CTIM-04. BIOMARKER IMMUNE CORRELATES IN NEWLY DIAGNOSED GLIOBLASTOMA (GBM) TREATED WITH ATEZOLIZUMAB IN COMBINATION WITH TEMOZOLOMIDE (TMZ) AND RADIATION

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi49-vi49
Author(s):  
Shiao-Pei Weathers ◽  
Mark Knafl ◽  
Edwin Parra ◽  
Sharia Hernandez ◽  
Luisa Solis ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Standard Of Care ◽  
Predictive Biomarker ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Newly Diagnosed ◽  
Immune Correlates ◽  
Newly Diagnosed Glioblastoma ◽  
Checkpoint Inhibitor Therapy ◽  
Pre Treatment

Abstract BACKGROUND Checkpoint inhibitor therapy has demonstrated overall limited efficacy in the treatment of GBM. Mechanisms of resistance to checkpoint blockade need to be better elucidated. Analysis of the tumor microenvironment is critical to identify correlates of response to immune checkpoint blockade. 60 newly diagnosed GBM patients unselected for MGMT status underwent treatment with concurrent atezolizumab with radiation therapy and TMZ followed by adjuvant atezolizumab and TMZ (NCT03174197). Clinical data has been reported previously. METHODS Tissue image immunoprofiling was conducted using 2 multiplex immunofluorescence (mIF) panels against; CD3, CD8, PD-1, PD-L1, Granzyme B, FOXP3, CD45RO, CD68, and GFAP antibodies. PDL-1 (Clone SP263) malignant cells expression was assessed by immunohistochemistry. Correlations between mIF biomarkers co-expressions, IHC PD-L1, and clinical outcome including OS, radiographic response, and PFS were evaluated. RESULTS Of 60 patients enrolled, image immunoprofiling was performed successfully on pre-treatment tissue in 48 patients. 20 of 60 patients underwent re-resection for suspected recurrent disease of which 10 patients had immunoprofiling performed successfully on pre and post treatment samples. An analysis of CD3CD8+ cytotoxic T lymphocytes was consistent with prior work, showing no or relatively low levels at baseline, and no association with clinical outcome. PDL-1 expression by IHC, at thresholds of >1% or >5%, was not associated with clinical outcome. Tumors with a higher number of GFAP-expressing cancer cells had a significantly lower tumor response (p< 0.05) and median OS (430 vs. 799 days, p< 0.01). CONCLUSIONS For newly diagnosed GBM patients treated with standard of care radiation and temozolomide in combination with atezolizumab, T-cell levels and PDL-1 expression were not predictive of outcome. GFAP may represent a novel predictive biomarker of overall survival. Ongoing studies to evaluate the gut microbiome and tumor genomic (WES, CNA) and transcriptomic (RNAseq) features of these and matched tumors are underway.

scholarly journals The Current Landscape of Immune Checkpoint Blockade in Metastatic Lung Squamous Cell Carcinoma

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1392
Author(s):  
Hong Yuan ◽  
Jing Liu ◽  
Jun Zhang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Checkpoint ◽  
Unmet Need ◽  
Lung Squamous Cell Carcinoma ◽  
Standard Of Care ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Programmed Death

In addition to surgery, chemotherapy, radiotherapy, and targeted therapy, immunotherapy has emerged as a standard pillar of cancer treatment. Immune checkpoint inhibitors (ICIs) such as targeting programmed death-1/programmed death ligand 1 (PD-1/PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) have been integrated into standard-of-care regimens for patients with advanced lung squamous cell carcinoma (LUSC), who were previously limited by the lack of treatment options. Atezolizumab, durvalumab, nivolumab, and pembrolizumab are all currently used as part of standard-of-care treatment for different stages of lung cancer. Recent successes and failures of immune checkpoint blockade-based combination therapies have provided significant insights into implementing combination strategies in LUSC. Therefore, there is an urgent need to correctly select patients who are more likely to respond to immunotherapy and understand the mechanisms of primary or acquired resistance. In this review, we aim at summarizing the emerging clinical data on the promise and challenge of ICIs, discussing the unmet need of potential biomarkers for predicting response or resistance to immunotherapy, and providing an overview of the current immune landscape and future directions in advanced LUSC.

