scholarly journals 689 ATRC-101 Drives Potent Single-Agent Activity in Mouse Syngeneic Tumor Models via a Novel Cellular Mechanism of Action

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A728-A728
Author(s):  
Yvonne Leung ◽  
Nikhil Vad ◽  
Anne Ye ◽  
Daniel Santos ◽  
Wei Cao ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Single Agent ◽  
Tumor Model ◽  
Innate Immune ◽  
Cell Populations ◽  
Innate Immune Cells ◽  
Syngeneic Tumor ◽  
Rnp Complex

BackgroundWe have previously demonstrated adaptive antibody responses targeting public tumor antigens in cancer patients. ATRC-101, a clinical stage, engineered version of an antibody identified in such a patient, displays robust single-agent activity in syngeneic tumor models requiring Fc receptors (FcRs) expressed by innate immune cells and the presence of CD8+ T cells. The novel target of ATRC-101 was found to be a tumor-restricted ribonucleoprotein (RNP) complex, and because RNP complexes drive T cell responses in infectious and autoimmune disease via innate immune cells, we further characterized the mechanism-of-action of ATRC-101. Here we describe changes in immune cell populations in a tumor model proximal to treatment initiation with ATRC-101.MethodsMice bearing EMT6 tumors received ATRC-101 beginning on day 7 post-tumor inoculation. Tissues were harvested between days 7 and 14 and analyzed by flow cytometry and immunohistochemistry. Transcriptome analysis was performed using RNA sequencing on whole tumors taken on days 7, 9, and 12.ResultsThe earliest significant changes induced by ATRC-101, relative to vehicle, were noted just 24 hours after dosing: increased numbers of cDC1 cells in blood, and decreased numbers of cDC2 cells in blood and M-MDSCs in tumor. A significant increase of CD8+ T cells was observed in blood 48 hours after dosing and in tumor 96 hours after dosing. Increased numbers of NK cells were also observed in blood and tumor at this later time. Multiplex analysis of circulating cytokines demonstrated a very early increase in myeloid chemo-attractants, such as MCP1 and MIP1a.Whole exome sequencing of tumor samples showed that ATRC-101 dosing drives a significant increase, relative to vehicle, in the expression of interferon-stimulated genes. Co-culturing experiments demonstrated that induced, bone marrow-derived dendritic cells are activated by ATRC-101 and its target in a dose-dependent fashion.ConclusionsDosing with ATRC-101 in the EMT6 syngeneic tumor model, in which ATRC-101 displays notable single-agent activity, leads to changes in immune cell composition in the blood and tumor, with the earliest changes observed in myeloid or myeloid-derived cell populations, and to the early appearance of myeloid chemo-attractants. We believe these data indicate that ATRC-101 acts proximally on the myeloid cell populations in the tumor, leading to a remodeling of the tumor environment and an adaptive immune response that includes CD8+ T cells driving tumor regression. Our data demonstrate that ATRC-101, bound to its target which is an RNP complex, can activate myeloid cells and are consistent with this activation occurring via FcR and Toll-like receptor (TLR) pathways.

scholarly journals Immunohistochemical phenotyping of T cells, granulocytes, and phagocytes in the muscle of cancer patients: association with radiologically defined muscle mass and gene expression

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ana Anoveros-Barrera ◽  
Amritpal S. Bhullar ◽  
Cynthia Stretch ◽  
Abha R. Dunichand-Hoedl ◽  
Karen J. B. Martins ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
T Cells ◽  
Cancer Patients ◽  
Muscle Mass ◽  
Muscle Fiber ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Cell Populations ◽  
Cd4 Cells ◽  
Gene Correlation

