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Pershina OV, Ermakova NN, Pakhomova AV, Pan ES, Sandrikina LA, Zhukova MA, Kogai LV, Dygai AM, Skurikhin EG. Age-Related Features of the Response of Cancer Stem Cells and T Cells in Experimental Lung Cancer. Bull Exp Biol Med 2024; 176:486-490. [PMID: 38492106 DOI: 10.1007/s10517-024-06052-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Indexed: 03/18/2024]
Abstract
The responses of tumor stem cells and various populations of CD4 and CD8 T cells of young and aged C57BL/6 mice were studied in a lung cancer model. Using Lewis lung carcinoma cell line, an orthotopic model of lung cancer was modeled. Cancer stem cells, circulating tumor cells, and various populations of CD4 and CD8 T cells in the blood and lung tissue were studied by cytometry. We revealed age-related differences in the content of various populations of CD4 and CD8 T cells in the blood and lungs of intact young and aged mice. Age-related features of the reaction of various populations of cancer stem cells and CD4 and CD8 T cells in the blood and lungs of animals in the Lewis lung carcinoma were shown.
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Affiliation(s)
- O V Pershina
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia.
| | - N N Ermakova
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - A V Pakhomova
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - E S Pan
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - L A Sandrikina
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - M A Zhukova
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - L V Kogai
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - A M Dygai
- Laboratory of Regenerative Pharmacology, E. D. Goldberg Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
- Research Institute of General Pathology and Pathophysiology, Moscow, Russia
| | - E G Skurikhin
- Research Institute of General Pathology and Pathophysiology, Moscow, Russia
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Ma W, Wei S, Long S, Tian EC, McLaughlin B, Jaimes M, Montoya DJ, Viswanath VR, Chien J, Zhang Q, Van Dyke JE, Chen S, Li T. Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry. Front Immunol 2023; 14:1206631. [PMID: 37638022 PMCID: PMC10449448 DOI: 10.3389/fimmu.2023.1206631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 07/20/2023] [Indexed: 08/29/2023] Open
Abstract
Introduction Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients. Methods PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis. Results Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively. Conclusion Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.
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Affiliation(s)
- Weijie Ma
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
- Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine, Dartmouth, NH, United States
| | - Sixi Wei
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Siqi Long
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Eddie C. Tian
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Bridget McLaughlin
- University of California Davis, Flow cytometry Shared Resource, Davis, CA, United States
| | | | - Dennis J. Montoya
- Department of Biochemistry and Molecular Medicine, University of California Davis, Sacramento, CA, United States
| | - Varun R. Viswanath
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
| | - Jeremy Chien
- Department of Biochemistry and Molecular Medicine, University of California Davis, Sacramento, CA, United States
| | - Qianjun Zhang
- Beckman Coulter Life Sciences, San Jose, CA, United States
| | - Jonathan E. Van Dyke
- University of California Davis, Flow cytometry Shared Resource, Davis, CA, United States
| | - Shuai Chen
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, Davis, CA, United States
| | - Tianhong Li
- Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis Comprehensive Cancer Center, University of California Davis School of Medicine, Sacramento, CA, United States
- Medical Service, Hematology and Oncology, Veterans Affairs Northern California Health Care System, Mather, CA, United States
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Nelli F, Signorelli C, Fabbri A, Giannarelli D, Virtuoso A, Giron Berrios JR, Marrucci E, Fiore C, Schirripa M, Chilelli MG, Primi F, Panichi V, Topini G, Silvestri MA, Ruggeri EM. Changes in Peripheral Immune Cells after the Third Dose of SARS-CoV-2 mRNA-BNT162b2 Vaccine and Disease Outcomes in Cancer Patients Receiving Immune Checkpoint Inhibitors: A Prospective Analysis of the Vax-on-Third-Profile Study. Cancers (Basel) 2023; 15:3625. [PMID: 37509286 PMCID: PMC10377319 DOI: 10.3390/cancers15143625] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 07/03/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Anti-SARS-CoV-2 mRNA vaccines can deeply affect cell-mediated immune responses in immunocompromised recipients, including cancer patients receiving active treatments. The clinical implications of changes in peripheral blood lymphocyte subsets following the third dose of mRNA-BNT162b2 vaccination (tozinameran) in patients on immune checkpoint blockade are not fully understood. We conducted a prospective analysis of the Vax-On-Third-Profile study to evaluate the impact of circulating lymphocyte dynamics on disease outcomes in this subgroup of patients. METHODS Recipients of booster dosing who had received before vaccination at least one course of an anti-PD-1/PD-L1 treatment for an advanced solid tumor were