scholarly journals Expression and prognosis analysis of JMJD5 in human cancers

2020 ◽  
Author(s):  
Hui Li ◽  
Qun Li ◽  
Hong Jing ◽  
Jianghai Zhao ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Prognostic Value ◽  
Normal Tissues ◽  
Human Cancers ◽  
Stomach Adenocarcinoma ◽  
Liver Hepatocellular Carcinoma

Abstract BackgroundJumonjiC (JmjC) domain-containing protein 5 (JMJD5) plays an important role in cancer metabolism. However, the prognostic value of JMJD5 in most human cancers is still unknown. In this study, we aim to investigate the expression and prognostic value of JMJD5, immune cells infiltration, and the correlations among them. MethodsWe performed a detailed cancer vs. normal analysis of JMJD5 mRNA expression via online Tumor Immune Estimation Resource (TIMER). The protein expressions of JMJD5 in various cancers vs. adjacent normal tissues were examined by immunohistochemistry (IHC) of tissue microarray sections (TMAs). Moreover, the Kaplan-Meier Plotter databases were used to evaluate the prognostic values in above cancers. The correlations between JMJD5 expression level and abundances of six immune infiltrating cells (B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils and dendritic cells) were explored by TIMER database in breast cancer (BRCA), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and stomach adenocarcinoma (STAD). The prognostic values of tumor- infiltrating immune cells were also investigated by TIMER in above four cancers. Finally, the COX proportional hazards model was used to investigate the correlations among clinical outcome, the abundance of immune cell infiltrates and the expression of JMJD5 in above four cancer types.ResultsThe expression of JMJD5 was significantly lower in human breast carcinoma (BRCA), cholangiocarcinoma (CHOL), liver hepatocellular carcinoma (LIHC) and lung cancer (LUC) but higher in prostate adenocarcinoma (PRAD) and stomach adenocarcinoma (STAD) comparing to their respective normal tissues. And high expression of JMJD5 has better prognosis only in BRCA, LIHC, LUC but the opposite effect in STAD. JMJD5 expression is significant correlation with the abundance of six immune cells infiltration in above four cancers. Both the BRCA or lung adenocarcinoma (LUAD) patients with abundance of B cell and the STAD patients with low level of macrophage have a better cumulative survival. ConclusionsWe provided novel evidence of JMJD5 as an essential prognostic biomarker in cancers through analyses the correlation of the JMJD5 expression, tumor-infiltrating B cells and macrophages and prognostic value. This study offers new perspectives therapeutic target in BRCA, LUAD and STAD.

scholarly journals Expression and Prognosis Analysis of JMJD5 in Human Cancers

2020 ◽  
Author(s):  
Hui Li ◽  
Qun Li ◽  
Hong Jing ◽  
Jianghai Zhao ◽  
Hui Zhang ◽  
...  
Keyword(s):  
B Cells ◽  
Immune Cells ◽  
Prognostic Value ◽  
Cancer Metabolism ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Normal Tissues ◽  
Human Cancers

Abstract JumonjiC (JmjC) domain-containing protein 5 (JMJD5) plays an important role in cancer metabolism. However, the prognostic value of JMJD5 in most human cancers is still unknown. In this study, we aim to investigate the expression and prognostic value of JMJD5, immune cells infiltration, and the correlations among them. We found: The expression of JMJD5 was significantly lower in human breast carcinoma (BRCA), cholangiocarcinoma (CHOL), liver hepatocellular carcinoma (LIHC) and lung cancer (LUC) but higher in prostate adenocarcinoma (PRAD) and stomach adenocarcinoma (STAD) comparing to their respective normal tissues by online Tumor Immune Estimation Resource (TIMER) and immunohistochemistry (IHC) of tissue microarray sections (TMAs) respectively. And high expression of JMJD5 has better prognosis only in BRCA, LIHC, LUC but the opposite effect in STAD by the Kaplan-Meier Plotter databases analyses. Further analysis revealed JMJD5 expression is significant correlation with the abundance of six immune cells infiltration in above four cancers by TIMER, and evaluated the prognostic value by the combination of JMJD5 expression with either B cells or macrophages tumor infiltration by the COX proportional hazards model. Both the BRCA or lung adenocarcinoma (LUAD) patients with abundance of B cell and the STAD patients with low level of macrophage have a better cumulative survival by TIMER. In conclusion, we provided novel evidence of JMJD5 as an essential prognostic biomarker in cancers through analyses the correction of the JMJD5 expression, tumor-infiltrating B cells and macrophages and prognostic value. This study offers new perspectives therapeutic target in BRCA, LUAD and STAD.