Abstract Background Inflammation is a recognized contributor to muscle wasting. Research in injury and myopathy suggests that interactions between the skeletal muscle and immune cells confer a pro-inflammatory environment that influences muscle loss through several mechanisms; however, this has not been explored in the cancer setting. This study investigated the local immune environment of the muscle by identifying the phenotype of immune cell populations in the muscle and their relationship to muscle mass in cancer patients. Methods Intraoperative muscle biopsies were collected from cancer patients (n = 30, 91% gastrointestinal malignancies). Muscle mass was assessed histologically (muscle fiber cross-sectional area, CSA; μm2) and radiologically (lumbar skeletal muscle index, SMI; cm2/m2 by computed tomography, CT). T cells (CD4 and CD8) and granulocytes/phagocytes (CD11b, CD14, and CD15) were assessed by immunohistochemistry. Microarray analysis was conducted in the muscle of a second cancer patient cohort. Results T cells (CD3+), granulocytes/phagocytes (CD11b+), and CD3−CD4+ cells were identified. Muscle fiber CSA (μm2) was positively correlated (Spearman’s r = > 0.45; p = < 0.05) with the total number of T cells, CD4, and CD8 T cells and granulocytes/phagocytes. In addition, patients with the smallest SMI exhibited fewer CD8 T cells within their muscle. Consistent with this, further exploration with gene correlation analyses suggests that the presence of CD8 T cells is negatively associated (Pearson’s r = ≥ 0.5; p = <0.0001) with key genes within muscle catabolic pathways for signaling (ACVR2B), ubiquitin proteasome (FOXO4, TRIM63, FBXO32, MUL1, UBC, UBB, UBE2L3), and apoptosis/autophagy (CASP8, BECN1, ATG13, SIVA1). Conclusion The skeletal muscle immune environment of cancer patients is comprised of immune cell populations from the adaptive and innate immunity. Correlations of T cells, granulocyte/phagocytes, and CD3−CD4+ cells with muscle mass measurements indicate a positive relationship between immune cell numbers and muscle mass status in cancer patients. Further exploration with gene correlation analyses suggests that the presence of CD8 T cells is negatively correlated with components of muscle catabolism.

scholarly journals Resistance of Natural Killer and T Cells to Venetoclax Allows for Combination Treatment with Cancer Immunotherapy Agents

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1118-1118 ◽  
Author(s):  
Elisabeth A Lasater ◽  
An D Do ◽  
Luciana Burton ◽  
Yijin Li ◽  
Erin Williams ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
B Cells ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Cd4 T Cells ◽  
Immune Cell ◽  
Single Agent ◽  
Employment Equity ◽  
Equity Ownership

