Transcriptome profiling of cervical cancer cells acquired resistance to cisplatin by deep sequencing

Figures & data

Table 1. Primer sequences used for qRT-PCR.

Target	Primer sequences (5′ to 3′)	Product size (bp)
SIPA1L1	Forward 5′-AAAACCATCGCCCCTTGAGT-3′	84
	Reverse 5′-TGCTGCTGTAAGGCTTCATCT-3′
FLNC	Forward5’-CATCTACTACACAGCGCCCGA-3′	109
	Reverse5′-CGGCAGGGGGTCACACG-3′
CD70	Forward5′-ACACTCTGCACCAACCTCAC-3′	106
	Reverse5-CCCTAATCAGCAGCAGTGGT-3′
LAMA4	Forward5′-ACGCCAGGATAGCCAAGAAC-3′	126
	Reverse5-GGTCCCAGACGCACTTATCA-3′
PDGFC	Forward5′-GAGCCGCATCTATTGGCAGC-3′	106
	Reverse5-GACAGGACAGAGGCGAAAAC-3′
CREB3L1	Forward 5′-TTGTGCTTTGTTCTGGTGCTG-3′	155
	Reverse 5-GCCCCGTCATCGTAGAATAGG-3′
COL4A6	Forward 5′-ATCCTCGAATCAAGGCGACA-3′	134
	Reverse 5-GGCCAGAAGAGCCTTTCAGT-3′
IL1A	Forward 5′-TTCTGGGAAACTCACGGCAC-3′	161
	Reverse 5-GTGAGACTCCAGACCTACGC-3′
WNT10B	Forward 5′-CTCGGTGAGAGCAAAGCCAG-3′	134
	Reverse 5-CCACTCCTCTTCACCGCTTC-3′
INHBB	Forward 5′-TGACAGGTGGAACATGGTGG-3′	126
	Reverse 5-TGCACGTCTAGGTTGAGTCG-3′
CACNA1H	Forward 5′-AGCGCCGGCCCTACT-3′	127
	Reverse 5-TCCATGGACATGGTGATGACG-3′
AKT3	Forward 5′-ACTCTGACAGCTCCCAAACG-3′	137
	Reverse 5-ACACTTCCAGCGTCAAGAGG-3′
HSP90B1	Forward 5′-TTCCGCCTTCCTTGTAGCAG-3′	71
	Reverse 5-CCCAGATGTGCTGGGTATCG-3′
CREB5	Forward 5′-TTCGTCCCTGTTTCTGGAGG-3′	140
	Reverse 5-TGGGGTCGGAGTTTGATCTG-3′
CAPDH	Forward 5′-ATGGGGAAGGTGAAGGTCGG-3′	180
	Reverse 5-GACGGTGCCATGGAATTTGC-3′

Table 2. Sequences of AKT3-siRNAs.

Target	Sequences
AKT3-siRNA1	Sense5′-GGAUGCCUCUACAACCCAUTT-3′ antisense5′-AUGGGUUGUAGAGGCAUCCTT-3′
AKT3-siRNA12	Sense5′-GCACACACUCUAACUGAAATT-3′ antisense 5′-UUUCAGUUAGAGUGUGUGCTT-3′
AKT3-siRNA13	Sense5′-GCUUUCAGGGCUCUUGAUATT-3′ antisense 5′-UAUCAAGAGCCCUGAAAGCTT-3′
The negative random siRNA	Sense5′-UUCUCCGAACGUGUCACGUTT-3′ antisense 5-ACGUGACACGUUCGGAGAATT-3′
The negative control FAM	Sense5′-UUCUCCGAACGUGUCACGUTT′ antisense 5′-ACGUGACACGUUCGGAGAATT-3′
The GAPDH positive control	sense5′-UGACCUCAACUACAUGGUUTT′ antisense 5′-AACCAUGUAGUUGAGGUCATT-3′

Figure 1. The inhibition rates of continuously variable concentrations of cisplatin on Hela and Hela/DDP. CCK-8 Assay was performed to do cytotoxicity test. Cell viability analyzed by measuring absorbance at 450 nm using a microplate reader. Data represent the mean ± SD of three individual experiments.

Figure 2. Volcano graphs of all DEG enrichment. Each point in the volcano diagram represents one differentially expressed gene, and the x-axis represents the log 2 (fold change) and the y-axis shows the –log 10 (1 − P). The greater the absolute value of the horizontal coordinate, the greater the difference between the two samples. The larger the ordinate value, the differential expression is more significant, and the differentially expressed gene is more reliable. In the green dots, the differentially expressed gene is down-regulated, and the red dots represent the differentially expressed genes. The black dots represent the non-differentially expressed genes.