scholarly journals Independent Prognostic Potential of GNPNAT1 in Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xiangyu Zheng ◽  
Yongwei Li ◽  
Chao Ma ◽  
Jinjun Zhang ◽  
Yanmin Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Cd4 T Cells ◽  
Prognostic Value ◽  
Marker Genes ◽  
Immune Signatures ◽  
Cox Analysis

Background. Glucosamine-Phosphate N-Acetyltransferase 1 (GNPNAT1) is a critical enzyme in the biosynthesis of uridine diphosphate-N-acetylglucosamine. It has many important functions, such as protein binding, monosaccharide binding, and embryonic development and growth. However, the role of GNPNAT1 in lung adenocarcinoma (LUAD) remains unclear. Methods. In this study, we explored the expression pattern and prognostic value of GNPNAT1 in LUAD across TCGA and GEO databases and assessed its independent prognostic value via Cox analysis. LinkedOmics and GEPIA2 were applied to investigate coexpression and functional networks associated with GNPNAT1. The TIMER web tool was deployed to assess the correlation between GNPNAT1 and the main six types of tumor-infiltrating immune cells. Besides, the correlations between GNPNAT1 and the LUAD common genetic mutations, TMB, and immune signatures were examined. Results. GNPNAT1 was validated upregulated in tumor tissues in TCGA-LUAD and GEO cohorts. Moreover, in both TCGA and GEO cohorts, high GNPNAT1 expression was found to be associated with poor overall survival. Cox analysis showed that high GNPNAT1 expression was an independent risk factor for LUAD. Functional network analysis suggested that GNPNAT1 regulates cell cycle, ribosome, proteasome, RNA transport, and spliceosome signaling through pathways involving multiple cancer-related kinases and E2F family. In addition, GNPNAT1 correlated with infiltrating levels of B cells, CD4+ T cells, and dendritic cells. B cells and dendritic cells could predict the outcome of LUAD, and B cells and CD4+ T cells were significant independent risk factors. The TMB and mutations of KRAS, EGFR, STK11, and TP53 were correlated with GNPNAT1. At last, the correlation analysis showed GNPNAT1 correlated with most of the immune signatures we performed. Conclusion. Our findings showed that GNPNAT1 was correlated to the prognosis and immune infiltration of LUAD. In particular, the tight relationship between GNPNAT1 and B cell marker genes may be the epicenter of the immune response and one of the key factors affecting the prognosis. Our findings laid the foundation for further research on the immunomodulatory role of GNPNAT1 in LUAD.

scholarly journals Differential Immune Landscape of Hepatocellular Carcinoma Suggests Potential role of Macrophages in Hepatocarcinogenesis

2021 ◽  
Vol 37 (3) ◽  
Author(s):  
Yusra Shafique ◽  
Muhammad Asif Qureshi ◽  
Saeed Khan ◽  
Talat Mirza
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Potential Role ◽  
Immune Cell ◽  
P Value

