Single-cell analyses identify tobacco smoke exposure-associated, dysfunctional CD16+ CD8 T cells with high cytolytic potential in peripheral blood

SUMMARYTobacco smoke exposure has been found to impact immune response, leukocyte subtypes, DNA methylation, and gene expression in human whole blood. Analysis with single cell technologies will resolve smoking associated (sub)population compositions, gene expression differences, and identification of rare subtypes masked by bulk fraction data. To characterize smoking-related gene expression changes in primary immune cells, we performed single-cell RNA sequencing (scRNAseq) on >45,000 human peripheral blood mononuclear cells (PBMCs) from smokers (n=4) and nonsmokers (n=4). Major cell type population frequencies showed strong correlation between scRNAseq and mass cytometry. Transcriptomes revealed an altered subpopulation of Natural Killer (NK)-like T lymphocytes in smokers, which expressed elevated levels of FCGR3A (gene encoding CD16) compared to other CD8 T cell subpopulations. Relatively rare in nonsmokers (median: 1.8%), the transcriptionally unique subset of CD8 T cells comprised 7.3% of PBMCs in smokers. Mass cytometry confirmed a significant increase (p = 0.03) in the frequency of CD16+ CD8 T cells in smokers. The majority of CD16+ CD8 T cells were CD45RA positive, indicating an effector memory re-expressing CD45RA T cell (TEMRA) phenotype. We expect that cigarette smoke alters CD8 T cell composition by shifting CD8 T cells toward differentiated functional states. Pseudotemporal ordering of CD8 T cell clusters revealed that smokers’ cells were biased toward later pseudotimes, and characterization of established markers in CD8 T cell subsets indicates a higher frequency of terminally differentiated cells in smokers than in nonsmokers, which corresponded with a lower frequency in naïve CD8 T cells. Consistent with an end-stage TEMRA phenotype, FCGR3A-expressing CD8 T cells were inferred as the most differentiated cluster by pseudotime analysis and expressed markers linked to senescence. Examination of differentially expressed genes in other PBMCs uncovered additional senescence-associated genes in CD4 T cells, NKT cells, NK cells, and monocytes. We also observed elevated Tregs, inducers of T cell senescence, in smokers. Taken together, our results suggest smoking-induced, senescence-associated immune cell dysregulation contributes to smoking-mediated pathologies.

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Single cell profiling of T and B cell repertoires following SARS-CoV-2 mRNA vaccine

10.1101/2021.07.14.452381 ◽

2021 ◽

Author(s):

Suhas Sureshchandra ◽

Sloan A. Lewis ◽

Brianna Doratt ◽

Allen Jankeel ◽

Izabela Ibraim ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

B Cell ◽

Single Cell ◽

Cd8 T Cells ◽

Natural Infection ◽

T Cell Responses ◽

Cd8 T Cell ◽

Cd4 T Cell ◽

Cell Responses

mRNA based vaccines for SARS-CoV-2 have shown exceptional clinical efficacy providing robust protection against severe disease. However, our understanding of transcriptional and repertoire changes following full vaccination remains incomplete. We used single-cell RNA sequencing and functional assays to compare humoral and cellular responses to two doses of mRNA vaccine with responses observed in convalescent individuals with asymptomatic disease. Our analyses revealed enrichment of spike-specific B cells, activated CD4 T cells, and robust antigen-specific polyfunctional CD4 T cell responses in all vaccinees. On the other hand, CD8 T cell responses were both weak and variable. Interestingly, clonally expanded CD8 T cells were observed in every vaccinee, as observed following natural infection. TCR gene usage, however, was variable, reflecting the diversity of repertoires and MHC polymorphism in the human population. Natural infection induced expansion of larger CD8 T cell clones occupied distinct clusters, likely due to the recognition of a broader set of viral epitopes presented by the virus not seen in the mRNA vaccine. Our study highlights a coordinated adaptive immune response where early CD4 T cell responses facilitate the development of the B cell response and substantial expansion of effector CD8 T cells, together capable of contributing to future recall responses.