eligible. Immunophenotyping of peripheral blood was performed before the third dose of tozinameran (timepoint-1) and four weeks later (timepoint-2) to quantify the absolute counts of lymphocyte subpopulations, including CD3+CD4+ T cells, CD3+CD8+ T cells, B cells, and NK cells. Logistic regression was used to analyze the relationship between lymphocyte subsets and durable clinical benefit (DCB). The log-rank test and Cox regression model were applied to evaluate the relationship between lymphocyte subpopulations and both vaccine-related time-to-treatment failure (V-TTF) and overall survival (OS). RESULTS We included a total of 56 patients with metastatic disease who were given a third dose of tozinameran between 23 September and 7 October 2021 (median age: 66 years; male: 71%). Most recipients had a diagnosis of lung cancer and were being treated with pembrolizumab or nivolumab. Compared to baseline, the third immunization resulted in an incremental change in the median counts of all lymphocyte subpopulations, which was statistically significant only for NK cells (p < 0.001). A significant correlation was found between NK cell counts and DCB at timepoint-2 (p < 0.001). Multivariate logistic regression analysis of DCB confirmed the predictive significance of high-level NK cell counts (p = 0.020). In multivariate Cox regression analysis, high-level NK cell counts independently predicted longer V-TTF [HR 0.34 (95% CI 0.14-0.80), p = 0.014] and OS [HR 0.36 (95% CI 0.15-0.89), p = 0.027]. CONCLUSIONS Our data suggest expansion of NK cell counts as the most noteworthy change in circulating lymphocytes after the third dose of tozinameran in cancer patients receiving PD-1/PD-L1-targeted agents. This change correlated with enhanced therapeutic efficacy, improving the rate of disease control, and prolonging survival outcomes. Similar findings have not been previously reported, implying that they have proof-of-concept value and warrant further confirmation.
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Affiliation(s)
- Fabrizio Nelli
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
- Thoracic Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Carlo Signorelli
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Agnese Fabbri
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Diana Giannarelli
- Biostatistics Unit, Scientific Directorate, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy
| | - Antonella Virtuoso
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
- Thoracic Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Julio Rodrigo Giron Berrios
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Eleonora Marrucci
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Cristina Fiore
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Marta Schirripa
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Mario Giovanni Chilelli
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Francesca Primi
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Valentina Panichi
- Cytofluorimetry Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Giuseppe Topini
- Cytofluorimetry Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Maria Assunta Silvestri
- Microbiology and Virology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
| | - Enzo Maria Ruggeri
- Medical Oncology Unit, Department of Oncology and Hematology, Central Hospital of Belcolle, 01100 Viterbo, Italy
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Geng R, Tang H, You T, Xu X, Li S, Li Z, Liu Y, Qiu W, Zhou N, Li N, Ge Y, Guo F, Sun Y, Wang Y, Li T, Bai C. Peripheral CD8+CD28+ T lymphocytes predict the efficacy and safety of PD-1/PD-L1 inhibitors in cancer patients. Front Immunol 2023; 14:1125876. [PMID: 36969245 PMCID: PMC10038730 DOI: 10.3389/fimmu.2023.1125876] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/21/2023] [Indexed: 03/12/2023] Open
Abstract
BackgroundProgrammed cell death protein-1/programmed cell death ligand-1 (PD-1/PD-L1) inhibitors works by reactivating immune cells. Considering the accessibility of noninvasive liquid biopsies, it is advisable to employ peripheral blood lymphocyte subsets to predict immunotherapy outcomes.MethodsWe retrospectively enrolled 87 patients with available baseline circulating lymphocyte subset data who received first-line PD-1/PD-L1 inhibitors at Peking Union Medical College Hospital between May 2018 and April 2022. Immune cell counts were determined by flow cytometry.ResultsPatients who responded to PD-1/PD-L1 inhibitors had significantly higher circulating CD8+CD28+ T-cell counts (median [range] count: 236 [30-536] versus 138 [36-460]/μL, p < 0.001). Using 190/μL as the cutoff value, the sensitivity and specificity of CD8+CD28+ T cells for predicting immunotherapy response were 0.689 and 0.714, respectively. Furthermore, the median progression-free survival (PFS, not reached versus 8.7 months, p < 0.001) and overall survival (OS, not reached versus 16.2 months, p < 0.001) were significantly longer in the patients with higher CD8+CD28+ T-cell counts. However, the CD8+CD28+ T-cell level was also associated with the incidence of grade 3-4 immune-related adverse events (irAEs). The sensitivity and specificity of CD8+CD28+ T cells for predicting irAEs of grade 3-4 were 0.846 and 0.667, respectively, at the threshold of CD8+CD28+ T cells ≥ 309/μL.ConclusionsHigh circulating CD8+CD28+ T-cell levels is a potential biomarker for immunotherapy response and better prognosis, while excessive CD8+CD28+ T cells (≥ 309/μL) may also indicate the emergence of severe irAEs.