Objectives: To investigate immune cell densities in tumor microenvironment of hepatocellular carcinoma. Methods: This cross-sectional study was conducted during 2017-2019 at the Dow University of Health Sciences Karachi. A total of 42 subsequent patients undergoing liver biopsy/resection and diagnosed with hepatocellular carcinoma were included in the study. Moreover, a total of 10 control tissues were also included. In order to investigate immune cells densities in hepatocellular carcinoma, immunohistochemistry was performed using antibodies including α-MPO(neutrophils), α-CD-68(macrophages), α-CD-3(T-cells), α-CD-20(B-cells), α-CD-4(CD4+ T-cells) and α-CD-8(CD8+ T-cells). Quantification of immune cells/mm2 was performed as per the College of American Pathologists’ guidelines. Data were analyzed using SPSS version 21. A p-value of 0.05 was considered significant at all times. Results: We report significantly increased infiltration of macrophages (mean macrophages= 306.57/mm2, p-value<0.05), moderately significant infiltration of neutrophils (p-value=0.06) and B-cells (p-value=0.07) while no significant infiltration of CD4+T-cells (p- value=0.31), and CD8+T-cells (p-value=0.39) in tumour microenvironment of patients with hepatocellular carcinoma. Conclusion: We provide evidence for increased macrophage infiltration in liver cancer microenvironment suggesting a potential role of these cells in hepatocarcinogenesis. doi: https://doi.org/10.12669/pjms.37.3.2973 How to cite this:Shafique Y, Qureshi MA, Khan S, Mirza T. Differential Immune Landscape of Hepatocellular Carcinoma Suggests Potential role of Macrophages in Hepatocarcinogenesis. Pak J Med Sci. 2021;37(3):---------. doi: https://doi.org/10.12669/pjms.37.3.2973 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

scholarly journals Identification of Therapeutic Targets and Prognostic Biomarkers Among Chemokine (C-C Motif) Ligands in the Liver Hepatocellular Carcinoma Microenvironment

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhongyi Jiang ◽  
Changchang Xing ◽  
Pusen Wang ◽  
Xueni Liu ◽  
Lin Zhong
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Western Blot ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Stromal Cells ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints ◽  
Immunological Therapy ◽  
Liver Hepatocellular Carcinoma

Background: Liver hepatocellular carcinoma (LIHC) is the third leading cause of cancer-related death and the sixth most common solid tumor worldwide. In the tumor microenvironment, the cross-talk between cancer cells, immune cells, and stromal cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. Chemokine (C-C motif) ligands (CCL) can directly target tumor cells and stromal cells, and they have been shown to regulate tumor cell proliferation, cancer stem-like cell properties, cancer invasiveness and metastasis, which directly and indirectly affect tumor immunity and influence cancer progression, therapy and patient outcomes. However, the prognostic values of chemokines CCL in LIHC have not been clarified.Methods: In this study, we comprehensively analyzed the relationship between transcriptional chemokines CCL and disease progression of LIHC using the ONCOMINE dataset, GEPIA, UALCAN, STRING, WebGestalt, GeneMANIA, TRRUST, DAVID 6.8, LinkedOmics, TIMER, GSCALite, and Open Targets. We validated the protein levels of chemokines CCL through western blot and immunohistochemistry.Results: The transcriptional levels of CCL5/8/11/13/15/18/20/21/25/26/27/28 in LIHC tissues were significantly elevated while CCL2/3/4/14/23/24 were significantly reduced. A significant correlation was found between the expression of CCL14/25 and the pathological stage of LIHC patients. LIHC patients with low transcriptional levels of CCL14/21 were associated with a significantly poor prognosis. The functions of differentially expressed chemokines CCL were primarily related to the chemokine signaling pathway, cytokine–cytokine receptor interactions, and TNF-α signaling pathway. Our data suggested that RELA/REL, NFKB1, STAT1/3/6, IRF3, SPI1, and JUN were key transcription factors for chemokines CCL. We found significant correlations among the expression of chemokines CCL and the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) and immune checkpoints (PD-1. PD-L1, and CTLA-4). The western blot and immunohistochemistry results showed that protein expression levels of CCL5 and CCL20 were upregulated in LIHC. CCL5 and CCL20 were significantly correlated with the clinical outcome of patients with LIHC, and could be negatively regulated by some drugs or small molecules.Conclusions: Our results may provide novel insights for the potential suitable targets of immunological therapy and prognostic biomarkers for LIHC.

