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Huang D, Liu AYN, Leung KS, Tang NLS. Direct Measurement of B Lymphocyte Gene Expression Biomarkers in Peripheral Blood Transcriptomics Enables Early Prediction of Vaccine Seroconversion. Genes (Basel) 2021; 12:genes12070971. [PMID: 34202032 PMCID: PMC8304400 DOI: 10.3390/genes12070971] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/16/2021] [Accepted: 06/21/2021] [Indexed: 11/16/2022] Open
Abstract
Peripheral blood transcriptome is a highly promising area for biomarker development. However, transcript abundances (TA) in these cell mixture samples are confounded by proportions of the component leukocyte subpopulations. This poses a challenge to clinical applications, as the cell of origin of any change in TA is not known without prior cell separation procedure. We developed a framework to develop a cell-type informative TA biomarkers which enable determination of TA of a single cell-type (B lymphocytes) directly in cell mixture samples of peripheral blood (e.g., peripheral blood mononuclear cells, PBMC) without the need for subpopulation separation. It is applicable to a panel of genes called B cell informative genes. Then a ratio of two B cell informative genes (a target gene and a stably expressed reference gene) obtained in PBMC was used as a new biomarker to represent the target gene expression in purified B lymphocytes. This approach, which eliminates the tedious procedure of cell separation and directly determines TA of a leukocyte subpopulation in peripheral blood samples, is called the Direct LS-TA method. This method is applied to gene expression datasets collected in influenza vaccination trials as early predictive biomarkers of seroconversion. By using TNFRSF17 or TXNDC5 as the target genes and TNFRSF13C or FCRLA as the reference genes, the Direct LS-TA B cell biomarkers were determined directly in the PBMC transcriptome data and were highly correlated with TA of the corresponding target genes in purified B lymphocytes. Vaccination responders had almost a 2-fold higher Direct LS-TA biomarker level of TNFRSF17 (log 2 SMD = 0.84, 95% CI = 0.47–1.21) on day 7 after vaccination. The sensitivity of these Direct LS-TA biomarkers in the prediction of seroconversion was greater than 0.7 and area-under curves (AUC) were over 0.8 in many datasets. In this paper, we report a straightforward approach to directly estimate B lymphocyte gene expression in PBMC, which could be used in a routine clinical setting. Moreover, the method enables the practice of precision medicine in the prediction of vaccination response. More importantly, seroconversion could now be predicted as early as day 7. As the acquired immunology pathway is common to vaccination against influenza and COVID-19, these biomarkers could also be useful to predict seroconversion for the new COVID-19 vaccines.
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Affiliation(s)
- Dan Huang
- Cytomics Limited, Hong Kong Science and Technology Park, Hong Kong, China; (D.H.); (A.Y.N.L.); (K.-S.L.)
| | - Alex Y. N. Liu
- Cytomics Limited, Hong Kong Science and Technology Park, Hong Kong, China; (D.H.); (A.Y.N.L.); (K.-S.L.)
| | - Kwong-Sak Leung
- Cytomics Limited, Hong Kong Science and Technology Park, Hong Kong, China; (D.H.); (A.Y.N.L.); (K.-S.L.)
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Nelson L. S. Tang
- Cytomics Limited, Hong Kong Science and Technology Park, Hong Kong, China; (D.H.); (A.Y.N.L.); (K.-S.L.)
- Department of Chemical Pathology and Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Hong Kong, China
- Correspondence:
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Sun Z, Xia W, Lyu Y, Song Y, Wang M, Zhang R, Sui G, Li Z, Song L, Wu C, Liew CC, Yu L, Cheng G, Cheng C. Immune-related gene expression signatures in colorectal cancer. Oncol Lett 2021; 22:543. [PMID: 34079596 PMCID: PMC8157333 DOI: 10.3892/ol.2021.12804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 03/11/2021] [Indexed: 12/24/2022] Open
Abstract
The immune system is crucial in regulating colorectal cancer (CRC) tumorigenesis. Identification of immune-related transcriptomic signatures derived from the peripheral blood of patients with CRC would provide insights into CRC pathogenesis, and suggest novel clues to potential immunotherapy strategies for the disease. The present study collected blood samples from 59 patients with CRC and 62 healthy control patients and performed whole blood gene expression profiling using microarray hybridization. Immune-related gene expression signatures for CRC were identified from immune gene datasets, and an algorithmic predictive model was constructed for distinguishing CRC from controls. Model performance was characterized using an area under the receiver operating characteristic curve (ROC AUC). Functional categories for CRC-specific gene expression signatures were determined using gene set enrichment analyses. A Kaplan-Meier plotter survival analysis was also performed for CRC-specific immune genes in order to characterize the association between gene expression and CRC prognosis. The present study identified five CRC-specific immune genes [protein phosphatase 3 regulatory subunit Bα (PPP3R1), amyloid β precursor protein, cathepsin H, proteasome activator subunit 4 and DEAD-Box Helicase 3 X-Linked]. A predictive model based on this five-gene panel showed good discriminatory power (independent test set sensitivity, 83.3%; specificity, 94.7%, accuracy, 89.2%; ROC AUC, 0.96). The candidate genes were involved in pathways associated with ‘adaptive immune responses’, ‘innate immune responses’ and ‘cytokine signaling’. The survival analysis found that a high level of PPP3R1 expression was associated with a poor CRC prognosis. The present study identified five CRC-specific immune genes that were potential diagnostic biomarkers for CRC. The biological function analysis indicated a close association between CRC pathogenesis and the immune system, and may reveal more information about the immunogenic and pathogenic mechanisms driving CRC in the future. Overall, the association between PPP3R1 expression and survival of patients with CRC revealed potential new targets for CRC immunotherapy.
