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Zhan X, Li J, Ding Y, Zhou F, Zeng R, Lei L, Zhang Y, Feng A, Qu Y, Yang Z. Pyroptosis-related long-noncoding RNA signature predicting survival and immunotherapy efficacy in patients with lung squamous cell carcinoma. Clin Exp Med 2024; 24:145. [PMID: 38960987 PMCID: PMC11222204 DOI: 10.1007/s10238-024-01409-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 06/19/2024] [Indexed: 07/05/2024]
Abstract
Pyroptosis-related long-noncoding RNAs (PRlncRNAs) play an important role in cancer progression. However, their role in lung squamous cell carcinoma (LUSC) is unclear. A risk model was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis based on RNA sequencing data from The Cancer Genome Atlas database. The LUSC cohort was divided into high- and low-risk groups based on the median risk score. For the prognostic value of the model, the Kaplan-Meier analysis, log-rank test, and Cox regression analysis were performed. A nomogram was constructed to predict the prognosis of patients, using a risk score and clinical parameters such as age, sex, clinical stage, and tumor node metastasis classification (TNM) stage. Afterwards, six common algorithms were employed to assess the invasion of immune cells. The Gene Set Enrichment Analysis (GSEA) was conducted to identify differences between patients at high and low risk. Furthermore, the pRRophetic package was employed to forecast the half-maximal inhibitory doses of prevalent chemotherapeutic drugs, while the tumor immune dysfunction and exclusion score was computed to anticipate the response to immunotherapy. The expression levels of the seven PRlncRNAs were examined in both LUSC and normal lung epithelial cell lines using RT-qPCR. Proliferation, migration, and invasion assays were also carried out to investigate the role of MIR193BHG in LUSC cells. Patients in the low-risk group showed prolonged survival in the total cohort or subgroup analysis. The Cox regression analysis showed that the risk model could act as an independent prognostic factor for patients with LUSC. The results of GSEA analysis revealed that the high-risk group showed enrichment of cytokine pathways, Janus tyrosine kinase/signal transducer and activator of the transcription signalling pathway, and Toll-like receptor pathway. Conversely, the low-risk group showed enrichment of several gene repair pathways. Furthermore, the risk score was positively correlated with immune cell infiltration. Moreover, patients in the high-risk category showed reduced responsiveness to conventional chemotherapeutic medications and immunotherapy. The majority of the long noncoding RNAs in the risk model were confirmed to be overexpressed in LUSC cell lines compared to normal lung epithelial cell lines by in vitro tests. Further studies have shown that downregulating the expression of MIR193BHG may inhibit the growth, movement, and infiltration capabilities of LUSC cells, whereas increasing the expression of MIR193BHG could enhance these malignant tendencies. This study found that PRlncRNAs were linked to the prognosis of LUSC patients. The risk model, evaluated across various clinical parameters and treatment modalities, shows potential as a future reference for clinical applications.
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Affiliation(s)
- Xiang Zhan
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China
| | - Jixian Li
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China
| | - Yi Ding
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China
| | - Fengge Zhou
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China
| | - Renya Zeng
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China
| | - Lingli Lei
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China
| | - Ying Zhang
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China
| | - Alei Feng
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China
| | - Yan Qu
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
| | - Zhe Yang
- Tumor Research and Therapy Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
- Tumor Research and Therapy Center, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong, China.
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Sun X, Li W, Li G, Yang H, Jiang Z, Shen L, Shen Y, Liu Y, Wang G. A novel long non-coding RNA LINC00524 facilitates invasion and metastasis through interaction with TDP43 in breast cancer. J Cell Mol Med 2024; 28:e18275. [PMID: 38568058 PMCID: PMC10989564 DOI: 10.1111/jcmm.18275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/20/2024] [Indexed: 04/05/2024] Open
Abstract
Breast cancer (BC) remains a significant health concern worldwide, with metastasis being a primary contributor to patient mortality. While advances in understanding the disease's progression continue, the underlying mechanisms, particularly the roles of long non-coding RNAs (lncRNAs), are not fully deciphered. In this study, we examined the influence of the lncRNA LINC00524 on BC invasion and metastasis. Through meticulous analyses of TCGA and GEO data sets, we observed a conspicuous elevation of LINC00524 expression in BC tissues. This increased expression correlated strongly with a poorer prognosis for BC patients. A detailed Gene Ontology analysis suggested that LINC00524 likely exerts its effects through RNA-binding proteins (RBPs) mechanisms. Experimentally, LINC00524 was demonstrated to amplify BC cell migration, invasion and proliferation in vitro. Additionally, in vivo tests showed its potent role in promoting BC cell growth and metastasis. A pivotal discovery was LINC00524's interaction with TDP43, which leads to the stabilization of TDP43 protein expression, an element associated with unfavourable BC outcomes. In essence, our comprehensive study illuminates how LINC00524 accelerates BC invasion and metastasis by binding to TDP43, presenting potential avenues for therapeutic interventions.