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T Cell Recognition of HCMV: Pan-Genome Analysis of Immunogenic Open-Reading Frames.

Blood ◽

10.1182/blood.v104.11.606.606 ◽

2004 ◽

Vol 104 (11) ◽

pp. 606-606 ◽

Cited By ~ 1

Author(s):

Louis J. Picker ◽

Andrew W. Sylwester ◽

Bridget L. Mitchell ◽

Cara Taormina ◽

Christian Pelte ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Cd8 T Cells ◽

Peripheral Blood ◽

Cell Response ◽

Cd8 T Cell ◽

Cross Reactivity ◽

T Cell Response ◽

Cd4 T Cell ◽

Cell Responses

Abstract Human Cytomegalovirus (HCMV) is among the largest and most complex of known viruses with 150–200nm virions enclosing a double stranded 230kb DNA genome capable of coding for >200 proteins. HCMV infection is life-long, and for the vast majority of immune competent individuals clinically benign. Disease occurs almost exclusively in the setting of immune deficiency, suggesting that the stable host-parasite relationship that characterizes these infections is the result of an evolutionarily “negotiated” balance between viral mechanisms of pathogenesis and the host immune response. In keeping with, and perhaps because of this balance, the human CD4+ T cell response to whole HCMV viral lysates is enormous, with median peripheral blood frequencies of HCMV-specific cells ~5–10 fold higher than for analogous preparations of other common viruses. Although certain HCMV ORFs have been identified as targets of either the CD4+ or CD8+ T cell response, the specificities comprising the CD4+ T cell response, and both the total frequencies and component parts of the CD8+ T cell response are unknown. Here, we used cytokine flow cytometry and ~14,000 overlapping 15mer peptides comprising all 213 HCMV ORFs encoding proteins >100 amino acids in length to precisely define the total CD4+ and CD8+ HCMV-specific T cell responses and the HCMV ORFs responsible for these responses in 33 HCMV-seropositive, HLA-disparate donors. An additional 9 HCMV seronegative donors were similarly examined to define the extent to which non-HCMV responses cross-react with HCMV-encoded epitopes. We found that when totaled, the median frequencies of HCMV-specific CD4+ and CD8+ T cells in the peripheral blood of the seropositive subjects were 4.0% and 4.5% for the total CD4+ or CD8+ T cell populations, respectively (which corresponds to 9.1% and 10.5% of the memory populations, respectively). The HCMV-specific CD4+ and CD8+ T cell responses included a median 12 and 7 different ORFs, respectively, and all told, 73 HCMV ORFs were identified as targets for both CD4+ and CD8+ T cells, 26 ORFs as targets for CD8+ T cells alone, and 43 ORFS as targets for CD4+ T cells alone. UL55, UL83, UL86, UL99, and UL122 were the HCMV ORFs most commonly recognized by CD4+ T cells; UL123, UL83, UL48, UL122 and UL28 were the HCMV ORFs most commonly recognized by CD8+ T cells. The relationship between immunogenicity and 1) HLA haplotype and 2) ORF expression and function will be discussed. HCMV-seronegative individuals were non-reactive with the vast majority of HCMV peptides. Only 7 potentially cross-reactive responses were identified (all by CD8+ T cells) to 3 ORFs (US32, US29 and UL116) out of a total of almost 4,000 potential responses, suggesting fortuitous cross-reactivity with HCMV epitopes is uncommon. These data provide the first glimpse of the total human T cell response to a complex infectious agent, and will provide insight into the rules governing immunodominance and cross-reactivity in complex viral infections of humans.

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WT1-Specific CD8+ T Lymphocytes May Participate in the Elimination of Acute Lymphoblastic Leukemia Following Allogeneic Stem Cell Transplantation.