Abstract Introduction: Intrinsic apoptosis is regulated by the BCL-2 family of proteins, which consists of both anti-apoptotic (BCL-2, BCL-XL, MCL-1) and pro-apoptotic (BIM, BAX, BAK, BAD) proteins. Interaction between these proteins, as well as stringent regulation of their expression, mediates cell survival and can rapidly induce cell death. A shift in balance and overexpression of anti-apoptotic proteins is a hallmark of cancer. Venetoclax (ABT-199/GDC-0199) is a potent, selective small molecule BCL-2 inhibitor that has shown preclinical and clinical activity across hematologic malignancies and is approved for the treatment of chronic lymphocytic leukemia with 17p deletion as monotherapy and in combination with rituximab. Objective: To investigate the effects of BCL-2 inhibition by venetoclax on viability and function of immune-cell subsets to inform combinability with cancer immunotherapies, such as anti-PD-L1. Methods and Results: B cells, natural killer (NK) cells, CD4+ T cells, and CD8+ T cells in peripheral blood mononuclear cells (PBMCs) from healthy donors (n=3) were exposed to increasing concentrations of venetoclax that are clinically achievable in patients, and percentage of live cells was assessed by flow-cytometry using Near-IR cell staining. B cells were more sensitive to venetoclax (IC50 of ~1nM) than CD8+ T cells (IC50 ~100nM), NK cells (IC50 ~200nM), and CD4+ T cells (IC50 ~500nM) (Figure A). CD8+ T-cell subset analysis showed that unstimulated naive, but not memory cells, were sensitive to venetoclax treatment (IC50 ~30nM and 240nM, respectively). Resistance to venetoclax frequently involves compensation by other BCL-2 family proteins (BCL-XL and MCL-1). As assessed by western blot in PBMCs isolated from healthy donors (n=6), BCL-XL expression was higher in NK cells (~8-fold) and CD4+ and CD8+ T cells (~2.5-fold) than in B cells (1X). MCL-1 protein expression was higher only in CD4+ T cells (1.8-fold) relative to B cells. To evaluate the effect of venetoclax on T-cell function, CD8+ T cells were stimulated ex vivo with CD3/CD28 beads, and cytokine production and proliferation were assessed. Venetoclax treatment with 400nM drug had minimal impact on cytokine production, including interferon gamma (IFNg), tumor necrosis factor alpha (TNFa), and IL-2, in CD8+ effector, effector memory, central memory, and naïve subsets (Figure B). CD8+ T-cell proliferation was similarly resistant to venetoclax, as subsets demonstrated an IC50 >1000nM for venetoclax. Taken together, these data suggest that survival of resting NK and T cells in not impaired by venetoclax, possibly due to increased levels of BCL-XL and MCL-1, and that T-cell activation is largely independent of BCL-2 inhibition. To evaluate dual BCL-2 inhibition and PD-L1 blockade, the syngeneic A20 murine lymphoma model that is responsive to anti-PD-L1 treatment was used. Immune-competent mice bearing A20 subcutaneous tumors were treated with clinically relevant doses of venetoclax, murine specific anti-PD-L1, or both agents. Single-agent anti-PD-L1 therapy resulted in robust tumor regression, while single-agent venetoclax had no effect. The combination of venetoclax and anti-PD-L1 resulted in efficacy comparable with single-agent anti-PD-L1 (Figure C), suggesting that BCL-2 inhibition does not impact immune-cell responses to checkpoint inhibition in vivo. These data support that venetoclax does not antagonize immune-cell function and can be combined with immunotherapy targets. Conclusions: Our data demonstrate that significant venetoclax-induced cell death at clinically relevant drug concentrations is limited to the B-cell subset and that BCL-2 inhibition is not detrimental to survival or activation of NK- or T-cell subsets. Importantly, preclinical mouse models confirm the combinability of BCL-2 and PD-L1 inhibitors. These data support the combined use of venetoclax and cancer immunotherapy agents in the treatment of patients with hematologic and solid tumor malignancies. Figure Figure. Disclosures Lasater: Genentech Inc: Employment. Do:Genentech Inc: Employment. Burton:Genentech Inc: Employment. Li:Genentech Inc: Employment. Oeh:Genentech Inc: Employment. Molinero:Genentech Inc: Employment, Equity Ownership, Patents & Royalties: Genentech Inc. Penuel:Genentech Inc: Employment. Sampath:Genentech Inc: Employment. Dail:Genentech: Employment, Equity Ownership. Belvin:CytomX Therapeutics: Equity Ownership. Sumiyoshi:Genentech Inc: Employment, Equity Ownership. Punnoose:Roche: Equity Ownership; Genentech Inc: Employment. Venstrom:Genentech Inc: Employment. Raval:Genentech Inc: Consultancy, Employment, Equity Ownership.

scholarly journals Immune Cell Profiles in Patients Treated with Lenalidomide and Alternate Day Prednisolone Maintenance Post Upfront ASCT for Multiple Myeloma (LEOPARD Trial)

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 34-35
Author(s):  
Anna Kalff ◽  
Sam Norton ◽  
Tiffany Khong ◽  
Malarmathy Ramachandran ◽  
Mary H. Young ◽  
...  
Keyword(s):  
T Cells ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Research Funding ◽  
Immune Cell ◽  
Cell Populations ◽  
Publicly Traded ◽  
Unsupervised Analysis ◽  
Hla Dr ◽  
Immune Profiling