scholarly journals Prognostic Value of Complement Component 2 and Its Correlation with Immune Infiltrates in Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Gang Ning ◽  
Yan-Lin Huang ◽  
Li-Min Zhen ◽  
Wen-Xiong Xu ◽  
Xue-Jun Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Prognostic Value ◽  
Complement Component ◽  
Healthy Controls ◽  
Single Nucleotide ◽  
Ampk Signaling ◽  
Normal Tissues ◽  
Ppar Signaling

Background. Single nucleotide polymorphism (SNP) of complement component 2 (C2) has been found to be significantly associated with hepatocellular carcinoma (HCC). However, little is known about the role and mechanism of C2 in HCC. In the present study, we aimed to explore the prognostic value of C2 and its correlation with tumor-infiltrating immune cells in HCC. Materials and Methods. mRNA expression was downloaded from TCGA (365 HCC patients and 50 healthy controls), GSE14520 (220 HCC patients and 220 adjacent normal tissues), and ICGC HCC (232 HCC patients) cohorts. Unpaired Student’s t-tests or ANOVA tests were used to evaluate differences of C2 expression. Univariate and multivariate analyses were used to analyze the prognostic value of C2. CIBERSORT was used to calculate the proportion of 22 kinds of tumor-infiltrating immune cells. Results. Significantly lower C2 expression was found at HCC compared to healthy controls, and C2 was associated with TNM stages. Higher C2 expression was significantly associated with better prognosis, and multivariate analysis showed that C2 was also an independent factor for the prognosis of HCC. Moreover, elevated CD4 T cells were found at HCC patients with higher C2 expression while the higher proportion of macrophage M0 cells was found in HCC patients with lower C2 expression. KEGG analysis showed that “cell cycle,” “AMPK signaling pathway,” and “PPAR signaling pathway” were enriched in HCC patients with higher C2 expression. Conclusion. C2 is a prognostic factor for HCC and may be used as a therapeutic target for future treatment of HCC.

scholarly journals AUNIP Expression Is Correlated With Immune Infiltration and Is a Candidate Diagnostic and Prognostic Biomarker for Hepatocellular Carcinoma and Lung Adenocarcinoma

2020 ◽  
Vol 10 ◽  
Author(s):  
Chenxi Ma ◽  
Wenyan Kang ◽  
Lu Yu ◽  
Zongcheng Yang ◽  
Tian Ding
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Copy Number Variation ◽  
Lung Adenocarcinoma ◽  
Copy Number ◽  
Prognostic Biomarker ◽  
Variation Analysis ◽  
Immune Infiltration ◽  
Number Variation

AUNIP, a novel prognostic biomarker, has been shown to be associated with stromal and immune scores in oral squamous cell carcinoma (OSCC). Nonetheless, its role in other cancer types was unclear. In this study, AUNIP expression was increased in hepatocellular carcinoma (HCC) and lung adenocarcinoma (LUAD) according to data from The Cancer Genome Atlas (TCGA) database, Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), and Gene Expression Omnibus (GEO) database (GSE45436, GSE102079, GSE10072, GSE31210, and GSE43458). Further, according to copy number variation analysis, AUNIP up-regulation may be associated with copy number variation. Immunohistochemistry showed AUNIP expression was higher in HCC and LUAD compared with the normal tissues. Receiver operating characteristic (ROC) curve analysis demonstrated that AUNIP is a candidate diagnostic biomarker for HCC and LUAD. Next, TCGA, International Cancer Genome Consortium (ICGC), and GEO (GSE31210 and GSE50081) data showed that increased AUNIP expression clearly predicted poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in HCC and LUAD. Additionally, multivariate Cox regression analysis involving various clinical factors showed that AUNIP is an independent prognostic biomarker for HCC and LUAD. Next, the role of AUNIP in HCC and LUAD was explored via a co-expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and a gene set variation analysis (GSVA). HCC and LUAD exhibited almost identical enrichment results. More specifically, high AUNIP expression was associated with DNA replication, cell cycle, oocyte meiosis, homologous recombination, mismatch repair, the p53 signal transduction pathway, and progesterone-mediated oocyte maturation. Lastly, the Tumor Immune Estimation Resource (TIMER) tool was used to determine the correlations of AUNIP expression with tumor immune infiltration. AUNIP expression was positively correlated with the infiltration degree of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells in HCC. However, AUNIP expression was negatively correlated with the infiltration degree of B cells, CD4+ T cells, and macrophages in LUAD. In addition, AUNIP expression was correlated with immune infiltration in various other tumors. In conclusion, AUNIP, which is associated with tumor immune infiltration, is a candidate diagnostic and prognostic biomarker for HCC and LUAD.