Blood ◽

10.1182/blood.v108.11.3679.3679 ◽

2006 ◽

Vol 108 (11) ◽

pp. 3679-3679 ◽

Cited By ~ 1

Author(s):

Katayoun Rezvani ◽

Agnes Yong ◽

Stephan Mielke ◽

Bipin N. Savani ◽

David A. Price ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Stem Cell ◽

T Cell ◽

Cd8 T Cells ◽

Lymphoblastic Leukemia ◽

T Cell Responses ◽

Cd8 T Cell ◽

Wt1 Gene ◽

Cell Responses

Abstract There is clinical evidence that a graft-versus-leukemia (GVL) effect occurs following allogeneic stem cell transplantation for acute lymphoblastic leukemia (ALL). However, the potency of this GVL effect is often associated with unwanted graft-versus-host-disease (GVHD) and disease relapse remains a major contributor to treatment failure. Wilms’ tumor gene 1 (WT1) is overexpressed in 70–90% of cases of ALL and has been identified as a convenient minimal residual disease (MRD) marker. WT1 is an attractive immunotherapeutic target in ALL because peptides derived from WT1 can induce CD8+ T-cell responses, and being non-allelic, WT1 would be unlikely to provoke GVHD. We investigated whether CD8+ T-cells directed against an HLA-A*0201 restricted epitope of WT1 (WT126) occur in ALL patients during the early phase of immune reconstitution post-SCT (days 30–180). We analyzed CD8+ T-cell responses against WT1 in 10 HLA-A*0201+ ALL SCT recipients and their respective donors using WT1/HLA-A*0201 tetrameric complexes and flow cytometry for intracellular IFN-gamma. We studied the kinetics WT1-specific CD8+ T-cell responses in consecutive samples obtained post-SCT. CD8+ T-cells recognizing WT1 were detected ex vivo in samples from 5 of 10 ALL patients post-SCT but not in patients pre-SCT. WT1-tetramer+ CD8+ T cells had a predominantly effector memory phenotype (CD45RO+CD27−CD57+). WT1 gene expression in pre-SCT and donor samples was assayed by quantitative real-time PCR (RQ-PCR). WT1 expression in PBMC from healthy donors was significantly lower than in patients (median 0, range 0–66 ×10−4 WT1/ABL compared to patients, median 12, range 0–2275 ×10−4 WT1/ABL) (P < 0.01). There was a strong correlation between the emergence of WT1-specific CD8+ T cells and a reduction in WT1 gene expression (P < 0.001) (as depicted below) suggesting direct anti-ALL activity post-SCT. Disappearance of WT1-specific CD8+ T-cells from the blood coincided with reappearance of WT1 gene transcripts, consistent with a molecular relapse, further supporting the direct involvement of WT1-specific CD8+ T-cells in the GVL response. These results provide evidence for the first time of spontaneous T-cell reactivity against a leukemia antigen in ALL patients. Our results support the immunogenicity of WT1 in ALL patients post-SCT and a potential application for WT1 peptides in post-transplant immunotherapy of ALL. Figure Figure

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AAV-2 Capsid-Specific CD8+ T Cells Limit the Duration of Gene Therapy in Humans and Cross-React with AAV-8 Capsid.

Blood ◽

10.1182/blood.v108.11.455.455 ◽

2006 ◽

Vol 108 (11) ◽

pp. 455-455 ◽

Cited By ~ 1

Author(s):

Federico Mingozzi ◽

Marcela V. Maus ◽

Denise E. Sabatino ◽

Daniel J. Hui ◽

John E.J. Rasko ◽

...

Keyword(s):