The LEOPARD trial evaluated lenalidomide and alternate day prednisolone (RAP) as post ASCT maintenance in newly diagnosed transplant eligible MM patients (TE NDMM). 60 patients were recruited. Estimated median potential follow-up was 44 months (IQR 26m - 52m). Median PFS from time of commencing RAP was 38.3m (95% CI, 25.8 to 54.8); median OS was not reached (71.4% of patients were alive at 36 months). Here we present the findings from correlative immune studies of this trial. Aims: To undertake mass cytometry (CyTOF) based immune profiling in patients with TE NDMM treated with RAP maintenance post ASCT. Methods: The LEOPARD trial was a phase II, multi centre, open label, single arm study of RAP maintenance after a single melphalan conditioned (200mg/m2) ASCT as part of up-front therapy. Patients were restaged at D+42 ASCT, and if eligible, were commenced on RAP maintenance (LEN 10mg daily increasing to 15mg daily after 8 weeks and alternate day prednisolone 50mg) within 8 weeks of D+0 of the ASCT. Therapy continued until toxicity/progression. CyTOF was performed in sequential samples in two selected groups of patients: long runners (LR, n=7), defined as those with PFS &gt; 36 months (median) and early relapsers (ER, n=8), defined as those who progressed/died before reaching the lower quartile of PFS. [All patients had peripheral blood collected at baseline (pre-ASCT), 6w post-ASCT and weeks 4, 8, 12, 20, 28 and 40 of RAP]. Cells were barcoded using the Cell-ID 20-Plex Pd barcoding kit (Fluidigm) followed by staining with sub-set/function defining antibodies (targeting myeloid, B, T and NK cells: CD45, CD3, CD19, CD5, CD1c, CD226. CD8, CD11c, CD16, CD127, CD138, CD123, NKG2A, TIGIT, TIM3, CD45RA. CD274, CD27, CD197, CD28, Ki67, CD66b, CD183, KLRG1, CD43, NKG2D, CD38, CD278/ICOS, CD25, HLA-DR, CD4, CD57, GramB, PD-1, CD14, CD56, CD11b, Tbet, CD33). Samples were acquired on the Helios instrument. Supervised analysis was performed to determine differences in canonical immune cell populations. Unsupervised analysis was then performed: data were clustered in the VORTEX package. Significant differences in cluster frequency were assessed by Mann-Whitney test for statistical significance. Cluster phenotypes were determined and validated via multiple visualisation approaches. Results: Median age was 56yrs for LR versus 63yrs for ER. Median PFS for LR was 46.3m (38.4 - 51.5m) versus 10.2 m (2.1 - 21.3m) for ER. Supervised analysis was performed on all samples, dichotomized into baseline and last time point sampled for each patient. At baseline, Ki67+CD8+ T cells, ICOS+CD8+ T cells, HLA-DR+CD4+ T cells and CD11c+ myeloid cells were enriched in LR compared to ER. At the last timepoint sampled, Ki67+CD8+ T cells and ICOS+CD8+ T cells were again enriched in LR compared to ER. Conversely, B-reg-like cells (CD19+CD5+CD43-) were enriched in ER compared to LR at the last timepoint sampled. Unsupervised analysis was performed on all samples (all timepoints were pooled). Five clusters were significantly enriched in LR compared to ER. Four of these clusters represented activated/cytotoxic NK cells: CD56 dim, CD16-, NKG2A(CD159a)+, NKG2D(CD314)+, Granzyme B+ and CD38+, and additional expression of CD57 on one cluster; one cluster represented a mature myeloid population, with high expression of HLA-DR, CD11b and CD11c and low expression of CD33. One cluster was significantly enriched in ER compared to LR, representing activated neutrophils, with high expression of CD66b, CD11b and CD16. The clusters that were enriched were then assessed longitudinally over all time points. There was no difference in the kinetics of these populations between groups. Conclusions Significant differences in both T-cell and NK cell populations were demonstrable at baseline in LR versus ER patients. Subsequently, durable responses to post-ASCT lenalidomide maintenance were associated with a cytotoxic, controlled immune response whereas early relapse was characterised by a more uncontrolled inflammatory response and the emergence of B-reg-like cells prior to relapse. We conclude that immune profiling at baseline and after initiation of therapy may help to predict a more sustained response to lenalidomide maintenance enabling pre-emptive tailored treatment decisions. Disclosures Kalff: Roche: Honoraria; Janssen: Honoraria; Amgen: Honoraria; CSL: Honoraria; Celgene: Honoraria. Young:Bristol Meyers Squibb: Current Employment, Current equity holder in publicly-traded company. Pierceall:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Thakurta:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company; Oxford University: Other: visiting professor. Oppermann:Bristol Meyers Squibb: Research Funding. Guo:Bristol Meyers Squibb: Research Funding. Reynolds:Novartis AG: Current equity holder in publicly-traded company. Spencer:AbbVie, Celgene, Haemalogix, Janssen, Sanofi, SecuraBio, Specialised Therapeutics Australia, Servier and Takeda: Consultancy; AbbVie, Amgen, Celgene, Haemalogix, Janssen, Sanofi, SecuraBio, Specialised Therapeutics Australia, Servier and Takeda: Honoraria; Amgen, Celgene, Haemalogix, Janssen, Servier and Takeda: Research Funding; Celgene, Janssen and Takeda: Speakers Bureau.

