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Yang W, Ou Y, Luo H, You L, Du H. Causal relationship between circulating immune cells and gastric cancer: a bidirectional Mendelian randomization analysis using UK Biobank and FinnGen datasets. Transl Cancer Res 2024; 13:4702-4713. [PMID: 39430856 PMCID: PMC11483344 DOI: 10.21037/tcr-24-480] [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: 03/24/2024] [Accepted: 08/01/2024] [Indexed: 10/22/2024]
Abstract
Background The role of immune cells in cancer pathogenesis remains controversial due to conflicting reports, potentially arising from various confounding factors. Emerging evidence suggests that cancer can also influence immune cell populations and functions, making it challenging to investigate their causal relationship. Traditional observational studies often fail to eliminate all confounding factors and are prone to reverse causality. Therefore, we employ Mendelian randomization (MR) to determine the causal relationship between immune cells and cancer, as this method can identify causal relationships independent of confounding factors and avoid reverse causality. Methods Genome-wide association study (GWAS) summary statistics on immune traits, encompassing 310 immune cell phenotypes, were obtained from 3,757 European individuals, with peripheral blood immune cells tested using flow cytometry. GWAS summary statistics for gastric cancer were derived from 476,116 European individuals across two large-scale biobanks: the UK Biobank and FinnGen. Gastric cancer was identified by the International Classification of Diseases, 9th Revision (ICD-9), and 10th Revision (ICD-10) codes. Significant single nucleotide polymorphisms (SNPs) for immune traits were extracted at a threshold of P<1×10-5, while a threshold of P<5×10-8 was used for gastric cancer GWAS data. Linkage imbalance-based clumping was performed to obtain independent SNPs, and those with F<10 were excluded to mitigate weak instrument bias. Phenoscanner V2 was used to exclude SNPs directly associated with potential confounders or outcomes. Two-sample MR was conducted using five MR methods, with inverse-variance-weighted (IVW) as the primary analysis method. A false discovery rate (FDR) correction was used to reduce the likelihood of type 1 errors. In addition, we conducted MR-Egger intercept tests and Cochran's Q tests. Results The numbers of CD4-CD8- T cells and IgD-CD27- B cells were positively correlated with the development of gastric cancer, with odds ratios (ORs) of 1.15 [95% confidence interval (CI), 1.07-1.24; P<0.001; PFDR=0.041; IVW method] and 1.07 (95% CI, 1.03-1.11; P=0.001; PFDR=0.187; IVW method), respectively. However, the percentage of IgD+CD24- B cells in lymphocytes were negatively associated with the development of gastric cancer (OR =0.90; 95% CI, 0.84-0.96; P=0.002; PFDR=0.187; IVW method). MR analysis of the above three immune cell phenotypes showed no significant heterogeneity or horizontal pleiotropy. In the reverse MR analysis, gastric cancer was not causally associated with any of the immune cell phenotypes. Conclusions Circulating CD4-CD8- T cells and IgD-CD27- B cells are positively correlated with the development of gastric cancer, while the percentage of IgD+CD24- B cells in lymphocytes are negatively correlated. These findings provide insight into the relationship between immune cells and gastric cancer pathogenesis and may serve as a basis for the development of immunotherapies for gastric cancer.
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Affiliation(s)
- Weimin Yang
- Department of Surgery, Beijing Jishuitan Hospital Guizhou Hospital, Guiyang, China
| | - Yang Ou
- Department of Surgery, Beijing Jishuitan Hospital Guizhou Hospital, Guiyang, China
| | - Hui Luo
- Department of Gastrointestinal Surgery, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Lijuan You
- Department of Anesthesiology, Huanggang Central Hospital Affiliated to Yangtze University, Huanggang, China
| | - Heng Du
- Department of Gastrointestinal Surgery, Huanggang Central Hospital Affiliated to Yangtze University, Huanggang, China
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2
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Liu XC, Sun KN, Zhu HR, Dai YL, Liu XF. Diagnostic and prognostic value of double-negative T cells in colorectal cancer. Heliyon 2024; 10:e34645. [PMID: 39114054 PMCID: PMC11305275 DOI: 10.1016/j.heliyon.2024.e34645] [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: 09/04/2023] [Revised: 07/05/2024] [Accepted: 07/12/2024] [Indexed: 08/10/2024] Open
Abstract
Objective To evaluate the T-lymphocyte subset distribution and the diagnostic and prognosis value of double-negative T (DNT) cells in colorectal cancer (CRC). Methods This retrospective study compared the T-lymphocyte subsets and DNT of 114 patients with CRC with those of 107 healthy controls (HC). The diagnostic potential of DNT and T-lymphocyte subsets was assessed using the receiver operating characteristic (ROC) curve, and prognostic values were evaluated using the Kaplan-Meier curve and the Cox regression model. Results The percentages of CD8+ T cells and DNT cells, and value of carcinoembryonic antigen (CEA), were remarkably higher in patients with CRC than in those with HC, but the ratio of CD4+/CD8+ was decreased. Using ROC curve analysis, DNT cell percentage, CEA, and CD4+/CD8+ ratio all had good diagnostic efficacy, with areas under the curve (AUCs) of 0.865, 0.786 and 0.624, respectively. The combination of DNT cell percentage and CEA had an AUC of 0.905, which was significantly higher than that of any single biomarker (p < 0.05). In univariate analysis, the Tumor Node Metastasis (TNM) clinical stage, CD4+/CD8+ ratio, and DNT cell percentage were significantly associated with overall survival (OS) (p < 0.05). In multivariate analysis, TNM clinical staging (HR = 2.37, 95 % CI: 1.15-4.90), a decreased CD4+/CD8+ ratio (HR = 0.33, 95 % CI: 0.15-0.74), and an increased DNT cell percentage (HR = 2.29, 95 % CI: 1.11-4.73) were independent prognostic factors for CRC. Conclusion The percentage of DNT cells may be useful as an evaluation index for CRC diagnosis and prognosis, which was even better when combined with serum CEA.
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Affiliation(s)
- Xiao-Cui Liu
- Senior Department of Ophthalmology, the Third Medical Center of PLA General Hospital, Beijing, 100039, China
| | - Ke-Na Sun
- Department of Laboratory Medicine, Weifang People's Hospital, Weifang, 261041, Shandong Province, China
| | - Hui-Ru Zhu
- Department of Laboratory Medicine, Weifang Medical University, Weifang, 261053, Shandong Province, China
| | - Yu-Ling Dai
- Department of Laboratory Medicine, Weifang Medical University, Weifang, 261053, Shandong Province, China
| | - Xiao-Fei Liu
- Department of Laboratory Medicine, the 960th Hospital of the PLA Joint Logistics Support Force, Ji'nan, 250031, Shandong Province, China
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3
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Thirman HL, Hayes MJ, Brown LE, Porco JA, Irish JM. Single Cell Profiling Distinguishes Leukemia-Selective Chemotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.01.591362. [PMID: 38826485 PMCID: PMC11142275 DOI: 10.1101/2024.05.01.591362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
A central challenge in chemical biology is to distinguish molecular families in which small structural changes trigger large changes in cell biology. Such families might be ideal scaffolds for developing cell-selective chemical effectors - for example, molecules that activate DNA damage responses in malignant cells while sparing healthy cells. Across closely related structural variants, subtle structural changes have the potential to result in contrasting bioactivity patterns across different cell types. Here, we tested a 600-compound Diversity Set of screening molecules from the Boston University Center for Molecular Discovery (BU-CMD) in a novel phospho-flow assay that tracked fundamental cell biological processes, including DNA damage response, apoptosis, M-phase cell cycle, and protein synthesis in MV411 leukemia cells. Among the chemotypes screened, synthetic congeners of the rocaglate family were especially bioactive. In follow-up studies, 37 rocaglates were selected and deeply characterized using 12 million additional cellular measurements across MV411 leukemia cells and healthy peripheral blood mononuclear cells. Of the selected rocaglates, 92% displayed significant bioactivity in human cells, and 65% selectively induced DNA damage responses in leukemia and not healthy human blood cells. Furthermore, the signaling and cell-type selectivity were connected to structural features of rocaglate subfamilies. In particular, three rocaglates from the rocaglate pyrimidinone (RP) structural subclass were the only molecules that activated exceptional DNA damage responses in leukemia cells without activating a detectable DNA damage response in healthy cells. These results indicate that the RP subset should be extensively characterized for anticancer therapeutic potential as it relates to the DNA damage response. This single cell profiling approach advances a chemical biology platform to dissect how systematic variations in chemical structure can profoundly and differentially impact basic functions of healthy and diseased cells.
