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HELLS Serves As a Poor Prognostic Biomarker and Its Downregulation

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Wang et al. BMC Med Genomics (2021) 14:189 https://doi.org/10.1186/s12920-021-01043-5 RESEARCH Open Access HELLS serves as a poor prognostic biomarker and its downregulation reserves the malignant phenotype in pancreatic cancer Feng‑Jiao Wang1,2†, Yan‑Hua Jing1,2†, Chien‑Shan Cheng1,2, Zhang‑Qi Cao1,2, Ju‑Ying Jiao1,2 and Zhen Chen1,2* Abstract Background: SMARCAs, belonged to SWI/SNF2 subfamilies, are critical to cellular processes due to their modulation of chromatin remodeling processes. Although SMARCAs are implicated in the tumor progression of various cancer types, our understanding of how those members afect pancreatic carcinogenesis is quite limited and improving this requires bioinformatics analysis and biology approaches. Methods: To address this issue, we investigated the transcriptional and survival data of SMARCAs in patients with pancreatic cancer using ONCOMINE, GEPIA, Human Protein Atlas, and Kaplan–Meier plotter. We further verifed the efect of signifcant biomarker on pancreatic cancer in vitro through functional experiment. Results: The Kaplan–Meier curve and log‑rank test analyses showed a positive correlation between SMARCA1/2/3/ SMARCAD1 and patients’ overall survival (OS). On the other hand, mRNA expression of SMARCA6 (also known as HELLS) showed a negative correlation with OS. Meanwhile, no signifcant correlation was found between SMARCA4/5/SMARCAL1 and tumor stages and OS. The knockdown of HELLS impaired the colony formation ability, and inhibited pancreatic cancer cell proliferation by arresting cells at S phase. Conclusions: Data mining analysis and cell function research demonstrated that HELLS played oncogenic roles in the development and progression of pancreatic cancer, and serve as a poor prognostic biomarker for pancreatic can‑ cer. Our work laid a foundation for further clinical applications of HELLS in pancreatic cancer. Keywords: SMARCA , HELLS, Pancreatic cancer, Prognostic value, Data mining analysis Introduction excessive deleterious mutations, and an overall frequency Te switch/sucrose nonfermenting complex (SWI/SNF) approaching TP53 mutations [2]. Recent studies inves- is an ATPase-dependent multisubunit complex modulat- tigated the crucial implication of the SWI/SNF protein ing gene expression involved in chromatin remodeling complex in the initiation and dediferentiation of various and transcriptional regulation [1]. Te whole-exome of neoplasms, which might attribute to its regulation of sequencing data, including 18 neoplastic entities diferentiation and cell proliferation through their enrich- from 24 published studies, showed widespread SWI/ ment promoters and enhancers active genes [3]. SNF mutations among diverse human cancers (20%), Several SWI/SNF2 family members are known by a SMARCA (SWI/SNF-related Matrix-associated, Actin- dependent Regulator Chromatin Group A) class or chro- *Correspondence: [email protected] †Feng‑Jiao Wang and Yan‑Hua Jing have contributed equally to this article matin subgroup remodeler. SMARCA class of chromatin 1 Department of Integrative Oncology, Fudan University Shanghai Cancer remodeling genes (SMARCAs) play a crucial role in chro- Center, 270 Dong An Road, Shanghai 200032, China matin remodeling, especially in double-strand damage Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Wang et al. BMC Med Genomics (2021) 14:189 Page 2 of 13 repair [4]. SMARCAs are further made up of SMARCA1, validated by Kaplan–Meier survival curves with a hazard SMARCA2, SMARCA3, SMARCA4, SMARCA5, ratio (HR) with 95% confdence intervals (CIs). A log- HELLS, SMARCAD1, and SMARCAL1 [5]. Previous rank P value < 0.05 was considered statically signifcant. studies purposed the SMARCA family members’ carci- nogenic role in several undiferentiated and diferenti- Immunohistochemistry staining ated cancers, including lung cancer and renal cell cancer Te Human Protein Atlas (HPA) (https:// www. prote inatl [4]. However, the expression patterns and the exact roles as. org/) is a website that aims to map human proteins in of SMARCAs in pancreatic cancer remained unclear. In cells, tissues, and organs by utilizing various omics tech- this study, the protein