Concurrent high PD-L1 expression and CD8+ immune cell infiltration predict PD-1 blockade efficacy in advanced EGFR-mutant NSCLC patients

Transcriptomic analysis of glucosidase II beta subunit (GluIIß) knockout A549 cells reveals its roles in regulation of cell adhesion molecules (CAMs) and anti-tumor immunity

Glucosidase II beta subunit (GluIIß), encoded from PRKCSH, is a subunit of the glucosidase II enzyme responsible for quality control of N-linked glycoprotein folding and suppression of GluIIß led to inhibitory effect of the receptor tyrosine kinase (RTKs) activities known to be critical for survival and development of cancer. In this study, we investigated the effect of GluIIß knockout on the global gene expression of cancer cells and its impact on functions of immune cells. GluIIß knockout lung adenocarcinoma A549 cell line was generated using CRISPR/Cas9-based genome editing system and subjected to transcriptomic analysis. Among 23,502 expressed transcripts, 1068 genes were significantly up-regulated and 807 genes greatly down-regulated. The KEGG enrichment analysis showed significant down-regulation of genes related extracellular matrix (ECM), ECM-receptor interaction, cytokine-cytokine receptor interaction and cell adhesion molecules (CAMs) in GluIIß knockout cells. Of 9 CAMs encoded DEG identified by KEGG enrichment analysis, real time RT-PCR confirmed 8 genes to be significantly down-regulated in all 3 different GluIIß knockout clones, which includes cadherin 4 (CDH4), cadherin 2 (CDH2), versican (VCAN), integrin subunit alpha 4 (ITGA4), endothelial cell-selective adhesion molecule (ESAM), CD274 (program death ligand-1 (PD-L1)), Cell Adhesion Molecule 1 (CADM1), and Nectin Cell Adhesion Molecule 3 (NECTIN3). Whereas PTPRF (Protein Tyrosine Phosphatase Receptor Type F) was significantly decreased only in 1 out of 3 knockout clones. Microscopic analysis revealed distinctively different cell morphology of GluIIβ knockout cells with lesser cytoplasmic and cell surface area compared to parental A549 cells and non-targeted transfected cells.Further investigations revealed that Jurkat E6.1 T cells or human peripheral blood mononuclear cells (PBMCs) co-cultured with GluIIß knockout A549 exhibited significantly increased viability and tumor cell killing activity compared to those co-cultured with non-target transfected cells. Analysis of cytokine released from Jurkat E6.1 T cells co-cultured with GluIIß knockout A549 cells showed significant increased level of angiogenin and significant decreased level of ENA-78. In conclusion, knockout of GluIIß from cancer cells induced altered gene expression profile that improved anti-tumor activities of co-cultured T lymphocytes and PBMCs thus suppression of GluIIß may represent a novel approach of boosting anti-tumor immunity.

Biomarkers of immunotherapy for non-small cell lung cancer

Immunotherapy is revolutionizing the treatment of non-small cell lung cancer by targeting immune checkpoint proteins, including programmed death-1, programmed death ligand 1 and cytotoxic T-lymphocyte-associated antigen 4. Several immune checkpoint inhibitors, including programmed death ligand 1 inhibitors, programmed death-1 inhibitors and cytotoxic T-lymphocyte-associated antigen 4 inhibitors, were approved for the treatment of patients with advanced non-small cell lung cancer. Programmed death ligand 1 expression is currently the only predictive biomarker for immune checkpoint inhibitors to guide the treatment strategy in these patients. However, programmed death ligand 1 expression is not a perfect biomarker for predicting the efficacy of immunotherapy. Therefore, various biomarkers such as tumour mutation burden, tumour microenvironment, gut microbiome and T-cell receptor repertoire have been proposed to predict the efficacy of immunotherapy more accurately. Additionally, combining different biomarkers may provide a more accurate prediction of response to immunotherapy. This article reports the review of the latest evidence of the predictive marker of immunotherapy in patients with advanced non-small cell lung cancer.

A Novel Scoring Model of Deubiquitination Patterns Predicts Prognosis and Immunotherapeutic Response in Hepatocellular Carcinoma

Aberrant expression of deubiquitinases (DUBs) is significantly associated with tumorigenesis. However, the precise impact of deubiquitination on the tumour microenvironment (TME) and immunotherapy in hepatocellular carcinoma (HCC) remains unclear. In this study, we comprehensively characterized the transcriptional and genetic alterations of 26 overall survival (OS)-related DUBs in HCC. The consensus clustering algorithm was used to identify patients with distinct deubiquitination patterns. We then established a DUBscore model using the principal component analysis (PCA) algorithm to quantify the deubiquitination patterns of individual HCC patients. Finally, we performed weighted gene coexpression network analysis (WGCNA) to identify the key DUBs. Consequently, three distinct deubiquitination patterns were identified, each showing significant differences in the characteristics of the TME, immune response, and clinical prognosis. Further analysis revealed that the DUBscore was an independent prognostic factor and could predict the response to immunotherapy for patients with HCC. Ultimately, BRCC3 was identified as a key DUB based on the DUBscore, which was significantly overexpressed in tumour tissues, as confirmed by qRT‒PCR and immunohistochemistry (IHC). We analysed the distribution and expression of BRCC3 in various types of immune cells using single-cell RNA sequencing (scRNA-seq). In conclusion, our study revealed the crucial role of deubiquitination patterns in shaping TME complexity and diversity. A more personalized and effective antitumour immunotherapy strategy can be developed by utilizing the DUBscore model to identify deubiquitination patterns in individual HCC patients. Our findings also highlight that BRCC3 may serve as a potential therapeutic target in HCC and a predictive marker for immunotherapeutic response.