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Affiliation(s)
- Ruixuan Geng
- Department of International Medical Services, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hui Tang
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tingting You
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiuxiu Xu
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Sijian Li
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Clinical Research Center for Obstetric and Gynecologic Diseases, Beijing, China
| | - Zepeng Li
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuan Liu
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Qiu
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Na Zhou
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ningning Li
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuping Ge
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fuping Guo
- Department of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuhong Sun
- Department of Radiation Oncology, Dandong First Hospital, Dandong, Liaoning, China
| | - Yingyi Wang
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Yingyi Wang, ; Taisheng Li,
| | - Taisheng Li
- Department of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Yingyi Wang, ; Taisheng Li,
| | - Chunmei Bai
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Riemann D, Turzer S, Ganchev G, Schütte W, Seliger B, Möller M. Monitoring Blood Immune Cells in Patients with Advanced Small Cell Lung Cancer Undergoing a Combined Immune Checkpoint Inhibitor/Chemotherapy. Biomolecules 2023; 13:biom13020190. [PMID: 36830562 PMCID: PMC9953684 DOI: 10.3390/biom13020190] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 01/18/2023] Open
Abstract
In this exploratory prospective observational study on 40 small cell lung cancer (SCLC) patients treated with a combination of chemotherapy and immune checkpoint inhibitors, blood immune cells were characterized by multi-color flow cytometry at the baseline and at the third therapy cycle. The numbers of neutrophils and of T-, B-, and NK cells, as well as the frequency of HLA-DRlow monocytes, 6-SulfoLacNAc (slan)+ non-classical monocytes and circulating dendritic cell (DC) subtypes were determined. The prognostic value of the parameters was evaluated by the patient's survival analysis with overall survival (OS) as the primary endpoint. In addition, blood cell parameters from SCLC patients were compared to those from non-SCLC (NSCLC). The global median OS of patients was 10.4 ± 1.1 months. Disease progression (15% of patients) correlated with a higher baseline neutrophil/lymphocyte ratio (NLR), more HLA-DRlow monocytes, and lower NK cell and DC numbers. The risk factors for poor OS were the presence of brain/liver metastases, a baseline NLR ≥ 6.1, HLA-DRlow monocytes ≥ 21% of monocytes, slan+ non-classical monocytes < 0.12%, and/or CD1c+ myeloid DC < 0.05% of leukocytes. Lymphocytic subpopulations did not correlate with OS. When comparing biomarkers in SCLC versus NSCLC, SCLC had a higher frequency of brain/liver metastases, a higher NLR, the lowest DC frequencies, and lower NK cell numbers. Brain/liver metastases had a substantial impact on the survival of SCLC patients. At the baseline, 45% of SCLC patients, but only 24% of NSCLC patients, had between three and five risk factors. A high basal NLR, a high frequency of HLA-DRlow monocytes, and low levels of slan+ non-classical monocytes were associated with poor survival in all lung cancer histotypes. Thus, the blood immune cell signature might contribute to a better prediction of SCLC patient outcomes and may uncover the pathophysiological peculiarities of this tumor entity.
