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Diagnosis System of Microscopic Hyperspectral Image of Hepatobiliary Tumors Based on Convolutional Neural Network. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:3794844. [PMID: 35341163 PMCID: PMC8947895 DOI: 10.1155/2022/3794844] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 02/09/2022] [Accepted: 02/16/2022] [Indexed: 11/29/2022]
Abstract
Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a very serious problem. This article mainly studies a diagnostic method of microscopic images of liver and gallbladder tumors. Under this research direction, this article proposes to use convolutional neural network to learn and use hyperspectral images to diagnose it. It is found that the addition of the convolutional neural network can greatly improve the actual map classification and the accuracy of the map, and effectively improve the success rate of the treatment. At the same time, the article designs related experiments to compare its feature extraction performance and classification situation. The experimental results in this article show that the improved diagnostic method based on convolutional neural network has an accuracy rate of 85%–90%, which is as high as 6%–8% compared with the traditional accuracy rate, and thus it effectively improves the clinical problem of hepatobiliary tumor treatment.
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2
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Li SC, Kabeer MH. Spatiotemporal switching signals for cancer stem cell activation in pediatric origins of adulthood cancer: Towards a watch-and-wait lifetime strategy for cancer treatment. World J Stem Cells 2018; 10:15-22. [PMID: 29531638 PMCID: PMC5840533 DOI: 10.4252/wjsc.v10.i2.15] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 01/25/2018] [Accepted: 02/24/2018] [Indexed: 02/06/2023] Open
Abstract
Pediatric origin of cancer stem cell hypothesis holds great promise and potential in adult cancer treatment, however; the road to innovation is full of obstacles as there are plenty of questions left unanswered. First, the key question is to characterize the nature of such stem cells (concept). Second, the quantitative imaging of pediatric stem cells should be implemented (technology). Conceptually, pediatric stem cell origins of adult cancer are based on the notion that plasticity in early life developmental programming evolves local environments to cancer. Technologically, such imaging in children is lacking as all imaging is designed for adult patients. We postulate that the need for quantitative imaging to measure space-time changes of plasticity in early life developmental programming in children may trigger research and development of the imaging technology. Such quantitative imaging of pediatric origin of adulthood cancer will help develop a spatiotemporal monitoring system to determine cancer initiation and progression. Clinical validation of such speculative hypothesis-that cancer originates in a pediatric environment-will help implement a wait-and-watch strategy for cancer treatment.
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Affiliation(s)
- Shengwen Calvin Li
- Neuro-oncology and Stem Cell Research Laboratory, Children's Hospital of Orange County, Department of Neurology, University of California-Irvine School of Medicine, Orange, CA 92868-3874, United States
| | - Mustafa H Kabeer
- Children's Hospital of Orange County, Department of Surgery, University of California-Irvine School of Medicine, Orange, CA 92868-3874, United States
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Chianchiano P, Pezhouh MK, Kim A, Luchini C, Cameron A, Weiss MJ, He J, Voltaggio L, Oshima K, Anders RA, Wood LD. Distinction of intrahepatic metastasis from multicentric carcinogenesis in multifocal hepatocellular carcinoma using molecular alterations. Hum Pathol 2018; 72:127-134. [PMID: 29180252 PMCID: PMC6435273 DOI: 10.1016/j.humpath.2017.11.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 11/10/2017] [Accepted: 11/15/2017] [Indexed: 02/07/2023]
Abstract
Patients with hepatocellular carcinoma (HCC) frequently have multiple anatomically distinct tumors. In these patients, multifocal HCC could represent intrahepatic metastases (IMs) of a single cancer or multicentric carcinogenesis (MC) with multiple independent neoplasms. To determine the frequency and clinical implications of these 2 possibilities, we performed histological and molecular analysis of 70 anatomically distinct HCCs from 24 patients. We assayed mutations in the TERT promoter region by Sanger sequencing and used next-generation sequencing to analyze the entire coding regions of 7 well-characterized HCC driver genes-based on shared or discordant mutations in these genes, we classified the HCCs in each patient as IM, MC, or indeterminate. Mutations in the TERT promoter were the most common alteration in our cohort, present in 71% of tumors analyzed. Mutations in the remaining genes occurred in less than 20% of analyzed tumors. We were able to determine the relatedness in 58% of the patients analyzed: MC occurred in 41% of patients, with 33% with exclusively MC and 8% with both MC and IM. IM occurred exclusively in 17% of patients, whereas the remainder were indeterminate. This study highlights the utility of molecular analyses to determine relatedness in multifocal HCC; however, targeted sequencing can only resolve this distinction in approximately 60% of patients with multifocal HCC.