Table 3. Summary of sequencing data.

Sample	Clean reads	Clean bases (bp)	GC content	% ≥Q30
Hela	23,859,099	7,004,676,698	52.22%	85.07%
Hela/DDP	25,795,601	7,536,948,834	52.52%	85.11%

Clean reads were paired-end reads of clean data.

Table 4. Summary of comparative analysis.

Sample	Hela	Hela/DDP
Total reads	47,718,198	51,591,202
Mapped reads	34,186,718 (71.64%)	36,824,747 (71.38%)
Unique mapped reads	31,557,244 (66.13%)	33,319,979 (64.58%)
Multiple map reads	2,629,474 (5.51%)	3,504,768 (6.79%)
Reads map to '+'	16,955,012 (35.53%)	18,241,684 (35.36%)
Reads map to '-'	17,038,216 (35.71%)	18,339,453 (35.55%)

Figure 3. Functional classification of gene ontology (GO) database on DEGs. The x-axis is the GO classification, the left of the y-axis is the percentage of the number of genes, and the right is the number of DEGs and all genes.

Figure 4. Functional classification of Cluster of Orthologous Groups of proteins (COG) database on DEGs. The x-axis shows the contents of COG, and the ordinate is the frequency of genes. Different functional classes reflect the corresponding period of genes and metabolism or physiological of environment.

Figure 5. Kyoto Encyclopaedia of Genes and Genomes (KEGG) database categorized DEGs. (A) KEGG functional annotation on DEGs. The x-axis represents the number of genes annotated to the pathway and the proportion of all genes. The y-axis shows the name of KEGG metabolic pathway. (B) Scatter plot of KEGG pathway enrichment. Each circle point represents a KEGG pathway. The ordinate is log₁₀ (Q value), Q value is the p value after multiple hypothesis tests. Thus, the bigger the enrichment factor, the more significant the enrichment level of DEGs in the pathway. (C) Pathway map of PI3K/AKT. The PI3K-AKT signalling pathway is annotated with most DEGs among all the referred pathways.

Table 5. Information of test genes from DEGs.

Gene	Regulation	log2FC(NGS)	log2FC (QPCR)
SIPA1L1	Down	−9.13739	−9.38
FLNC	Down	−8.4867	−8.15
LAMA4	Down	−8.0453	−7.99
CD70	Down	−7.9683	−8.49
PDGFC	Down	−7.4057	−9.23
CREB3L1	Down	−7.2777	−10.31
COL4A6	Down	−4.2364	−3.45
IL1A	Down	−4.0243	−5.34
WNT10B	Up	7.4032	5.17
INHBB	Up	9.0030	10.45
CACNA1H	Up	9.5110	6.15
HSP90B1	Up	2.5753	2.56
CREB5	Up	3.6541	3.94
AKT3	Up	4.2039	6.13

Figure 6. Differentially expressed genes revealed by deep sequencing validated using quantitative real-time reverse transcription PCR (qRT-PCR). Comparison of the relative expressions obtained using two platforms showed quite correspondence for most pairs. The left columns of every double bars represent the log 2 ratio fold change in each DEG with the application of next-generation sequencing (NGS) and right columns represent log 2 fold changes using qRT-PCR.

Figure 7. mRNA and protein level alteration after treating with AKT3-siRNA or inhibitor. (A) qRT-PCR was performed for AKT3. The expression level of it was normalized to the level in Hela cells. Hela/DDP cells were treated with AKT3-siRNA, Nonsense-siRNA or MK-2206, and harvested after 24 h of transfection. (B) The effect of AKT3-siRNA on the levels of AKT3 mRNA expressions in Hela/DDP cells. (C) Immunoblot depicting Akt3 and pAkt protein levels.

Figure 8. Knockdown AKT3 in Hela/DDP cells increased its sensitivity to cisplatin and apoptotic rate. (A) CCK-8 assay showed that after treating with AKT3-siRNA Hela/DDP’s sensitive to cisplatin changed slightly. (B) CCK-8 assay was performed to examine cell survival. After treating with MK-2206 for 24 h, Hela/DDP cells showed more sensitive to cisplatin. (C) Apoptotic rate of Hela/DDP cells was measured through using Annexin-V/PI staining on a flow cytometry.