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Affiliation(s)
- Dagmar Riemann
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
- Correspondence: ; Tel.: +49-345-5571358
| | - Steffi Turzer
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
| | - Georgi Ganchev
- Clinic of Internal Medicine, Hospital Martha-Maria Halle-Dölau, 06120 Halle, Germany
| | - Wolfgang Schütte
- Clinic of Internal Medicine, Hospital Martha-Maria Halle-Dölau, 06120 Halle, Germany
| | - Barbara Seliger
- Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
| | - Miriam Möller
- Clinic of Internal Medicine, Hospital Martha-Maria Halle-Dölau, 06120 Halle, Germany
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Cell Therapy with Human Reprogrammed CD8 + T-Cells Has Antimetastatic Effects on Lewis Lung Carcinoma in C57BL/6 Mice. Int J Mol Sci 2022; 23:ijms232415780. [PMID: 36555420 PMCID: PMC9779156 DOI: 10.3390/ijms232415780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/28/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Using a model of Lewis lung carcinoma (LLC) in vitro and in vivo, we previously demonstrated increased antitumor activity in CD8+ T-cells reprogrammed with an MEK inhibitor and PD-1 blocker. In this follow-up study, we carried out the reprogramming of human CD8+ T-cells (hrT-cell) using the MEK inhibitor and PD-1 blocker and targeted LLC cells. The effects of hrT-cell therapy were studied in a mouse model of spontaneous metastasis of a solid LLC tumor. We found antimetastatic activity of hrT-cells, a decrease in the number of cancer cells and cancer stem cells in the lungs, and an increase in the number of T-cells in the blood (including effector T-cells). Thus, reprogramming of human CD8+ T-cells with an MEK inhibitor and PD-1 blocker with targeted training by tumor target cells is a potential platform for developing a new approach to targeted lung cancer therapy.
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Emerging Immune-Monitoring System for Immune Checkpoint Inhibitors. LIFE (BASEL, SWITZERLAND) 2022; 12:life12081229. [PMID: 36013407 PMCID: PMC9410458 DOI: 10.3390/life12081229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/06/2022] [Accepted: 08/09/2022] [Indexed: 11/17/2022]
Abstract
Immune checkpoint inhibitors (ICIs) have a major impact on cancer treatment. However, the therapeutic efficacy of ICIs is only effective in some patients. Programmed death ligand 1 (PD-L1), tumor mutation burden (TMB), and high-frequency microsatellite instability (MSI-high) are markers that predict the efficacy of ICIs but are not universally used in many carcinomas. The gut microbiota has received much attention recently because of its potential to have a significant impact on immune cells in the cancer microenvironment. Metabolites of the gut microbiota modulate immunity and have a strong influence on the therapeutic efficacy of ICI. It has been suggested that the gut microbiota may serve as a novel marker to predict the therapeutic efficacy of ICI. Therefore, there is an urgent need to develop biomarkers that can predict anti-tumor effects and adverse events, and the study of the gut microbiota is essential in this regard.
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Nelli F, Panichi V, Fabbri A, Natoni F, Giannarelli D, Topini G, Virtuoso A, Giron Berrios JR, Marrucci E, Pessina G, Silvestri MA, Ruggeri EM. Dynamic Changes of Peripheral NK Cells Predict Outcome in Patients with PD-L1 Positive Non-small-cell Lung Cancer Undergoing Immune Checkpoint Inhibitors as Second-line Therapy. Cancer Invest 2022; 40:710-721. [PMID: 35736808 DOI: 10.1080/07357907.2022.2092635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
We evaluated immune cell frequencies in peripheral blood samples of 41 NSCLC patients before and after second-line therapy with anti-PD-1/PD-L1 agents. Changes in lymphocyte subsets and their correlation with clinical response, progression-free survival (PFS), and overall survival (OS) were analyzed. We observed an increase in median values of all lymphocyte subsets, being significant only for NK cells. A correlation was retrieved between higher post-treatment NK cell level and clinical benefit. On multivariate analysis, PD-L1 tumor proportion score ≥1% and higher post-treatment NK cell counts were predictive of longer PFS and OS. Co-presence of these factors was characterized by longer survival.