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Affiliation(s)
- Peter Chianchiano
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Maryam Kherad Pezhouh
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Amy Kim
- Division of Gastroenterology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Claudio Luchini
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, Verona 37134, Italy
| | - Andrew Cameron
- Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD 21231
| | - Matthew J Weiss
- Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD 21231
| | - Jin He
- Department of Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD 21231
| | - Lysandra Voltaggio
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Kiyoko Oshima
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Robert A Anders
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA
| | - Laura D Wood
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
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Jiang W, Shen Y, Ding Y, Ye C, Zheng Y, Zhao P, Liu L, Tong Z, Zhou L, Sun S, Zhang X, Teng L, Timko MP, Fan L, Fang W. A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system. Int J Cancer 2018; 142:357-368. [PMID: 28921531 DOI: 10.1002/ijc.31054] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 08/24/2017] [Accepted: 09/04/2017] [Indexed: 12/30/2022]
Abstract
Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment.
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Affiliation(s)
- Weiqin Jiang
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yifei Shen
- Institute of Bioinformatics & IBM Bio-computational Laboratory, Zhejiang University, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
| | - Yongfeng Ding
- Department of Surgical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Chuyu Ye
- Institute of Bioinformatics & IBM Bio-computational Laboratory, Zhejiang University, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
| | - Yi Zheng
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Peng Zhao
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Precision Diagnosis & Treatment for Hepatobiliary & Pancreatic Tumor of Zhejiang Province, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lulu Liu
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Zhou Tong
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Linfu Zhou
- Medical Biotechnology Laboratory, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shuo Sun
- Institute of Bioinformatics & IBM Bio-computational Laboratory, Zhejiang University, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
| | - Xingchen Zhang
- Institute of Bioinformatics & IBM Bio-computational Laboratory, Zhejiang University, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
| | - Lisong Teng
- Department of Surgical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Precision Diagnosis & Treatment for Hepatobiliary & Pancreatic Tumor of Zhejiang Province, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Michael P Timko
- Departments of Biology and Public Health Science, University of Virginia, Charlottesville, VA, 22904
| | - Longjiang Fan
- Institute of Bioinformatics & IBM Bio-computational Laboratory, Zhejiang University, Hangzhou, China
- Research Center for Air Pollution and Health, Zhejiang University, Hangzhou, China
| | - Weijia Fang
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Precision Diagnosis & Treatment for Hepatobiliary & Pancreatic Tumor of Zhejiang Province, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
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Liang Y, Xie SB, Wu CH, Hu Y, Zhang Q, Li S, Fan YG, Leng RX, Pan HF, Xiong HB, Ye DQ. Coagulation cascade and complement system in systemic lupus erythematosus. Oncotarget 2017; 9:14862-14881. [PMID: 29599912 PMCID: PMC5871083 DOI: 10.18632/oncotarget.23206] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 11/16/2017] [Indexed: 12/26/2022] Open
Abstract
This study was conducted to (1) characterize coagulation cascade and complement system in systemic lupus erythematosus (SLE); (2) evaluate the associations between coagulation cascade, complement system, inflammatory response and SLE disease severity; (3) test the diagnostic value of a combination of D-dimer and C4 for lupus activity. Transcriptomics, proteomics and metabolomics were performed in 24 SLE patients and 24 healthy controls. The levels of ten coagulations, seven complements and three cytokines were measured in 112 SLE patients. Clinical data were collected from 2025 SLE patients. The analysis of multi-omics data revealed the common links for the components of coagulation cascade and complement system. The results of ELISA showed coagulation cascade and complement system had an interaction effect on SLE disease severity, this effect was pronounced among patients with excess inflammation. The analysis of clinical data revealed a combination of D-dimer and C4 provided good diagnostic performance for lupus activity. This study suggested that coagulation cascade and complement system become 'partners in crime', contributing to SLE disease severity and identified the diagnostic value of D-dimer combined with C4for lupus activity.
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Affiliation(s)
- Yan Liang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China
| | | | - Chang-Hao Wu
- Department of Biochemical Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, UK
| | - Yuan Hu
- Department of Medicine, Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Qin Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
| | - Si Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
| | - Yin-Guang Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
| | - Rui-Xue Leng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
| | - Hua-Bao Xiong
- Department of Medicine, Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dong-Qing Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, PR China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Anhui, PR China
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Abstract
Local recurrence of pancreatic cancer (PC) can occur in the pancreatic remnant. In addition, new primary PC can develop in the remnant. There are limited data available regarding this so-called remnant PC. The aim of this review was to describe the characteristics and therapeutic strategy regarding remnant PC. A literature search was performed using Medline published in English according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The incidence of remnant PC has been reported to be 3% to 5%. It is difficult to distinguish local recurrence from new primary PC. Genetic diagnosis such as Kirsten rat sarcoma viral oncogene homolog mutation may resolve this problem. For patients with remnant PC, repeated pancreatectomy can be performed. Residual total pancreatectomy is the most common procedure. Recent studies have described the safety of the operation because of recent surgical progress and perioperative care. The patients with remnant PC without distant metastasis have shown good long-term outcomes, especially those who underwent repeated pancreatectomy. Adjuvant chemotherapy may contribute to longer survival. In conclusion, this review found that both local recurrence and new primary PC can develop in the pancreatic remnant. Repeated pancreatectomy for the remnant PC is a feasible procedure and can prolong patient survival.
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