scholarly journals Analysis of adaptive immune cell populations and phenotypes in the patients infected by SARS-CoV-2

2020 ◽  
Author(s):  
Xiaofeng Yang ◽  
Tongxin Dai ◽  
Xiaobo Zhou ◽  
Hongbo Qian ◽  
Rui Guo ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Age Groups ◽  
Cell Populations ◽  
Adaptive Immune ◽  
Adaptive Immune Cell ◽  
Cell Percentage ◽  
Enhanced Expression ◽  
Functional Features

AbstractCoronavirus disease-2019 (COVID-19), caused by SARS-CoV-2, has rapidly spread to most of countries in the world, threatening the health and lives of many people. Unfortunately, information regarding the immunological characteristics in COVID-19 patients remains limited. Here we collected the blood samples from 18 healthy donors (HD) and 38 COVID-19 patients to analyze changes in the adaptive immune cell populations and phenotypes. In comparison to HD, the lymphocyte percentage was slightly decreased, the percentages of CD4 and CD8 T cells in lymphocytes are similar, whereas B cell percentage increased in COVID-19 patients. T cells, especially CD8 T cells, showed an enhanced expression of late activation marker CD25 and exhaustion marker PD-1. Importantly, SARS-CoV-2 induced an increased percentage of T follicular helpher (Tfh)- and germinal center B-like (GCB-like) cells in the blood. However, the parameters in COVD-19 patients remained unchanged across various age groups. Therefore, we demonstrated that the T and B cells can be activated normally and exhibit functional features. These data provide a clue that the adaptive immunity in most people could be primed to induce a significant immune response against SARS-CoV-2 infection upon receiving standard medical care.

scholarly journals IFN-γPriming Effects on the Maintenance of Effector Memory CD4+T Cells and on Phagocyte Function: Evidences from Infectious Diseases

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Henrique Borges da Silva ◽  
Raíssa Fonseca ◽  
José M. Alvarez ◽  
Maria Regina D’Império Lima
Keyword(s):  
T Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Innate Immune ◽  
Effector Memory ◽  
Innate Immune Cells ◽  
Chronic Infections ◽  
Cell Functions ◽  
Memory Cd4 T Cells

Although it has been established that effector memory CD4+T cells play an important role in the protective immunity against chronic infections, little is known about the exact mechanisms responsible for their functioning and maintenance, as well as their effects on innate immune cells. Here we review recent data on the role of IFN-γpriming as a mechanism affecting both innate immune cells and effector memory CD4+T cells. Suboptimal concentrations of IFN-γare seemingly crucial for the optimization of innate immune cell functions (including phagocytosis and destruction of reminiscent pathogens), as well as for the survival and functioning of effector memory CD4+T cells. Thus, IFN-γpriming can thus be considered an important bridge between innate and adaptive immunity.

scholarly journals Innate Immune Cells in Pressure Overload-Induced Cardiac Hypertrophy and Remodeling