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Affiliation(s)
- Fabrizio Nelli
- Department of Oncology and Hematology, Medical Oncology, Central Hospital of Belcolle, Viterbo, Italy
| | - Valentina Panichi
- Department of Oncology and Hematology, Flow Cytometry, Central Hospital of Belcolle, Viterbo, Italy
| | - Agnese Fabbri
- Department of Oncology and Hematology, Medical Oncology, Central Hospital of Belcolle, Viterbo, Italy
| | - Federica Natoni
- Department of Oncology and Hematology, Molecular Biology, Central Hospital of Belcolle, Viterbo, Italy
| | - Diana Giannarelli
- Biostatistics Unit, Scientific Directorate, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy
| | - Giuseppe Topini
- Department of Oncology and Hematology, Flow Cytometry, Central Hospital of Belcolle, Viterbo, Italy
| | - Antonella Virtuoso
- Department of Oncology and Hematology, Medical Oncology, Central Hospital of Belcolle, Viterbo, Italy
| | | | - Eleonora Marrucci
- Department of Oncology and Hematology, Medical Oncology, Central Hospital of Belcolle, Viterbo, Italy
| | - Gloria Pessina
- Department of Oncology and Hematology, Molecular Biology, Central Hospital of Belcolle, Viterbo, Italy
| | - Maria Assunta Silvestri
- Department of Oncology and Hematology, Flow Cytometry, Central Hospital of Belcolle, Viterbo, Italy
| | - Enzo Maria Ruggeri
- Department of Oncology and Hematology, Medical Oncology, Central Hospital of Belcolle, Viterbo, Italy
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Zhu M, Li X, Cheng X, Yi X, Ye F, Li X, Hu Z, Zhang L, Nie J, Li X. Association of the tissue infiltrated and peripheral blood immune cell subsets with response to radiotherapy for rectal cancer. BMC Med Genomics 2022; 15:107. [PMID: 35534879 PMCID: PMC9082952 DOI: 10.1186/s12920-022-01252-6] [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: 04/26/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Background Tumor microenvironment plays pivotal roles in carcinogenesis, cancer development and metastasis. Composition of cancer immune cell subsets can be inferred by deconvolution of gene expression profile accurately. Compositions of the cell types in cancer microenvironment including cancer infiltrating immune and stromal cells have been reported to be associated with the cancer outcomes markers for cancer prognosis. However, rare studies have been reported on their association with the response to preoperative radiotherapy for rectal cancer. Methods In this paper, we deconvoluted the immune/stromal cell composition from the gene expression profiles. We compared the composition of immune/stromal cell types in the RT responsive versus nonresponsive for rectal cancer. We also compared the peripheral blood immune cell subset composition in the stable diseases versus progressive diseases of rectal cancer patients with fluorescence-activated cell sorting from our institution. Results Compared with the non-responsive group, the responsive group showed higher proportions of CD4+ T cell (0.1378 ± 0.0368 vs. 0.1071 ± 0.0373, p = 0.0215), adipocytes, T cells CD4 memory resting, and lower proportions of CD8+ T cell (0.1798 ± 0.0217 vs. 0.2104 ± 0.0415, p = 0.0239), macrophages M2, and preadipocytes in their cancer tissue. The responsive patients showed a higher ratio of CD4+/CD8+ T cell proportions (mean 0.7869 vs. 0.5564, p = 0.0210). Consistently, the peripheral blood dataset showed higher proportion of CD4+ T cells and higher ratio of CD4+/CD8+ T cells, and lower proportion of CD8+ T cells for favorable prognosis. We validated these results with a pooled dataset of GSE3493 and GSE35452, and more peripheral blood data, respectively. Finally, we imported these eight cell features including eosinophils and macrophage M1 to Support Vector Machines and could predict the pre-radiotherapy responsive versus non-responsive with an accuracy of 76%, ROC AUC 0.77, 95% confidential interval of 0.632–0.857, better than the gene signatures. Conclusions Our results showed that the proportions of tumor-infiltrating subsets and peripheral blood immune cell subsets can be important immune cell markers and treatment targets for outcomes of radiotherapy for rectal cancer. Supplementary Information The online version contains supplementary material available at 10.1186/s12920-022-01252-6.
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Affiliation(s)
- Min Zhu
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 350 Shushanhu Road, Hefei, 230031, People's Republic of China.,Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China
| | - Xingjie Li
- Institute of Physical Science and Information Technology, Anhui University, 111 Jiulong Road, Hefei, 230601, People's Republic of China
| | - Xu Cheng
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China
| | - Xingxu Yi
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China
| | - Fang Ye
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China
| | - Xiaolai Li
- Hefei Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 350 Shushanhu Road, Hefei, 230031, People's Republic of China
| | - Zongtao Hu
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China
| | - Liwei Zhang
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China.
| | - Jinfu Nie
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 350 Shushanhu Road, Hefei, 230031, People's Republic of China. .,Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China.
| | - Xueling Li
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 350 Shushanhu Road, Hefei, 230031, People's Republic of China. .,Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, People's Republic of China.
