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In vivo metabolic imaging identifies lipid vulnerability in a preclinical model of Her2+/Neu breast cancer residual disease and recurrence. NPJ Breast Cancer 2022; 8:111. [PMID: 36163365 PMCID: PMC9512922 DOI: 10.1038/s41523-022-00481-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 09/16/2022] [Indexed: 11/08/2022] Open
Abstract
Recurrent cancer cells that evade therapy is a leading cause of death in breast cancer patients. This risk is high for women showing an overexpression of human epidermal growth factor receptor 2 (Her2). Cells that persist can rely on different substrates for energy production relative to their primary tumor counterpart. Here, we characterize metabolic reprogramming related to tumor dormancy and recurrence in a doxycycline-induced Her2+/Neu model of breast cancer with varying times to recurrence using longitudinal fluorescence microscopy. Glucose uptake (2-NBDG) and mitochondrial membrane potential (TMRE) imaging metabolically phenotype mammary tumors as they transition to regression, dormancy, and recurrence. “Fast-recurrence” tumors (time to recurrence ~55 days), transition from glycolysis to mitochondrial metabolism during regression and this persists upon recurrence. “Slow-recurrence” tumors (time to recurrence ~100 days) rely on both glycolysis and mitochondrial metabolism during recurrence. The increase in mitochondrial activity in fast-recurrence tumors is attributed to a switch from glucose to fatty acids as the primary energy source for mitochondrial metabolism. Consequently, when fast-recurrence tumors receive treatment with a fatty acid inhibitor, Etomoxir, tumors report an increase in glucose uptake and lipid synthesis during regression. Treatment with Etomoxir ultimately prolongs survival. We show that metabolic reprogramming reports on tumor recurrence characteristics, particularly at time points that are essential for actionable targets. The temporal characteristics of metabolic reprogramming will be critical in determining the use of an appropriate timing for potential therapies; namely, the notion that metabolic-targeted inhibition during regression reports long-term therapeutic benefit.
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Masciale V, Banchelli F, Grisendi G, D’Amico R, Maiorana A, Stefani A, Morandi U, Stella F, Dominici M, Aramini B. Cancer Stem Cells and Cell Cycle Genes as Independent Predictors of Relapse in Non-small Cell Lung Cancer: Secondary Analysis of a Prospective Study. Stem Cells Transl Med 2022; 11:797-804. [PMID: 35674389 PMCID: PMC9397651 DOI: 10.1093/stcltm/szac040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 05/07/2022] [Indexed: 11/15/2022] Open
Abstract
Purpose Cancer stem cells (CSCs) are described as resistant to chemotherapy and radiotherapy. It has been shown that CSCs influence disease-free survival in patients undergoing surgery for lung cancer (NCT04634630). We recently described an overexpression of CSCs recurrence-related genes (RG) in lung cancer. This study aims to investigate CSC frequency and RG expression as predictors of disease-free survival in lung cancer. Experimental Design This secondary analysis of a prospective cohort study involved 22 surgical tumor specimens from 22 patients harboring early (I-II) and locally advanced (IIIA) stages ACL and SCCL. Cell population frequency analysis of ALDHhigh (CSCs) and ALDHlow (cancer cells) was performed on each tumor specimen. In addition, RG expression was assessed for 31 target genes separately in ALDHhigh and ALDHlow populations. CSCs frequency and RG expression were assessed as predictors of disease-free survival by Cox analysis. Results CSCs frequency and RG expression were independent predictors of disease-free survival. CSC frequency was not related to disease-free survival in early-stage patients (HR = 0.84, 95%CI = 0.53-1.33, P = .454), whereas it was a risk factor for locally advanced-stage patients (HR = 1.22, 95%CI = 1.09-1.35, P = .000). RG expression—if measured in CSCs—was related to a higher risk of recurrence (HR = 1.19, 95%CI = 1.03-1.39, P = .021). The effect of RG expression measured in cancer cells on disease-free survival was lower and was not statistically significant (HR = 1.12, 95%CI = 0.94-1.33, P = .196). Conclusions CSCs frequency and RG expression are independent predictors of relapse in lung cancer. Considering these results, CSCs and RG may be considered for both target therapy and prognosis.
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Affiliation(s)
| | | | | | - Roberto D’Amico
- Center of Medical Statistics, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Antonino Maiorana
- Institute of Pathology, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Alessandro Stefani
- Division of Thoracic Surgery, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Uliano Morandi
- Division of Thoracic Surgery, Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Franco Stella
- Division of Thoracic Surgery, Department of Experimental, Diagnostic and Specialty Medicine—DIMES of the Alma Mater Studiorum, University of Bologna, G.B. Morgagni—L. Pierantoni Hospital, Forlì, Italy
| | | | - Beatrice Aramini
- Corresponding author: Beatrice Aramini, MD, PhD, Division of Thoracic Surgery, Department of Experimental, Diagnostic and Specialty Medicine—DIMES of the Alma Mater Studiorum, University of Bologna, G.B. Morgagni—L. Pierantoni Hospital, 34 Carlo Forlanini Street, 47121 Forlì, Italy.
