scholarly journals Digitally quantified CD8+ cells: the best candidate marker for an immune cell score in non-small cell lung cancer?

2020 ◽  
Author(s):  
Thomas K Kilvaer ◽  
Erna-Elise Paulsen ◽  
Sigve Andersen ◽  
Mehrdad Rakaee ◽  
Roy M Bremnes ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Open Source Software ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung ◽  
Candidate Marker ◽  
Digital Quantification ◽  
Immune Cell Score ◽  
Histological Subgroups

Abstract The TNM classification is well established as a state-of-the-art prognostic and treatment-decision-making tool for non-small cell lung cancer (NSCLC) patients. However, incorporation of biological data may hone the TNM system. This article focuses on choosing and incorporating subsets of tissue-infiltrating lymphocyte (TIL), detected by specific immunohistochemistry and automatically quantified by open source software, into a TNM-Immune cell score (TNM-I) for NSCLC. We use common markers (CD3, CD4, CD8, CD20 and CD45RO) of TILs to identify TIL subsets in tissue micro-arrays comprising tumor tissue from 553 patients resected for primary NSCLC. The number of TILs is automatically quantified using open source software (QuPath). Their prognostic efficacy, alone and within a TNM-I model, is evaluated in all patients and histological subgroups. Compared with previous manual semi-quantitative scoring of TILs in the same cohort, the present digital quantification proved superior. As a proof-of-concept, we construct a TNM-I, using TNM categories and the CD8+ TIL density. The TNM-I is an independent prognosticator of favorable diagnosis in both the overall cohort and in the main histological subgroups. In conclusion, CD8+ TIL density is the most promising candidate marker for a TNM-I in NSCLC. The prognostic efficacy of the CD8+ TIL density is strongest in lung squamous cell carcinomas, whereas both CD8+ TILs and CD20+ TILs, or a combination of these, may be candidates for a TNM-I in lung adenocarcinoma. Furthermore, based on the presented results, digital quantification is the preferred method for scoring TILs in the future.

scholarly journals Biomarkers and Gene Signatures to Predict Durable Response to Pembrolizumab in Non-Small Cell Lung Cancer

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3828
Author(s):  
Anello Marcello Poma ◽  
Rossella Bruno ◽  
Iacopo Pietrini ◽  
Greta Alì ◽  
Giulia Pasquini ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung ◽  
First Line ◽  
Durable Response ◽  
Nsclc Patients

Pembrolizumab has been approved as first-line treatment for advanced Non-small cell lung cancer (NSCLC) patients with tumors expressing PD-L1 and in the absence of other targetable alterations. However, not all patients that meet these criteria have a durable benefit. In this monocentric study, we aimed at refining the selection of patients based on the expression of immune genes. Forty-six consecutive advanced NSCLC patients treated with pembrolizumab in first-line setting were enrolled. The expression levels of 770 genes involved in the regulation of the immune system was analysed by the nanoString system. PD-L1 expression was evaluated by immunohistochemistry. Patients with durable clinical benefit had a greater infiltration of cytotoxic cells, exhausted CD8, B-cells, CD45, T-cells, CD8 T-cells and NK cells. Immune cell scores such as CD8 T-cell and NK cell were good predictors of durable response with an AUC of 0.82. Among the immune cell markers, XCL1/2 showed the better performance in predicting durable benefit to pembrolizumab, with an AUC of 0.85. Additionally, CD8A, CD8B and EOMES showed a high specificity (>0.86) in identifying patients with a good response to treatment. In the same series, PD-L1 expression levels had an AUC of 0.61. The characterization of tumor microenvironment, even with the use of single markers, can improve patients’ selection for pembrolizumab treatment.

scholarly journals P1.04-03 Suppressive Immune Cell Profiling in Patients with Non-Small Cell Lung Cancer

2018 ◽  
Vol 13 (10) ◽  
pp. S526
Author(s):  
J. Koh ◽  
K.Y. Lee ◽  
B. Kim ◽  
M.S. Kim ◽  
H.J. Cho ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals Seven Autophagy-Related Genes are Associated with the Tumor Immune Microenvironment in Predicting Survival Risk of Non-Small Cell Lung Cancer

2021 ◽  
Author(s):  
Huihui Jiang ◽  
Aiqun Xu ◽  
Min Li ◽  
Rui Han ◽  
Enze Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Small Cell ◽  
Gene Set Enrichment Analysis ◽  
Small Cell Lung