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Affiliation(s)
- Hannah L. Thirman
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Chemical & Physical Biology Program, Vanderbilt University, Nashville, TN, USA
| | - Madeline J. Hayes
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lauren E. Brown
- Department of Chemistry and Center for Molecular Discovery (BU-CMD), Boston University, Boston, MA, USA
| | - John A. Porco
- Department of Chemistry and Center for Molecular Discovery (BU-CMD), Boston University, Boston, MA, USA
| | - Jonathan M. Irish
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
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4
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Medina S, Brockman AA, Cross CE, Hayes MJ, Mobley BC, Mistry AM, Chotai S, Weaver KD, Thompson RC, Chambless LB, Ihrie RA, Irish JM. IL-8 Instructs Macrophage Identity in Lateral Ventricle Contacting Glioblastoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.29.587030. [PMID: 38585888 PMCID: PMC10996638 DOI: 10.1101/2024.03.29.587030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, CD32+ HLA-DRhi macrophages were shown to have displaced resident microglia in GBM tumors that contact the lateral ventricle stem cell niche. Since these lateral ventricle contacting GBM tumors have especially poor outcomes, identifying the origin and role of these CD32+ macrophages is likely critical to developing successful GBM immunotherapies. Here, we identify these CD32+ cells as M_IL-8 macrophages and establish that IL-8 is sufficient and necessary for tumor cells to instruct healthy macrophages into CD32+ M_IL-8 M2 macrophages. In ex vivo experiments with conditioned medium from primary human tumor cells, inhibitory antibodies to IL-8 blocked the generation of CD32+ M_IL-8 cells. Finally, using a set of 73 GBM tumors, IL-8 protein is shown to be present in GBM tumor cells in vivo and especially common in tumors contacting the lateral ventricle. These results provide a mechanistic origin for CD32+ macrophages that predominate in the microenvironment of the most aggressive GBM tumors. IL-8 and CD32+ macrophages should now be explored as targets in combination with GBM immunotherapies, especially for patients whose tumors present with radiographic contact with the ventricular-subventricular zone stem cell niche.
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Affiliation(s)
- Stephanie Medina
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Asa A Brockman
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
| | - Claire E Cross
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Madeline J Hayes
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bret C Mobley
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Akshitkumar M Mistry
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Silky Chotai
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyle D Weaver
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reid C Thompson
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lola B Chambless
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rebecca A Ihrie
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jonathan M Irish
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
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5
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Shea AA, Heffron CL, Grieco JP, Roberts PC, Schmelz EM. Obesity modulates the cellular and molecular microenvironment in the peritoneal cavity: implication for ovarian cancer risk. Front Immunol 2024; 14:1323399. [PMID: 38264656 PMCID: PMC10803595 DOI: 10.3389/fimmu.2023.1323399] [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: 10/17/2023] [Accepted: 12/12/2023] [Indexed: 01/25/2024] Open
Abstract
Introduction Abdominal obesity increases the risk of developing ovarian cancer but the molecular mechanisms of how obesity supports ovarian cancer development remain unknown. Here we investigated the impact of obesity on the immune cell and gene expression profiles of distinct abdominal tissues, focusing on the peritoneal serous fluid (PSF) and the omental fat band (OFB) as critical determinants for the dissemination of ovarian metastases and early metastatic events within the peritoneal cavity. Methods Female C57BL/6 mice were fed a low-fat (LFD) or a high-fat diet (HFD) for 12 weeks until the body weights in the HFD group were significantly higher and the mice displayed an impaired glucose tolerance. Then the mice were injected with the murine ovarian cancer cells (MOSE-LTICv) while remaining on their diets. After 21 days, the mice were sacrificed, tumor burden was evaluated and tissues were harvested. The immune cell composition of abdominal tissues and changes in gene expression in the PSF and OFB were evaluated by flow cytometry and qPCR RT2-profiler PCR arrays and confirmed by qRT-PCR, respectively. Other peritoneal adipose tissues including parametrial and retroperitoneal white adipose tissues as well as blood were also investigated. Results While limited effects were observed in the other peritoneal adipose tissues, feeding mice the HFD led to distinct changes in the immune cell composition in the PSF and the OFB: a depletion of B cells but an increase in myeloid-derived suppressor cells (MDSC) and mono/granulocytes, generating pro-inflammatory environments with increased expression of cyto- and chemokines, and genes supporting adhesion, survival, and growth, as well as suppression of apoptosis. This was associated with a higher peritoneal tumor burden compared to mice fed a LFD. Changes in cellular and genetic profiles were often exacerbated by the HFD. There was a large overlap in genes that were modulated by both the HFD and the cancer cells, suggesting that this 'genetic fingerprint' is important for ovarian metastases to the OFB. Discussion In accordance with the 'seed and soil' theory, our studies show that obesity contributes to the generation of a pro-inflammatory peritoneal environment that supports the survival of disseminating ovarian cancer cells in the PSF and the OFB and enhances the early metastatic adhesion events in the OFB through an increase in extracellular matrix proteins and modulators such as fibronectin 1 and collagen I expression as well as in genes supporting growth and invasion such as Tenacin C. The identified genes could potentially be used as targets for prevention strategies to lower the ovarian cancer risk in women with obesity.
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Affiliation(s)
- Amanda A. Shea
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA, United States
| | - Connie Lynn Heffron
- Department of Biomedical Sciences and Pathobiology, Virginia Tech, Blacksburg, VA, United States
| | - Joseph P. Grieco
- Graduate Program in Translational Biology, Medicine, and Health, Virginia Tech, Blacksburg, VA, United States
| | - Paul C. Roberts
- Department of Biomedical Sciences and Pathobiology, Virginia Tech, Blacksburg, VA, United States
| | - Eva M. Schmelz
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA, United States
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6
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Mas G, Man N, Nakata Y, Martinez-Caja C, Karl D, Beckedorff F, Tamiro F, Chen C, Duffort S, Itonaga H, Mookhtiar AK, Kunkalla K, Valencia AM, Collings CK, Kadoch C, Vega F, Kogan SC, Shiekhattar R, Morey L, Bilbao D, Nimer SD. The SWI/SNF chromatin-remodeling subunit DPF2 facilitates NRF2-dependent antiinflammatory and antioxidant gene expression. J Clin Invest 2023; 133:e158419. [PMID: 37200093 PMCID: PMC10313367 DOI: 10.1172/jci158419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/16/2023] [Indexed: 05/20/2023] Open
Abstract
During emergency hematopoiesis, hematopoietic stem cells (HSCs) rapidly proliferate to produce myeloid and lymphoid effector cells, a response that is critical against infection or tissue injury. If unresolved, this process leads to sustained inflammation, which can cause life-threatening diseases and cancer. Here, we identify a role of double PHD fingers 2 (DPF2) in modulating inflammation. DPF2 is a defining subunit of the hematopoiesis-specific BAF (SWI/SNF) chromatin-remodeling complex, and it is mutated in multiple cancers and neurological disorders. We uncovered that hematopoiesis-specific Dpf2-KO mice developed leukopenia, severe anemia, and lethal systemic inflammation characterized by histiocytic and fibrotic tissue infiltration resembling a clinical hyperinflammatory state. Dpf2 loss impaired the polarization of macrophages responsible for tissue repair, induced the unrestrained activation of Th cells, and generated an emergency-like state of HSC hyperproliferation and myeloid cell-biased differentiation. Mechanistically, Dpf2 deficiency resulted in the loss of the BAF catalytic subunit BRG1 from nuclear factor erythroid 2-like 2-controlled (NRF2-controlled) enhancers, impairing the antioxidant and antiinflammatory transcriptional response needed to modulate inflammation. Finally, pharmacological reactivation of NRF2 suppressed the inflammation-mediated phenotypes and lethality of Dpf2Δ/Δ mice. Our work establishes an essential role of the DPF2-BAF complex in licensing NRF2-dependent gene expression in HSCs and immune effector cells to prevent chronic inflammation.