scholarly journals Novel Prognostic Markers for Liver Hepatocellular Carcinoma and Their Roles in Immune Infiltration of the Tumor Microenvironment

2021 ◽  
Author(s):  
Meihai Deng ◽  
Hao Liang ◽  
Kunpeng Hu ◽  
Zhaozhong Zhong ◽  
Zhiyong Xiong ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Rna Seq ◽  
Hub Genes ◽  
Novel Biomarkers ◽  
Liver Hepatocellular Carcinoma ◽  
Memory Cd4 T Cells

Abstract Background: Liver hepatocellular carcinoma (LIHC) is one of the most common malignant cancers worldwide, the overall prognosis of LIHC remains unsatisfactory. Valuable prognostic biomarkers are still urgently needed for LIHC. This study aimed to explore hub genes associated with the prognosis of LIHC and tumor microenvironmental immune infiltration, providing potential prognostic biomarker and therapeutic target for LIHC. Methods: RNA-seq counts data for LIHC samples were obtained from TCGA database. RNA-seq counts data for normal liver samples were obtained from GTEx database. Weighted gene co-expression network analysis (WGCNA) was used to cluster differentially expressed genes with similar expression profiles to form modules and significant modules and key genes were screened. Next, these genes was verified by cox analyses and overall survival analysis. Further, CIBERSORT was used to explore the relationship between these genes and tumor infiltrating immune cells. Results: A total number of 2661 significant DEGs were included for consensus WGCNA analysis, which identified 6 modules. Blue module (r=0.85, p<0.0001) showed high relationship with LIHC, which included 400 genes. After the overall survival analyses of hub genes, CDC20, CDCA5, CDCA8, KIF2C and KIFC1 were identified as five potential marker genes, which would result in an unfavorable prognosis in LIHC. Further CIBERSORT analysis showed these novel biomarkers expression levels in LIHC were positively correlated with activated memory CD4+ T cells, follicular helper T cells, regulatory T cells and macrophages M0. While, resting memory CD4+ T cells, monocytes, macrophages M2, resting mast cells showed a negative correlation with the 5 novel biomarkers expression levels. Conclusions: The study screened 5 genes with marked prognostic capability for LIHC and found these genes were correlated with the infiltration of immune cells in LIHC tumor microenvironment. The findings might provide a more detailed molecular mechanism underlying LIHC occurrence and progression, holding promise for acting as potential biomarkers and therapeutic targets.

Prognostic value of peripheral naive CD8+ T cells in oligometastatic non-small-cell lung cancer

2021 ◽  
Author(s):  
Xin Zhao ◽  
Yan Zhang ◽  
Zhenlin Gao ◽  
Yaguang Han
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
T Cells ◽  
Small Cell Lung Cancer ◽  
Immune Cells ◽  
Prognostic Value ◽  
Progression Free Survival ◽  
Small Cell ◽  
Small Cell Lung ◽  
Free Survival

Aim: This study aimed to investigate the prognostic value of peripheral naive and memory CD8+ and CD4+ T cells and other immune cells in patients with oligometastatic non-small-cell lung cancer (NSCLC) undergoing radiotherapy (RT). Methods: A total of 142 patients with oligometastatic NSCLC treated with RT were enrolled, and their blood samples were collected within 3 days before RT. Immune cells were identified by flow cytometry. Results: Patients with high levels of naive CD8+ T cells had longer overall survival (p = 0.004) and progression-free survival (p = 0.001) than those with low levels of naive CD8+ T cells. Multivariate analyses revealed that naive CD8+ T cells were independently correlated with overall survival (p = 0.019) and progression-free survival (p = 0.024). Conclusion: The results suggest that peripheral naive CD8+ T cells may be an independent prognostic indicator for patients with oligometastatic NSCLC undergoing RT.