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Chang YT, Tsai WC, Lin WZ, Wu CC, Yu JC, Tseng VS, Liao GS, Hu JM, Hsu HM, Chang YJ, Lin MC, Chu CM, Yang CY. A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer. Front Oncol 2022; 11:759952. [PMID: 35155184 PMCID: PMC8829566 DOI: 10.3389/fonc.2021.759952] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/21/2021] [Indexed: 12/31/2022] Open
Abstract
Background Immunoglobulin-related genes are associated with the favorable prognosis of triple-negative breast cancer (TNBC) patients. We aimed to analyze the function and prognostic value of immunoglobulin lambda constant 2 (IGLC2) in TNBC patients. Methods We knocked down the gene expression of IGLC2 (IGLC2-KD) in MDA-MB-231 cells to evaluate the proliferation, migration, and invasion of tumors via 3-(4,5-Dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, wound healing, and transwell cell migration assay respectively. Relapse-free survival (RFS) and distant metastasis-free survival (DMFS) analyses were conducted using the KM plotter online tool. The GSE76275 data set was used to analyze the association of IGLC2 and clinical characteristics. A pathway enrichment analysis was conducted using the next-generation sequencing data of wild-type and IGLC2-KD MDA-MB-231 cells. Results The low gene expression of IGLC2 was related to unfavorable RFS, DMFS. The high expression of IGLC2 was exhibited in the basal-like immune-activated (BLIA) TNBC molecular subtype, which was immune-activated and showed excellent response to immune therapy. IGLC2 was positively correlated with programmed death-ligand 1 (PD-L1) as shown by Spearman correlation (r = 0.25, p < 0.0001). IGLC2 had a strong prognostic effect on lymph node-negative TNBC (RFS range: 0.31, q value= 8.2e-05; DMFS = 0.16, q value = 8.2e-05) but had no significance on lymph node-positive ones. The shRNA-mediated silencing of IGLC2 increased the proliferation, migration, and invasion of MDA-MB-231 cells. The results of pathway enrichment analysis showed that IGLC2 is related to the PI3K-Akt signaling pathway, MAPK signaling pathway, and extracellular matrix–receptor interaction. We confirmed that MDA-MB-231 tumor cells expressed IGLC2, subverting the traditional finding of generation by immune cells. Conclusions IGLC2 linked with the proliferation, migration, and invasion of MDA-MB-231 cells. A high expression of IGLC2 was related to favorable prognosis for TNBC patients. IGLC2 may serve as a biomarker for the identification of TNBC patients who can benefit the most from immune checkpoint blockade treatment.
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Affiliation(s)
- Yu-Tien Chang
- School of Public Health, National Defense Medical Center, Taipei, Taiwan
| | - Wen-Chiuan Tsai
- Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Wei-Zhi Lin
- Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Chia-Chao Wu
- Division of Nephrology, Department of Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Jyh-Cherng Yu
- Division of General Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Vincent S Tseng
- Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan
| | - Guo-Shiou Liao
- Division of General Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Je-Ming Hu
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan.,Division of Colorectal Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.,School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Huan-Ming Hsu
- Division of General Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.,Department of Surgery, Songshan Branch of Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Yu-Jia Chang
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.,Cell Physiology and Molecular Image Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.,Cancer Research Center and Translational Laboratory, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan
| | - Meng-Chiung Lin
- Division of Gastroenterology, Department of Medicine, Taichung Armed Forces General Hospital, Taichung, Taiwan.,Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan
| | - Chi-Ming Chu
- Division of Biostatistics and Informatics, Department of Epidemiology, School of Public Health, National Defense Medical Center, Taipei, Taiwan.,Big Data Research Center, Fu-Jen Catholic University, New Taipei City, Taiwan.,Department of Public Health, China Medical University, Taichung, Taiwan.,Department of Healthcare Administration and Medical Informatics College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chien-Yi Yang
- Department of Surgery, Songshan Branch of Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
