Collagen type VII α1 chain: A promising prognostic and immune infiltration biomarker of pancreatic cancer

Ding,Cheng; Yu,Zhangping; Li,Xianliang; Zhu,Jiqiao; Dai,Menghua; He,Qiang

doi:10.3892/ol.2023.13663

Collagen type VII α1 chain: A promising prognostic and immune infiltration biomarker of pancreatic cancer

Authors:
- Cheng Ding
- Zhangping Yu
- Xianliang Li
- Jiqiao Zhu
- Menghua Dai
- Qiang He
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Affiliations: Department of Hepatobiliary Surgery, Beijing Chao‑Yang Hospital Affiliated to Capital Medical University, Beijing 100020, P.R. China, Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, P.R. China
Published online on: January 5, 2023 https://doi.org/10.3892/ol.2023.13663
Article Number: 77
Copyright: © Ding et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Pancreatic cancer (PC) is a stubborn malignancy with high lethality and a low 5‑year overall survival (OS) rate. Collagen type VII α1 chain (COL7A1), a major component of the extracellular matrix, serves important roles in numerous physiological processes and various illnesses. COL7A1 protein acts as an anchoring fibril between the external epithelial cells and the underlying stroma, and mutation of COL7A1 could cause recessive dystrophic epidermolysis bullosa. Raw data for PC were acquired from The Cancer Genome Atlas and the Gene Expression Omnibus database, and raw data for the normal pancreas were obtained from the Genotype‑Tissue Expression database. COL7A1 mRNA expression in PC tissues was compared with that in either paired (GSE15471 dataset) or unpaired (all other data) normal pancreas tissues. The association between COL7A1 mRNA expression and clinicopathological factors was assessed using logistic regression analysis. Cox analysis and Kaplan‑Meier analysis were used to evaluate the role of COL7A1 mRNA expression in prognosis and nomograms were constructed. Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, Gene Set Enrichment Analysis (GSEA) and single‑sample GSEA (ssGSEA) were performed to evaluate the relevant functions of COL7A1 and correlation with immune cell infiltration. Furthermore, reverse transcription‑quantitative PCR was used to assess the mRNA expression levels of COL7A1 in PC. The present study demonstrated that COL7A1 mRNA expression was higher in PC tissues compared with in normal pancreas tissues. The Kaplan‑Meier survival analysis indicated that patients with PC with high COL7A1 mRNA expression had shorter overall survival (OS), disease‑specific survival (DSS) and progression‑free interval (PFI) times compared with patients with PC with low COL7A1 mRNA expression. Multivariate analysis demonstrated that COL7A1 mRNA expression was an independent risk factor for OS, DSS and PFI. Nomogram and calibration plots were constructed to predict the prognosis of patients with PC. GSEA demonstrated that high mRNA expression levels of COL7A1 were associated with multiple cancer‑related pathways. ssGSEA analysis indicated that COL7A1 expression was positively associated with natural killer CD56bright cells and T helper (Th)2 cells, and negatively associated with Th17 cells and eosinophils. The results of the present study suggested that COL7A1 could be an independent biomarker and an influential moderator of immune infiltration in PC.

