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Romo-Rodríguez R, Zamora-Herrera G, López-Blanco JA, López-García L, Rosas-Cruz A, Alfaro-Hernández L, Trejo-Pichardo CO, Alberto-Aguilar DR, Casique-Aguirre D, Vilchis-Ordoñez A, Solis-Poblano JC, García-Stivalet LA, Terán-Cerqueda V, Luna-Silva NC, Garrido-Hernández MÁ, Cano-Cuapio LS, Ayala-Contreras K, Domínguez F, del Campo-Martínez MDLÁ, Juárez-Avendaño G, Balandrán JC, Pérez-Tapia SM, Fernández-Giménez C, Zárate-Rodríguez PA, López-Aguilar E, Treviño-García A, Duque-Molina C, Bonifaz LC, Núñez-Enríquez JC, Cárdenas-González M, Álvarez-Buylla ER, Ramírez-Ramírez D, Pelayo R. Subclassification of B-acute lymphoblastic leukemia according to age, immunophenotype and microenvironment, predicts MRD risk in Mexican children from vulnerable regions. Front Oncol 2024; 13:1304662. [PMID: 38250553 PMCID: PMC10796993 DOI: 10.3389/fonc.2023.1304662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/01/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction The decisive key to disease-free survival in B-cell precursor acute lymphoblastic leukemia in children, is the combination of diagnostic timeliness and treatment efficacy, guided by accurate patient risk stratification. Implementation of standardized and high-precision diagnostic/prognostic systems is particularly important in the most marginalized geographic areas in Mexico, where high numbers of the pediatric population resides and the highest relapse and early death rates due to acute leukemias are recorded even in those cases diagnosed as standard risk. Methods By using a multidimensional and integrated analysis of the immunophenotype of leukemic cells, the immunological context and the tumor microenvironment, this study aim to capture the snapshot of acute leukemia at disease debut of a cohort of Mexican children from vulnerable regions in Puebla, Oaxaca and Tlaxcala and its potential use in risk stratification. Results and discussion Our findings highlight the existence of a distinct profile of ProB-ALL in children older than 10 years, which is associated with a six-fold increase in the risk of developing measurable residual disease (MRD). Along with the absence of CD34+ seminal cells for normal hematopoiesis, this ProB-ALL subtype exhibited several characteristics related to poor prognosis, including the high expression level of myeloid lineage markers such as MPO and CD33, as well as upregulation of CD19, CD34, CD24, CD20 and nuTdT. In contrast, it showed a trend towards decreased expression of CD9, CD81, CD123, CD13, CD15 and CD21. Of note, the mesenchymal stromal cell compartment constituting their leukemic niche in the bone marrow, displayed characteristics of potential suppressive microenvironment, such as the expression of Gal9 and IDO1, and the absence of the chemokine CXCL11. Accordingly, adaptive immunity components were poorly represented. Taken together, our results suggest, for the first time, that a biologically distinct subtype of ProB-ALL emerges in vulnerable adolescents, with a high risk of developing MRD. Rigorous research on potential enhancing factors, environmental or lifestyle, is crucial for its detection and prevention. The use of the reported profile for early risk stratification is suggested.
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Affiliation(s)
- Rubí Romo-Rodríguez
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Gabriela Zamora-Herrera
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Instituto de Fisiología, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - Jebea A. López-Blanco
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Lucero López-García
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Arely Rosas-Cruz
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Laura Alfaro-Hernández
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico
| | - César Omar Trejo-Pichardo
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Dulce Rosario Alberto-Aguilar
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT), Mexico City, Mexico
| | - Diana Casique-Aguirre
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT), Mexico City, Mexico
| | - Armando Vilchis-Ordoñez
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Hospital Infantil de México ‘Federico Gómez’, Secretaría de Salud, Mexico City, Mexico
| | - Juan Carlos Solis-Poblano
- Servicio de Hematología, Unidad Médica de Alta Especialidad, Hospital de Especialidades “Manuel Avila Camacho”, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Lilia Adela García-Stivalet
- Servicio de Hematología, Unidad Médica de Alta Especialidad, Hospital de Especialidades “Manuel Avila Camacho”, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Vanessa Terán-Cerqueda
- Servicio de Hematología, Unidad Médica de Alta Especialidad, Hospital de Especialidades “Manuel Avila Camacho”, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | | | | | | | - Karen Ayala-Contreras
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Fabiola Domínguez
- Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | | | | | - Juan Carlos Balandrán
- Department of Pathology, New York University (NYU) School of Medicine, New York, NY, United States
| | - Sonia Mayra Pérez-Tapia
- Unidad de Desarrollo e Investigación en Bioterapéuticos (UDIBI), Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City, Mexico
| | - Carlos Fernández-Giménez
- Cancer Research Center-Instituto de Biología Molecular y Celular del Cáncer-Universidad de Salamanca-Centro Superior de Investigaciones Científicas (IBMCC-USAL-CSIC), Department of Medicine and Cytometry Service-Nucleus Platform, Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Biomedical Research Institute of Salamanca (IBSAL), University of Salamanca, Salamanca, Spain
| | | | - Enrique López-Aguilar
- Coordinación de Atención Oncológica, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Aurora Treviño-García
- Organo de Operación Administrativa Desconcentrada, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Célida Duque-Molina
- Dirección de Prestaciones Médicas, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Laura C. Bonifaz