Engineered immunostimulatory cells can convert PBMCs from chronic lymphocytic leukemia (CLL) patients into potent tumor killing immune cells.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 7517-7517
Author(s):  
Joshua W. Keegan ◽  
Frank Borriello ◽  
Stacey M. Fernandes ◽  
Jennifer R. Brown ◽  
James A. Lederer
Keyword(s):  
T Cells ◽  
B Cells ◽  
Tumor Cell ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Killing Activity ◽  
Tumor Killing ◽  
Tumor Cell Killing ◽  
Potent Tumor

7517 Background: Alloplex Biotherapeutics has developed a cellular therapeutic that uses ENgineered Leukocyte ImmunoSTimulatory cell lines called ENLIST cells to activate and expand populations of tumor killing effector cells from human peripheral blood mononuclear cells (PBMCs). This process leads to a 300-fold expansion of NK cells, CD8+ T cells, NKT cells, and TCRγδ T cells that are called SUPLEXA cells, which will be cryopreserved and transferred back into patients as an autologous immune cell therapy for cancer. In this study, PBMCs from CLL patients were used to generate SUPLEXA cells as a first approach to comparatively profile SUPLEXA cells from cancer patients and normal healthy volunteers (NHVs). Methods: ENLIST cell lines were engineered by expressing curated immunomodulatory proteins in the SK-MEL-2 melanoma cell line. Two million (M) PBMCs from 10 CLL patients or 2 NHVs were incubated with 0.4 M freeze/thaw killed ENLIST cells for 5 days in XVIVO-15 medium with 2% heat-inactivated human AB serum (XAB2) and then split 1:15 in XAB2 containing IL-7 and IL-15 to expand. After 9 days, SUPLEXA cells were harvested and cryopreserved. Results: Original PBMCs and matched SUPLEXA cells from each donor were thawed and characterized by mass cytometry (CyTOF) using a 47-marker antibody panel. CyTOF staining results of PBMCs from CLL patients demonstrated approximately 95% leukemia cells and few T cells, NK cells, B cells, and monocytes. CyTOF staining of SUPLEXA cells from all 10 CLL patients showed expansion of NK cells (17%), CD8 T cells (11%), and CD4 T cells (7.5%) that were similar in phenotype to SUPLEXA cells from NHVs showing high expression of granzymes and perforin that are indicative of potent tumor cell killing activity. Cancer cells in the original CLL PBMC samples were reduced to 0.78%. However, a population of non-T/non-B cells (60% ± 9.5%) was detected in SUPLEXA cells from all CLL patients that require further characterization. Next, SUPLEXA cells from CLL and NHV patients were comparatively tested for tumor cell killing activity at 2:1, 1:1, and 1:2 effector to target cell (MEL-14 melanoma cells expressing RFP) ratios. Percent killing of tumor cells by SUPLEXA cells prepared from CLL patients (77.8% ± 2.6% at 2:1) and NHVs (81.5% ± 0.3% at 2:1) were nearly identical at all effector to target ratios. Conclusions: We demonstrate for the first time that PBMCs from CLL patients can be converted into SUPLEXA cells despite low numbers of normal immune cells at baseline and the known immunologic impairment present in CLL patients. Importantly, SUPLEXA cells derived from CLL patients acquire potent tumor killing activity that is indistinguishable from SUPLEXA cells prepared from NHVs. Taken together, these findings support the feasibility of converting PBMCs from CLL patients with low percentages of NK and T cells into an autologous cellular therapy for cancer.

Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 32-33
Author(s):  
Tomohiro Aoki ◽  
Lauren C. Chong ◽  
Katsuyoshi Takata ◽  
Katy Milne ◽  
Elizabeth Chavez ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Expression Patterns ◽  
The Other ◽  
Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

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