Gene Therapy ◽

T Cells ◽

T Cell ◽

Cell Population ◽

Cd8 T Cells ◽

Peripheral Blood ◽

Transgene Expression ◽

Cd8 T Cell ◽

Target Cells

Abstract Efforts to establish an adeno-associated viral (AAV) vector-mediated gene therapy for the treatment of hemophilia B have been hindered by an immune response to the viral capsid antigen. Preclinical studies in small and large animal models of the disease showed long-term factor IX (F.IX) transgene expression and correction of the phenotype. However, in a recent phase I/II clinical trial in humans (Manno et al., Nat. Med. 2006), after hepatic gene transfer with an AAV-2 vector expressing human F.IX transgene, expression lasted for only a few weeks, declining to baseline concurrently with a peak in liver enzymes. We hypothesized that T cells directed towards AAV capsid antigens displayed by transduced hepatocytes were activated and these mediated destruction of the transduced hepatocytes, thereby causing loss of transgene expression and a transient transaminitis. Peripheral blood mononuclear cells isolated from AAV-infused subjects were stained with an AAV capsid-specific MHC class I pentamer either directly or after in vitro expansion. Two weeks after vector infusion 0.14% of circulating CD8+ T cells were capsid-specific on direct staining, and five weeks after infusion the capsid-specific population had expanded to 0.5% of the circulating CD8+ T cells, indicating proliferation of this T cell subset. By 20 weeks after vector infusion, the capsid-specific CD8+ T cell population had contracted to the level seen at 2 weeks. The expansion and contraction of this capsid-specific CD8+ T cell population paralleled the rise and fall of serum transaminases in the subject observed. Subsequent ex vivo studies of PBMC showed the presence of a readily expandable pool of capsid-specific CD8+ T cells up to 2.5 years post vector-infusion. Similarly, we were able to expand AAV-specific CD8+ T cells from peripheral blood of normal donors, suggesting the existence of a T cell memory pool. Expanded CD8+ T cells were functional as evidenced by specific lysis of HLA-matched target cells and by IFN-γsecretion in response to AAV epitopes. It has been argued that potentially harmful immune responses could be avoided by switching AAV serotypes, however, capsid protein sequences are highly conserved among different serotypes, as are some immunodominant epitopes that we identified. Indeed, we demonstrated that capsid-specific CD8+ T cells from AAV-infused hemophilic subjects functionally cross-react with AAV-8. Moreover, cells expanded from normal donors with AAV-2 vector capsids proliferated upon culture with AAV-8 capsids, demonstrating that both vectors could be processed appropriately in vitro to present the epitopic peptide to capsid-specific T cells. This suggests that AAV-2-specific memory CD8+ T cells normally present in humans likely would expand upon exposure to AAV-8 capsid epitopes. We conclude that the use of immunomodulatory therapy may be a better approach to achieving durable transgene expression in the setting of AAV-mediated gene therapy.

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Autoproliferation Contributes to Clonal Expansion and Changes In Cellular Topography In T Cell Large Granular Lymphocyte (LGL) Leukemia

Blood ◽

10.1182/blood.v116.21.1373.1373 ◽

2010 ◽

Vol 116 (21) ◽

pp. 1373-1373

Author(s):

JianXiang Zou ◽

Jeffrey S Painter ◽

Fanqi Bai ◽

Lubomir Sokol ◽

Thomas P. Loughran ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Cd8 T Cells ◽