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Affiliation(s)
- Gloria Mas
- Sylvester Comprehensive Cancer Center and
| | - Na Man
- Sylvester Comprehensive Cancer Center and
| | - Yuichiro Nakata
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | | | | | - Felipe Beckedorff
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | | | - Chuan Chen
- Sylvester Comprehensive Cancer Center and
| | | | | | | | | | - Alfredo M. Valencia
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Chemical Biology Program, Harvard University, Cambridge, Massachusetts, USA
| | - Clayton K. Collings
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Cigall Kadoch
- Department of Pediatric Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Francisco Vega
- Sylvester Comprehensive Cancer Center and
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Scott C. Kogan
- Helen Diller Family Comprehensive Cancer Center and
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - Ramin Shiekhattar
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Lluis Morey
- Sylvester Comprehensive Cancer Center and
- Department of Human Genetics, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Daniel Bilbao
- Sylvester Comprehensive Cancer Center and
- Department of Pathology and Laboratory Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Stephen D. Nimer
- Sylvester Comprehensive Cancer Center and
- Department of Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA
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Giacomelli M, Monti M, Pezzola DC, Lonardi S, Bugatti M, Missale F, Cioncada R, Melocchi L, Giustini V, Villanacci V, Baronchelli C, Manenti S, Imberti L, Giurisato E, Vermi W. Immuno-Contexture and Immune Checkpoint Molecule Expression in Mismatch Repair Proficient Colorectal Carcinoma. Cancers (Basel) 2023; 15:3097. [PMID: 37370706 DOI: 10.3390/cancers15123097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/01/2023] [Accepted: 06/01/2023] [Indexed: 06/29/2023] Open
Abstract
Colorectal carcinoma (CRC) represents a lethal disease with heterogeneous outcomes. Only patients with mismatch repair (MMR) deficient CRC showing microsatellite instability and hyper-mutated tumors can obtain clinical benefits from current immune checkpoint blockades; on the other hand, immune- or target-based therapeutic strategies are very limited for subjects with mismatch repair proficient CRC (CRCpMMR). Here, we report a comprehensive typing of immune infiltrating cells in CRCpMMR. We also tested the expression and interferon-γ-modulation of PD-L1/CD274. Relevant findings were subsequently validated by immunohistochemistry on fixed materials. CRCpMMR contain a significantly increased fraction of CD163+ macrophages (TAMs) expressing TREM2 and CD66+ neutrophils (TANs) together with decrease in CD4-CD8-CD3+ double negative T lymphocytes (DNTs); no differences were revealed by the analysis of conventional and plasmacytoid dendritic cell populations. A fraction of tumor-infiltrating T-cells displays an exhausted phenotype, co-expressing PD-1 and TIM-3. Remarkably, expression of PD-L1 on fresh tumor cells and TAMs was undetectable even after in vitro stimulation with interferon-γ. These findings confirm the immune suppressive microenvironment of CRCpMMR characterized by dense infiltration of TAMs, occurrence of TANs, lack of DNTs, T-cell exhaustion, and interferon-γ unresponsiveness by host and tumor cells. Appropriate bypass strategies should consider these combinations of immune escape mechanisms in CRCpMMR.
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Affiliation(s)
- Mauro Giacomelli
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Matilde Monti
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
| | - Diego Cesare Pezzola
- Department of Surgery, Surgery Division II, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Silvia Lonardi
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
| | - Mattia Bugatti
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
| | - Francesco Missale
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
- Department of Head & Neck Oncology & Surgery Otorhinolaryngology, Antoni Van Leeuwenhoek-Nederlands Kanker Instituut, 1066 CX Amsterdam, The Netherlands
| | - Rossella Cioncada
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Laura Melocchi
- Department of Pathology, Fondazione Poliambulanza, 25124 Brescia, Italy
| | - Viviana Giustini
- CREA Laboratory, AIL Center for Hemato-Oncologic Research, Diagnostic Department, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Vincenzo Villanacci
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Carla Baronchelli
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Stefania Manenti
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
| | - Luisa Imberti
- Section of Microbiology, University of Brescia, 25123 Brescia, Italy
| | - Emanuele Giurisato
- Department of Biotechnology Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, UK
| | - William Vermi
- Department of Pathology, ASST Spedali Civili di Brescia, 25123 Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25123 Brescia, Italy
- Department of Pathology and Immunology, School of Medicine, Washington University, Saint Louis, MO 63130, USA
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8
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Wang G, Lyudovyk O, Kim JY, Lin YH, Elhanati Y, Mathew D, Wherry EJ, Herati RS, Greenplate AR, Greenbaum B, Vardhana SA, Huang AC. High-throughput interrogation of immune responses using the Human Immune Profiling Pipeline. STAR Protoc 2023; 4:102289. [PMID: 37159385 PMCID: PMC10193120 DOI: 10.1016/j.xpro.2023.102289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/29/2022] [Accepted: 04/14/2023] [Indexed: 05/11/2023] Open
Abstract
The current abundance of immunotherapy clinical trials presents an opportunity to learn about the underlying mechanisms and pharmacodynamic effects of novel drugs on the human immune system. Here, we present a protocol to study how these immune responses impact clinical outcomes using large-scale high-throughput immune profiling of clinical cohorts. We describe the Human Immune Profiling Pipeline, which comprises an end-to-end solution from flow cytometry results to computational approaches and unsupervised patient clustering based on lymphocyte landscape. For complete details on the use and execution of this protocol, please refer to Lyudovyk et al. (2022).1.
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Affiliation(s)
- Guanning Wang
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Olga Lyudovyk
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Tri-institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Justin Y Kim
- Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
| | - Ya-Hui Lin
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yuval Elhanati
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Divij Mathew
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - E John Wherry
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA; Institute for Immunology and Immune Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Ramin S Herati
- Department of Medicine, New York University School of Medicine, New York, NY, USA
| | - Allison R Greenplate
- Institute for Immunology and Immune Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin Greenbaum
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Physiology, Biophysics & Systems Biology, Weill Cornell Medicine, Weill Cornell Medical College, New York, NY, USA.
| | - Santosha A Vardhana
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA; Lymphoma Service, Division of Hematologic Malignancies, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Alexander C Huang
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute for Immunology and Immune Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA.
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9
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Criado I, Nieto WG, Oliva-Ariza G, Fuentes-Herrero B, Teodosio C, Lecrevisse Q, Lopez A, Romero A, Almeida J, Orfao A. Age- and Sex-Matched Normal Leukocyte Subset Ranges in the General Population Defined with the EuroFlow Lymphocyte Screening Tube (LST) for Monoclonal B-Cell Lymphocytosis (MBL) vs. Non-MBL Subjects. Cancers (Basel) 2022; 15:cancers15010058. [PMID: 36612056 PMCID: PMC9817826 DOI: 10.3390/cancers15010058] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/02/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Reference ranges of blood-circulating leukocyte populations by, e.g., age and sex, are required for monitoring immune-cell kinetics. Most previous reports in which flow cytometry has been used to define the reference ranges for leukocyte counts included a limited number of donors and/or cell populations and/or did not consider age and sex simultaneously. Moreover, other factors not previously considered in the definition of normal ranges, such as the presence of chronic-lymphocytic-leukemia (CLL)-like low-count monoclonal B-cell lymphocytosis (MBLlo), might also be associated with an altered distribution of leukocytes in blood in association with an immunodeficiency and increased risk of infection and cancer. Here, we established reference cell-count ranges for the major populations of leukocytes in blood of non-MBL and MBLlo adult Caucasians matched by age and sex using the EuroFlow Lymphocyte Screening Tube (LST). A total of 706 Caucasian adult donors—622 non-MBL and 84 MBLlo—were recruited from the general population. Among non-MBL donors, the total leukocyte, neutrophil, basophil dendritic cell and monocyte counts remained stable through adulthood, while the absolute numbers of T- and B-cell populations and plasma cells decreased with age. The number of eosinophils and NK-cell increased over time, with clear differences according to sex for certain age ranges. In MBLlo subjects, few differences in the absolute cell counts by age (vs. non-MBL) were observed, and MBLlo men and women showed similar trends to non-MBL subjects except for the B-cell count drop observed in >70 y-men, which was more pronounced in MBLlo vs. non-MBL controls. Building robust age- and sex-matched reference ranges for the most relevant immune-cell populations in the blood of non-MBL donors is essential to appropriately identify an altered immune status in different clinical settings and highlight the altered immune-cell profiles of MBLlo subjects.
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Affiliation(s)
- Ignacio Criado
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Wendy G. Nieto
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Guillermo Oliva-Ariza
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Blanca Fuentes-Herrero
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Cristina Teodosio
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Quentin Lecrevisse
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Antonio Lopez
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Alfonso Romero
- Centro de Atención Primaria de Salud Miguel Armijo, Sanidad de Castilla y León (SACyL), 37007 Salamanca, Spain
| | - Julia Almeida
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Correspondence: (J.A.); (A.O.); Tel.: +34-923-29-4811 (J.A.)
| | - Alberto Orfao
- Translational and Clinical Research Program, Centro de Investigación del Cáncer (IBMCC; CSIC–Universidad de Salamanca); Cytometry Service, NUCLEUS; Departamento de Medicina, Universidad de Salamanca (https://ror.org/02f40zc51) and Institute of Biomedical Research of Salamanca (IBSAL), 37007 Salamanca, Spain
- Biomedical Research Networking Centre Consortium of Oncology (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain
- Correspondence: (J.A.); (A.O.); Tel.: +34-923-29-4811 (J.A.)