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Affiliation(s)
- Zhenqing Sun
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Wei Xia
- Department of Nuclear Medicine, The Seventh People's Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200137, P.R. China
| | - Yali Lyu
- R&D Department, Huaxia Bangfu Technology Incorporated, Beijing 100000, P.R. China
| | - Yanan Song
- Department of Nuclear Medicine, The Seventh People's Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200137, P.R. China
| | - Min Wang
- R&D Department, Huaxia Bangfu Technology Incorporated, Beijing 100000, P.R. China
| | - Ruirui Zhang
- R&D Department, Huaxia Bangfu Technology Incorporated, Beijing 100000, P.R. China
| | - Guode Sui
- Department of General Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Zhenlu Li
- Department of General Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Li Song
- Department of General Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Changliang Wu
- Department of General Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Choong-Chin Liew
- Golden Health Diagnostics Inc., Yan Cheng, Jiangsu 224000, P.R. China.,Department of Clinical Pathology and Laboratory Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Lei Yu
- R&D Department, Huaxia Bangfu Technology Incorporated, Beijing 100000, P.R. China
| | - Guang Cheng
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266000, P.R. China
| | - Changming Cheng
- R&D Department, Huaxia Bangfu Technology Incorporated, Beijing 100000, P.R. China
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Zou C, Lyu Y, Jiang J, Cao Y, Wang M, Sang C, Zhang R, Li H, Liew CC, Cheng C, Zhao S. Use of peripheral blood transcriptomic biomarkers to distinguish high-grade cervical squamous intraepithelial lesions from low-grade lesions. Oncol Lett 2020; 20:2280-2290. [PMID: 32765790 PMCID: PMC7403635 DOI: 10.3892/ol.2020.11779] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 05/07/2020] [Indexed: 01/10/2023] Open
Abstract
It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.
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Affiliation(s)
- Cunhua Zou
- Gynecology Center, Qingdao Women and Children's Hospital, Qingdao, Shandong 266034, P.R. China
| | - Yali Lyu
- R&D Center, Shanghai Homeostasis Bio-Technology Inc., Shanghai 201203, P.R. China
| | - Jing Jiang
- Gynecology Center, Qingdao Lianchi Maternity and Infant Hospital, Qingdao, Shandong 266034, P.R. China
| | - Yuan Cao
- Gynecology Center, Qingdao Women and Children's Hospital, Qingdao, Shandong 266034, P.R. China
| | - Min Wang
- R&D Center, Shanghai Homeostasis Bio-Technology Inc., Shanghai 201203, P.R. China
| | - Changmei Sang
- Gynecology Center, Qingdao Women and Children's Hospital, Qingdao, Shandong 266034, P.R. China
| | - Ruirui Zhang
- R&D Center, Shanghai Homeostasis Bio-Technology Inc., Shanghai 201203, P.R. China
| | - Haifeng Li
- Gynecology Center, Qingdao Women and Children's Hospital, Qingdao, Shandong 266034, P.R. China
| | - Choong-Chin Liew
- Golden Health Diagnostics Inc., Yancheng, Jiangsu 224000, P.R. China.,Department of Clinical Pathology and Laboratory Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.,Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Changming Cheng
- R&D Center, Shanghai Homeostasis Bio-Technology Inc., Shanghai 201203, P.R. China
| | - Shuping Zhao
- Gynecology Center, Qingdao Women and Children's Hospital, Qingdao, Shandong 266034, P.R. China
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Hou H, Lyu Y, Jiang J, Wang M, Zhang R, Liew CC, Wang B, Cheng C. Peripheral blood transcriptome identifies high-risk benign and malignant breast lesions. PLoS One 2020; 15:e0233713. [PMID: 32497068 PMCID: PMC7272048 DOI: 10.1371/journal.pone.0233713] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 05/11/2020] [Indexed: 01/22/2023] Open
Abstract
Background Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls. Methods Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions. Results Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification. Conclusion A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.
