Etiology-Specific Analysis of Hepatocellular Carcinoma Transcriptome Reveals Genetic Dysregulation in Pathways Implicated in Immunotherapy Efficacy
Abstract
:1. Introduction
2. Results
2.1. Identification of Dysregulated Immune-Associated Genes in Etiology-Specific HCC and Correlation with Patient Survival
2.2. Correlation of IA Gene Expressions with Clinical Variables
2.3. Correlation of IA Gene Expressions with Copy Number Variations and Mutation Events Using REVEALER
2.4. Identification of Frequently Disrupted Immune-Associated Pathways in HCC through Differential Mutational Load
2.5. Identification of Potential miRNAs Involved in Regulation of IA Genes
2.6. In Vitro Validation of IA Gene Expression in Cell Lines after Alcohol Exposure
3. Discussion
4. Materials and Methods
4.1. RNA-Sequencing Datasets and Clinical Data
4.2. mRNA Differential Expression Analyses
4.3. Association of Candidate Genes’ Expressions with Patient Survival and Clinical Variables
4.4. Information-Coefficient Based Correlation of IA Gene Expression with Genomic Alterations
4.5. Identification of Differential Mutational Load in Immune-Associated Pathways
4.6. Assessing Potential Involvement of miRNAs in Regulating IA Genes
4.7. Validation of IA Gene Expression with Quantitative PCR (qPCR)
- CCL14 forward: AATACAGCTAAAGTTGGTGGGG
- CCL14 reverse: TCAAAGCAGGGAAGCTCCAA
- CKLF forward: GGCACTAACTGTGACATCTATGA
- CKLF reverse: TCACAAGTGCAAACACAAGCA
- IQGAP2 forward: TCAAGTGTAGGAAGGAGTTGTGG
- IQGAP2 reverse: CTGGATCTGGGGTGCTATTCC
- KITLG forward: TATGTCCCCGGGATGGATGT
- KITLG reverse: TTTGGCCTTCCCTTTCTCAGG
- NDRG2 forward: GGGACAGGGATGGAAAATGGT
- NDRG2 reverse: CCACATGAACCCGCACAAAG
- SEC61G forward: TTTAGGTGTCGGTTGGGTAGG
- SEC61G reverse: CTCACACCCTCACACTTGTTC
- SOCS2 forward: AGAGCCGGAGAGTCTGGTTT
- SOCS2 reverse: ATAGCGATCCTTGGCCCTTG
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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HCC Drinkers without HBV vs. Nondrinker Normals | HCC Drinkers without HBV vs. Drinker Normals | ||||||
Gene Name | Fold Change | FDR | p-Value | Gene Name | Fold Change | FDR | p-Value |
APOB | −2.16 | 9.0 × 10−13 | 7.0 × 10−10 | APLN | 16.65 | 1.7 × 10−6 | 3.5 × 10−4 |
CAMK4 | −4.12 | 7.2 × 10−16 | 3.1 × 10−13 | CAMK4 | −5.90 | 2.6 × 10−8 | 1.5 × 10−6 |
CAPG | 3.73 | 4.0 × 10−10 | 5.5 × 10−7 | CLEC1B | −22.88 | 6.8 × 10−5 | 3.7 × 10−2 |
CBX8 | 2.73 | 1.9 × 10−15 | 9.0 × 10−13 | DNASE1L3 | −6.63 | 1.4 × 10−5 | 5.2 × 10−3 |
CCL14 | −2.93 | 2.2 × 10−7 | 5.4 × 10−4 | SOCS2 | −7.10 | 2.0 × 10−9 | 6.9 × 10−8 |