- Coordinación de Investigación en Salud, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Juan Carlos Núñez-Enríquez
- Unidad Médica de Alta Especialidad (UMAE) Hospital de Pediatría “Dr. Silvestre Frenk Freund” Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | | | | | - Dalia Ramírez-Ramírez
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
| | - Rosana Pelayo
- Laboratorio de Citómica del Cáncer Infantil, Centro de Investigación Biomédica de Oriente, Instituto Mexicano del Seguro Social, Puebla, Mexico
- Unidad de Educación e Investigación, Instituto Mexicano del Seguro Social, Mexico City, Mexico
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Li X, Chen Y, Wang T, Liu Z, Yin G, Wang Z, Sui C, Zhu L, Chen W. GPR81-mediated reprogramming of glucose metabolism contributes to the immune landscape in breast cancer. Discov Oncol 2023; 14:140. [PMID: 37500811 PMCID: PMC10374510 DOI: 10.1007/s12672-023-00709-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/31/2023] [Indexed: 07/29/2023] Open
Abstract
BACKGROUND Local tumor microenvironment (TME) plays a crucial role in immunotherapy for breast cancer (BC). Whereas, the molecular mechanism responsible for the crosstalk between BC cells and surrounding immune cells remains unclear. The present study aimed to determine the interplay between GPR81-mediated glucometabolic reprogramming of BC and the immune landscape in TME. MATERIALS AND METHODS Immunohistochemistry (IHC) assay was first performed to evaluate the association between GPR81 and the immune landscape. Then, several stable BC cell lines with down-regulated GPR81 expression were established to directly identify the role of GPR81 in glucometabolic reprogramming, and western blotting assay was used to detect the underlying molecular mechanism. Finally, a transwell co-culture system confirmed the crosstalk between glucometabolic regulation mediated by GPR81 in BC and induced immune attenuation. RESULTS IHC analysis demonstrated that the representation of infiltrating CD8+ T cells and FOXP3+ T cells were dramatically higher in BC with a triple negative (TN) subtype in comparison with that with a non-TN subtype (P < 0.001). Additionally, the ratio of infiltrating CD8+ to FOXP3+ T cells was significantly negatively associated with GPR81 expression in BC with a TN subtype (P < 0.001). Furthermore, GPR81 was found to be substantially correlated with the glycolytic capability (P < 0.001) of BC cells depending on a Hippo-YAP signaling pathway (P < 0.001). In the transwell co-culture system, GPR81-mediated reprogramming of glucose metabolism in BC significantly contributed to a decreased proportion of CD8+ T (P < 0.001) and an increased percentage of FOXP3+ T (P < 0.001) in the co-cultured lymphocytes. CONCLUSION Glucometabolic reprogramming through a GPR81-mediated Hippo-YAP signaling pathway was responsible for the distinct immune landscape in BC. GPR81 was a potential biomarker to stratify patients before immunotherapy to improve BC's clinical prospect.
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Affiliation(s)
- Xiaofeng Li
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yiwen Chen
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ting Wang
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Zifan Liu
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Guotao Yin
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ziyang Wang
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Cancer Hospital Airport Hospital, Tianjin, China
| | - Chunxiao Sui
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Lei Zhu
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Wei Chen
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Molecular Imaging and Nuclear Medicine,Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
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Gou Q, Liu Z, Xie Y, Deng Y, Ma J, Li J, Zheng H. Systematic evaluation of tumor microenvironment and construction of a machine learning model to predict prognosis and immunotherapy efficacy in triple-negative breast cancer based on data mining and sequencing validation. Front Pharmacol 2022; 13:995555. [PMID: 36225561 PMCID: PMC9548553 DOI: 10.3389/fphar.2022.995555] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The role of the tumor microenvironment (TME) in predicting prognosis and therapeutic efficacy has been demonstrated. Nonetheless, no systematic studies have focused on TME patterns or their function in the effectiveness of immunotherapy in triple-negative breast cancer. Methods: We comprehensively estimated the TME infiltration patterns of 491 TNBC patients from four independent cohorts, and three cohorts that received immunotherapy were used for validation. The TME subtypes were comprehensively evaluated based on immune cell infiltration levels in TNBC, and the TRG score was identified and systematically correlated with representative tumor characteristics. We sequenced 80 TNBC samples as an external validation cohort to make our conclusions more convincing. Results: Two TME subtypes were identified and were highly correlated with immune cell infiltration levels and immune-related pathways. More representative TME-related gene (TRG) scores calculated by machine learning could reflect the fundamental characteristics of TME subtypes and predict the efficacy of immunotherapy and the prognosis of TNBC patients. A low TRG score, characterized by activation of immunity and ferroptosis, indicated an activated TME phenotype and better prognosis. A low TRG score showed a better response to immunotherapy in TNBC by TIDE (Tumor Immune Dysfunction and Exclusion) analysis and sensitivity to multiple drugs in GDSC (Genomics of Drug Sensitivity in Cancer) analysis and a significant therapeutic advantage in patients in the three immunotherapy cohorts. Conclusion: TME subtypes played an essential role in assessing the diversity and complexity of the TME in TNBC. The TRG score could be used to evaluate the TME of an individual tumor to enhance our understanding of the TME and guide more effective immunotherapy strategies.