2021 ◽  
Vol 9 ◽  
Author(s):  
Xin Liu ◽  
Guo-Ping Shi ◽  
Junli Guo
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
Mast Cells ◽  
Immune Cells ◽  
Immune Cell ◽  
Pressure Overload ◽  
Natural Killer T Cells ◽  
Innate Immune ◽  
Innate Immune Cells ◽  
Killer T Cells

Pressure overload and heart failure are among the leading causes of cardiovascular morbidity and mortality. Accumulating evidence suggests that inflammatory cell activation and release of inflammatory mediators are of vital importance during the pathogenesis of these cardiac diseases. Yet, the roles of innate immune cells and subsequent inflammatory events in these processes remain poorly understood. Here, we outline the possible underlying mechanisms of innate immune cell participation, including mast cells, macrophages, monocytes, neutrophils, dendritic cells, eosinophils, and natural killer T cells in these pathological processes. Although these cells accumulate in the atrium or ventricles at different time points after pressure overload, their cardioprotective or cardiodestructive activities differ from each other. Among them, mast cells, neutrophils, and dendritic cells exert detrimental function in experimental models, whereas eosinophils and natural killer T cells display cardioprotective activities. Depending on their subsets, macrophages and monocytes may exacerbate cardiodysfunction or negatively regulate cardiac hypertrophy and remodeling. Pressure overload stimulates the secretion of cytokines, chemokines, and growth factors from innate immune cells and even resident cardiomyocytes that together assist innate immune cell infiltration into injured heart. These infiltrates are involved in pro-hypertrophic events and cardiac fibroblast activation. Immune regulation of cardiac innate immune cells becomes a promising therapeutic approach in experimental cardiac disease treatment, highlighting the significance of their clinical evaluation in humans.

scholarly journals Innate Immunity Mediated Inflammation and Beta Cell Function: Neighbors or Enemies?

2021 ◽  
Vol 11 ◽  
Author(s):  
Antonio Citro ◽  
Francesco Campo ◽  
Erica Dugnani ◽  
Lorenzo Piemonti
Keyword(s):  
T Cells ◽  
Beta Cell ◽  
Immune Cells ◽  
Cell Function ◽  
Immune Cell ◽  
Active Role ◽  
Pancreatic Tissue ◽  
Innate Immune ◽  
Innate Immune Cells ◽  
Beta Cell Destruction

Type 1 diabetes (T1D) is still considered a huge burden because the available treatments are not effective in preventing the onset or progression of the disease. Recently, the idea that diabetes is an autoimmune disease mediated exclusively by T cells has been reshaped. In fact, T cells are not the only players with an active role in beta cell destruction. Macrophages and neutrophils, which physiologically reside in pancreatic tissue, can also participate in tissue homeostasis and damage by promoting innate immune responses and modulating inflammation. During the development of the pancreatic islet inflammation there is a strong interplay of both adaptive and innate immune cells, and the presence of innate immune cells has been demonstrated both in exocrine and endocrine pancreatic compartments during the earliest stages of insulitis. Innate immune cell populations secrete cytokines, which must be considered both as physiological and pathological mediators. In fact, it has been demonstrated that cytokines could regulate directly and indirectly insulin secretion and, simultaneously, trigger inflammatory reaction. Indeed, cytokines pathways could represent targets both to improve glucose metabolism and to prevent autoimmune damage. Concordantly, the combination of immunomodulatory strategies against both innate and adaptive immunity should be tested in the next future, as they can be more efficient to prevent or delay islet damage and T1D onset.