CD226 | −3.03 | 8.9 × 10−9 | 1.6 × 10−5 | UBE2S | 5.93 | 1.4 × 10−5 | 5.2 × 10−3 |
CKLF | 2.71 | 1.1 × 10−11 | 1.1 × 10−8 | VIPR1 | −12.77 | 5.2 × 10−12 | 6.3 × 10−11 |
CLEC1B | −26.29 | 7.3 × 10−12 | 6.9 × 10−9 | ||||
CYP2C9 | −3.34 | 7.8 × 10−8 | 1.7 × 10−4 | ||||
DNASE1L3 | −6.62 | 2.2 × 10−13 | 1.6 × 10−10 | ||||
IGKV4-1 | −5.33 | 1.7 × 10−6 | 4.9 × 10−3 | ||||
IMPDH1 | 2.08 | 3.6 × 10−6 | 1.2 × 10−2 | ||||
IQGAP2 | −1.97 | 1.3 × 10−9 | 1.9 × 10−6 | ||||
KITLG | 2.14 | 4.6 × 10−6 | 1.5 × 10−2 | ||||
KLRD1 | −2.54 | 7.3 × 10−7 | 2.0 × 10−3 | ||||
LPCAT1 | 3.07 | 1.2 × 10−10 | 1.4 × 10−7 | ||||
MSC | 6.00 | 2.1 × 10−10 | 2.6 × 10−7 | ||||
NDRG2 | −2.46 | 1.2 × 10−9 | 1.7 × 10−6 | ||||
PGF | 2.06 | 5.2 × 10−6 | 1.7 × 10−2 | ||||
RAB24 | 2.31 | 9.6 × 10−15 | 5.1 × 10−12 | ||||
SEC61G | 2.14 | 5.1 × 10−9 | 8.7 × 10−6 | ||||
SOCS2 | −6.45 | 5.3 × 10−19 | 1.3 × 10−16 | ||||
SPP1 | 25.97 | 8.7 × 10−22 | 1.3 × 10−19 | ||||
TAGAP | −2.49 | 9.6 × 10−6 | 3.3 × 10−2 | ||||
UBE2S | 5.14 | 2.2 × 10−21 | 3.7 × 10−19 | ||||
VIPR1 | −10.80 | 6.2 × 10−27 | 4.0 × 10−25 | ||||
HCC Drinkers with HBV vs. Drinker Normals | HCC Drinkers vs. HCC Nondrinkers | ||||||
Gene Name | Fold Change | FDR | p-Value | Gene Name | Fold Change | FDR | p-Value |
APLN | 18.60 | 2.6 × 10−6 | 5.0 × 10−4 | CCL18 | 1.72 | 1.0 × 10−2 | 2.6 × 10−2 |
CAMK4 | −3.83 | 4.4 × 10−5 | 1.7 × 10−2 | CKLF | 1.36 | 3.5 × 10−3 | 5.1 × 10−3 |
CLEC1B | −28.26 | 7.9 × 10−8 | 5.2 × 10−6 | MMP9 | 1.88 | 5.3 × 10−3 | 1.0 × 10−2 |
DNASE1L3 | −5.45 | 9.6 × 10−6 | 2.6 × 10−3 | ||||
NDRG2 | −2.97 | 3.9 × 10−7 | 4.2 × 10−5 | ||||
UBE2S | 4.85 | 1.0 × 10−4 | 4.8 × 10−2 | ||||
VIPR1 | −8.65 | 2.1 × 10−7 | 1.9 × 10−5 | ||||
HCC Drinkers with HBV vs. Nondrinker Normals | HCC Nondrinkers with HBV vs. Nondrinker Normals | ||||||
Gene Name | Fold Change | FDR | p-Value | Gene Name | Fold Change | FDR | p-Value |
CAMK4 | −2.71 | 5.7 × 10−9 | 8.0 × 10−6 | APLN | 13.78 | 1.2 × 10−33 | 1.6 × 10−31 |
CAPG | 3.47 | 3.1 × 10−9 | 4.2 × 10−6 | CAMK4 | −2.89 | 9.0 × 10−13 | 1.3 × 10−9 |
CBX8 | 2.23 | 3.6 × 10−12 | 2.5 × 10−9 | CAPG | 3.30 | 1.1 × 10−9 | 2.7 × 10−6 |
CCL14 | −3.01 | 2.8 × 10−9 | 3.7 × 10−6 | CBX8 | 2.14 | 7.7 × 10−14 | 9.9 × 10−11 |
CD226 | −2.39 | 1.0 × 10−6 | 2.4 × 10−3 | CCL14 | −3.76 | 4.7 × 10−20 | 2.7 × 10−17 |
CKLF | 3.26 | 6.9 × 10−14 | 3.3 × 10−11 | CD226 | −2.82 | 1.1 × 10−11 | 1.9 × 10−8 |
CLEC1B | −32.63 | 7.6 × 10−20 | 1.1 × 10−17 | CLEC1B | −76.69 | 7.5 × 10−45 | 3.9 × 10−43 |
CYP2C9 | −3.38 | 2.7 × 10−7 | 5.7 × 10−4 | CTHRC1 | 13.81 | 3.5 × 10−19 | 2.2 × 10−16 |