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10
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Newman-Rivera AM, Kurzhagen JT, Rabb H. TCRαβ+ CD4-/CD8- "double negative" T cells in health and disease-implications for the kidney. Kidney Int 2022; 102:25-37. [PMID: 35413379 PMCID: PMC9233047 DOI: 10.1016/j.kint.2022.02.035] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/10/2022] [Accepted: 02/28/2022] [Indexed: 12/22/2022]
Abstract
Double negative (DN) T cells, one of the least studied T lymphocyte subgroups, express T cell receptor αβ but lack CD4 and CD8 coreceptors. DN T cells are found in multiple organs including kidney, lung, heart, gastrointestinal tract, liver, genital tract, and central nervous system. DN T cells suppress inflammatory responses in different disease models including experimental acute kidney injury, and significant evidence supports an important role in the pathogenesis of systemic lupus erythematosus. However, little is known about these cells in other kidney diseases. Therefore, it is important to better understand different functions of DN T cells and their signaling pathways as promising therapeutic targets, particularly with the increasing application of T cell-directed therapy in humans. In this review, we aim to summarize studies performed on DN T cells in normal and diseased organs in the setting of different disease models with a focus on kidney.
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Affiliation(s)
| | | | - Hamid Rabb
- Nephrology Division, Johns Hopkins University, Baltimore, Maryland, USA.
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11
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Imam S, Paparodis RD, Rafiqi SI, Ali S, Niaz A, Kanzy A, Tovar YE, Madkhali MA, Elsherif A, Khogeer F, Zahid ZA, Sarwar H, Karim T, Salim N, Jaume JC. Thyroid Cancer Screening Using Tumor-Associated DN T Cells as Immunogenomic Markers. Front Oncol 2022; 12:891002. [PMID: 35692772 PMCID: PMC9186057 DOI: 10.3389/fonc.2022.891002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/22/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThyroid nodules are an extremely common entity, and surgery is considered the ultimate diagnostic strategy in those with unclear malignant potential. Unfortunately, strategies aiming to predict the risk of malignancy have inadequate specificity. Our group recently found that the microenvironment of thyroid cancer is characterized by an enhanced immune invasion and activated immune response mediated by double-negative T lymphocytes (DN T) (CD3+CD4-CD8-), which are believed to enable or promote tumorigenesis. In the present work, we try to use the DN T cells’ proportion in thyroid fine-needle aspiration (FNA) material as a predictor of the risk of malignancy.MethodsWe recruited 127 patients and obtained ultrasound-guided FNA samples from subjects with cytology-positive or suspicious for malignancy and from those with benign nodular goiter associated with compressive symptoms (such as dysphagia, shortness of breath, or hoarseness), Hashimoto thyroiditis, and Graves’ disease. Out of 127, we investigated 46 FNA samples of patients who underwent total thyroidectomy and for which postoperative histological diagnosis by the academic pathologists was available. We specifically measured the number of cells expressing CD3+CD4-CD8- (DN T) as a function of total CD3+ cells in FNA samples using flow cytometry. We correlated their FNA DN T-cell proportions with the pathological findings.ResultsThe DN T cells were significantly more abundant in lymphocytic infiltrates of thyroid cancer cases compared to benign nodule controls (p < 0.0001). When the DN T-cell population exceeded a threshold of 9.14%, of total CD3+ cells, the negative likelihood ratio of being cancer-free was 0.034 (96.6% sensitivity, 95% CI, 0.915–1.000, p < 0.0001). DN T cells at <9.14% were not found in any subject with benign disease (specificity 100%). The high specificity of the test is promising, since it abolishes a false-positive diagnosis and in turn unnecessary surgical procedures.ConclusionThe present study proposes DN T cells’ proportion as a preoperative diagnostic signature for thyroid cancer that with integration of RNA transcriptomics can provide a simplified technology based on the PCR assay for the ease of operation.
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Affiliation(s)
- Shahnawaz Imam
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
- *Correspondence: Shahnawaz Imam, ; Juan C. Jaume,
| | - Rodis D. Paparodis
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
- Private Practitioner, Patras, Greece
| | - Shafiya Imtiaz Rafiqi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Sophia Ali
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Azra Niaz
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Abed Kanzy
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Yara E. Tovar
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Mohammed A. Madkhali
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Ahmed Elsherif
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Feras Khogeer
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Zeeshan A. Zahid
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Haider Sarwar
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
- Windsor University School of Medicine, Cayon St. Kitts West Indies, Saint Kitts and Nevis
| | - Tamanna Karim
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Nancy Salim
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
| | - Juan C. Jaume
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
- Center for Diabetes and Endocrine Research (CeDER), University of Toledo, Toledo, OH, United States
- *Correspondence: Shahnawaz Imam, ; Juan C. Jaume,
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12
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Wu Z, Zheng Y, Sheng J, Han Y, Yang Y, Pan H, Yao J. CD3 +CD4 -CD8 - (Double-Negative) T Cells in Inflammation, Immune Disorders and Cancer. Front Immunol 2022; 13:816005. [PMID: 35222392 PMCID: PMC8866817 DOI: 10.3389/fimmu.2022.816005] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 01/21/2022] [Indexed: 12/28/2022] Open
Abstract
The crucial role of CD4+ and CD8+ T cells in shaping and controlling immune responses during immune disease and cancer development has been well established and used to achieve marked clinical benefits. CD3+CD4-CD8- double-negative (DN) T cells, although constituting a rare subset of peripheral T cells, are gaining interest for their roles in inflammation, immune disease and cancer. Herein, we comprehensively review the origin, distribution and functions of this unique T cell subgroup. First, we focused on characterizing multifunctional DN T cells in various immune responses. DN regulatory T cells have the capacity to prevent graft-versus-host disease and have therapeutic value for autoimmune disease. T helper-like DN T cells protect against or promote inflammation and virus infection depending on the specific settings and promote certain autoimmune disease. Notably, we clarified the role of DN tumor-infiltrating lymphocytes and outlined the potential for malignant proliferation of DN T cells. Finally, we reviewed the recent advances in the applications of DN T cell-based therapy for cancer. In conclusion, a better understanding of the heterogeneity and functions of DN T cells may help to develop DN T cells as a potential therapeutic tool for inflammation, immune disorders and cancer.
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Affiliation(s)
- Zhiheng Wu
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yu Zheng
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jin Sheng
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yicheng Han
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yanyan Yang
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Hongming Pan
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Junlin Yao
- Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China
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13
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Lo YC, Keyes TJ, Jager A, Sarno J, Domizi P, Majeti R, Sakamoto KM, Lacayo N, Mullighan CG, Waters J, Sahaf B, Bendall SC, Davis KL. CytofIn enables integrated analysis of public mass cytometry datasets using generalized anchors. Nat Commun 2022; 13:934. [PMID: 35177627 PMCID: PMC8854441 DOI: 10.1038/s41467-022-28484-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 01/27/2022] [Indexed: 11/09/2022] Open
Abstract
The increasing use of mass cytometry for analyzing clinical samples offers the possibility to perform comparative analyses across public datasets. However, challenges in batch normalization and data integration limit the comparison of datasets not intended to be analyzed together. Here, we present a data integration strategy, CytofIn, using generalized anchors to integrate mass cytometry datasets from the public domain. We show that low-variance controls, such as healthy samples and stable channels, are inherently homogeneous, robust against stimulation, and can serve as generalized anchors for batch correction. Single-cell quantification comparing mass cytometry data from 989 leukemia files pre- and post normalization with CytofIn demonstrates effective batch correction while recapitulating the gold-standard bead normalization. CytofIn integration of public cancer datasets enabled the comparison of immune features across histologies and treatments. We demonstrate the ability to integrate public datasets without necessitating identical control samples or bead standards for fast and robust analysis using CytofIn.
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Affiliation(s)
- Yu-Chen Lo
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Timothy J Keyes
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Medical Scientist Training Program, Stanford University School of Medicine, Stanford, CA, USA
| | - Astraea Jager
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jolanda Sarno
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Pablo Domizi
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Ravindra Majeti
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Kathleen M Sakamoto
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Norman Lacayo
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Charles G Mullighan
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jeffrey Waters
- Center for Cancer Cellular Therapy, Cancer Correlative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA
| | - Bita Sahaf
- Center for Cancer Cellular Therapy, Cancer Correlative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA
| | - Sean C Bendall
- Center for Cancer Cellular Therapy, Cancer Correlative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kara L Davis
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
- Center for Cancer Cellular Therapy, Cancer Correlative Sciences Unit, Stanford University School of Medicine, Stanford, CA, USA.
