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Research Article Identification of ATP8B1 As a Tumor Suppressor Gene for Colorectal Cancer and Its Involvement in Phospholipid Homeostasis

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Research Article Identification of ATP8B1 As a Tumor Suppressor Gene for Colorectal Cancer and Its Involvement in Phospholipid Homeostasis Hindawi BioMed Research International Volume 2020, Article ID 2015648, 16 pages https://doi.org/10.1155/2020/2015648 Research Article Identification of ATP8B1 as a Tumor Suppressor Gene for Colorectal Cancer and Its Involvement in Phospholipid Homeostasis Li Deng,1,2 Geng-Ming Niu,1 Jun Ren,1 and Chong-Wei Ke 1 1Department of General Surgery, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai, China 2Department of General Surgery, The Shanghai Public Health Clinical Center, Fudan University, Shanghai, China Correspondence should be addressed to Chong-Wei Ke; [email protected] Received 5 May 2020; Revised 16 July 2020; Accepted 17 August 2020; Published 29 September 2020 Academic Editor: Luis Loura Copyright © 2020 Li Deng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Homeostasis of membrane phospholipids plays an important role in cell oncogenesis and cancer progression. The flippase ATPase class I type 8b member 1 (ATP8B1), one of the P4-ATPases, translocates specific phospholipids from the exoplasmic to the cytoplasmic leaflet of membranes. ATP8B1 is critical for maintaining the epithelium membrane stability and polarity. However, the prognostic values of ATP8B1 in colorectal cancer (CRC) patients remain unclear. We analyzed transcriptomics, genomics, and clinical data of CRC samples from The Cancer Genome Atlas (TCGA). ATP8B1 was the only potential biomarker of phospholipid transporters in CRC. Its prognostic value was also validated with the data from the Gene Expression Omnibus (GEO). Compared to the normal group, the expression of ATP8B1 was downregulated in the tumor group and the CRC cell lines, which declined with disease progression. The lower expression level of ATP8B1 was also significantly associated with worse survival outcomes in both the discovery samples (359 patients) and the validation samples (566 patients). In multivariate analyses, low ATP8B1 levels predicted unfavorable OS (adjusted HR 1.512, 95% CI: 1.069-2.137; P =0:019) and were associated with poor progress-free interval (PFI) (adjusted HR: 1.62, 95% CI: 1.207-2.174; P =0:001). The pathway analysis results showed that the underexpression of ATP8B1 was negatively associated with phospholipid transport, phospholipid metabolic process, and cell-cell adherent junction and positively associated with the epithelial-mesenchymal transition in CRC. Our analysis suggests that ATP8B1 is a potential cancer suppressor in CRC patients and may offer new strategies for CRC therapy. 1. Introduction porter families, including P4-ATPases (flippases), ATP- binding cassette (ABC) transporters (floppases), and scram- Colorectal cancer (CRC) is the third most common cancer blases [5]. Decreased expression of flippases causes abnormal and the fourth leading cause of cancer-related deaths globally membrane phospholipid distribution, thereby enhancing [1]. Early detection and improved treatment strategies tumor progression and metastasis [6]. The subsets of ABC decrease the total CRC mortality [2]. However, the five-year transporters (ABCB1, ABCC1, and ABCG2) have widely relative survival rate of patients with metastatic disease is been reported as multidrug efflux pumps conferring tumor estimated at between 10% and 14% [2]. Alteration of the resistance to chemotherapy [7]. The deficiency of either somatic copy number, CpG island hypermethylation, and ABCB4 or ATP11C (a member of P4-ATPases) is associated microsatellite instability are the major relative mechanisms with liver oncogenesis [8, 9]. Upregulated PLSCR1 expres- associated with poor prognosis in CRC patients [3]. There- sion (a member of scramblases) can inhibit tumor growth fore, biomarkers are vital for the diagnosis, prognostication, and proliferation [10]. The genetic alteration of ATP8B1 and development of anticancer drugs for CRC patients [4]. has also been detected in CRC and hepatocellular carcinoma Membrane phospholipid homeostasis plays a vital role in [11, 12]. However, the prognostic role of membrane phos- several biological processes. This depends on three trans- pholipid transporters in CRC has not been elucidated. This 2 BioMed Research International study explored the expression of all the 31 genes coding for Table 1: Patient demographics. phospholipid transporters and evaluated the associations with Discovery dataset Validation dataset prognosis in CRC using the data from The Cancer Genome n n Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. (TCGA CRC, = 359) (GSE39582, = 566) Our analysis indicates that ATP8B1 may be a novel oncogene Gender suppressor in CRC patients. The correlation of ATP8B1 with Male 194 (54%) 310 (55%) the normal function of membrane phospholipids and proteins Female 165 (46%) 256 (45%) coupled with its underexpression could be a valuable indicator Age (years) of unfavorable clinical outcomes of CRC patients. Median 66 (55-74.5) 