Abstract Background: Non-small cell lung cancer (NSCLC) ranks first among global cancer-related deaths. Despite the emergence of various immunological and targeted therapies, immune tolerance remains a barrier to treatment. Methods: It has been found that this obstacle can be overcome by targeting autophagy-related genes (ATGs). ATGs were screened by coexpression analysis and the genes related to the prognosis of lung cancer were screened using Kaplan–Meier (K-M) survival analysis, univariate Cox regression, and multivariate Cox regression. The prognostic risk model of ATGs was constructed and verified using K-M survival analysis and receiver operating characteristic (ROC) curve analysis. Results: The prognostic risk model of ATGs was constructed. Gene set enrichment analysis (GSEA) showed that the function and pathway of ATG enrichment were closely related to immune cell function. CIBERSORT, LM22 matrix, and Pearson correlation analysis showed that risk signals were significantly correlated with immune cell infiltration and immune checkpoint genes. Conclusions: We identified and independently verified the ATG (AL691432.2, MMP2-AS1, AC124067.2, CRNDE, ABALON, AL161431.1, NKILA) in NSCLC patients and found that immune regulation in the tumor microenvironment is closely related to this gene.

scholarly journals Investigation on Potential Correlation Between the RNA-Binding Protein of Evolutionarily Conserved MEX3 Family and Non–Small-Cell Lung Cancer

2021 ◽  
Author(s):  
Ming Zhang ◽  
Hualiang Zhang ◽  
Linfeng Cao ◽  
Gouxin Hou ◽  
Chao Lu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Rna Binding ◽  
Immune Cell ◽  
Tumor Development ◽  
Treatment Strategies ◽  
Small Cell ◽  
Small Cell Lung ◽  
Tumor Cell Death

Abstract Background As mRNA binding proteins, MEX3 (muscle excess 3) family highlights its unique characteristics and plays an emerging role in post-transcriptionally regulating programmed of biological processes, including tumor cell death and immunological relevance. These have been shown to be involved in various diseases, however, the role of MEX3 in non-small-cell lung cancer (NSCLC) has not been fully elucidated. Results In this study, we found that the sequence or copy number of MEX3 gene did not change significantly, which can explain the stability of malignant tumor development through the COSMIC database. Further, gene expression in NSCLC was examined using the Oncomine™ database, and the prognostic value of each gene was analyzed by Kaplan-Meier analysis. The results showed that overexpressed of MEX3A, MEX3B, MEX3C and MEX3D were associated with significantly lower OS in patients with NSCLC and LUAD, while overexpressed of MEX3D was associated with significantly poorer OS in patients with LUSC. We also applied the Tumor Immune Estimation Resource (TIMER) tool to assess the correlations between distinct MEX3 and the infiltrating immune cell landscape. Conclusion On this subject, we have learned about the complexity and heterogeneity of NSCLC through MEX3. We found that most of MEX3 is highly expressed in NSCLC. High expression indicates a poor prognosis and has a certain immune correlation. Therefore, these conclusions can lay a framework for the prognosis of NSCLC patients and the development of treatment strategies in the future.

scholarly journals Evaluation Expression of miR-146a and miR-155 in Non-Small-Cell Lung Cancer Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Neda K. Dezfuli ◽  
Shamila D. Alipoor ◽  
Neda Dalil Roofchayee ◽  
Sharareh Seyfi ◽  
Babak Salimi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Negative Correlation ◽  
Peripheral Blood ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cell Frequency ◽  
Positive Correlation ◽  
Nsclc Patients