and mRNA expression, prognos- nologies that contain immunohistochemistry-based pro- tic values, and potential functions of diferent SMARCA tein expression, mass spectrometry-based proteomics, family members in pancreatic cancer were systematically transcriptomics, and systems biology [11]. In this study, explored. diferent SMARCA members’ expression between pan- creatic cancer and normal tissues was verifed by immu- Materials and methods nohistochemistry image. ONCOMINE database analysis ONCOMINE database (www. oncom ine. org) is a publicly Functional enrichment analysis accessible online cancer microarray database to collect, Metascape (http:// metas cape. org) is a free gene-list anal- standardize, analyze, and deliver cancer transcriptome ysis tool for gene annotation and analysis and an auto- data to the biomedical research community [6]. Te mated meta-analysis tool to understand common and expression levels of SMARCA gene family members in unique pathways within a group of orthogonal target-dis- diferent types of cancer tissues and their adjacent nor- covery studies [12]. In this study, the neighboring genes mal samples were identifed using ONCOMINE data- based on TCGA and GTEx expression datasets with sim- base. Te diferences were compared by students’ t-test. ilar expression pattern with SMARCA family members Te threshold was restricted as follows: P value: 0.01, fold were detected using GEPIA, respectively. Te selected change: 2, gene rank: 10%, data type: mRNA. correlate genes were further used to conduct pathway and process enrichment analysis by Metascape. For this, GEPIA dataset analysis the Gene Ontology (GO) enrichment analysis, includ- Gene Expression Profling Interactive Analysis (GEPIA) ing biological processes (BP), cellular components (CC), (http:// gepia2. cancer- pku. cn/) is a developed interactive and molecular functions (MF) were used for predicting web server for estimating the RNA sequencing expres- the functional roles of SMARCAs mutations and similar sion data, based on 9,736 tumors and 8,587 normal genes associated with SMARCAs mutations. Kyoto Ency- samples from the Cancer Genome Atlas (TCGA) and clopedia of Genes and Genomes pathways (KEGG) ana- Genotype-Tissue Expression (GTEx) dataset projects. lyzed the SMARCA family members-related pathways Te UCSC Xena project (http:// xena. ucsc. edu/) has and closely related neighbor genes of SMARCAs muta- recomputed all raw RNA-Seq data based on a standard tions. A P value cut-of < 0.01, a minimum overlap of 3, processing pipeline, thus minimizing diferences from and a minimum enrichment factor of 1.5 were considered distinct sources and making such data more compatible. as statistically signifcant. In addition, GEPIA provides essential interactive and customizable functions, including diferential expression Western blotting analysis, profling plotting, patient survival analysis, simi- Cells were collected and lysed in cold RIPA bufer sup- lar gene detection, correlation analysis, and dimensional- plemented with phenylmethanesulfonyl fuoride (PMSF; ity reduction analysis [7]. Beyotime, China) and centrifuged at 14,000 rpm and 4 °C for 15 min. Total protein concentrations were deter- Kaplan–Meier plotter mined with a BCA protein assay kit (Beyotime, China). Te prognostic value of mRNA expression of SMARCAs Equal amounts of denatured protein samples were sepa- in pancreatic cancers was evaluated using an open online rated by electrophoresis using 10% SDS-PAGE gel fast database, Kaplan–Meier Plotter (http:// kmplot. com/ preparation kits (Epizyme, China), and then transferred analy sis/). Tis database provided gene expression data onto 0.45 μm polyvinylidene difuoride (PVDF; Millipore, and survival information of patients with liver cancer and USA) membranes. Subsequently, the membranes were many other cancer types, such as breast cancer, ovarian blocked with 5% BSA diluted in Tris-bufered saline with cancer, lung cancer, and gastric cancer [8–10]. Patients 0.1% Tween-20 (TBST) at room temperature. Ten, the were divided into high and low expression groups PVDF membranes were incubated with primary anti- according to the median values of mRNA expression and bodies against β-actin (1:1000; Proteintech) and HELLS Wang et al. BMC Med Genomics (2021) 14:189
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