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Affiliation(s)
- Xianglin Sun
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
| | - Wenfeng Li
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
| | - Gang Li
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
| | - Huan Yang
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
| | - Zhenglin Jiang
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
| | - Lihua Shen
- Department of PathologyAffiliated Hospital of Nantong UniversityNantongChina
| | | | - Yifei Liu
- Department of PathologyAffiliated Hospital of Nantong UniversityNantongChina
| | - Guohua Wang
- Department of Physiology and Hypoxic Biomedicine, Institute of Special Environmental MedicineNantong UniversityNantongChina
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Qiu L, Tao A, Liu F, Ge X, Li C. Potential prognostic value of a eight ferroptosis-related lncRNAs model and the correlative immune activity in oral squamous cell carcinoma. BMC Genom Data 2022; 23:80. [PMID: 36384476 PMCID: PMC9667687 DOI: 10.1186/s12863-022-01097-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/02/2022] [Indexed: 11/17/2022] Open
Abstract
Background To investigate the prognostic value of ferroptosis-related long noncoding RNAs (lncRNAs) in oral squamous cell carcinoma (OSCC) and to construct a prognostic risk and immune activity model. Methods We obtained clinical and RNA-seq information on OSCC patient data in The Cancer Genome Atlas (TCGA) Genome Data Sharing (GDC) portal. Through a combination of a differential analysis, Pearson correlation analysis and Cox regression analysis, ferroptosis-related lncRNAs were identified, and a prognostic model was established based on these ferroptosis-related lncRNAs. The accuracy of the model was evaluated via analyses based on survival curves, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA). Univariate Cox and multivariate Cox regression analyses were performed to evaluate independent prognostic factors. Then, the infiltration and functional enrichment of immune cells in high- and low-risk groups were compared. Finally, certain small-molecule drugs that potentially target OSCC were predicted via use of the L1000FWD database. Results The prognostic model included 8 ferroptosis-related lncRNAs (FIRRE, LINC01305, AC099850.3, AL512274.1, AC090246.1, MIAT, AC079921.2 and LINC00524). The area under the ROC curve (AUC) was 0.726. The DCA revealed that the risk score based on the prognostic model was a better prognostic indicator than other clinical indicators. The multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for OSCC. There were differences in immune cell infiltration, immune functions, m6A-related gene expression levels, and signal pathway enrichment between the high- and low-risk groups. Subsequently, several small-molecule drugs were predicted for use against differentially expressed ferroptosis-related genes in OSCC. Conclusions We constructed a new prognostic model of OSCC based on ferroptosis-related lncRNAs. The model is valuable for prognostic prediction and immune evaluation, laying a foundation for the study of ferroptosis-related lncRNAs in OSCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-022-01097-z.
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Yao JM, Zhao JY, Lv FF, Yang XB, Wang HJ. A Potential Nine-lncRNAs Signature Identification and Nomogram Diagnostic Model Establishment for Papillary Thyroid Cancer. Pathol Oncol Res 2022; 28:1610012. [PMID: 35280112 PMCID: PMC8906208 DOI: 10.3389/pore.2022.1610012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 01/19/2022] [Indexed: 12/24/2022]
Abstract
The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.
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Affiliation(s)
- Jin-Ming Yao
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
| | - Jun-Yu Zhao
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
| | - Fang-Fang Lv
- Department of Endocrinology and Metabology, The 960th hospital of the PLA Joint Logistics Support Force, Jinan, China
| | - Xue-Bo Yang
- Beijing Splinger Institute of Medicine, Jinan, China
| | - Huan-Jun Wang
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
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Feng C, Liu S, Shang Z. Identification and Validation of an EMT-Related LncRNA Signature for HNSCC to Predict Survival and Immune Landscapes. Front Cell Dev Biol 2022; 9:798898. [PMID: 35273966 PMCID: PMC8902443 DOI: 10.3389/fcell.2021.798898] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/30/2021] [Indexed: 12/24/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) are increasingly recognized as decisive factors in the progression of head and neck squamous cell carcinoma (HNSCC), and they participate in the epithelial–mesenchymal transformation (EMT) of HNSCC. LncRNAs are closely related to the prognosis of patients with HNSCC; thus, it is essential to identify EMT-related lncRNAs with prognostic value for HNSCC. The coexpression network of EMT-related lncRNAs was constructed using The Cancer Genome Atlas (TCGA). An EMT-related eight-lncRNA-based prognostic signature was constructed using LASSO Cox regression and Cox proportional hazards analyses. Univariate and multivariate analyses and stratified prognosis confirmed that the prognostic signature was an independent predictive factor. Subsequently, we performed immune cell infiltration analysis, gene set enrichment analysis (GSEA), and single-sample GSEA (ssGSEA) pathway enrichment analysis to uncover the potential molecular mechanisms of prognostic differences in the high- and low-risk groups. Next, we discussed the relationship between the prognostic signature and immune checkpoint-related genes, their TIDE scores, and the sensitivity of common chemotherapeutics. Finally, we further verified the expression differences in lncRNAs that were included in our signature via RT–qPCR in eighteen paired tissues. In summary, this prognostic signature provides powerful prognostic biomarkers for HNSCC and could serve as a predictor for the sensitivity of common chemotherapeutics and immunotherapy responses as well as providing a reference for further personalized treatment.
