups: biological process (BP), cellular component (CC), and Molecular function (MF). The GO analysis with the most significant enrichment in the BP, CC, and MF subgroups by C-vs-N comparison groups is regulation of transcription, DNA-templated, cytosol and metal ion binding, respectively. In C-vs-YC group, the GO analysis with the most significant enrichment in the BP, CC, and MF subgroups is regulation of transcription, DNA-templated, nucleoplasm and double-stranded DNA binding. In YC-vs-N group, the GO analysis with the most significant enrichment in the BP, CC, and MF subgroups is regulation of transcription from RNA polymerase II promoter, cytosol and metal ion binding (Figure 4A-C).
Construction Of The Circrna-mirna Interaction Network In Drug Resistance/hif-1
We combined the chip data (OE2016Q1031Y) from another of our published articles to draw the cirRNA-miRNA-mRNA network in the group C vs YC, and found that, 15 cirRNA were up-regulated (Red), 8 cirRNA was down-regulated (Green) (Figure 5A). GO enrichment analysis of the cirRNA-miRNA-mRNA network, the bubble diagram shows the top 20 enriched GO terms (P<0.05) (Figure 5B). KEGG pathway enrichment analysis of the cirRNA-miRNA-mRNA network, and found out potential relationship between differential expression genes with changes of cell pathways, such as HIF-1 pathway, Central carbon metabolism in cancer, AMPK signaling pathway, Autophagy-animal and so on (Figure 5C). Later, we analyzed the cirRNA-miRNA-mRNA network involved in the HIF-1 pathway, found that the correlation between each dysregulated circRNA-miRNAs-mRNA, circRNA_06551, circRNA_14668, circRNA_04497, circRNA_08683, circRNA_09923(Green, down-regulation) and circRNA_23636, circRNA_15734(Red, up-regulation) (Figure 5D).