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1	Siegel RL, Miller KD, Fuchs HE and Jemal A: Cancer statistics, 2021. CA Cancer J Clin. 71:7–33. 2021. View Article : Google Scholar : PubMed/NCBI
2	Huang J, Lok V, Ngai CH, Zhang L, Yuan J, Lao XQ, Ng K, Chong C, Zheng ZJ and Wong MCS: Worldwide burden of, risk factors for, and trends in pancreatic cancer. Gastroenterology. 160:744–754. 2021. View Article : Google Scholar : PubMed/NCBI
3	Khalaf N, El-Serag HB, Abrams HR and Thrift AP: Burden of pancreatic cancer: From epidemiology to practice. Clin Gastroenterol Hepatol. 19:876–884. 2021. View Article : Google Scholar : PubMed/NCBI
4	Anderson NM and Simon MC: The tumor microenvironment. Curr Biol. 30:R921–R925. 2020. View Article : Google Scholar : PubMed/NCBI
5	Mao X, Xu J, Wang W, Liang C, Hua J, Liu J, Zhang B, Meng Q, Yu X and Shi S: Crosstalk between cancer-associated fibroblasts and immune cells in the tumor microenvironment: New findings and future perspectives. Mol Cancer. 20:1312021. View Article : Google Scholar : PubMed/NCBI
6	Ziani L, Chouaib S and Thiery J: Alteration of the antitumor immune response by cancer-associated fibroblasts. Front Immunol. 9:4142018. View Article : Google Scholar : PubMed/NCBI
7	Beer TW, Ng LB and Murray K: Mast cells have prognostic value in Merkel cell carcinoma. Am J Dermatopathol. 30:27–30. 2008. View Article : Google Scholar : PubMed/NCBI
8	Kolset SO and Pejler G: Serglycin: A structural and functional chameleon with wide impact on immune cells. J Immunol. 187:4927–4933. 2011. View Article : Google Scholar : PubMed/NCBI
9	Weniger M, Honselmann KC and Liss AS: The extracellular matrix and pancreatic cancer: A complex relationship. Cancers (Basel). 10:3162018. View Article : Google Scholar : PubMed/NCBI
10	Leinwand J and Miller G: Regulation and modulation of antitumor immunity in pancreatic cancer. Nat Immunol. 21:1152–1159. 2020. View Article : Google Scholar : PubMed/NCBI
11	Mizrahi JD, Surana R, Valle JW and Shroff RT: Pancreatic cancer. Lancet. 395:2008–2020. 2020. View Article : Google Scholar : PubMed/NCBI
12	Gelse K, Pöschl E and Aigner T: Collagens-structure, function, and biosynthesis. Adv Drug Deliv Rev. 55:1531–1546. 2003. View Article : Google Scholar : PubMed/NCBI
13	Klingberg S, Mortimore R, Parkes J, Chick JE, Clague AE, Murrell D, Weedon D and Glass IA: Prenatal diagnosis of dominant dystrophic epidermolysis bullosa, by COL7A1 molecular analysis. Prenat Diagn. 20:618–622. 2000. View Article : Google Scholar : PubMed/NCBI
14	Martins VL, Vyas JJ, Chen M, Purdie K, Mein CA, South AP, Storey A, McGrath JA and O'Toole EA: Increased invasive behaviour in cutaneous squamous cell carcinoma with loss of basement-membrane type VII collagen. J Cell Sci. 122:1788–1799. 2009. View Article : Google Scholar : PubMed/NCBI
15	Kita Y, Mimori K, Tanaka F, Matsumoto T, Haraguchi N, Ishikawa K, Matsuzaki S, Fukuyoshi Y, Inoue H, Natsugoe S, et al: Clinical significance of LAMB3 and COL7A1 mRNA in esophageal squamous cell carcinoma. Eur J Surg Oncol. 35:52–58. 2009. View Article : Google Scholar : PubMed/NCBI
16	Baba Y, Iyama K, Honda S, Ishikawa S, Miyanari N and Baba H: Cytoplasmic expression of type VII collagen is related to prognosis in patients with esophageal squamous cell carcinoma. Oncology. 71:221–228. 2006. View Article : Google Scholar : PubMed/NCBI
17	Oh SE, Oh MY, An JY, Lee JH, Sohn TS, Bae JM, Choi MG and Kim KM: Prognostic value of highly expressed type VII collagen (COL7A1) in patients with gastric cancer. Pathol Oncol Res. 27:16098602021. View Article : Google Scholar : PubMed/NCBI
18	Wickham H: (2016) ggplot2: Elegant graphics for data analysis. Springer-Verlag; New York: ISBN 978-3-319-24277-4.
19	Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC and Müller M: pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 12:772011. View Article : Google Scholar : PubMed/NCBI
20	Love MI, Huber W and Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15:5502014. View Article : Google Scholar : PubMed/NCBI
21	Yu G, Wang LG, Han Y and He QY: clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS. 16:284–287. 2012. View Article : Google Scholar : PubMed/NCBI