Peripheral Blood ◽

Cd8 T Cell ◽

Effector Memory ◽

Ki67 Expression ◽

Terminal Effector ◽

Lgl Leukemia

Abstract Abstract 1373 Introduction: LGL leukemia is associated with cytopenias and expansion of clonally-derived mature cytotoxic CD8+ lymphocytes. The etiology of LGL leukemia is currently unknown, however, T cell activation, loss of lymph node homing receptor L-selectin (CD62L), and increased accumulation of T cells in the bone marrow may lead to suppressed blood cell production. The broad resistance to Fas (CD95) apoptotic signals has lead to the hypothesis that amplification of clonal cells occurs through apoptosis resistance. However, the proliferative history has not been carefully studied. To define possible mechanism of LGL leukemia expansion, T cell phenotype, proliferative history, and functional-related surface marker expression were analyzed. Methods: Peripheral blood mononuclear cells (PBMCs) were obtained from 16 LGL leukemia patients that met diagnostic criteria based on the presence of clonal aβ T cells and >300 cells/ml CD3+/CD57+ T cells in the peripheral blood. Samples were obtained from 10 age-matched healthy individuals from the Southwest Florida Blood Services for comparisons. Multi-analyte flow cytometry was conducted for expression of CD3, CD4/8, CD45RA, CD62L, CD27, CD28, CD25, CD127, IL15Ra, IL21a, CCR7 (all antibodies from BD Biosciences). The proliferative index was determined by Ki67 expression in fixed and permeabilized cells (BD Biosciences) and the proliferative history in vivo was assessed by T-cell-receptor excision circle (TREC) measurement using real-time quantitative PCR (qRT-PCR) in sorted CD4+ and CD8+ T cells. TRECs are episomal fragments generated during TCR gene rearrangements that fail to transfer to daughter cells and thus diminish with each population doubling that reflects the in vivo proliferative history. Results: Compared to healthy controls, significantly fewer CD8+ naïve cells (CD45RA+/CD62L+, 8.4 ± 10.8 vs 24.48 ± 11.99, p=0.003) and higher CD8+ terminal effector memory (TEM) T cells (CD45RA+/CD62L-, 67.74 ± 28.75 vs 39.33 ± 11.32, p=0.007) were observed in the peripheral blood. In contrast, the percentage of CD4+ naïve and memory cells (naïve, central memory, effector memory, and terminal effector memory based on CD45RA and CD62L expression) was similar in patients as compared to controls. The expression of CD27 (31.32 ± 34.64 vs 71.73 ± 20.63, p=0.003) and CD28 (31.38 ± 31.91 vs 70.02 ± 22.93, p=0.002) were lower in CD8+ T cell from patients with LGL leukemia and this reduction predominated within the TEM population (17.63±24.5 vs 70.98±22.5 for CD27, p<0.0001 and 13±20.5 vs 69.43± 21.59 for CD28, p<0.0001). Loss of these markers is consistent with prior antigen activation. There was no difference in CD25 (IL2Ra, p=0.2) expression on CD4+ or CD8+ T cells, but CD127 (IL7Ra, p=0.001), IL15Ra, and IL21Ra (p=0.15) were overexpressed in TEM CD8+ T cell in patients vs controls. All of these cytokine receptors belong to the IL2Rβg-common cytokine receptor superfamily that mediates homeostatic proliferation. In CD8+ T cells in patients, the IL-21Ra was also overexpressed in naïve, central and effector memory T cells. The topography of the expanded CD8+ T cell population was therefore consistent with overexpression of activation markers and proliferation-associated cytokine receptors. Therefore, we next analyzed Ki67 expression and TREC DNA copy number to quantify actively dividing cells and determine the proliferative history, respectively. We found that LGL leukemia patients have more actively dividing CD8+ TEM T cells compared to controls (3.2 ± 3.12 in patients vs 0.44 ± 0.44 in controls, p=0.001). Moreover, the TREC copy number in CD8+ T cells was statistically higher in healthy individuals after adjusting for age (177.54 ± 232 in patients vs 1015 ± 951 in controls, p=0.019). These results show that CD8+ cells in the peripheral compartment have undergone more population doublings in vivo compared to healthy donors. In contrast, the TREC copies in CD4+ T-cells were similar between LGL patients and controls (534.4 ± 644 in patients vs 348.78 ± 248.16 in controls, p>0.05) demonstrating selective cellular proliferation within the CD8 compartment. Conclusions: CD8+ T- cells are undergoing robust cellular activation, contraction in repertoire diversity, and enhanced endogenous proliferation in patients with LGL leukemia. Collectively, these results suggest that clonal expansion is at least partially mediated through autoproliferation in T-LGL leukemia. Disclosures: No relevant conflicts of interest to declare.

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CD8+ T cells in tumor parenchyma and stroma by image analysis (IA) and gene expression profiling (GEP): Potential biomarkers for immuno-oncology (I-O) therapy.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.2594 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 2594-2594

Author(s):