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14
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Apostolidis SA, Kakara M, Painter MM, Goel RR, Mathew D, Lenzi K, Rezk A, Patterson KR, Espinoza DA, Kadri JC, Markowitz DM, E Markowitz C, Mexhitaj I, Jacobs D, Babb A, Betts MR, Prak ETL, Weiskopf D, Grifoni A, Lundgreen KA, Gouma S, Sette A, Bates P, Hensley SE, Greenplate AR, Wherry EJ, Li R, Bar-Or A. Cellular and humoral immune responses following SARS-CoV-2 mRNA vaccination in patients with multiple sclerosis on anti-CD20 therapy. Nat Med 2021; 27:1990-2001. [PMID: 34522051 PMCID: PMC8604727 DOI: 10.1038/s41591-021-01507-2] [Citation(s) in RCA: 365] [Impact Index Per Article: 91.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 08/16/2021] [Indexed: 02/08/2023]
Abstract
SARS-CoV-2 messenger RNA vaccination in healthy individuals generates immune protection against COVID-19. However, little is known about SARS-CoV-2 mRNA vaccine-induced responses in immunosuppressed patients. We investigated induction of antigen-specific antibody, B cell and T cell responses longitudinally in patients with multiple sclerosis (MS) on anti-CD20 antibody monotherapy (n = 20) compared with healthy controls (n = 10) after BNT162b2 or mRNA-1273 mRNA vaccination. Treatment with anti-CD20 monoclonal antibody (aCD20) significantly reduced spike-specific and receptor-binding domain (RBD)-specific antibody and memory B cell responses in most patients, an effect ameliorated with longer duration from last aCD20 treatment and extent of B cell reconstitution. By contrast, all patients with MS treated with aCD20 generated antigen-specific CD4 and CD8 T cell responses after vaccination. Treatment with aCD20 skewed responses, compromising circulating follicular helper T (TFH) cell responses and augmenting CD8 T cell induction, while preserving type 1 helper T (TH1) cell priming. Patients with MS treated with aCD20 lacking anti-RBD IgG had the most severe defect in circulating TFH responses and more robust CD8 T cell responses. These data define the nature of the SARS-CoV-2 vaccine-induced immune landscape in aCD20-treated patients and provide insights into coordinated mRNA vaccine-induced immune responses in humans. Our findings have implications for clinical decision-making and public health policy for immunosuppressed patients including those treated with aCD20.
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Grants
- U19AI082630 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- T32 AR076951 NIAMS NIH HHS
- AI082630 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- R21 AI142638 NIAID NIH HHS
- AI108545 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- R01 AI152236 NIAID NIH HHS
- 75N9301900065 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- AI149680 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- T32 CA009140 NCI NIH HHS
- R01 AI118694 NIAID NIH HHS
- U19 AI082630 NIAID NIH HHS
- AI152236 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- P30-AI0450080 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- T32 AR076951-01 U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
- R01 AI105343 NIAID NIH HHS
- AI105343 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- R01 AI155577 NIAID NIH HHS
- UM1 AI144288 NIAID NIH HHS
- U19 AI149680 NIAID NIH HHS
- AI155577 U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER)
- SI-2011-37160 National Multiple Sclerosis Society (National MS Society)
- UC4 DK112217 NIDDK NIH HHS
- P01 AI108545 NIAID NIH HHS
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (Division of Intramural Research of the NIAID)
- Penn | Perelman School of Medicine, University of Pennsylvania (Perelman School of Medicine at the University of Pennsylvania)
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Affiliation(s)
- Sokratis A Apostolidis
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Rheumatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mihir Kakara
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mark M Painter
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rishi R Goel
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Divij Mathew
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kerry Lenzi
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ayman Rezk
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kristina R Patterson
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Diego A Espinoza
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immunology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jessy C Kadri
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel M Markowitz
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Clyde E Markowitz
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ina Mexhitaj
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Dina Jacobs
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Allison Babb
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Michael R Betts
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Eline T Luning Prak
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniela Weiskopf
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Alba Grifoni
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Kendall A Lundgreen
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sigrid Gouma
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Paul Bates
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Center for Research on Coronavirus and Other Emerging Pathogens, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott E Hensley
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Allison R Greenplate
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - E John Wherry
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Rui Li
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Amit Bar-Or
- Center for Neuroinflammation and Experimental Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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15
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Barone SM, Paul AGA, Muehling LM, Lannigan JA, Kwok WW, Turner RB, Woodfolk JA, Irish JM. Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy. eLife 2021; 10:e64653. [PMID: 34350827 PMCID: PMC8370768 DOI: 10.7554/elife.64653] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 08/02/2021] [Indexed: 12/31/2022] Open
Abstract
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease-specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders EXpanding (T-REX) was created to identify changes in both rare and common cells across human immune monitoring settings. T-REX identified cells with highly similar phenotypes that localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized MHCII tetramer reagents that mark rhinovirus-specific CD4+ cells were left out during analysis and then used to test whether T-REX identified biologically significant cells. T-REX identified rhinovirus-specific CD4+ T cells based on phenotypically homogeneous cells expanding by ≥95% following infection. T-REX successfully identified hotspots of virus-specific T cells by comparing infection (day 7) to either pre-infection (day 0) or post-infection (day 28) samples. Plotting the direction and degree of change for each individual donor provided a useful summary view and revealed patterns of immune system behavior across immune monitoring settings. For example, the magnitude and direction of change in some COVID-19 patients was comparable to blast crisis acute myeloid leukemia patients undergoing a complete response to chemotherapy. Other COVID-19 patients instead displayed an immune trajectory like that seen in rhinovirus infection or checkpoint inhibitor therapy for melanoma. The T-REX algorithm thus rapidly identifies and characterizes mechanistically significant cells and places emerging diseases into a systems immunology context for comparison to well-studied immune changes.
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Affiliation(s)
- Sierra M Barone
- Department of Cell and Developmental Biology, Vanderbilt UniversityNashvilleUnited States
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical CenterNashvilleUnited States
| | - Alberta GA Paul
- Allergy Division, Department of Medicine, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Lyndsey M Muehling
- Allergy Division, Department of Medicine, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Joanne A Lannigan
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of MedicineCharlottesvilleUnited States
| | - William W Kwok
- Benaroya Research Institute at Virginia MasonSeattleUnited States
| | - Ronald B Turner
- Department of Pediatrics, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Judith A Woodfolk
- Allergy Division, Department of Medicine, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Jonathan M Irish
- Department of Cell and Developmental Biology, Vanderbilt UniversityNashvilleUnited States
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical CenterNashvilleUnited States
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical CenterNashvilleUnited States
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16
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Vallejo Ardila DL, Walsh KA, Fifis T, Paolini R, Kastrappis G, Christophi C, Perini MV. Immunomodulatory effects of renin-angiotensin system inhibitors on T lymphocytes in mice with colorectal liver metastases. J Immunother Cancer 2021; 8:jitc-2019-000487. [PMID: 32448803 PMCID: PMC7253054 DOI: 10.1136/jitc-2019-000487] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/25/2020] [Indexed: 12/12/2022] Open
Abstract
Background It is now recognized that many anticancer treatments positively modulate the antitumor immune response. Clinical and experimental studies have shown that inhibitors of the classical renin–angiotensin system (RAS) reduce tumor progression and are associated with better outcomes in patients with colorectal cancer. RAS components are expressed by most immune cells and adult hematopoietic cells, thus are potential targets for modulating tumor-infiltrating immune cells and can provide a mechanism of tumor control by the renin–angiotensin system inhibitors (RASi). Aim To investigate the effects of the RASi captopril on tumor T lymphocyte distribution in a mouse model of colorectal liver metastases. Methods Liver metastases were established in a mouse model using an autologous colorectal cancer cell line. RASi (captopril 750 mg/kg) or carrier (saline) was administered to the mice daily via intraperitoneal injection, from day 1 post-tumor induction to endpoint (day 15 or 21 post-tumor induction). At the endpoint, tumor growth was determined, and lymphocyte infiltration and composition in the tumor and liver tissues were analyzed by flow cytometry and immunohistochemistry (IHC). Results Captopril significantly decreased tumor viability and impaired metastatic growth. Analysis of infiltrating T cells into liver parenchyma and tumor tissues by IHC and flow cytometry showed that captopril significantly increased the infiltration of CD3+ T cells into both tissues at day 15 following tumor induction. Phenotypical analysis of CD45+ CD3+ T cells indicated that the major contributing phenotype to this influx is a CD4 and CD8 double-negative T cell (DNT) subtype, while CD4+ T cells decreased and CD8+ T cells remained unchanged. Captopril treatment also increased the expression of checkpoint receptor PD-1 on CD8+and DNT subsets. Conclusion Captopril treatment modulates the immune response by increasing the infiltration and altering the phenotypical composition of T lymphocytes and may be a contributing mechanism for tumor control.