DNASE1L3 | −5.40 | 4.4 × 10−14 | 2.0 × 10−11 | CYP2C9 | −3.88 | 3.3 × 10−12 | 5.3 × 10−9 |
DUSP10 | −2.15 | 7.5 × 10−8 | 1.4 × 10−4 | DNASE1L3 | −7.82 | 1.7 × 10−37 | 1.6 × 10−35 |
KITLG | 2.97 | 1.2 × 10−11 | 9.7 × 10−9 | DUSP10 | −2.35 | 5.0 × 10−14 | 6.2 × 10−11 |
KLRD1 | −2.73 | 1.0 × 10−9 | 1.2 × 10−6 | FYN | −2.03 | 1.5 × 10−12 | 2.3 × 10−9 |
LPCAT1 | 2.76 | 2.1 × 10−9 | 2.6 × 10−6 | KITLG | 2.39 | 7.4 × 10−8 | 2.3 × 10−4 |
MSC | 7.90 | 2.4 × 10−11 | 2.1 × 10−8 | KLRD1 | −2.82 | 1.3 × 10−11 | 2.2 × 10−8 |
NDRG2 | −2.79 | 4.8 × 10−19 | 8.3 × 10−17 | LPCAT1 | 2.16 | 7.6 × 10−8 | 2.4 × 10−4 |
RAB24 | 2.26 | 5.0 × 10−14 | 2.3 × 10−11 | MSC | 6.65 | 8.2 × 10−9 | 2.2 × 10−5 |
SOCS2 | −3.70 | 1.6 × 10−9 | 2.0 × 10−6 | MT-RNR2 | −2.21 | 1.5 × 10−11 | 2.7 × 10−8 |
SPP1 | 15.71 | 6.9 × 10−15 | 2.7 × 10−12 | NDRG2 | −2.81 | 7.8 × 10−23 | 3.2 × 10−20 |
UBE2S | 4.06 | 2.2 × 10−17 | 5.5 × 10−15 | PGF | 3.09 | 5.0 × 10−8 | 1.5 × 10−4 |
VIPR1 | −7.31 | 1.2 × 10−16 | 3.5 × 10−14 | RAB24 | 2.19 | 1.3 × 10−17 | 1.0 × 10−14 |
SOCS2 | −3.93 | 3.9 × 10−16 | 3.7 × 10−13 | ||||
TNFRSF4 | 5.61 | 9.0 × 10−27 | 2.3 × 10−24 | ||||
UBE2S | 3.67 | 6.8 × 10−20 | 4.0 × 10−17 | ||||
VIPR1 | −13.83 | 9.5 × 10−55 | 1.3 × 10−53 |
Comparison: HCC Drinkers vs. HCC Nondrinkers | ||
---|---|---|
Pathway Name | Odds Ratio | p-Value |
B-cell receptor pathway | 2.735 | 0.004 |
T-cell receptor pathway | 1.901 | 0.029 |
Classical complement system activation pathway | 2.184 | 0.047 |
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Li, W.T.; Zou, A.E.; Honda, C.O.; Zheng, H.; Wang, X.Q.; Kisseleva, T.; Chang, E.Y.; Ongkeko, W.M. Etiology-Specific Analysis of Hepatocellular Carcinoma Transcriptome Reveals Genetic Dysregulation in Pathways Implicated in Immunotherapy Efficacy. Cancers 2019, 11, 1273. https://doi.org/10.3390/cancers11091273
Li WT, Zou AE, Honda CO, Zheng H, Wang XQ, Kisseleva T, Chang EY, Ongkeko WM. Etiology-Specific Analysis of Hepatocellular Carcinoma Transcriptome Reveals Genetic Dysregulation in Pathways Implicated in Immunotherapy Efficacy. Cancers. 2019; 11(9):1273. https://doi.org/10.3390/cancers11091273
Chicago/Turabian StyleLi, Wei Tse, Angela E. Zou, Christine O. Honda, Hao Zheng, Xiao Qi Wang, Tatiana Kisseleva, Eric Y. Chang, and Weg M. Ongkeko. 2019. "Etiology-Specific Analysis of Hepatocellular Carcinoma Transcriptome Reveals Genetic Dysregulation in Pathways Implicated in Immunotherapy Efficacy" Cancers 11, no. 9: 1273. https://doi.org/10.3390/cancers11091273