BackgroundNon−small-cell lung cancer (NSCLC) is the major type of lung cancer. MicroRNAs (miRNAs) are novel markers and targets in cancer therapy and can act as both tumor suppressors and oncogenes and affect immune function. The aim of this study was to investigate the expression of miR146a and miR155 in linked to blood immune cell phenotypes and serum cytokines in NSCLC patients.MethodsThirty-three NSCLC patients and 30 healthy subjects were enrolled in this study. The allele frequencies of potential DNA polymorphisms were studied using polymerase chain reaction (PCR)–restriction fragment length polymorphism (PCR-RFLP) analysis in peripheral blood samples. Quantitative reverse transcription PCR (qRT-PCR) was used to measure the expression of miR-146a and miR-155 in peripheral blood mononuclear cells (PBMCs). Serum cytokine (IL-1β, IL-6, TNF-α, TGF-β, IL-4, IFN-γ) levels were determined by ELISA. The frequency of circulating CD3+CTLA-4+ and CD4+CD25+FOXP3+ (T regulatory cells/Treg) expression was measured by flow cytometry.ResultsmiR-146a was significantly downregulated in PBMC of NSCLC patients (P ≤ 0.001). Moreover, IL-6 and TGF-β levels were elevated in NSCLC patients (P ≤ 0.001, P ≤ 0.018, respectively). CD3+ CTLA-4+ and Treg cells frequencies were higher in patients than in control subjects (P ≤ 0.0001, P ≤ 0.0001, respectively). There was a positive correlation between miR-155 and IL-1β levels (r=0.567, p ≤ 0.001) and a negative correlation between miR-146a and TGF-β levels (r=-0.376, P ≤ 0.031) in NSCLC patients. No significant differences were found in the relative expression of miR-146a and miR-155, cytokine levels or immune cell numbers according to miR-146a and miR-155 (GG/GC/CC, TT/AT/AA) genotypes. However, there was a positive correlation between miR-146a and IL-1β levels (r=0.74, P ≤ 0.009) in GG subjects and a positive correlation between miR-146a expression and CD3+CTLA4+ cell frequency (r=0.79, P ≤ 0.01) in CC genotyped subjects. Conversely, a negative correlation between miR-146a expression and Treg cell frequency (r=−0.87, P ≤ 0.05) was observed with the GG genotype. A positive correlation between miR-155 and IL-1β expression (r=0.58, p ≤ 0.009) in the TT genotype and between miR-155 expression and CD3+CTLA-4 cell frequency (r=0.75, P ≤ 0.01) was observed in the AT genotype.ConclusionsThe current data suggest that the miR-146a expression in PBMC and serum TGF-β and IL-1β levels may act as blood markers in NSCLC patients. Further study is needed to elucidate the link between immune cells and serum miR146 at early disease stages.

Using a multiplexed immunofluorescence approach to compare immune cell populations in subtypes of non-small cell lung cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20702-e20702
Author(s):  
Anna Juncker-Jensen ◽  
Vivek Reddy ◽  
Erinn Parnell ◽  
Mate Levente Nagy ◽  
Judy Kuo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cell ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Protein Level ◽  
Immune Cell ◽  
Small Cell ◽  
Cell Segmentation ◽  
Small Cell Lung ◽  
Cell Composition

e20702 Background: Non-small cell lung cancer (NSCLC) accounts for approximately 80-85% of all lung cancer cases, and is characterized by a poor response to chemotherapy and a low survival rate. While immunotherapy has recently emerged as a successful approach in the treatment of NSCLC patients only 20-25% of patients show a positive response to anti-PD/PDL1 therapy, stressing the urgent need for additional immunotherapy options. NSCLC is a very heterogeneous disease with the two most common types being adenocarcinoma (ADCA) and squamous cell carcinoma (SCC). While a study using flow cytometry to analyze NSCLC on protein level reported the immune cell composition to be fundamentally different in ADCA compared with SCC (Daraselia et al. Am J Cancer Res, 2012 2(1):93), to the best of our knowledge this study will be the first of its kind performing an extensive analysis of NSCLS immune cell composition in tissue. Methods: In order to perform this comprehensive immunoprofiling of the NSCLC subtypes ADCA and SCC we will be using MultiOmyx™, an immunofluorescence (IF) multiplexing assay with similar staining characteristics as standard IHC stains but with the significant advantage that up to 60 protein biomarkers can be interrogated from a single FFPE section. Proprietary cell segmentation algorithms generate unique IDs for every cell and deep learning based cell classification algorithms then identify positive cells for each biomarker. Results: Using a 16-marker panel consisting of CD3, CD4, CD8, FoxP3, CD20, CD68, CD163, CD15, PD1, PDL1, ICOS, OX40, LAG-3, TIM-3, and PanCK we will analyze the proportion of B cells, T cell subtypes, M1/M2-type tumor-associated macrophages, as well as the expression of PD1/PDL1, in addition to novel immunotherapy targets LAG3, TIM3, ICOS, and OX40 in 20 samples from patients with NSCLC (10 ADCA and 10 SCC). Finally, from the same FFPE blocks that we will use to profile the immune cell composition on protein level we will also be extracting DNA/RNA in order to perform T cell receptor (TCR) sequencing, which will provide additional information on the diversity of T cells present in these tumors. Conclusions: It is our hope that these data will help provide new insights into the biology of ADCA and SCC that can ultimately be used to explore novel immunotherapeutic interventions for lung cancer treatment.

MA08.06 Immune Cell Profiles as Predictors of Survival in Surgically Treated Non-Small Cell Lung Cancer (NSCLC)

2021 ◽  
Vol 16 (10) ◽  
pp. S910
Author(s):  
L. Sellmer ◽  
J. Kovács ◽  
J. Neumann ◽  
J. Walter ◽  
D. Kauffmann-Guerrero ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung
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