scholarly journals Virus-specific memory T cell responses unmasked by immune checkpoint blockade cause hepatitis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
James A. Hutchinson ◽  
Katharina Kronenberg ◽  
Paloma Riquelme ◽  
Jürgen J. Wenzel ◽  
Gunther Glehr ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Serum Antibody ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Effector Memory ◽  
Specific Memory ◽  
Immune Mediated ◽  
Antibody Titres ◽  
Pre Treatment ◽  
After Cancer

AbstractTreatment of advanced melanoma with combined PD-1/CTLA-4 blockade commonly causes serious immune-mediated complications. Here, we identify a subset of patients predisposed to immune checkpoint blockade-related hepatitis who are distinguished by chronic expansion of effector memory CD4+ T cells (TEM cells). Pre-therapy CD4+ TEM cell expansion occurs primarily during autumn or winter in patients with metastatic disease and high cytomegalovirus (CMV)-specific serum antibody titres. These clinical features implicate metastasis-dependent, compartmentalised CMV reactivation as the cause of CD4+ TEM expansion. Pre-therapy CD4+ TEM expansion predicts hepatitis in CMV-seropositive patients, opening possibilities for avoidance or prevention. 3 of 4 patients with pre-treatment CD4+ TEM expansion who received αPD-1 monotherapy instead of αPD-1/αCTLA-4 therapy remained hepatitis-free. 4 of 4 patients with baseline CD4+ TEM expansion given prophylactic valganciclovir and αPD-1/αCTLA-4 therapy remained hepatitis-free. Our findings exemplify how pathogen exposure can shape clinical reactions after cancer therapy and how this insight leads to therapeutic innovations.

HLA-A*03 is a Predictive Biomarker of Poor Response to Immune Checkpoint Blockade in Cancer

2021 ◽  
Author(s):  
Vivek Naranbhai ◽  
Mathias Viard ◽  
Michael Dean ◽  
Stefan Groha ◽  
David A. Braun ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Poor Response ◽  
Predictive Biomarker ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade

Association of the diversity and composition of the gut microbiome with responses and survival (PFS) in metastatic melanoma (MM) patients (pts) on anti-PD-1 therapy.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 3008-3008 ◽  
Author(s):  
Jennifer Ann Wargo ◽  
Vancheswaran Gopalakrishnan ◽  
Christine Spencer ◽  
Tatiana Karpinets ◽  
Alexandre Reuben ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Large Cohort ◽  
Checkpoint Blockade ◽  
Cancer Types ◽  
Pre Treatment ◽  
Immune Profiling ◽  
Made In

3008 Background: Significant advances have been made in cancer therapy with immune checkpoint blockade. However, responses in pts with MM are variable, and insights are needed to identify biomarkers of response and strategies to overcome resistance. There is a growing appreciation of the role of the microbiome in cancer, and evidence in murine models that modulation of the gut microbiome may enhance responses to immune checkpoint blockade, though this has not been well studied in pts. Thus we evaluated the microbiome in a large cohort of pts with MM, focusing on responses to anti-PD-1. Methods: We collected oral (n = 234) and gut microbiome samples (n = 120) on a large cohort of of MM patients (n = 221). Of note, the majority of pts were treated with PD-1 based therapy (n = 105). Pts on anti-PD1 were classified as either responders (R) or non-responders (NR) based on RECIST criteria, and 16S rRNA and whole genome shotgun (WGS) sequencing were performed. Immune profiling (via immunohistochemistry, flow cytometry, cytokines and gene expression profiling) was also done in available pre-treatment tumors at baseline. Results: Significant differences in diversity and composition of the gut microbiome were noted in R vs NR to anti-PD-1, with a higher diversity of bacteria in R vs NR (p = 0.03). Differences were also noted in the composition of gut bacteria, with a higher abundance of Clostridiales in R and of Bacteroidales in NR. Immune profiling demonstrated increased tumor immune infiltrates in R pts , with a higher density of CD8+T cells; this correlated with abundance of specific bacteria enriched in the gut microbiome (r = 0.59, 0.014). Other features of enhanced immunity were also noted, and WGS revealed differential metabolic signatures in R vs NR. Furthermore, diversity (p = 0.009; HR = 7.67) and abundance of specific bacteria in R (p = 0.007; HR = 3.88) was associated with improved PFS to anti-PD-1 therapy. Conclusions: Diversity and composition of the gut microbiome differ in R vs NR pts with MM receiving anti-PD-1 therapy. These have potentially far-reaching implications, though results need to be validated in larger cohorts across cancer types.

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