Li Liang1, Mengling Liu1, Xun Sun1, Yitao Yuan1, Ke Peng1, Khalid Rashid1, Yiyi Yu1, Yuehong Cui1, Yanjie Chen2,3, Tianshu Liu4,5. 1. Department of Medical Oncology, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, 200032, People's Republic of China. 2. Department of Gastroenterology, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, 200032, People's Republic of China. chen.yanjie@zs-hospital.sh.cn. 3. Shanghai Institute of Liver Diseases, Shanghai, China. chen.yanjie@zs-hospital.sh.cn. 4. Department of Medical Oncology, Zhongshan Hospital, Fudan University, No. 180, Fenglin Road, Xuhui District, Shanghai, 200032, People's Republic of China. liu.tianshu@zs-hospital.sh.cn. 5. Center of Evidence-based Medicine, Fudan University, Shanghai, China. liu.tianshu@zs-hospital.sh.cn.
Abstract
BACKGROUND: The anti-epidermal growth factor receptor (EGFR) antibody introduces adaptable variations to the transcriptome and triggers tumor immune infiltration, resulting in colorectal cancer (CRC) treatment resistance. We intended to identify genes that play essential roles in cetuximab resistance and tumor immune cell infiltration. METHODS: A cetuximab-resistant CACO2 cellular model was established, and its transcriptome variations were detected by microarray. Meanwhile, public data from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database were downloaded. Integrated bioinformatics analysis was applied to detect differentially expressed genes (DEGs) between the cetuximab-resistant and the cetuximab-sensitive groups. Then, we investigated correlations between DEGs and immune cell infiltration. The DEGs from bioinformatics analysis were further validated in vitro and in clinical samples. RESULTS: We identified 732 upregulated and 1259 downregulated DEGs in the induced cellular model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, along with Gene Set Enrichment Analysis and Gene Set Variation Analysis, indicated the functions of the DEGs. Together with GSE59857 and GSE5841, 12 common DEGs (SATB-2, AKR1B10, ADH1A, ADH1C, MYB, ATP10B, CDX-2, FAR2, EPHB2, SLC26A3, ORP-1, VAV3) were identified and their predictive values of cetuximab treatment were validated in GSE56386. In online Genomics of Drug Sensitivity in Cancer (GDSC) database, nine of twelve DEGs were recognized in the protein-protein (PPI) network. Based on the transcriptome profiles of CRC samples in TCGA and using Tumor Immune Estimation Resource Version 2.0, we bioinformatically determined that SATB-2, ORP-1, MYB, and CDX-2 expressions were associated with intensive infiltration of B cell, CD4+ T cell, CD8+ T cell and macrophage, which was then validated the correlation in clinical samples by immunohistochemistry. We found that SATB-2, ORP-1, MYB, and CDX-2 were downregulated in vitro with cetuximab treatment. Clinically, patients with advanced CRC and high ORP-1 expression exhibited a longer progression-free survival time when they were treated with anti-EGFR therapy than those with low ORP-1 expression. CONCLUSIONS: SATB-2, ORP-1, MYB, and CDX-2 were related to cetuximab sensitivity as well as enhanced tumor immune cell infiltration in patients with CRC.
BACKGROUND: The anti-epidermal growth factor receptor (EGFR) antibody introduces adaptable variations to the transcriptome and triggers tumor immune infiltration, resulting in colorectal cancer (CRC) treatment resistance. We intended to identify genes that play essential roles in cetuximab resistance and tumor immune cell infiltration. METHODS: A cetuximab-resistant CACO2 cellular model was established, and its transcriptome variations were detected by microarray. Meanwhile, public data from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database were downloaded. Integrated bioinformatics analysis was applied to detect differentially expressed genes (DEGs) between the cetuximab-resistant and the cetuximab-sensitive groups. Then, we investigated correlations between DEGs and immune cell infiltration. The DEGs from bioinformatics analysis were further validated in vitro and in clinical samples. RESULTS: We identified 732 upregulated and 1259 downregulated DEGs in the induced cellular model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, along with Gene Set Enrichment Analysis and Gene Set Variation Analysis, indicated the functions of the DEGs. Together with GSE59857 and GSE5841, 12 common DEGs (SATB-2, AKR1B10, ADH1A, ADH1C, MYB, ATP10B, CDX-2, FAR2, EPHB2, SLC26A3, ORP-1, VAV3) were identified and their predictive values of cetuximab treatment were validated in GSE56386. In online Genomics of Drug Sensitivity in Cancer (GDSC) database, nine of twelve DEGs were recognized in the protein-protein (PPI) network. Based on the transcriptome profiles of CRC samples in TCGA and using Tumor Immune Estimation Resource Version 2.0, we bioinformatically determined that SATB-2, ORP-1, MYB, and CDX-2 expressions were associated with intensive infiltration of B cell, CD4+ T cell, CD8+ T cell and macrophage, which was then validated the correlation in clinical samples by immunohistochemistry. We found that SATB-2, ORP-1, MYB, and CDX-2 were downregulated in vitro with cetuximab treatment. Clinically, patients with advanced CRC and high ORP-1 expression exhibited a longer progression-free survival time when they were treated with anti-EGFR therapy than those with low ORP-1 expression. CONCLUSIONS:SATB-2, ORP-1, MYB, and CDX-2 were related to cetuximab sensitivity as well as enhanced tumor immune cell infiltration in patients with CRC.
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