Comparison of different predictive biomarker testing assays for PD-1/PD-L1 checkpoint inhibitors response: a systematic review and network meta-analysis

Background

Accurate prediction of efficacy of programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) checkpoint inhibitors is of critical importance. To address this issue, a network meta-analysis (NMA) comparing existing common measurements for curative effect of PD-1/PD-L1 monotherapy was conducted.

Methods

We searched PubMed, Embase, the Cochrane Library database, and relevant clinical trials to find out studies published before Feb 22, 2023 that use PD-L1 immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), microsatellite instability (MSI), multiplex IHC/immunofluorescence (mIHC/IF), other immunohistochemistry and hematoxylin-eosin staining (other IHC&HE) and combined assays to determine objective response rates to anti-PD-1/PD-L1 monotherapy. Study-level data were extracted from the published studies. The primary goal of this study was to evaluate the predictive efficacy and rank these assays mainly by NMA, and the second objective was to compare them in subgroup analyses. Heterogeneity, quality assessment, and result validation were also conducted by meta-analysis.

Findings

144 diagnostic index tests in 49 studies covering 5322 patients were eligible for inclusion. mIHC/IF exhibited highest sensitivity (0.76, 95% CI: 0.57-0.89), the second diagnostic odds ratio (DOR) (5.09, 95% CI: 1.35-13.90), and the second superiority index (2.86). MSI had highest specificity (0.90, 95% CI: 0.85-0.94), and DOR (6.79, 95% CI: 3.48-11.91), especially in gastrointestinal tumors. Subgroup analyses by tumor types found that mIHC/IF, and other IHC&HE demonstrated high predictive efficacy for non-small cell lung cancer (NSCLC), while PD-L1 IHC and MSI were highly efficacious in predicting the effectiveness in gastrointestinal tumors. When PD-L1 IHC was combined with TMB, the sensitivity (0.89, 95% CI: 0.82-0.94) was noticeably improved revealed by meta-analysis in all studies.

Interpretation

Considering statistical results of NMA and clinical applicability, mIHC/IF appeared to have superior performance in predicting response to anti PD-1/PD-L1 therapy. Combined assays could further improve the predictive efficacy. Prospective clinical trials involving a wider range of tumor types are needed to establish a definitive gold standard in future.

Classification of Tumor Immune Microenvironment According to Programmed Death-Ligand 1 Expression and Immune Infiltration Predicts Response to Immunotherapy Plus Chemotherapy in Advanced Patients With NSCLC

INTRODUCTION

According to mechanisms of adaptive immune resistance, tumor immune microenvironment (TIME) is classified into four types: (1) programmed death-ligand 1 (PD-L1)-negative and tumor-infiltrating lymphocyte (TIL)-negative (type I); (2) PD-L1-positive and TIL-positive (type II); (3) PD-L1-negative and TIL-positive (type III); and (4) PD-L1-positive and TIL-negative (type IV). However, the relationship between the TIME classification model and immunotherapy efficacy has not been validated by any large-scale randomized controlled clinical trial among patients with advanced NSCLC.

METHODS

On the basis of RNA-sequencing and immunohistochemistry data from the ORIENT-11 study, we optimized the TIME classification model and evaluated its predictive value for the efficacy of immunotherapy plus chemotherapy.

RESULTS

PD-L1 mRNA expression and immune score calculated by the ESTIMATE method were the strongest predictors for the efficacy of immunotherapy plus chemotherapy. Therefore, they were determined as the optimized definition of the TIME classification system. When compared between combination therapy and chemotherapy alone, only the type II subpopulation with high immune score and high PD-L1 mRNA expression was significantly associated with improved progression-free survival (PFS) (hazard ratio = 0.12, 95% confidence interval: 0.06-0.25, p < 0.001) and overall survival (hazard ratio = 0.27, 95% confidence interval: 0.13-0.55, p < 0.001). In the combination group, the type II subpopulation had a much longer survival time, not even reaching the median PFS or overall survival, but the other three subpopulations were susceptible to having similar PFS. In the chemotherapy group, there was no marked association between survival outcomes and TIME subtypes.

CONCLUSIONS

Only patients with both high PD-L1 expression and high immune infiltration could benefit from chemotherapy plus immunotherapy in first-line treatment of advanced NSCLC. For patients lacking either PD-L1 expression or immune infiltration, chemotherapy alone might be a better treatment option to avoid unnecessary toxicities and financial burdens.