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Affiliation(s)
- Qiheng Gou
- Department of Medical Oncology of Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Molecular Diagnosis of Cancer, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zijian Liu
- Department of Medical Oncology of Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yuxin Xie
- Department of Medical Oncology of Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Molecular Diagnosis of Cancer, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- *Correspondence: Yuxin Xie,
| | - Yulan Deng
- Department of Medical Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Ji Ma
- Department of Medical Oncology of Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Jiangping Li
- Institute of Thoracic Oncology and Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Hong Zheng
- Department of Medical Oncology of Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Laboratory of Molecular Diagnosis of Cancer, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Staros R, Michalak A, Rusinek K, Mucha K, Pojda Z, Zagożdżon R. Perspectives for 3D-Bioprinting in Modeling of Tumor Immune Evasion. Cancers (Basel) 2022; 14:cancers14133126. [PMID: 35804898 PMCID: PMC9265021 DOI: 10.3390/cancers14133126] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 05/31/2022] [Accepted: 06/23/2022] [Indexed: 02/07/2023] Open
Abstract
In a living organism, cancer cells function in a specific microenvironment, where they exchange numerous physical and biochemical cues with other cells and the surrounding extracellular matrix (ECM). Immune evasion is a clinically relevant phenomenon, in which cancer cells are able to direct this interchange of signals against the immune effector cells and to generate an immunosuppressive environment favoring their own survival. A proper understanding of this phenomenon is substantial for generating more successful anticancer therapies. However, classical cell culture systems are unable to sufficiently recapture the dynamic nature and complexity of the tumor microenvironment (TME) to be of satisfactory use for comprehensive studies on mechanisms of tumor immune evasion. In turn, 3D-bioprinting is a rapidly evolving manufacture technique, in which it is possible to generate finely detailed structures comprised of multiple cell types and biomaterials serving as ECM-analogues. In this review, we focus on currently used 3D-bioprinting techniques, their applications in the TME research, and potential uses of 3D-bioprinting in modeling of tumor immune evasion and response to immunotherapies.
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Affiliation(s)
- Rafał Staros
- Department of Immunology, Transplantation and Internal Medicine, Medical University of Warsaw, 02-006 Warsaw, Poland; (R.S.); (K.M.)
| | - Agata Michalak
- Department of Regenerative Medicine, Maria Sklodowska-Curie National Institute of Oncology, 02-781 Warsaw, Poland; (A.M.); (K.R.); (Z.P.)
| | - Kinga Rusinek
- Department of Regenerative Medicine, Maria Sklodowska-Curie National Institute of Oncology, 02-781 Warsaw, Poland; (A.M.); (K.R.); (Z.P.)
| | - Krzysztof Mucha
- Department of Immunology, Transplantation and Internal Medicine, Medical University of Warsaw, 02-006 Warsaw, Poland; (R.S.); (K.M.)
| | - Zygmunt Pojda
- Department of Regenerative Medicine, Maria Sklodowska-Curie National Institute of Oncology, 02-781 Warsaw, Poland; (A.M.); (K.R.); (Z.P.)
| | - Radosław Zagożdżon
- Department of Immunology, Transplantation and Internal Medicine, Medical University of Warsaw, 02-006 Warsaw, Poland; (R.S.); (K.M.)
- Department of Regenerative Medicine, Maria Sklodowska-Curie National Institute of Oncology, 02-781 Warsaw, Poland; (A.M.); (K.R.); (Z.P.)
- Department of Clinical Immunology, Medical University of Warsaw, 02-006 Warsaw, Poland
- Correspondence: ; Tel.: +48-22-502-14-72; Fax: +48-22-502-21-59
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