68.1 (59-76) (IQR) 2. Methods >65 vs. ≤65 184 vs. 175 342 vs. 124 Stage 2.1. Data Acquisition. The TCGA pan-cancer data for Toil ∗ RNA sequencing Recompute was downloaded from the I5637 UCSC Xena browser [13] (https://xenabrowser.net/ II 134 264 datapages/). Gene expression was normalized to eliminate III 116 205 ff computational batch e ects [13]. All gene expressions were IV 53 60 transformed using a log2 TPM scale. Approximately 382 KRAS status colorectal tumors and 51 normal colorectal samples were obtained from the TCGA pan-cancer data to identify the Wild type 217 (60%) 328 (58%) DEGs for phospholipid transporters, including 32 matched Mutant 142 (40%) 217 (39%) tumors and normal samples. High-quality survival data was N/A — 21 (3%) also downloaded from the UCSC Xena browser [14]. After BRAF status excluding data with incomplete follow-up information, 359 Wild type 307 (86%) 461 (82%) of 382 CRC patients were selected for further analysis. The Mutant 52 (14%) 51 (9%) microarray dataset (GSE39582) with clinical features was N/A — 54 (9%) obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) to validate the retrieved information. GSE39582 was measured TP53 status using the Affymetrix Human Genome U133 Plus 2.0 Array. Wild type 140 (39%) 161 (28%) All the raw data for mRNA expression were normalized using Mutant 219 (61%) 190 (34%) the Limma R package and transformed into a log2 scale. The N/A — 215 (38%) probe showing the highest expression level was selected for OS scenarios where two or more probes were annotated to one Median 22.4 (months) 51 (months) gene symbol. The tidy RNASeq and protein spectra data were Range 0-150 (months) 0-201 (months) obtained from Wang et al. [15]. They were used to identify dif- ferent ATP8B1 expressions in 44 CRC cell lines by comparing 77/282 191/371 Event/nonevent the TCGA colorectal tumor and normal tissue samples. Infor- ∗∗ mative data on gene mutations for KRAS, BRAF, and TP53 PFI or RFS and microsatellite instability in TCGA were obtained from Median 19.6 (months) 43 (months) the Genomic Data Commons (GDC) through the TCGAbio- Range 0-150 (months) 0-201 (months) links R package [16]. The GSE39582 data also contained this 100/259 177/380 information. Subtypes of Consensus Molecular Subtypes Event/nonevent (CMS) were obtained by calculating transcriptome data from ∗Stage I group included four stage 0 cases in the GSE38582 dataset. ∗∗PFI the CMScaller R package [17]. (progress-free interval) was provided in the TCGA CRC cohort, while RFS (relapse-free survival) was obtained in GSE38582. 2.2. Identifying the Differentially Expressed Genes for Phospholipid Transporters. All the transporter genes for P4- gene rank. The relationship between ATP8B1 expression and ATPases, ABC transporters, and scramblases were obtained genomic details in CRC was displayed through the cBioportal from previous reports [5, 18]. The differentially expressed (http://www.cbioportal.org/) [20]. Besides, the differences in genes (DEGs) were identified using the Wilcoxon signed- ATP8B1 DNA methylation on MEXPRESS (https://mexpress rank test and false discovery rate (FDR). The cutoff values .be/index.html) were determined between colorectal tumors were determined based on the FDR < 0:05 and ∣log2 fold and normal tissues [21]. The results for cBioportal and change ðFCÞ ∣ >1. MEXPRESS were calculated from the TCGA CRC data. 2.3. Online Database. The Oncomine database (https://www 2.4. Gene Set Enrichment Analysis and Gene Ontology .oncomine.org/resource/login.html) was used to explore the Analysis of ATP8B1-Related Genes in CRC. Gene set enrich- ATP8B1expression level in previous studies [19]. The following ment analysis (GSEA) of TCGA colorectal data was per- parameters were used: “cancer vs. normal analysis,”“gene sum- formed using the clusterProfiler R package [22]. The Kyoto mary view,” P value of 0.01, fold change of 1.5, and top 10% Encyclopedia of Genes and Genomes (KEGG) and the Broad BioMed Research International 3 ABCB11 40 30 ABCG2 ATP11A PLSCR4 ATP8B1 20 ABCC1 -Log10 (FDR) ABCB1 10 ATP8A2 ABCG5 ATP8B3 0 –6 –4 –2 0 2 Log2 (fold change) Signifcant Down NA Up (a) Gene HR (95%CI) P value ATP8B1 0.668 (0.505−0.885) 0.005 ABCB11 1.8 (0.988−3.282) 0.055 ATP8B3 1.433 (0.913−2.251) 0.118 ABCC1 0.81 (0.59−1.111) 0.191 ATP8A2 2.251 (0.644−7.868) 0.204 ABCG2 1.084 (0.821−1.431) 0.569 ABCB1 1.031 (0.901−1.18) 0.66 ABCG5 0.929 (0.586−1.475) 0.756 ATP11A 0.967 (0.762−1.227) 0.785 PLSCR4 0.997 (0.754−1.318) 0.981 0.25 0.5 1 1.5 2 2.5 OS index (b) Figure 1: Continued. 4 BioMed Research International Disease summary for ATP8B1 Cancer Outlier vs. Analysis type by cancer normal Bladder cancer 1 Brain and CNS cancer 1 8 3 Breast cancer 5 11 Cervical cancer 1 11 Colorectal cancer 15 2 8 Esophageal cancer 1 2 3 Gastric cancer 5 Head and neck cancer 1 13 Kidney cancer 1 3 Leukemia 2 8 Liver cancer 1 Lung cancer 1 6 8 Lymphoma 1 5 1 Melanoma 1 3 4 Myeloma 33 Other cancer 4 1 7 Ovarian cancer 1 1 Pancreatic cancer 5 Prostate cancer 1 6 Sarcoma 1 2 Signifcant unique analyses 14 19 37 75 Total unique analyses 324 644 115510 10 % Cell color is determined by the best gene rank percentile for the analyses within the cell.
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