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Affiliation(s)
- Hong Hou
- Qingdao Central Hospital/Qingdao Cancer Hospital, Qingdao, Shandong Province, People’s Republic of China
| | - Yali Lyu
- Huaxia Bangfu Technology Incorporated, Beijing, People’s Republic of China
| | - Jing Jiang
- Qingdao Lianchi Maternity and Infant Hospital, Qingdao, Shandong Province, People’s Republic of China
| | - Min Wang
- Huaxia Bangfu Technology Incorporated, Beijing, People’s Republic of China
| | - Ruirui Zhang
- Huaxia Bangfu Technology Incorporated, Beijing, People’s Republic of China
| | - Choong-Chin Liew
- Golden Health Diagnostics Incorporated, Jiangsu, People’s Republic of China
- Late of Department of Clinical Pathology and Laboratory Medicine, University of Toronto, Canada
- Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Binggao Wang
- Qingdao Central Hospital/Qingdao Cancer Hospital, Qingdao, Shandong Province, People’s Republic of China
- * E-mail: (BW); (CC)
| | - Changming Cheng
- Huaxia Bangfu Technology Incorporated, Beijing, People’s Republic of China
- * E-mail: (BW); (CC)
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Wang Y, Cheng C, Zhang Z, Wang J, Wang Y, Li X, Gao R, Wang Z, Fang Y, Wang J, Wang M, Fan Q, Periya S, Zhang H, Tsuang MT, Liew CC. Blood-based dynamic genomic signature for obsessive-compulsive disorder. Am J Med Genet B Neuropsychiatr Genet 2018; 177:709-716. [PMID: 30350918 DOI: 10.1002/ajmg.b.32675] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 07/03/2018] [Accepted: 07/05/2018] [Indexed: 12/29/2022]
Abstract
No biologically based diagnostic criteria are in clinical use today for obsessive-compulsive disorder (OCD), schizophrenia, and major depressive disorder (MDD), which are defined with reference to Diagnostic and Statistical Manual clinical symptoms alone. However, these disorders cannot always be well distinguished on clinical grounds and may also be comorbid. A biological blood-based dynamic genomic signature that can differentiate among OCD, MDD, and schizophrenia would therefore be of great utility. This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD-specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six-gene panel (COPS7A, FKBP1A, FIBP, TP73-AS1, SDF4, and GOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver-operating-characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood-based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.
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Affiliation(s)
- Yuan Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Changming Cheng
- Research and Development Department, Shanghai Biomedical Laboratory, Shanghai, People's Republic of China.,Research and Development Department, Bionexus Gene Laboratory, Penang, Malaysia
| | - Zongfeng Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jianyu Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yao Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Xiaoping Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Rui Gao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zhen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yiru Fang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Min Wang
- Research and Development Department, Shanghai Biomedical Laboratory, Shanghai, People's Republic of China
| | - Qing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Sanggetha Periya
- Research and Development Department, Bionexus Gene Laboratory, Penang, Malaysia
| | - Haiyin Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, San Diego, California
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Shi J, Cheng C, Ma J, Liew CC, Geng X. Gene expression signature for detection of gastric cancer in peripheral blood. Oncol Lett 2018; 15:9802-9810. [PMID: 29928354 PMCID: PMC6004726 DOI: 10.3892/ol.2018.8577] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2017] [Accepted: 11/07/2017] [Indexed: 12/12/2022] Open
Abstract
Gastric cancer (stomach cancer) is the fifth most common malignancy and the third leading cause of cancer-associated mortality worldwide. Identifying gastric cancer patients at an early and curable stage of the disease is essential if mortality rates for this disease are to decrease. A non-invasive blood-based test that is an indicator of gastric cancer risk would likely be of benefit in identifying gastric cancer patients at an early stage, and such a test may enhance clinical decision making. This study identified a four-gene expression signature in peripheral blood samples associated with gastric cancer. A total of 216 blood samples were collected, including those from 36 gastric cancer patients, 55 healthy controls and 125 patients with other carcinomas, and gene expression profiles were examined using an Affymetrix Gene Profiling microarray. Blood gene expression profiles were compared between patients with stomach cancer, healthy controls and patients affected with other malignancies. A four-gene panel was identified comprising purine-rich element binding protein B, structural maintenance of chromosomes 1A, DENN/MADD domain containing 1B and programmed cell death 4. The four-gene panel discriminated gastric cancer with an area under the receiver-operating-characteristic curve of 0.99, an accuracy of 95%, sensitivity of 92% and specificity of 96%. The non-invasive nature of the blood test, together with the relatively high accuracy of the four-gene panel may assist physicians in gastric cancer screening decision making.
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Affiliation(s)
- Jianing Shi
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, Anhui 230601, P.R. China
| | - Changming Cheng
- Sentinel Center, Shanghai Biomedical Laboratory, Shanghai 200436, P.R. China.,National Engineering Center for Biochip at Shanghai, Shanghai Biochip Co., Ltd., Shanghai 201203, P.R. China
| | - Jun Ma
- Department of Research, Golden Health Diagnostics Inc., Yancheng, Jiangsu 224000, P.R. China
| | - Choong-Chin Liew
- Sentinel Center, Shanghai Biomedical Laboratory, Shanghai 200436, P.R. China.,Department of Research, Golden Health Diagnostics Inc., Yancheng, Jiangsu 224000, P.R. China.,Department of Clinical Pathology and Laboratory Medicine, University of Toronto, Toronto, Ontario, ON M5S 1A8, Canada.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Xiaoping Geng
- Department of General Surgery, The Second Hospital of Anhui Medical University, Hefei, Anhui 230601, P.R. China
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