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Affiliation(s)
- Dora Lucia Vallejo Ardila
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Katrina A Walsh
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Theodora Fifis
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Rita Paolini
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Georgios Kastrappis
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Christopher Christophi
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
| | - Marcos Vinicius Perini
- Surgery, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia
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17
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Paijens ST, Vledder A, de Bruyn M, Nijman HW. Tumor-infiltrating lymphocytes in the immunotherapy era. Cell Mol Immunol 2021; 18:842-859. [PMID: 33139907 PMCID: PMC8115290 DOI: 10.1038/s41423-020-00565-9] [Citation(s) in RCA: 467] [Impact Index Per Article: 116.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 09/24/2020] [Indexed: 02/07/2023] Open
Abstract
The clinical success of cancer immune checkpoint blockade (ICB) has refocused attention on tumor-infiltrating lymphocytes (TILs) across cancer types. The outcome of immune checkpoint inhibitor therapy in cancer patients has been linked to the quality and magnitude of T cell, NK cell, and more recently, B cell responses within the tumor microenvironment. State-of-the-art single-cell analysis of TIL gene expression profiles and clonality has revealed a remarkable degree of cellular heterogeneity and distinct patterns of immune activation and exhaustion. Many of these states are conserved across tumor types, in line with the broad responses observed clinically. Despite this homology, not all cancer types with similar TIL landscapes respond similarly to immunotherapy, highlighting the complexity of the underlying tumor-immune interactions. This observation is further confounded by the strong prognostic benefit of TILs observed for tumor types that have so far respond poorly to immunotherapy. Thus, while a holistic view of lymphocyte infiltration and dysfunction on a single-cell level is emerging, the search for response and prognostic biomarkers is just beginning. Within this review, we discuss recent advances in the understanding of TIL biology, their prognostic benefit, and their predictive value for therapy.
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Affiliation(s)
- Sterre T Paijens
- Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Annegé Vledder
- Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marco de Bruyn
- Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hans W Nijman
- Department of Obstetrics and Gynecology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
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18
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Healey DCC, Cephus JY, Barone SM, Chowdhury NU, Dahunsi DO, Madden MZ, Ye X, Yu X, Olszewski K, Young K, Gerriets VA, Siska PJ, Dworski R, Hemler J, Locasale JW, Poyurovsky MV, Peebles RS, Irish JM, Newcomb DC, Rathmell JC. Targeting In Vivo Metabolic Vulnerabilities of Th2 and Th17 Cells Reduces Airway Inflammation. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2021; 206:1127-1139. [PMID: 33558372 PMCID: PMC7946768 DOI: 10.4049/jimmunol.2001029] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/12/2021] [Indexed: 12/17/2022]
Abstract
T effector cells promote inflammation in asthmatic patients, and both Th2 and Th17 CD4 T cells have been implicated in severe forms of the disease. The metabolic phenotypes and dependencies of these cells, however, remain poorly understood in the regulation of airway inflammation. In this study, we show the bronchoalveolar lavage fluid of asthmatic patients had markers of elevated glucose and glutamine metabolism. Further, peripheral blood T cells of asthmatics had broadly elevated expression of metabolic proteins when analyzed by mass cytometry compared with healthy controls. Therefore, we hypothesized that glucose and glutamine metabolism promote allergic airway inflammation. We tested this hypothesis in two murine models of airway inflammation. T cells from lungs of mice sensitized with Alternaria alternata extract displayed genetic signatures for elevated oxidative and glucose metabolism by single-cell RNA sequencing. This result was most pronounced when protein levels were measured in IL-17-producing cells and was recapitulated when airway inflammation was induced with house dust mite plus LPS, a model that led to abundant IL-4- and IL-17-producing T cells. Importantly, inhibitors of the glucose transporter 1 or glutaminase in vivo attenuated house dust mite + LPS eosinophilia, T cell cytokine production, and airway hyperresponsiveness as well as augmented the immunosuppressive properties of dexamethasone. These data show that T cells induce markers to support metabolism in vivo in airway inflammation and that this correlates with inflammatory cytokine production. Targeting metabolic pathways may provide a new direction to protect from disease and enhance the effectiveness of steroid therapy.
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Affiliation(s)
- Diana C Contreras Healey
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Jacqueline Y Cephus
- Department of Medicine, Division of Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Sierra M Barone
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN 37232
| | - Nowrin U Chowdhury
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Debolanle O Dahunsi
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Matthew Z Madden
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Xiang Ye
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Xuemei Yu
- Kadmon Corporation, New York, NY 10016
| | | | - Kirsten Young
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Valerie A Gerriets
- Department of Basic Science, California Northstate University College of Medicine, Elk Grove, CA 95757
| | - Peter J Siska
- Internal Medicine III, University Hospital Regensburg, 93042 Regensburg, Germany
| | - Ryszard Dworski
- Department of Medicine, Division of Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Jonathan Hemler
- Department of Pediatrics, University of Virginia, Charlottesville, VA 22904
| | - Jason W Locasale
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC 27710; and
| | | | - R Stokes Peebles
- Department of Medicine, Division of Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN 37232
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Jonathan M Irish
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN 37232
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Dawn C Newcomb
- Department of Medicine, Division of Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN 37232
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Jeffrey C Rathmell
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232;
- Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, TN 37232
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19
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Examining the Relationship between Circulating CD4- CD8- Double-Negative T Cells and Outcomes of Immuno-Checkpoint Inhibitor Therapy-Looking for Biomarkers and Therapeutic Targets in Metastatic Melanoma. Cells 2021; 10:cells10020406. [PMID: 33669266 PMCID: PMC7920027 DOI: 10.3390/cells10020406] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/10/2021] [Accepted: 02/14/2021] [Indexed: 11/23/2022] Open
Abstract
Background: The role of circulating CD4−/CD8− double-negative T cells (DNTs) in the immune response to melanoma is poorly understood, as are the effects of checkpoint inhibitors on T cell subpopulations. Methods: We performed a basal and longitudinal assessment of circulating immune cells, including DNTs, in metastatic melanoma patients treated with checkpoint blockade in a single-center cohort, and examined the correlations levels of immune cells with clinical features and therapy outcomes. Results: Sixty-eight patients (48 ipilimumab, 20 PD1 inhibitors) were enrolled in the study. Our analysis indicated that better outcomes were associated with normal LDH, fewer than three metastatic sites, an ECOG performance status of 0, M1a stage, lower WBC and a higher lymphocyte count. The increase in lymphocyte count and decrease of DNTs were significantly associated with the achievement of an overall response. The median value of DNT decreased while the CD4+ and NK cells increased in patients that responded to treatment compare to those who did not respond to treatment. Conclusions: DNT cells change during treatment with checkpoint inhibitors and may be adept at sensing the immune response to melanoma. The complementary variation of DNT cells with respect to CD4+ and other immune actors may improve the reliability of lymphocyte assessment. Further investigation of DNT as a potential target in checkpoint inhibitor resistant melanoma is warranted.
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20
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Barone SM, Paul AG, Muehling LM, Lannigan JA, Kwok WW, Turner RB, Woodfolk JA, Irish JM. Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.07.31.190454. [PMID: 32766581 PMCID: PMC7402038 DOI: 10.1101/2020.07.31.190454] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders Expanding (T-REX) was created to identify changes in both very rare and common cells in diverse human immune monitoring settings. T-REX identified cells that were highly similar in phenotype and localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized reagents used to detect the rhinovirus-specific CD4+ cells, MHCII tetramers, were not used during unsupervised analysis and instead 'left out' to serve as a test of whether T-REX identified biologically significant cells. In the rhinovirus challenge study, T-REX identified virus-specific CD4+ T cells based on these cells being a distinct phenotype that expanded by ≥95% following infection. T-REX successfully identified hotspots containing virus-specific T cells using pairs of samples comparing Day 7 of infection to samples taken either prior to infection (Day 0) or after clearing the infection (Day 28). Mapping pairwise comparisons in samples according to both the direction and degree of change provided a framework to compare systems level immune changes during infectious disease or therapy response. This revealed that the magnitude and direction of systemic immune change in some COVID-19 patients was comparable to that of blast crisis acute myeloid leukemia patients undergoing induction chemotherapy and characterized the identity of the immune cells that changed the most. Other COVID-19 patients instead matched an immune trajectory like that of individuals with rhinovirus infection or melanoma patients receiving checkpoint inhibitor therapy. T-REX analysis of paired blood samples provides an approach to rapidly identify and characterize mechanistically significant cells and to place emerging diseases into a systems immunology context.