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10
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Cancer Immunology: From Molecular Mechanisms to Therapeutic Opportunities. Cells 2022; 11:cells11030459. [PMID: 35159269 PMCID: PMC8834057 DOI: 10.3390/cells11030459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 01/25/2022] [Indexed: 02/01/2023] Open
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11
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Skurikhin E, Pershina O, Zhukova M, Widera D, Ermakova N, Pan E, Pakhomova A, Morozov S, Kubatiev A, Dygai A. Potential of Stem Cells and CART as a Potential Polytherapy for Small Cell Lung Cancer. Front Cell Dev Biol 2021; 9:778020. [PMID: 34926461 PMCID: PMC8678572 DOI: 10.3389/fcell.2021.778020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 11/18/2021] [Indexed: 12/15/2022] Open
Abstract
Despite the increasing urgency of the problem of treating small cell lung cancer (SCLC), information on the causes of its development is fragmentary. There is no complete understanding of the features of antitumor immunity and the role of the microenvironment in the development of SCLC resistance. This impedes the development of new methods for the diagnosis and treatment of SCLC. Lung cancer and chronic obstructive pulmonary disease (COPD) have common pathogenetic factors. COPD is a risk factor for lung cancer including SCLC. Therefore, the search for effective approaches to prevention, diagnosis, and treatment of SCLC in patients with COPD is an urgent task. This review provides information on the etiology and pathogenesis of SCLC, analyses the effectiveness of current treatment options, and critically evaluates the potential of chimeric antigen receptor T cells therapy (CART therapy) in SCLC. Moreover, we discuss potential links between lung cancer and COPD and the role of endothelium in the development of COPD. Finally, we propose a new approach for increasing the efficacy of CART therapy in SCLC.
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Affiliation(s)
- Evgenii Skurikhin
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
- *Correspondence: Evgenii Skurikhin,
| | - Olga Pershina
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
| | - Mariia Zhukova
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
| | - Darius Widera
- Stem Cell Biology and Regenerative Medicine Group, School of Pharmacy, University of Reading, Reading, United Kingdom
| | - Natalia Ermakova
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
| | - Edgar Pan
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
| | - Angelina Pakhomova
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
| | - Sergey Morozov
- Institute of General Pathology and Pathophysiology, Moscow, Russia
| | - Aslan Kubatiev
- Institute of General Pathology and Pathophysiology, Moscow, Russia
| | - Alexander Dygai
- Laboratory of Regenerative Pharmacology, Goldberg ED Research Institute of Pharmacology and Regenerative Medicine, Tomsk National Research Medical Centre of the Russian Academy of Sciences, Tomsk, Russia
- Institute of General Pathology and Pathophysiology, Moscow, Russia
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12
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Yu X, Wang Z, Chen Y, Yin G, Liu J, Chen W, Zhu L, Xu W, Li X. The Predictive Role of Immune Related Subgroup Classification in Immune Checkpoint Blockade Therapy for Lung Adenocarcinoma. Front Genet 2021; 12:771830. [PMID: 34721552 PMCID: PMC8554034 DOI: 10.3389/fgene.2021.771830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 09/30/2021] [Indexed: 01/17/2023] Open
Abstract
Background: In lung adenocarcinoma (LUAD), the predictive role of immune-related subgroup classification in immune checkpoint blockade (ICB) therapy remains largely incomplete. Methods: Transcriptomics analysis was performed to evaluate the association between immune landscape and ICB therapy in lung adenocarcinoma and the associated underlying mechanism. First, the least absolute shrinkage and selection operator (LASSO) algorithm and K-means algorithm were used to identify immune related subgroups for LUAD cohort from the Cancer Genome Atlas (TCGA) database (n = 572). Second, the immune associated signatures of the identified subgroups were characterized by evaluating the status of immune checkpoint associated genes and the immune cell infiltration. Then, potential responses to ICB therapy based on the aforementioned immune related subgroup classification were evaluated via tumor immune dysfunction and exclusion (TIDE) algorithm analysis, and survival analysis and further Cox proportional hazards regression analysis were also performed for LUAD. In the end, gene set enrichment analysis (GSEA) was performed to explore the metabolic mechanism potentially responsible for immune related subgroup clustering. Additionally, two LUAD cohorts from the Gene Expression Omnibus (GEO) database were used as validation cohort. Results: A total of three immune related subgroups with different immune-associated signatures were identified for LUAD. Among them, subgroup 1 with higher infiltration scores for effector immune cells and immune checkpoint associated genes exhibited a potential response to IBC therapy and a better survival, whereas subgroup 3 with lower scores for immune checkpoint associated genes but higher infiltration scores for suppressive immune cells tended to be insensitive to ICB therapy and have an unfavorable prognosis. GSEA revealed that the status of glucometabolic reprogramming in LUAD was potentially responsible for the immune-related subgroup classification. Conclusion: In summary, immune related subgroup clustering based on distinct immune associated signatures will enable us to screen potentially responsive LUAD patients for ICB therapy before treatment, and the discovery of metabolism associated mechanism is beneficial to comprehensive therapeutic strategies making involving ICB therapy in combination with metabolism intervention for LUAD.