Peter M Szabo ◽

George Lee ◽

Scott Ely ◽

Vipul Baxi ◽

Harsha Pokkalla ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

Cd8 T Cells ◽

Tumor Biology ◽

Geographical Location ◽

Cd8 T Cell ◽

Invasive Margin ◽

Potential Biomarker ◽

Tumor Parenchyma

2594 Background: Distribution patterns of CD8+ T cells within the tumor microenvironment (TME) can be assessed by IA, which may reflect underlying tumor biology and serve as a potential biomarker to assess the utility of I-O therapy. These patterns are variable and may be classified as immune desert (minimal infiltrate), excluded (T cells confined to tumor stroma or to the invasive margin), or inflamed (T cells diffusely infiltrating tumor parenchyma and stroma). We hypothesized that association of a GEP signature with abundance of parenchymal and stromal T-cell infiltrates may identify biomarkers of response or resistance to I-O therapy. To test this, we applied an AI-powered IA platform to quantify CD8+ T cells by geographical location and used GEP to define both CD8 abundance and associated geographic localization to tumor parenchyma and stroma. Methods: We performed an analysis using a tumor inflammatory GEP assay and CD8 immunohistochemistry on procured specimens (335 melanoma, 391 SCCHN). Digitized slides were used to train a convolutional neural network to quantify the number of CD8+ T cells in stroma, tumor parenchyma, parenchyma-stromal interface, and invasive margin. Generalized constrained regression models were used to predict GEP signatures specifically for stromal and parenchymal CD8+ T cells. Results: Parenchymal and stromal GEP scores were highly concordant with CD8+ infiltrate geography (adj- r2: 0.67, 0.65, respectively; P ≤ 0.01). Little overlap existed between gene sets associated with parenchymal and stromal CD8 T-cell geographies. CSF1R and NECTIN2 gene expression was observed to correlate inversely with parenchymal localization and directly with stromal CD8+ T-cell abundance. Conclusions: GEP signatures can be identified that are concordant with various CD8+ T-cell localization patterns in melanoma and SCCHN, demonstrating that GEP-IA can be developed to identify the immune status of interest in the TME. The specific genes identified have potential to elucidate mechanisms of resistance and/or inform I-O targets that can be further evaluated in relation to clinical significance in future studies.

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Increased IL-4+ CD8+ T cells in peripheral blood and autoreactive CD8+ T cell lines of patients with inflammatory arthritis

Rheumatology ◽

10.1093/rheumatology/ken089 ◽

2008 ◽

Vol 47 (6) ◽

pp. 795-803 ◽

Cited By ~ 8

Author(s):

H. J. Baek ◽

L. Zhang ◽

L. B. Jarvis ◽

J. S. H. Gaston

Keyword(s):

T Cells ◽

T Cell ◽

Cell Lines ◽

Cd8 T Cells ◽

Peripheral Blood ◽

Inflammatory Arthritis ◽

Cd8 T Cell ◽

T Cell Lines

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The Immune Evasion Paradox: Immunoevasins of Murine Cytomegalovirus Enhance Priming of CD8 T Cells by Preventing Negative Feedback Regulation

Journal of Virology ◽

10.1128/jvi.01510-08 ◽

2008 ◽

Vol 82 (23) ◽

pp. 11637-11650 ◽

Cited By ~ 50

Author(s):

Verena Böhm ◽

Christian O. Simon ◽

Jürgen Podlech ◽

Christof K. Seckert ◽

Dorothea Gendig ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

Negative Feedback ◽

Cd8 T Cells ◽

Viral Gene Expression ◽

Cd8 T Cell ◽

Murine Cytomegalovirus ◽

Viral Gene ◽

Infected Cells

ABSTRACT Cytomegaloviruses express glycoproteins that interfere with antigen presentation to CD8 T cells. Although the molecular modes of action of these “immunoevasins” differ between cytomegalovirus species, the convergent biological outcome is an inhibition of the recognition of infected cells. In murine cytomegalovirus, m152/gp40 retains peptide-loaded major histocompatibility complex class I molecules in a cis-Golgi compartment, m06/gp48 mediates their vesicular sorting for lysosomal degradation, and m04/gp34, although not an immunoevasin in its own right, appears to assist in the concerted action of all three molecules. Using the Ld-restricted IE1 epitope YPHFMPTNL in the BALB/c mouse model as a paradigm, we provide here an explanation for the paradox that immunoevasins enhance CD8 T-cell priming although they inhibit peptide presentation in infected cells. Adaptive immune responses are initiated in the regional lymph node (RLN) draining the site of pathogen exposure. In particular for antigens that are not virion components, the magnitude of viral gene expression providing the antigens is likely a critical parameter in priming efficacy. We have therefore focused on the events in the RLN and have related priming to intranodal viral gene expression. We show that immunoevasins enhance priming by downmodulating an early CD8 T-cell-mediated “negative feedback” control of the infection in the cortical region of the RLN, thus supporting the model that immunoevasins improve antigen supply for indirect priming by uninfected antigen-presenting cells. As an important consequence, these findings predict that deletion of immunoevasin genes in a replicative vaccine virus is not a favorable option but may, rather, be counterproductive.