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Affiliation(s)
- Sierra M. Barone
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alberta G.A. Paul
- Allergy Division, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Lyndsey M. Muehling
- Allergy Division, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Joanne A. Lannigan
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - William W. Kwok
- Benaroya Research Institute at Virginia Mason, Seattle, WA, USA
| | - Ronald B. Turner
- Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Judith A. Woodfolk
- Allergy Division, Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Jonathan M. Irish
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
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21
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Proietti I, Skroza N, Bernardini N, Tolino E, Balduzzi V, Marchesiello A, Michelini S, Volpe S, Mambrin A, Mangino G, Romeo G, Maddalena P, Rees C, Potenza C. Mechanisms of Acquired BRAF Inhibitor Resistance in Melanoma: A Systematic Review. Cancers (Basel) 2020; 12:E2801. [PMID: 33003483 PMCID: PMC7600801 DOI: 10.3390/cancers12102801] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 09/21/2020] [Accepted: 09/25/2020] [Indexed: 12/18/2022] Open
Abstract
This systematic review investigated the literature on acquired v-raf murine sarcoma viral oncogene homolog B1 (BRAF) inhibitor resistance in patients with melanoma. We searched MEDLINE for articles on BRAF inhibitor resistance in patients with melanoma published since January 2010 in the following areas: (1) genetic basis of resistance; (2) epigenetic and transcriptomic mechanisms; (3) influence of the immune system on resistance development; and (4) combination therapy to overcome resistance. Common resistance mutations in melanoma are BRAF splice variants, BRAF amplification, neuroblastoma RAS viral oncogene homolog (NRAS) mutations and mitogen-activated protein kinase kinase 1/2 (MEK1/2) mutations. Genetic and epigenetic changes reactivate previously blocked mitogen-activated protein kinase (MAPK) pathways, activate alternative signaling pathways, and cause epithelial-to-mesenchymal transition. Once BRAF inhibitor resistance develops, the tumor microenvironment reverts to a low immunogenic state secondary to the induction of programmed cell death ligand-1. Combining a BRAF inhibitor with a MEK inhibitor delays resistance development and increases duration of response. Multiple other combinations based on known mechanisms of resistance are being investigated. BRAF inhibitor-resistant cells develop a range of 'escape routes', so multiple different treatment targets will probably be required to overcome resistance. In the future, it may be possible to personalize combination therapy towards the specific resistance pathway in individual patients.
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Affiliation(s)
- Ilaria Proietti
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Nevena Skroza
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Nicoletta Bernardini
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Ersilia Tolino
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Veronica Balduzzi
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Anna Marchesiello
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Simone Michelini
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Salvatore Volpe
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Alessandra Mambrin
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | - Giorgio Mangino
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, 00185 Rome, Italy; (G.M.); (G.R.)
| | - Giovanna Romeo
- Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, 00185 Rome, Italy; (G.M.); (G.R.)
- Department of Infectious, Parasitic and Immune-Mediated Diseases, Istituto Superiore di Sanità, 00185 Rome, Italy
- Institute of Molecular Biology and Pathology, Consiglio Nazionale delle Ricerche, 00185 Rome, Italy
| | - Patrizia Maddalena
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
| | | | - Concetta Potenza
- Dermatology Unit “Daniele Innocenzi”, Department of Medical-Surgical Sciences and Bio-Technologies, Sapienza University of Rome, Fiorini Hospital, Polo Pontino, 04019 Terracina, Italy; (N.S.); (N.B.); (E.T.); (V.B.); (A.M.); (S.M.); (S.V.); (A.M.); (P.M.); (C.P.)
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22
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Mathew D, Giles JR, Baxter AE, Oldridge DA, Greenplate AR, Wu JE, Alanio C, Kuri-Cervantes L, Pampena MB, D'Andrea K, Manne S, Chen Z, Huang YJ, Reilly JP, Weisman AR, Ittner CAG, Kuthuru O, Dougherty J, Nzingha K, Han N, Kim J, Pattekar A, Goodwin EC, Anderson EM, Weirick ME, Gouma S, Arevalo CP, Bolton MJ, Chen F, Lacey SF, Ramage H, Cherry S, Hensley SE, Apostolidis SA, Huang AC, Vella LA, Betts MR, Meyer NJ, Wherry EJ. Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications. Science 2020; 369:eabc8511. [PMID: 32669297 PMCID: PMC7402624 DOI: 10.1126/science.abc8511] [Citation(s) in RCA: 1119] [Impact Index Per Article: 223.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 07/09/2020] [Indexed: 12/12/2022]
Abstract
Coronavirus disease 2019 (COVID-19) is currently a global pandemic, but human immune responses to the virus remain poorly understood. We used high-dimensional cytometry to analyze 125 COVID-19 patients and compare them with recovered and healthy individuals. Integrated analysis of ~200 immune and ~50 clinical features revealed activation of T cell and B cell subsets in a proportion of patients. A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses reaching >30% of circulating B cells. However, another subgroup had lymphocyte activation comparable with that in uninfected individuals. Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change. Our analyses identified three immunotypes associated with poor clinical trajectories versus improving health. These immunotypes may have implications for the design of therapeutics and vaccines for COVID-19.
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Affiliation(s)
- Divij Mathew
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Josephine R Giles
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Amy E Baxter
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Derek A Oldridge
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Allison R Greenplate
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jennifer E Wu
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Cécile Alanio
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Leticia Kuri-Cervantes
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - M Betina Pampena
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kurt D'Andrea
- Division of Translational Medicine and Human Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sasikanth Manne
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Zeyu Chen
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yinghui Jane Huang
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John P Reilly
- Division of Pulmonary, Allergy and Critical Care Medicine, Center for Translational Lung Biology, Lung Biology Institute, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ariel R Weisman
- Division of Pulmonary, Allergy and Critical Care Medicine, Center for Translational Lung Biology, Lung Biology Institute, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Caroline A G Ittner
- Division of Pulmonary, Allergy and Critical Care Medicine, Center for Translational Lung Biology, Lung Biology Institute, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Oliva Kuthuru
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jeanette Dougherty
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kito Nzingha
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas Han
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Justin Kim
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ajinkya Pattekar
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Gastroenterology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Eileen C Goodwin
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Elizabeth M Anderson
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Madison E Weirick
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sigrid Gouma
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Claudia P Arevalo
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marcus J Bolton
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Fang Chen
- Center for Cellular Immunotherapies, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Simon F Lacey
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Cellular Immunotherapies, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Holly Ramage
- Department of Microbiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sara Cherry
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott E Hensley
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sokratis A Apostolidis
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Rheumatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alexander C Huang
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Laura A Vella
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Infectious Disease, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Michael R Betts
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nuala J Meyer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - E John Wherry
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Parker Institute for Cancer Immunotherapy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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23
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Beckermann KE, Hongo R, Ye X, Young K, Carbonell K, Healey DCC, Siska PJ, Barone S, Roe CE, Smith CC, Vincent BG, Mason FM, Irish JM, Rathmell WK, Rathmell JC. CD28 costimulation drives tumor-infiltrating T cell glycolysis to promote inflammation. JCI Insight 2020; 5:138729. [PMID: 32814710 PMCID: PMC7455120 DOI: 10.1172/jci.insight.138729] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 07/08/2020] [Indexed: 02/06/2023] Open
Abstract
Metabolic reprogramming dictates the fate and function of stimulated T cells, yet these pathways can be suppressed in T cells in tumor microenvironments. We previously showed that glycolytic and mitochondrial adaptations directly contribute to reducing the effector function of renal cell carcinoma (RCC) CD8+ tumor-infiltrating lymphocytes (TILs). Here we define the role of these metabolic pathways in the activation and effector functions of CD8+ RCC TILs. CD28 costimulation plays a key role in augmenting T cell activation and metabolism, and is antagonized by the inhibitory and checkpoint immunotherapy receptors CTLA4 and PD-1. While RCC CD8+ TILs were activated at a low level when stimulated through the T cell receptor alone, addition of CD28 costimulation greatly enhanced activation, function, and proliferation. CD28 costimulation reprogrammed RCC CD8+ TIL metabolism with increased glycolysis and mitochondrial oxidative metabolism, possibly through upregulation of GLUT3. Mitochondria also fused to a greater degree, with higher membrane potential and overall mass. These phenotypes were dependent on glucose metabolism, as the glycolytic inhibitor 2-deoxyglucose both prevented changes to mitochondria and suppressed RCC CD8+ TIL activation and function. These data show that CD28 costimulation can restore RCC CD8+ TIL metabolism and function through rescue of T cell glycolysis that supports mitochondrial mass and activity.