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Affiliation(s)
- Xiaozhou Yu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Ziyang Wang
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China.,Department of Molecular Imaging and Nuclear Medicine, Tianjin Cancer Hospital Airport Hospital, Tianjin, China
| | - Yiwen Chen
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Guotao Yin
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Jianjing Liu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wei Chen
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Lei Zhu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wengui Xu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Xiaofeng Li
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.,Tianjin's Clinical Research Center for Cancer, Tianjin, China
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13
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Wang Y, Tong Z, Zhang W, Zhang W, Buzdin A, Mu X, Yan Q, Zhao X, Chang HH, Duhon M, Zhou X, Zhao G, Chen H, Li X. FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients. Front Oncol 2021; 11:683419. [PMID: 34164344 PMCID: PMC8216110 DOI: 10.3389/fonc.2021.683419] [Citation(s) in RCA: 79] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 05/17/2021] [Indexed: 12/14/2022] Open
Abstract
A patient's response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.
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Affiliation(s)
- Ye Wang
- Clinical Laboratory, Qingdao Central Hospital, The Second Affiliated Hospital of Medical College of Qingdao University, Qingdao, China
| | - Zhuang Tong
- Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, China
| | - Wenhua Zhang
- Clinical Laboratory, Qingdao Central Hospital, The Second Affiliated Hospital of Medical College of Qingdao University, Qingdao, China
| | - Weizhen Zhang
- Department of Biology, University of California – Santa Cruz, Santa Cruz, CA, United States
| | - Anton Buzdin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Xiaofeng Mu
- Clinical Laboratory, Qingdao Central Hospital, The Second Affiliated Hospital of Medical College of Qingdao University, Qingdao, China
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Qing Yan
- Clinical Laboratory, Qingdao Central Hospital, The Second Affiliated Hospital of Medical College of Qingdao University, Qingdao, China
| | - Xiaowen Zhao
- Clinical Laboratory, Qingdao Central Hospital, The Second Affiliated Hospital of Medical College of Qingdao University, Qingdao, China
| | - Hui-Hua Chang
- Department of Pathology & Laboratory Medicine, University of California, Los Angeles (UCLA) Technology Center for Genomics & Bioinformatics, Los Angeles, CA, United States
| | - Mark Duhon
- Department of Pathology & Laboratory Medicine, University of California, Los Angeles (UCLA) Technology Center for Genomics & Bioinformatics, Los Angeles, CA, United States
| | - Xin Zhou
- Department of Medicine, Qiqihaer First Hospital, Qiqihar, China
| | - Gexin Zhao
- Department of Pathology & Laboratory Medicine, University of California, Los Angeles (UCLA) Technology Center for Genomics & Bioinformatics, Los Angeles, CA, United States
| | - Hong Chen
- Department of Medicine, Qiqihaer First Hospital, Qiqihar, China
| | - Xinmin Li
- Department of Pathology & Laboratory Medicine, University of California, Los Angeles (UCLA) Technology Center for Genomics & Bioinformatics, Los Angeles, CA, United States
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