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Affiliation(s)
- Chunyu Feng
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
| | - Shaopeng Liu
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
| | - Zhengjun Shang
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
- Department of Oral and Maxillofacial Head and Neck Oncology, School and Hospital of Stomatology, Wuhan University, Wuhan, China
- *Correspondence: Zhengjun Shang,
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Wei J, Zeng Y, Gao X, Liu T. A novel ferroptosis-related lncRNA signature for prognosis prediction in gastric cancer. BMC Cancer 2021; 21:1221. [PMID: 34774009 PMCID: PMC8590758 DOI: 10.1186/s12885-021-08975-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 11/05/2021] [Indexed: 01/21/2023] Open
Abstract
Background Gastric cancer (GC) is a common malignant cancer with a poor prognosis. Ferroptosis has been shown to play crucial roles in GC development. Long non-coding RNAs (lncRNAs) is also associated with tumor progression in GC. This study aimed to screen the prognostic ferroptosis-related lncRNAs and to construct a prognostic risk model for GC. Methods Ferroptosis-related lncRNAs from The Cancer Genome Atlas (TCGA) GC expression data was downloaded. First, single factor Cox proportional hazard regression analysis was used to select seven prognostic ferroptosis-related lncRNAs from TCGA database. And then, the selected lncRNAs were further included in the multivariate Cox proportional hazard regression analysis to establish the prognostic model. A nomogram was constructed to predict individual survival probability. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the risk model. Results We constructed a prognostic ferroptosis-related lncRNA signature in this study. Kaplan-Meier curve analysis revealed a significantly better prognosis for the low-risk group than for the high-risk group (P = 2.036e-05). Multivariate Cox proportional risk regression analysis demonstrated that risk score was an independent prognostic factor [hazard ratio (HR) = 1.798, 95% confidence interval (CI) =1.410–2.291, P < 0.001]. A nomogram, receiver operating characteristic curve, and principal component analysis were used to predict individual prognosis. Finally, the expression levels of AP003392.1, AC245041.2, AP001271.1, and BOLA3-AS1 in GC cell lines and normal cell lines were tested by qRT-PCR. Conclusions This risk model was shown to be a novel method for predicting prognosis for GC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08975-2.
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Affiliation(s)
- Jianming Wei
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Ye Zeng
- Department of Laboratory Medicine, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xibo Gao
- Department of Dermatology, Tianjin Children's Hospital, Tianjin, China
| | - Tong Liu
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China.
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Chen G, Yang G, Long J, Yang J, Qin C, Luo W, Qiu J, Zhao F, You L, Zhang T, Zhao Y. Comprehensive Analysis of Autophagy-Associated lncRNAs Reveal Potential Prognostic Prediction in Pancreatic Cancer. Front Oncol 2021; 11:596573. [PMID: 34123773 PMCID: PMC8188897 DOI: 10.3389/fonc.2021.596573] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 04/19/2021] [Indexed: 12/15/2022] Open
Abstract
Pancreatic cancer (PC) is a highly malignant tumor in the digestive system. Both long noncoding RNAs (lncRNAs) and autophagy play vital roles in the development and progress of PC. Here, we constructed a prognostic risk score system based on the expression profile of autophagy-associated lncRNAs for prognostic prediction in PC patients. Firstly, we extracted the expression profile of lncRNA and clinical information from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The autophagy-associated genes were from The Human Autophagy Database. Through Cox regression and survival analysis, we screened out seven autophagy-associated lncRNAs and built the risk score system in which the patients with PC were distinguished into high- and low-risk groups in both training and validation datasets. PCA plot displayed distinct discrimination, and risk score system displayed independently predictive value for PC patient survival time by multivariate Cox regression. Then, we built a lncRNA and mRNA co-expression network via Cytoscape and Sankey diagram. Finally, we analyzed the function of lncRNAs in high- and low-risk groups by gene set enrichment analysis (GSEA). The results showed that autophagy and metabolism might make significant effects on PC patients of low-risk groups. Taken together, our study provides a new insight to understand the role of autophagy-associated lncRNAs and finds novel therapeutic and prognostic targets in PC.
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Affiliation(s)
- Guangyu Chen
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Gang Yang
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Junyu Long
- Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinshou Yang
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Cheng Qin
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wenhao Luo
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiangdong Qiu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fangyu Zhao
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lei You
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Taiping Zhang
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Clinical Immunology Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yupei Zhao
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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