22	Hänzelmann S, Castelo R and Guinney J: GSVA: Gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 14:72013. View Article : Google Scholar : PubMed/NCBI
23	Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, Angell H, Fredriksen T, Lafontaine L, Berger A, et al: Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 39:782–795. 2013. View Article : Google Scholar : PubMed/NCBI
24	Nagy Á, Munkácsy G and Győrffy B: Pancancer survival analysis of cancer hallmark genes. Sci Rep. 11:60472021. View Article : Google Scholar : PubMed/NCBI
25	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI
26	Walker C, Mojares E and Del Río Hernández A: Role of extracellular matrix in development and cancer progression. Int J Mol Sci. 19:30282018. View Article : Google Scholar : PubMed/NCBI
27	Gatseva A, Sin YY, Brezzo G and Van Agtmael T: Basement membrane collagens and disease mechanisms. Essays Biochem. 63:297–312. 2019. View Article : Google Scholar : PubMed/NCBI
28	Martins VL, Caley MP, Moore K, Szentpetery Z, Marsh ST, Murrell DF, Kim MH, Avari M, McGrath JA, Cerio R, et al: Suppression of TGFβ and angiogenesis by type VII collagen in cutaneous SCC. J Natl Cancer Inst. 108:djv2932015. View Article : Google Scholar : PubMed/NCBI
29	Pedersen SF, Flinck M and Pardo LA: The interplay between dysregulated ion transport and mitochondrial architecture as a dangerous liaison in cancer. Int J Mol Sci. 22:52092021. View Article : Google Scholar : PubMed/NCBI
30	Marchi S, Giorgi C, Galluzzi L and Pinton P: Ca2+ fluxes and cancer. Mol Cell. 78:1055–1069. 2020. View Article : Google Scholar : PubMed/NCBI
31	Han Y, Liu C, Zhang D, Men H, Huo L, Geng Q, Wang S, Gao Y, Zhang W, Zhang Y and Jia Z: Mechanosensitive ion channel Piezo1 promotes prostate cancer development through the activation of the Akt/mTOR pathway and acceleration of cell cycle. Int J Oncol. 55:629–644. 2019.PubMed/NCBI
32	Oshi M, Newman S, Tokumaru Y, Yan L, Matsuyama R, Endo I, Katz MHG and Takabe K: High G2M pathway score pancreatic cancer is associated with worse survival, particularly after margin-positive (R1 or R2) resection. Cancers (Basel). 12:28712020. View Article : Google Scholar : PubMed/NCBI
33	Krebs AM, Mitschke J, Losada ML, Schmalhofer O, Boerries M, Busch H, Boettcher M, Mougiakakos D, Reichardt W, Bronsert P, et al: The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat Cell Biol. 19:518–529. 2017. View Article : Google Scholar : PubMed/NCBI
34	Zhou P, Li B, Liu F, Zhang M, Wang Q, Liu Y, Yao Y and Li D: The epithelial to mesenchymal transition (EMT) and cancer stem cells: Implication for treatment resistance in pancreatic cancer. Mol Cancer. 16:522017. View Article : Google Scholar : PubMed/NCBI
35	Fang Y, Saiyin H, Zhao X, Wu Y, Han X and Lou W: IL-8-positive tumor-infiltrating inflammatory cells are a novel prognostic marker in pancreatic ductal adenocarcinoma patients. Pancreas. 45:671–678. 2016. View Article : Google Scholar : PubMed/NCBI
36	Zhang Y, Velez-Delgado A, Mathew E, Li D, Mendez FM, Flannagan K, Rhim AD, Simeone DM, Beatty GL and di Magliano MP: Myeloid cells are required for PD-1/PD-L1 checkpoint activation and the establishment of an immunosuppressive environment in pancreatic cancer. Gut. 66:124–136. 2017. View Article : Google Scholar : PubMed/NCBI
37	Protti MP and De Monte L: Immune infiltrates as predictive markers of survival in pancreatic cancer patients. Front Physiol. 4:2102013. View Article : Google Scholar : PubMed/NCBI
38	Yang MW, Tao LY, Jiang YS, Yang JY, Huo YM, Liu DJ, Li J, Fu XL, He R, Lin C, et al: Perineural invasion reprograms the immune microenvironment through cholinergic signaling in pancreatic ductal adenocarcinoma. Cancer Res. 80:1991–2003. 2020. View Article : Google Scholar : PubMed/NCBI
39	Marcon F, Zuo J, Pearce H, Nicol S, Margielewska-Davies S, Farhat M, Mahon B, Middleton G, Brown R, Roberts KJ and Moss P: NK cells in pancreatic cancer demonstrate impaired cytotoxicity and a regulatory IL-10 phenotype. Oncoimmunology. 9:18454242020. View Article : Google Scholar : PubMed/NCBI