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Zhang Q, Hu H, Chen SY, Liu CJ, Hu FF, Yu J, Wu Y, Guo AY. Transcriptome and Regulatory Network Analyses of CD19-CAR-T Immunotherapy for B-ALL. GENOMICS PROTEOMICS & BIOINFORMATICS 2019; 17:190-200. [PMID: 31201998 PMCID: PMC6620363 DOI: 10.1016/j.gpb.2018.12.008] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 11/06/2018] [Accepted: 12/30/2018] [Indexed: 12/31/2022]
Abstract
Chimeric antigen receptor (CAR) T cell therapy has exhibited dramatic anti-tumor efficacy in clinical trials. In this study, we reported the transcriptome profiles of bone marrow cells in four B cell acute lymphoblastic leukemia (B-ALL) patients before and after CD19-specific CAR-T therapy. CD19-CAR-T therapy remarkably reduced the number of leukemia cells, and three patients achieved bone marrow remission (minimal residual disease negative). The efficacy of CD19-CAR-T therapy on B-ALL was positively correlated with the abundance of CAR and immune cell subpopulations, e.g., CD8+ T cells and natural killer (NK) cells, in the bone marrow. Additionally, CD19-CAR-T therapy mainly influenced the expression of genes linked to cell cycle and immune response pathways, including the NK cell mediated cytotoxicity and NOD-like receptor signaling pathways. The regulatory network analyses revealed that microRNAs (e.g., miR-148a-3p and miR-375), acting as oncogenes or tumor suppressors, could regulate the crosstalk between the genes encoding transcription factors (TFs; e.g., JUN and FOS) and histones (e.g., HIST1H4A and HIST2H4A) involved in CD19-CAR-T therapy. Furthermore, many long non-coding RNAs showed a high degree of co-expression with TFs or histones (e.g., FOS and HIST1H4B) and were associated with immune processes. These transcriptome analyses provided important clues for further understanding the gene expression and related mechanisms underlying the efficacy of CAR-T immunotherapy.
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Affiliation(s)
- Qiong Zhang
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hui Hu
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Si-Yi Chen
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Chun-Jie Liu
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Fei-Fei Hu
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jianming Yu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Yaohui Wu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - An-Yuan Guo
- Hubei Bioinformatics and Molecular Imaging Key Laboratory, Department of Bioinformatics and Systems Biology, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
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Amanzadeh A, Molla-Kazemiha V, Samani S, Habibi-Anbouhi M, Azadmanesh K, Abolhassani M, Shokrgozar MA. New synergistic combinations of differentiation-inducing agents in the treatment of acute promyelocytic leukemia cells. Leuk Res 2018; 68:98-104. [PMID: 29602066 DOI: 10.1016/j.leukres.2018.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 12/29/2017] [Accepted: 01/14/2018] [Indexed: 10/18/2022]
Abstract
Acute promyelocytic leukemia (APL) was considered to be one of the most lethal forms of leukemia in adults before the introduction of the vitamin A metabolite all-trans retinoic acid (ATRA). Surprisingly, it has been confirmed that FICZ (6-Formylindolo (3, 2-b) carbazole) enhances ATRA-induced differentiation. Moreover, a number of studies have demonstrated that anti CD44 monoclonal antibody (mAb) induces to bring back differentiation blockage the leukemic stem cells. The level of differentiation markers including CD11b and CD11c in NB4 cells was assessed by flow cytometry. The induction of apoptosis was also evaluated. We estimated the induction potential of a triple compound of ATRA-FICZ, anti-CD44 maps. The cells showed the gradually increased expression levels of CD11b and CD11c. A mixture of a "CD44 mAb, ATRA and FICZ effectively promoted granulocytic maturation resulting in increased rates of apoptosis. The differences in expression of CD11b and CD11c at 5 μg/ml and 10 μg/ml were significant. These phenomena were highest at 10 μg/ml CD44 mAb concentrations. Synergistic induction differentiation and apoptosis of APL cells by using a co-treatment with novel triple compound are more effective for eradicating blasts and controlling the metastasis. Our results show that the addition of anti-CD44 mAb improves "ATRA-FICZ"-induced differentiation and has potential to reduce usual chemotherapy based treatments. Taken together, this compound may lead to novel clinical applications of differentiation-based approaches for APL and other types of leukemia. Further clinical studies would be recommended to clarify the clinical efficacy.