High density and proximity of CD8+ T cells to tumor cells are correlated with better response to nivolumab treatment in metastatic pleural mesothelioma

BACKGROUND

The efficacy of immune checkpoint inhibitors (ICIs) in pleural mesothelioma has recently been established. The response to ICIs can be predicted by quantitative analysis of cells and their spatial distribution in the tumor microenvironment (TME). However, the detailed composition of the TME in pleural mesothelioma has not been reported. We evaluated the association between the TME and response to ICIs in this cancer.

METHODS

A retrospective analysis of 22 pleural mesothelioma patients treated with nivolumab in different centers was performed using surgical specimens. Four patients had a partial response to nivolumab (response group) and 18 patients had stable or progressive disease (nonresponse group). The number of CD4, CD8, FoxP3, CK, and PD-L1 positive cells, cell density, and cell-to-cell distance were analyzed by multiplex immunofluorescence.

RESULTS

PD-L1 expression did not differ significantly between the response and nonresponse groups. The density of total T cells and of CD8⁺ T cells was significantly higher in the response than in the nonresponse group. CD8⁺ T cells were more clustered and located closer to tumor cells, whereas regulatory T cells were located further from tumor cells in the response than in the nonresponse group.

CONCLUSIONS

High density and spatial proximity of CD8⁺ T cells to tumor cells were associated with better response to nivolumab, whereas the proximity of regulatory T cells to tumor cells was associated with worse response, suggesting that the distinct landscape of the TME could be a potential predictor of ICI efficacy in pleural mesothelioma.

Association between CD8+ tumor-infiltrating lymphocytes and prognosis of non-small cell lung cancer patients treated with PD-1/PD-L1 inhibitors: a systematic review and meta-analysis

BACKGROUND

A meta-analysis method was used to investigate the prognostic value of CD8+ tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC) patients treated with PD-1/PD-L1 inhibitors.

METHODS

A database search of PubMed, Embase, Web of Science and Cochrane Library up until February 7th, 2023. A clinical study on the relationship between CD8+ TILs and PD-1/PD-L1 inhibitors in the therapeutics of NSCLC. RevMan 5.3 and StataMP 17.0 software were used for meta-analysis. The outcome indicators incorporated overall survival (OS), progression-free survival (PFS) and objective response rate (ORR).

RESULTS

Nineteen articles with 1488 patients were included. The analysis results showed that high CD8+ TILs were associated with better OS (HR=0.60, 95% CI: 0.46-0.77; P<0.0001), PFS (HR=0.68, 95% CI: 0.53-0.88; P=0.003) and ORR (OR=2.26, 95% CI: 1.52-3.36; P<0.0001) in NSCLC patients treated with PD-1/PD-L1 inhibitors. Subgroup analysis indicated that patients with high CD8+ TILs had good clinical prognostic benefits whether the location of CD8+ TILs was intratumoral or stromal, and compared with East Asian, high CD8+ TILs in Caucasians showed a better prognosis. High CD8+ TILs in peripheral blood did not improve OS (HR=0.83, 95% CI: 0.69-1.01; P=0.06) and PFS (HR=0.93, 95% CI: 0.61-1.14; P=0.76) in NSCLC patients receiving PD-1/PD-L1 inhibitors.

CONCLUSION

In spite of the location of CD8+ TILs, high densities of CD8+ TILs were predictive of treatment outcomes in NSCLC patients treated with PD-1/PD-L1 inhibitors. However, high CD8+ TILs in peripheral blood had no predictive effect.

Analyses of single extracellular vesicles from non-small lung cancer cells to reveal effects of epidermal growth factor receptor inhibitor treatments

Precision cancer medicine has changed the treatment landscape of non-small cell lung cancer (NSCLC) as illustrated by the introduction of tyrosine kinase inhibitors (TKIs) towards mutated epidermal growth factor receptor (EGFR). However, as responses to EGFR-TKIs are heterogenous among NSCLC patients, there is a need for ways to early monitor changes in treatment response in a non-invasive way e.g., in patient's blood samples. Recently, extracellular vesicles (EVs) have been identified as a source of tumor biomarkers which could improve on non-invasive liquid biopsy-based diagnosis of cancer. However, the heterogeneity in EVs is high. Putative biomarker candidates may be hidden in the differential expression of membrane proteins in a subset of EVs hard to identify using bulk techniques. Using a fluorescence-based approach, we demonstrate that a single-EV technique can detect alterations in EV surface protein profiles. We analyzed EVs isolated from an EGFR-mutant NSCLC cell line, which is refractory to EGFR-TKIs erlotinib and responsive to osimertinib, before and after treatment with these drugs and after cisplatin chemotherapy. We studied expression level of five proteins; two tetraspanins (CD9, CD81), and three markers of interest in lung cancer (EGFR, programmed death-ligand 1 (PD-L1), human epidermal growth factor receptor 2 (HER2)). The data reveal alterations induced by the osimertinib treatment compared to the other two treatments. These include the growth of the PD-L1/HER2-positive EV population, with the largest increase in vesicles exclusively expressing one of the two proteins. The expression level per EV decreased for these markers. On the other hand, both the TKIs had a similar effect on the EGFR-positive EV population.