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Single-Cell Profiling Reveals Contribution of Tumor Extrinsic and Intrinsic Factors to BCMA-Targeted CAR-T Cell Efficacy in Multiple Myeloma

Blood ◽

10.1182/blood-2021-150923 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 326-326

Author(s):

David T. Melnekoff ◽

Yogita Ghodke-Puranik ◽

Oliver Van Oekelen ◽

Adolfo Aleman ◽

Bhaskar Upadhyaya ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

T Cell ◽

Single Cell ◽

Cd8 T Cells ◽

Research Funding ◽

Mononuclear Cells ◽

Poor Responders ◽

Car T Cell ◽

Car T

Abstract Background: BCMA CAR-T cell therapy has shown great promise in relapsed/refractory multiple myeloma (RRMM) patients, even though there is unpredictable variability in the duration and depth of response. The mechanisms behind these divergent outcomes and relapse are not well understood and heterogeneity of MM patients at the level of both tumor genomics and tumor microenvironment (TME) likely contributes to this important knowledge gap. To explore this question, we performed a longitudinal high resolution single cell genomic and proteomic analysis of bone marrow (BM) and peripheral blood (PB) samples in MM patients treated with BCMA CAR-T. Methods: Longitudinal comprehensive immune phenotyping of 3.5 million peripheral blood mononuclear cells (PBMC, CD45+CD66b-) from 11 BCMA CAR-T (idecabtagene vicleucel, ide-cel) patients was achieved via mass cytometry (CyTOF) with a panel of 39 markers. In addition, a total of 45,161 bone marrow mononuclear cells (BMMC) were analyzed from 6 patients before initiation of ide-cel therapy and at relapse by unbiased mRNA profiling via single-cell RNA-seq (scRNA-seq) using the GemCode system (10x Genomics). Downstream analysis was performed using the CATALYST and Seurat R packages, respectively. Immune cell populations are reported as % of PBMC and CD138- BMMC respectively, unless noted otherwise. Reported p values correspond to non-parametric tests or paired t test where applicable. Results: We compared baseline immune cell populations in the PB and the TME (BM) with regards to depth of CAR-T response. In PB, good responders (≥VGPR) had a higher proportion of CD8+ T cells (37% in good vs 11% in poor responders (<VGPR), p=0.08) and a lower proportion of CD14+ monocytes (30% vs 61%, p=0.28) and NK cells (2% vs 6%, p=0.08). In the TME, a similar trend was confirmed for CD8+ T cells and CD14+ monocytes. (Fig. 1A) Longitudinal analysis of PBMCs revealed phenotypic changes coinciding with CAR-T expansion; CD14+ monocytes declined from week 0 to week 4 after CAR-T infusion (40% vs 13%, p=0.04), while (non-CAR) CD8+ T cells expanded from week 0 to week 4 (32% vs 43%, p=0.15). The non-CAR CD8+ T cell expansion is characterized by differentiation towards a CD8+ effector-memory phenotype (EM, CCR7-CD45RA-) (73% vs 92% of CD8+ T cells, p=0.005). (Fig. 1B) BM samples at CAR-T relapse showed reversal of this shift: CD14+ monocyte levels remain constant or are slightly elevated, while non-CAR CD8+ T cells decrease at relapse. scRNA-seq of BMMC revealed significant gene expression changes between screening and relapse tumor samples, suggesting tumor-intrinsic factors of CAR-T response. For example, when comparing the pre and post tumor samples of a patient with durable response (PFS 652 days), we observed a significant upregulation of gene expression of pro-inflammatory chemokines (CCL3, CCL4), anti-apoptotic genes (MCL-1, FOSB, JUND), and NF-kB signaling genes (NFKBIA) in post tumor. Gene Set Enrichment Analysis (GSEA) of differentially expressed genes showed significant enrichment for TNFA signaling via NF-kB Hallmark Pathway (p.adj = 0.04). We observed similar statistically significant findings between other screening and relapse samples within our cohort, as well as upon comparison of baseline samples of poor vs good responders. (Fig. 1C, D) Thus, our data suggest that anti-apoptotic gene expression could be one of the tumor intrinsic mechanisms of CAR-T therapy resistance. Notably, we did not observe loss of BCMA expression in any tumor samples. Conclusion: Single cell immune profiling and transcriptomic sequencing highlights changes in the PB, TME and within the tumor, which in concert may influence CAR-T efficacy. Our integrated data analysis indicates general immune activation after CAR-T cell infusion that returns to baseline levels at relapse. Specifically, the expansion of non-CAR cytotoxic CD8+ EM T cells provides a rationale for co-administration of IMiDs to enhance CAR-T efficacy. Significant up-regulation of anti-apoptotic genes at baseline in poor responders, and at relapse in good responders, suggest a novel tumor-mediated escape mechanism. Targeting the MCL-1/BCL-2 axis may augment CAR-T efficacy by sensitizing tumor cells and enhancing the effect of CAR-T killing. We will confirm these findings in a longitudinal cohort of BMMC/PBMC CITE-seq patients (n=23) and will present results at the conference. Figure 1 Figure 1. Disclosures Sebra: Sema4: Current Employment. Parekh: Foundation Medicine Inc: Consultancy; Amgen: Research Funding; PFIZER: Research Funding; CELGENE: Research Funding; Karyopharm Inv: Research Funding.