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Affiliation(s)
- Amir Amanzadeh
- National Cell Bank of Iran, Pasteur Institute of Iran, Tehran, Iran
| | | | - Saeed Samani
- Department of Tissue Engineering & Applied Cell Sciences, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | - Mohsen Abolhassani
- Department of Immunology, Hybridoma Laboratory, Pasteur Institute of Iran, Tehran, Iran
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Maschietto M, Tahira AC, Puga R, Lima L, Mariani D, Paulsen BDS, Belmonte-de-Abreu P, Vieira H, Krepischi AC, Carraro DM, Palha JA, Rehen S, Brentani H. Co-expression network of neural-differentiation genes shows specific pattern in schizophrenia. BMC Med Genomics 2015; 8:23. [PMID: 25981335 PMCID: PMC4493810 DOI: 10.1186/s12920-015-0098-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Accepted: 05/05/2015] [Indexed: 12/21/2022] Open
Abstract
Background Schizophrenia is a neurodevelopmental disorder with genetic and environmental factors contributing to its pathogenesis, although the mechanism is unknown due to the difficulties in accessing diseased tissue during human neurodevelopment. The aim of this study was to find neuronal differentiation genes disrupted in schizophrenia and to evaluate those genes in post-mortem brain tissues from schizophrenia cases and controls. Methods We analyzed differentially expressed genes (DEG), copy number variation (CNV) and differential methylation in human induced pluripotent stem cells (hiPSC) derived from fibroblasts from one control and one schizophrenia patient and further differentiated into neuron (NPC). Expression of the DEG were analyzed with microarrays of post-mortem brain tissue (frontal cortex) cohort of 29 schizophrenia cases and 30 controls. A Weighted Gene Co-expression Network Analysis (WGCNA) using the DEG was used to detect clusters of co-expressed genes that werenon-conserved between adult cases and controls brain samples. Results We identified methylation alterations potentially involved with neuronal differentiation in schizophrenia, which displayed an over-representation of genes related to chromatin remodeling complex (adjP = 0.04). We found 228 DEG associated with neuronal differentiation. These genes were involved with metabolic processes, signal transduction, nervous system development, regulation of neurogenesis and neuronal differentiation. Between adult brain samples from cases and controls there were 233 DEG, with only four genes overlapping with the 228 DEG, probably because we compared single cell to tissue bulks and more importantly, the cells were at different stages of development. The comparison of the co-expressed network of the 228 genes in adult brain samples between cases and controls revealed a less conserved module enriched for genes associated with oxidative stress and negative regulation of cell differentiation. Conclusion This study supports the relevance of using cellular approaches to dissect molecular aspects of neurogenesis with impact in the schizophrenic brain. We showed that, although generated by different approaches, both sets of DEG associated to schizophrenia were involved with neocortical development. The results add to the hypothesis that critical metabolic changes may be occurring during early neurodevelopment influencing faulty development of the brain and potentially contributing to further vulnerability to the illness. Electronic supplementary material The online version of this article (doi:10.1186/s12920-015-0098-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Mariana Maschietto
- LIM23 (Medical Investigation Laboratory 23), University of Sao Paulo Medical School (USP), São Paulo, SP, Brazil. .,Institute of Psychiatry-University of Sao Paulo, Medical School (FMUSP), São Paulo, SP, Brazil.
| | - Ana C Tahira
- LIM23 (Medical Investigation Laboratory 23), University of Sao Paulo Medical School (USP), São Paulo, SP, Brazil. .,Institute of Psychiatry-University of Sao Paulo, Medical School (FMUSP), São Paulo, SP, Brazil.
| | - Renato Puga
- Hospital Israelita Albert Einstein, São Paulo, Brazil.
| | - Leandro Lima
- Post-graduation Program Institute of Mathematics and Statistics, University of Sao Paulo, São Paulo, SP, Brazil.
| | - Daniel Mariani
- Post-graduation Program Institute of Mathematics and Statistics, University of Sao Paulo, São Paulo, SP, Brazil.
| | | | | | - Henrique Vieira
- Post-graduation Program Institute of Mathematics and Statistics, University of Sao Paulo, São Paulo, SP, Brazil.
| | - Ana Cv Krepischi
- Institute of Biosciences, University of São Paulo, São Paulo, SP, Brazil.
| | - Dirce M Carraro
- International Research Center-AC Camargo Cancer Center, São Paulo, Brazil.
| | - Joana A Palha
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal. .,ICVS/3B's-PT Government Associate Laboratory, Braga, Guimarães, Portugal.
| | - Stevens Rehen
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. .,D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil.
| | - Helena Brentani
- LIM23 (Medical Investigation Laboratory 23), University of Sao Paulo Medical School (USP), São Paulo, SP, Brazil. .,Institute of Psychiatry-University of Sao Paulo, Medical School (FMUSP), São Paulo, SP, Brazil. .,Department of Psychiatry, University of Sao Paulo, Medical School (FMUSP), Rua Dr Ovídio Pires de Campos,785-CEP 05403-010, São Paulo, SP, Caixa Postal n 3671, Brazil. .,National Institute of Developmental Psychiatry for Children and Adolescents, CNPq, São Paulo, SP, Brazil.
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