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Evaluation of breast cancer stem cells in human primary breast carcinoma and their role in aggressive behavior of the disease. J Clin Transl Res 2021; 7:687-700. [PMID: 34778599 PMCID: PMC8580523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 04/07/2021] [Accepted: 09/07/2021] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND AIM To delineate the underlying molecular mechanisms responsible for the intratumoral enrichment of breast cancer stem cells (BCSCs) in aggressive breast tumors, we evaluated the frequency and characteristics of BCSCs within the tumor tissue in primary human breast carcinomas. We assessed the expression profiles of various genes in cancer cells (CC) and stromal cells (SC) from these tumors to delineate the role played by the cellular niche in de novo origin or expansion of intra-tumoral cancer stem cells (CSC). METHOD The study included primary tumor and adjacent normal breast tissue specimens from chemotherapy-naïve breast carcinoma patients. The BCSCs, identified as Lin-CD44+CD24- and aldehyde dehydrogenase 1 A1 positive, were enumerated. The flow-cytometrically sorted stromal, and CC were processed for gene expression profiling using a custom-designed polymerase chain reaction array of genes known to facilitate disease progression. RESULTS The frequency of BCSCs within the tumor mass correlated significantly with histopathological and molecular grades of tumors, indicating a direct relationship of BCSC with the aggressive behavior of breast cancer. Further, a significantly increased expression of the genes associated with growth factors, cytokines and matricellular proteins in tumors were found in high BCSCs compared to Lo-BCSC tumors, suggesting the possible contribution of stromal and CC in an intratumoral expansion of CSCs. Similarly, a significant upregulation of genes associated with hypoxia and angiogenesis in Hi-BCSCs tumors further supported the role of a hypoxic environment. CONCLUSION Overall, the findings suggest the molecular crosstalk between SC and CC potentially (directly or indirectly) contributes to the expansion of CSC. RELEVANCE FOR PATIENTS The current study highlights the importance of CSC as a potential future predictive/prognostic marker for aggressive breast cancer. The present study predicts the potential risk stratification based on the frequency of BCSCs in primary breast tumors and existing prognostic factors.
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Advanced sensitivity amplification strategies for voltammetric immunosensors of tumor marker: State of the art. Biosens Bioelectron 2021; 178:113021. [DOI: 10.1016/j.bios.2021.113021] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/27/2020] [Accepted: 01/18/2021] [Indexed: 12/24/2022]
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Genetic heterogeneity and prognostic impact of recurrent ANK2 and TP53 mutations in mantle cell lymphoma: a multi-centre cohort study. Sci Rep 2020; 10:13359. [PMID: 32770099 PMCID: PMC7414214 DOI: 10.1038/s41598-020-70310-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 07/21/2020] [Indexed: 12/13/2022] Open
Abstract
The molecular features of mantle cell lymphoma (MCL), including its increased incidence, and complex therapies have not been investigated in detail, particularly in East Asian populations. In this study, we performed targeted panel sequencing (TPS) and whole-exome sequencing (WES) to investigate the genetic alterations in Korean MCL patients. We obtained a total of 53 samples from MCL patients from five Korean university hospitals between 2009 and 2016. We identified the recurrently mutated genes such as SYNE1, ATM, KMT2D, CARD11, ANK2, KMT2C, and TP53, which included some known drivers of MCL. The mutational profiles of our cohort indicated genetic heterogeneity. The significantly enriched pathways were mainly involved in gene expression, cell cycle, and programmed cell death. Multivariate analysis revealed that ANK2 mutations impacted the unfavourable overall survival (hazard ratio [HR] 3.126; P = 0.032). Furthermore, TP53 mutations were related to worse progression-free survival (HR 7.813; P = 0.043). Among the recurrently mutated genes with more than 15.0% frequency, discrepancies were found in only 5 genes from 4 patients, suggesting comparability of the TPS to WES in practical laboratory settings. We provide the unbiased genetic landscape that might contribute to MCL pathogenesis and recurrent genes conferring unfavourable outcomes.
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Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis. Sci Rep 2019; 9:4484. [PMID: 30872752 PMCID: PMC6418134 DOI: 10.1038/s41598-019-40826-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 02/22/2019] [Indexed: 02/06/2023] Open
Abstract
Gene co-expression network analysis (GCNA) can detect alterations in regulatory activities in case/control comparisons. We propose a framework to detect novel genes and networks for predicting breast cancer recurrence. Thirty-four prognosis candidate genes were selected based on a literature review. Four Gene Expression Omnibus Series (GSE) microarray datasets (n = 920) were used to create gene co-expression networks based on these candidates. We applied the framework to four comparison groups according to node (+/−) and recurrence (+/−). We identified a sub-network containing two candidate genes (LST1 and IGHM) and six novel genes (IGHA1, IGHD, IGHG1, IGHG3, IGLC2, and IGLJ3) related to B cell-specific immunoglobulin. These novel genes were correlated with recurrence under the control of node status and were found to function as tumor suppressors; higher mRNA expression indicated a lower risk of recurrence (hazard ratio, HR = 0.87, p = 0.001). We created an immune index score by performing principle component analysis and divided the genes into low and high groups. This discrete index significantly predicted relapse-free survival (RFS) (high: HR = 0.77, p = 0.019; low: control). Public tool KM Plotter and TCGA-BRCA gene expression data were used to validate. We confirmed these genes are correlated with RFS and distal metastasis-free survival (DMFS) in triple-negative breast cancer (TNBC) and general breast cancer.