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Affiliation(s)
| | - Rachel Hongo
- Department of Medicine, Division of Hematology and Oncology, and
| | - Xiang Ye
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kirsten Young
- Department of Medicine, Division of Hematology and Oncology, and
| | - Katie Carbonell
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Diana C. Contreras Healey
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter J. Siska
- Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Sierra Barone
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Caroline E. Roe
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Christof C. Smith
- Lineberger Comprehensive Cancer Center; Department of Medicine Division of Hematology and Oncology, Department of Microbiology and Immunology, Curriculum in Bioinformatics and Computational Biology, Computational Medicine Program, University of North Carolina (UNC), Chapel Hill, North Carolina, USA
| | - Benjamin G. Vincent
- Lineberger Comprehensive Cancer Center; Department of Medicine Division of Hematology and Oncology, Department of Microbiology and Immunology, Curriculum in Bioinformatics and Computational Biology, Computational Medicine Program, University of North Carolina (UNC), Chapel Hill, North Carolina, USA
| | - Frank M. Mason
- Department of Medicine, Division of Hematology and Oncology, and
| | - Jonathan M. Irish
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - W. Kimryn Rathmell
- Department of Medicine, Division of Hematology and Oncology, and
- Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jeffrey C. Rathmell
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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24
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Leelatian N, Sinnaeve J, Mistry AM, Barone SM, Brockman AA, Diggins KE, Greenplate AR, Weaver KD, Thompson RC, Chambless LB, Mobley BC, Ihrie RA, Irish JM. Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells. eLife 2020; 9:56879. [PMID: 32573435 PMCID: PMC7340505 DOI: 10.7554/elife.56879] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 06/04/2020] [Indexed: 12/16/2022] Open
Abstract
A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cells whose abundance independently and continuously stratified patient survival. Statistical validation within the workflow included repeated runs of stochastic steps and cell subsampling. Biological validation used an orthogonal platform, immunohistochemistry, and a larger cohort of 73 glioblastoma patients to confirm the findings from the pilot cohort. RAPID was also validated to find known risk stratifying cells and features using published data from blood cancer. Thus, RAPID provides an automated, unsupervised approach for finding statistically and biologically significant cells using cytometry data from patient samples.
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Affiliation(s)
- Nalin Leelatian
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States.,Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, United States
| | - Justine Sinnaeve
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States
| | - Akshitkumar M Mistry
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States.,Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, United States
| | - Sierra M Barone
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
| | - Asa A Brockman
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States
| | - Kirsten E Diggins
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States
| | - Allison R Greenplate
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States.,Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, United States
| | - Kyle D Weaver
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, United States
| | - Reid C Thompson
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, United States
| | - Lola B Chambless
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, United States
| | - Bret C Mobley
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, United States
| | - Rebecca A Ihrie
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States.,Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, United States
| | - Jonathan M Irish
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States.,Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, United States.,Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, United States
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25
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Mathew D, Giles JR, Baxter AE, Greenplate AR, Wu JE, Alanio C, Oldridge DA, Kuri-Cervantes L, Pampena MB, D’Andrea K, Manne S, Chen Z, Huang YJ, Reilly JP, Weisman AR, Ittner CA, Kuthuru O, Dougherty J, Nzingha K, Han N, Kim J, Pattekar A, Goodwin EC, Anderson EM, Weirick ME, Gouma S, Arevalo CP, Bolton MJ, Chen F, Lacey SF, Hensley SE, Apostolidis S, Huang AC, Vella LA, Betts MR, Meyer NJ, Wherry EJ. Deep immune profiling of COVID-19 patients reveals patient heterogeneity and distinct immunotypes with implications for therapeutic interventions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.05.20.106401. [PMID: 32511371 PMCID: PMC7263500 DOI: 10.1101/2020.05.20.106401] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
COVID-19 has become a global pandemic. Immune dysregulation has been implicated, but immune responses remain poorly understood. We analyzed 71 COVID-19 patients compared to recovered and healthy subjects using high dimensional cytometry. Integrated analysis of ~200 immune and >30 clinical features revealed activation of T cell and B cell subsets, but only in some patients. A subgroup of patients had T cell activation characteristic of acute viral infection and plasmablast responses could reach >30% of circulating B cells. However, another subgroup had lymphocyte activation comparable to uninfected subjects. Stable versus dynamic immunological signatures were identified and linked to trajectories of disease severity change. These analyses identified three "immunotypes" associated with poor clinical trajectories versus improving health. These immunotypes may have implications for therapeutics and vaccines.
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Affiliation(s)
- Divij Mathew
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Josephine R. Giles
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
- Parker Institute for Cancer Immunotherapy at University of Pennsylvania Perelman School of Medicine
| | - Amy E. Baxter
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Allison R. Greenplate
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Jennifer E. Wu
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
- Parker Institute for Cancer Immunotherapy at University of Pennsylvania Perelman School of Medicine
| | - Cécile Alanio
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
- Parker Institute for Cancer Immunotherapy at University of Pennsylvania Perelman School of Medicine
| | - Derek A. Oldridge
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine
| | - Leticia Kuri-Cervantes
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - M. Betina Pampena
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Kurt D’Andrea
- Division of Translational Medicine and Human Genetics, Perelman School of Medicine at the University of Pennsylvania
| | - Sasikanth Manne
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Zeyu Chen
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Yinghui Jane Huang
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - John P. Reilly
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Ariel R, Weisman
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Caroline A.G. Ittner
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Oliva Kuthuru
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Jeanette Dougherty
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Kito Nzingha
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Nicholas Han
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Justin Kim
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
| | - Ajinkya Pattekar
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Division of Gastroenterology, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Eileen C. Goodwin
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Elizabeth M. Anderson
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Madison E. Weirick
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Sigrid Gouma
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Claudia P. Arevalo
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Marcus J. Bolton
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Fang Chen
- Center for Cellular Immunotherapies,University of Pennsylvania Perelman School of Medicine
| | - Simon F. Lacey
- Center for Cellular Immunotherapies,University of Pennsylvania Perelman School of Medicine
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine
| | - Scott E. Hensley
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Sokratis Apostolidis
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Division of Rheumatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Alexander C. Huang
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Division of Hematology and Oncology, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - Laura A. Vella
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Division of Infectious Disease, Department of Pediatrics, Children’s Hospital of Philadelphia
| | | | - Michael R. Betts
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine
| | - Nuala J. Meyer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine
| | - E. John Wherry
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine
- Parker Institute for Cancer Immunotherapy at University of Pennsylvania Perelman School of Medicine
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26
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Valpione S, Galvani E, Tweedy J, Mundra PA, Banyard A, Middlehurst P, Barry J, Mills S, Salih Z, Weightman J, Gupta A, Gremel G, Baenke F, Dhomen N, Lorigan PC, Marais R. Immune-awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy. NATURE CANCER 2020; 1:210-221. [PMID: 32110781 PMCID: PMC7046489 DOI: 10.1038/s43018-019-0022-x] [Citation(s) in RCA: 141] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 12/17/2019] [Indexed: 12/19/2022]
Abstract
Our understanding of how checkpoint inhibitors (CPI) affect T cell evolution is incomplete, limiting our ability to achieve full clinical benefit from these drugs. Here we analyzed peripheral T cell populations after one cycle of CPI and identified a dynamic awakening of the immune system revealed by T cell evolution in response to treatment. We sequenced T cell receptors (TCR) in plasma cell-free DNA (cfDNA) and peripheral blood mononuclear cells (PBMC) and performed phenotypic analysis of peripheral T cell subsets from metastatic melanoma patients treated with CPI. We found that early peripheral T cell turnover and TCR repertoire dynamics identified which patients would respond to treatment. Additionally, the expansion of a subset of immune-effector peripheral T cells we call TIE cells correlated with response. These events are prognostic and occur within 3 weeks of starting immunotherapy, raising the potential for monitoring patients responses using minimally invasive liquid biopsies."
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Affiliation(s)
- Sara Valpione
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
- The Christie NHS Foundation Trust, Manchester, UK
| | - Elena Galvani
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Joshua Tweedy
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Piyushkumar A Mundra
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Antonia Banyard
- Advanced Imaging and Flow Cytometry, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Philippa Middlehurst
- Manchester Cancer Research Centre Biobank, The Christie NHS Foundation Trust, Manchester, UK
| | - Jeff Barry
- Advanced Imaging and Flow Cytometry, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | - Sarah Mills
- Manchester Cancer Research Centre Biobank, The Christie NHS Foundation Trust, Manchester, UK
| | - Zena Salih
- The Christie NHS Foundation Trust, Manchester, UK
| | - John Weightman
- Molecular Biology Core Facility, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | | | - Gabriela Gremel
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
- Boehringer Ingelheim, Vienna, Austria
| | - Franziska Baenke
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
- German Cancer Consortium (DKTK), German Cancer Research Centre (DKFZ), Heidelberg, Germany
- Department of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Nathalie Dhomen
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK
| | | | - Richard Marais
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, UK.
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