Analyzing Flow Cytometry or Targeted Gene Expression Data Influences Clinical Discoveries—Profiling Blood Samples of Pancreatic Ductal Adenocarcinoma Patients

Introduction:Monitoring the therapeutic response of pancreatic ductal adenocarcinoma (PDAC) patients is crucial to determine treatment strategies. Several studies have examined the effectiveness of FOLFIRINOX as a first-line treatment in patients with locally advanced pancreatic cancer, but little attention has been paid to the immunologic alterations in peripheral blood caused by this chemotherapy regimen. Furthermore, the influence of the measurement type (e.g., flow cytometry and targeted gene expression) on the clinical discoveries is unknown. Therefore, we aimed to scrutinize the influence of using flow cytometry or targeted immune gene expression to study the immunological changes in blood samples of PDAC patients who were treated with a single-cycle FOLFIRINOX combined with lipegfilgrastim (FFX-Lipeg). Material and Methods: Whole-blood samples from 44 PDAC patients were collected at two time points: before the first FOLFIRINOX cycle and 14 days after the first cycle. EDTA blood tubes were used for multiplex flow cytometry analyses to quantify 18 immune cell populations and for complete blood count tests as the standard clinical routine. The flow cytometry data were analyzed with FlowJo software. In addition, Tempus blood tubes were used to isolate RNA and measure 1230 immune-related genes using NanoString Technology®. Data quality control, normalization, and analysis were performed using nSolver™ software and the Advanced Analysis module. Results: FFX-Lipeg treatment increased the number of neutrophils and monocytes, as shown by flow cytometry and complete blood count in concordance with elevated gene expression measured via targeted gene expression profiling analysis. Interestingly, flow cytometry analysis showed an increase in the number of B and T cells after treatment, while targeted gene expression analysis showed a decrease in B and T cell-specific gene expression. Conclusions: Targeted gene expression complements flow cytometry analysis to provide a comprehensive understanding of the effects of FFX-Lipeg. Flow cytometry and targeted gene expression showed increases in neutrophils and monocytes after FFX-Lipeg. The number of lymphocytes is increased after treatment; nevertheless, their cell-specific gene expression levels are downregulated. This highlights that different techniques influence clinical discoveries. Therefore, it is important to carefully select the measurement technique used to study the effect of a treatment.</p

Case Report: Adequate T and B Cell Responses in a SARS-CoV-2 Infected Patient After Immune Checkpoint Inhibition

After the COVID-19 outbreak, non-evidence based guidelines were published to advise clinicians on the adjustment of oncological treatment during this pandemic. As immune checkpoint inhibitors directly affect the immune system, concerns have arisen about the safety of immunotherapy during this pandemic. However, data on the immune response in oncology patients treated with immunotherapy are still lacking. Here, we present the adaptive immune response in a SARS-CoV-2 infected patient who was treated with immune checkpoint inhibitors for advanced renal cell cancer. To evaluate the immune response in this patient, the number of T cells and their major subsets were measured according to expression of markers for co-signalling, maturation, and chemotaxis at baseline, during therapy, and during the SARS-CoV-2 infection. In addition, plasma samples were analyzed for IgM and IgG antibodies and the ability of these antibodies to neutralise SARS-CoV-2. Despite several risk factors for an impaired immune response to SARS-CoV-2, both T- and B-cell responses were observed. Moreover, after treatment with immune checkpoint inhibitors, a sufficient cellular and humoral immune response was achieved in this SARS-CoV-2 infected patient. These findings warrant renewed discussion on withholding of immune checkpoint inhibitors during an ongoing COVID-19 pandemic

Anti–PD-1 Efficacy in Patients with Metastatic Urothelial Cancer Associates with Intratumoral Juxtaposition of T Helper-Type 1 and CD8þ T cells

Purpose: PD-1 inhibition results in durable antitumor responses in a proportion of patients with metastatic urothelial cancer (mUC). The majority of patients, however, do not experience clinical benefit. In this study, we aimed to identify early changes in T-cell subsets that underlie anti–PD-1 efficacy in patients with mUC. Experimental Design: Paired samples were collected from peripheral blood, plasma, and metastatic lesions of 56 patients with mUC at baseline and weeks 6 and 12 after initiating pembrolizumab treatment (200 mg intravenously, every 3 weeks). Samples were analyzed using multiplex flow cytometry, ELISA, and in situ stainings, including cellular network analysis. Treatment response was evaluated as best overall response according to RECIST v1.1, and patients were classified as responder (complete or partial response) or nonresponder (progressive disease). Results: In responders, baseline fractions of CD4þ T cells expressing cosignaling receptors were higher compared with nonresponders. The fraction of circulating PD-1þ CD4þ T cells decreased at weeks 6 and 12, whereas the fraction of 4-1BBþ CD28þ CD4þ T cells increased at week 12. In metastatic lesions of responders, the baseline density of T helper-type 1 (Th1) cells, defined as T-betþ CD4þ T cells, was higher as compared to nonresponders. Upon treatment, Th1 cells became localized in close proximity to CD8þ T cells, CD11bþ myeloid cells, and tumor cells. Conclusions: A decrease in the fraction of circulating PD-1þ CD4þ T cells, and juxtaposition of Th1, CD8þ, and myeloid cells was associated with response to anti–PD-1 treatment in patients with mUC

Serum cytokine levels are associated with tumor progression during FOLFIRINOX chemotherapy and overall survival in pancreatic cancer patients

Background: Biomarkers predicting treatment response may be used to stratify patients with pancreatic ductal adenocarcinoma (PDAC) for available therapies. The aim of this study was to evaluate the association of circulating cytokines with FOLFIRINOX response and with overall survival (OS). Methods: Serum samples were collected before start and after the first cycle of FOLFIRINOX from patients with PDAC (n=83) of all disease stages. Overall, 34 circulating cytokines were analyzed with a multiplex immunoassay. In addition, changes in peripheral blood immune cell counts were determined by flow cytometry to correlate with differences in cytokine levels. Chemotherapy response was determined by CT scans with the RECIST 1.1 criteria, as disease control (n=64) or progressive disease (n=19) within eight cycles of FOLFIRINOX. Results: Patients with high serum IL-1RA concentrations after one cycle of chemotherapy were less likely to have tumor progression during FOLFIRINOX (OR 0.25, P=0.040). Increase of circulating IL-1RA concentrations correlated with increase of total, classical (CD14+CD16-), and non-classical monocytes (CD14-CD16+), and dendritic cells. In multivariable cox regression, including the variables chemotherapy response outcome and baseline CA19-9 level, serum concentrations of IL-7 (HR 2.14, P=0.010), IL-18 (HR 2.00, P=0.020), and MIP-1β (HR 0.51, P=0.025) after one cycle of FOLFIRINOX showed correlations with OS. Conclusions: Circulating IL-1RA, IL-7, IL-18, and MIP-1β concentrations are biomarkers associated with FOLFIRINOX response in PDAC patients, suggesting an important role for specific immune cells in chemotherapy response and PDAC progression. Cytokine-based treatment might improve patient outcome and should be evaluated in future studies