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Zhang H, Zeng J, Tan Y, Lu L, Sun C, Liang Y, Zou H, Yang X, Tan Y. Subgroup analysis reveals molecular heterogeneity and provides potential precise treatment for pancreatic cancers. Onco Targets Ther 2018; 11:5811-5819. [PMID: 30254473 PMCID: PMC6140745 DOI: 10.2147/ott.s163139] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background The relationship between molecular heterogeneity and clinical features of pancreatic cancer remains unclear. In this study, pancreatic cancer was divided into different subgroups to explore its specific molecular characteristics and potential therapeutic targets. Patients and methods Expression profiling data were downloaded from The Cancer Genome Atlas database and standardized. Bioinformatics techniques such as unsupervised hierarchical clustering was used to explore the optimal molecular subgroups in pancreatic cancer. Clinical pathological features and pathways in each subgroup were also analyzed to find out the potential clinical applications and initial promotive mechanisms of pancreatic cancer. Results Pancreatic cancer was divided into three subgroups based on different gene expression features. Patients included in each subgroup had specific biological features and responded significantly different to chemotherapy. Conclusion Three distinct subgroups of pancreatic cancer were identified, which means that patients in each subgroup might benefit from targeted individual management.
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Affiliation(s)
- Heying Zhang
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
| | - Juan Zeng
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
| | | | - Lin Lu
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Cheng Sun
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
| | - Yusi Liang
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
| | - Huawei Zou
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
| | - Xianghong Yang
- Department of Pathology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China
| | - Yonggang Tan
- Department of Oncology, Shengjing Hospital, China Medical University, Shenyang, People's Republic of China,
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Gao H, Yang M, Zhang X. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Oncol Lett 2018; 15:5027-5033. [PMID: 29545900 PMCID: PMC5840762 DOI: 10.3892/ol.2018.7940] [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: 06/22/2017] [Accepted: 01/22/2018] [Indexed: 12/04/2022] Open
Abstract
The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.
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Affiliation(s)
- Haiyan Gao
- Department of Breast Surgery, Changzhou No. 2 People's Hospital, Affiliated to Nanjing Medical University, Changzhou, Jiangsu 213000, P.R. China
| | - Mei Yang
- Department of Breast Surgery, Changzhou No. 2 People's Hospital, Affiliated to Nanjing Medical University, Changzhou, Jiangsu 213000, P.R. China
| | - Xiaolan Zhang
- Department of Breast Surgery, Changzhou No. 2 People's Hospital, Affiliated to Nanjing Medical University, Changzhou, Jiangsu 213000, P.R. China
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Wu T, Wang Y, Jiang R, Lu X, Tian J. A pathways-based prediction model for classifying breast cancer subtypes. Oncotarget 2017; 8:58809-58822. [PMID: 28938599 PMCID: PMC5601695 DOI: 10.18632/oncotarget.18544] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 05/01/2017] [Indexed: 11/25/2022] Open
Abstract
Breast cancer is highly heterogeneous and is classified into four subtypes characterized by specific biological traits, treatment responses, and clinical prognoses. We performed a systemic analysis of 698 breast cancer patient samples from The Cancer Genome Atlas project database. We identified 136 breast cancer genes differentially expressed among the four subtypes. Based on unsupervised clustering analysis, these 136 core genes efficiently categorized breast cancer patients into the appropriate subtypes. Functional enrichment based on Kyoto Encyclopedia of Genes and Genomes analysis identified six functional pathways regulated by these genes: JAK-STAT signaling, basal cell carcinoma, inflammatory mediator regulation of TRP channels, non-small cell lung cancer, glutamatergic synapse, and amyotrophic lateral sclerosis. Three support vector machine (SVM) classification models based on the identified pathways effectively classified different breast cancer subtypes, suggesting that breast cancer subtype-specific risk assessment based on disease pathways could be a potentially valuable approach. Our analysis not only provides insight into breast cancer subtype-specific mechanisms, but also may improve the accuracy of SVM classification models.
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Affiliation(s)
- Tong Wu
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Heilongjiang Province, China
| | - Yunfeng Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Heilongjiang Province, China
| | - Ronghui Jiang
- Department of Surgery, Yanbian No.2 People's Hospital, Jilin Province, China
| | - Xinliang Lu
- Institute of Immunology, Zhejiang University School of Medicine, Zhejiang Province, China
| | - Jiawei Tian
- Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Heilongjiang Province, China
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