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Single-Cell Analysis of Antigen-Specific CD8+ T-Cell Transcripts Reveals Profiles Specific to mRNA or Adjuvanted Protein Vaccines

Frontiers in Immunology ◽

10.3389/fimmu.2021.757151 ◽

2021 ◽

Vol 12 ◽

Author(s):

Trine Sundebo Meldgaard ◽

Fabiola Blengio ◽

Denise Maffione ◽

Chiara Sammicheli ◽

Simona Tavarini ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Cd8 T Cells ◽

Single Cell Analysis ◽

Expression Profiles ◽

Cd8 T Cell ◽

Cellular Heterogeneity ◽

Cell Analysis

CD8+ T cells play a key role in mediating protective immunity after immune challenges such as infection or vaccination. Several subsets of differentiated CD8+ T cells have been identified, however, a deeper understanding of the molecular mechanism that underlies T-cell differentiation is lacking. Conventional approaches to the study of immune responses are typically limited to the analysis of bulk groups of cells that mask the cells’ heterogeneity (RNA-seq, microarray) and to the assessment of a relatively limited number of biomarkers that can be evaluated simultaneously at the population level (flow and mass cytometry). Single-cell analysis, on the other hand, represents a possible alternative that enables a deeper characterization of the underlying cellular heterogeneity. In this study, a murine model was used to characterize immunodominant hemagglutinin (HA533-541)-specific CD8+ T-cell responses to nucleic- and protein-based influenza vaccine candidates, using single-cell sorting followed by transcriptomic analysis. Investigation of single-cell gene expression profiles enabled the discovery of unique subsets of CD8+ T cells that co-expressed cytotoxic genes after vaccination. Moreover, this method enabled the characterization of antigen specific CD8+ T cells that were previously undetected. Single-cell transcriptome profiling has the potential to allow for qualitative discrimination of cells, which could lead to novel insights on biological pathways involved in cellular responses. This approach could be further validated and allow for more informed decision making in preclinical and clinical settings.

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