Association of preoperative neutrophil-to-lymphocyte ratio with immune populations in the tumor microenvironment of patients with clear cell renal cell carcinoma.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 688-688
Author(s):  
Alejandro Sanchez ◽  
Ming Liu ◽  
Briana Nixon ◽  
Mazyar Ghanaat ◽  
Renzo DiNatale ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Populations ◽  
Cell Renal Cell Carcinoma ◽  
Sarcomatoid Differentiation

688 Background: Currently, there are no blood biomarkers that reflect the composition of immune cells in the tumor microenvironment (TME) of patients with clear cell renal cell carcinoma (ccRCC). High pre-operative neutrophil-to-lymphocyte ratio (NLR) is associated with adverse oncologic outcomes in ccRCC. However, how NLR relates to the immune cell composition in the TME is not well understood. Methods: We performed flow cytometry on tumor and adjacent normal renal tissue from a prospective cohort of patients who underwent surgery from 6/2015-7/2017. Immune cell populations, as a percent of total CD45+, were compared to baseline age, sex, body mass index (BMI), SSIGN score, sarcomatoid differentiation, and AJCC stage (I-IV). NLR was calculated using pre-operative absolute neutrophil-to-lymphocyte counts and further categorized as inflamed if NLR was ≥ 3. Correlations between continuous variables were performed using Spearman’s rank correlation. Comparisons of means were made using the Wilcoxon signed-rank test. Results: Among 48 patients, 32 (71%) were male, median age was 59 (IQR 52-66), BMI of 38.5 (IQR 26-32.6), SSIGN score of 8 (IQR 5-12), 9 (20%) had sarcomatoid differentiation, and 20 (44%) had metastases at presentation. No correlations were found between age, BMI, and different immune cell populations or NLR. A higher ratio of tissue resident (CD8a+CD49a+CD103+) to circulating (CD8a+CD49a-CD103-) CD8+ T-cells in the TME was associated with increasing stage at presentation (p = 0.02). Inflamed patients had similar total CD45+, CD8+ T cell, CD4+ T cell, and macrophage immune infiltration. However, inflamed patients had a higher proportion of CD8+ Tres infiltration (p = 0.04) and a trend towards higher neutrophil infiltration (p = 0.15). Conclusions: A higher proportion of resident CD8+T-cells correlated with advanced disease at presentation. NLR may reflect a change in the type of CD8+T cell population found in the TME. This population of CD8+ T-cells, and NLR as a possible biomarker should be validated and further investigated in a larger cohort of patients. Funding: Ruth L. Kirschstein Research Service Award T32CA082088 (A.S., M.G.)

scholarly journals Antiviral memory CD8 T-cell differentiation, maintenance, and secondary expansion occur independently of MyD88

Blood ◽  
2011 ◽  
Vol 117 (11) ◽  
pp. 3123-3130 ◽  
Author(s):  
Adeeb H. Rahman ◽  
Ruan Zhang ◽  
Christopher D. Blosser ◽  
Baidong Hou ◽  
Anthony L. DeFranco ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Cell Expansion ◽  
Cd8 T Cell ◽  
Innate Immune ◽  
Innate Immune Cells ◽  
Memory Cd8 T Cells ◽  
T Cell Expansion

Abstract Inflammatory signals induced during infection regulate T-cell expansion, differentiation, and memory formation. Toll-like receptors (TLRs) are inflammatory mediators that allow innate immune cells to recognize and respond to invading pathogens. In addition to their role in innate immune cells, we have found that signals delivered through the TLR adapter protein myeloid differentiation protein 88 (MyD88) play a critical, T cell–intrinsic role in supporting the survival and accumulation of antigen-specific effector cells after acute viral infection. However, the importance of MyD88-dependent signals in regulating the generation and maintenance of memory T cells remained unclear. To address this, we used a novel, inducible knockout system to examine whether MyD88 is required for optimal memory CD8 T-cell generation and responses after lymphocytic choriomeningitis virus infection. We show that whereas MyD88 is critical for initial T-cell expansion, it is not required for the subsequent differentiation and stable maintenance of a memory T-cell population. Furthermore, in contrast to naive CD8 T cells, memory CD8 T cells do not depend on MyD88 for their secondary expansion. Our findings clarify the importance of MyD88 during distinct phases of the antiviral T-cell response and establish differential dependence on MyD88 signaling as a novel characteristic that distinguishes naive from memory CD8 T cells.

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