The Predictive Efficacy of Tumor Mutation Burden (TMB) on Nonsmall Cell Lung Cancer Treated by Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis

Identification of an immune-related genes signature in lung adenocarcinoma to predict survival and response to immune checkpoint inhibitors

BACKGROUND

Although advances in immune checkpoint inhibitor (ICI) research have provided a new treatment approach for lung adenocarcinoma (LUAD) patients, their survival is still unsatisfactory, and there are issues in the era of response prediction to immunotherapy.

METHODS

Using bioinformatics methods, a prognostic signature was constructed, and its predictive ability was validated both in the internal and external datasets (GSE68465). We also explored the tumor-infiltrating immune cells, mutation profiles, and immunophenoscore (IPS) in the low-and high-risk groups.

RESULTS

As far as we are aware, this is the first study which introduces a novel prognostic signature model using BIRC5, CBLC, S100P, SHC3, ANOS1, VIPR1, LGR4, PGC, and IGKV4.1. According to multivariate analysis, the 9-immune-related genes (IRGs) signature provided an independent prognostic factor for the overall survival (OS). The low-risk group had better OS, and the tumor mutation burden (TMB) was significantly lower in this group. Moreover, the risk scores were negatively associated with the tumor-infiltrating immune cells, like CD8+ T cells, macrophages, dendritic cells, and NK cells. In addition, the IPS were significantly higher in the low-risk group as they had higher gene expression of immune checkpoints, suggesting that ICIs could be a promising treatment option for low-risk LUAD patients.

CONCLUSION

The combination of these 9-IRGs not only could efficiently predict overall survival of LUAD patients but also show a powerful association with the expression of immune checkpoints and response to ICIs based on IPS; hoping this model paves the way for better stratification and management of patients in clinical practice.

Epigenetic modification in radiotherapy and immunotherapy for cancers

Radiotherapy (RT) is one of the primary treatment modalities in managing cancer patients. Recently, combined RT and immunotherapy (IT) (i.e., radio-IT [RIT]) have been aggressively investigated in managing cancer patients. However, several issues in conducting RIT are challenging, such as incorporating advanced irradiation techniques, predictive/prognostic biomarkers, and other treatment modalities. Several clinical efforts and novel biomarkers have been introduced and developed to solve these challenges. For example, stereotactic radiosurgery/stereotactic radiotherapy, stereotactic body radiotherapy/stereotactic ablative body radiotherapy, and FLASH-RT have been applied for delivering precise irradiation to lung and liver tumors in conjunction with IT. Besides, several novel IT agents and incorporations of other therapies, such as targeted and thermal therapies, have been further investigated. The present study reviewed the emerging challenges of RIT in modern oncology. We also evaluated clinical practice, bench research, and multimodality treatments. In addition to several clinically applicable biomarkers, we emphasize the roles of advanced irradiation techniques and epigenetic modification as predictive/prognostic biomarkers and potential therapeutic targets. For example, 6(m) A-based epigenetic agents demonstrate the potential to enhance the treatment effects of RIT. However, further prospective randomized trials should be conducted to confirm their roles.

The Predictive Value of BUB1 in the Prognosis of Oral Squamous Cell Carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is the most common type of malignant tumour in the oral cavity, and it is known for its poor prognosis. Budding uninhibited by benzimidazoles 1 (BUB1) may be related to cancer prognosis; however, the specific relationship between BUB1 and OSCC prognosis remains largely unexplored.

METHODS

The mRNA levels of BUB1 were analysed using data from the TCGA_OSCC and GSE23558 cohorts. OSCC samples from the TCGA_OSCC dataset were divided into low- and high-BUB1 expression groups based on the median BUB1 level. Furthermore, results of survival analysis, tumour mutation burden (TMB), gene set enrichment analysis (GSEA) pathways, and drug-sensitivity analysis were compared between the 2 groups.

RESULTS

Based on the data from the TCGA_OSCC and GSE23558 cohorts, BUB1 mRNA levels were significantly upregulated in OSCC tissues compared to healthy controls. Moreover, high expression of BUB1 may serve as an independent indicator of poor prognosis in OSCC. Additionally, patients with high BUB1 expression also exhibited increased levels of immune checkpoints and TMB, suggesting that patients with high BUB1 expression may benefit from immunotherapy. Mechanistically, transcription factors ZFP64, TCF3, and ZNF281 were found to potentially bind to the promoter region of BUB1, thereby regulating its gene expression. Furthermore, GSEA results showed that BUB1 expression was closely related to cell cycle and tumour-related pathways in OSCC. Drug-sensitivity analysis showed that patients with high BUB1 expression may be more sensitive to gemcitabine, paclitaxel, or imatinib.

CONCLUSIONS

Collectively, results demonstrated that high BUB1 levels may be related to a poor prognosis of OSCC, highlighting its potential as a novel prognostic biomarker for OSCC.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Characterization of an endoplasmic reticulum stress-associated lncRNA prognostic signature and the tumor-suppressive role of RP11-295G20.2 knockdown in lung adenocarcinoma

Endoplasmic reticulum stress (ERS) is commonly induced by accumulating misfolded or unfolded proteins in tumor microenvironment. Long non-coding RNAs (lncRNAs) play important roles in ERS response and lung adenocarcinoma (LUAD) progression. However, the role of ERS-related lncRNAs in LUAD remains unknown. In this study, we aimed to identify ERS-associated lncRNAs with prognostic value in LUAD and characterize their clinical implications. Cox and least absolute shrinkage and selection operator regression analyses identified nine ERS-related lncRNAs with independent prognostic abilities, including five protective factors (CROCCP2, KIAA0125, LINC0996, RPARP-AS1 and TBX5-AS1) and four risk factors (LINC0857, LINC116, RP11-21L23.2 and RP11-295G20.2). We developed an ERS-related lncRNA risk prediction model in predicting overall survival of LUAD patients, which classified TCGA cohorts into high-risk (HS) and low-risk (LS) groups. Comprehensive bioinformatic analyses revealed HS patients featured with late-stage tumors, greater mutation burdens, weaker anti-tumor immunity/responses, and lower sensitivity to targeted drugs compared to LS patients, contributing to tumor progression and a poor prognosis. Functional enrichment analysis implicated these ERS-related lncRNAs in cell migration, cell death, and immunity. Furthermore, expression of the most significantly upregulated risk lncRNA, RP11-295G20.2, was validated at the mRNA level using clinical LUAD samples. Knockdown of RP11-295G20.2 obviously reduced ERS and suppressed proliferation, invasion, and migration of LUAD cells. This novel ERS-related lncRNA signature provides a new biomarker for prognostic prediction, and ERS-associated RP11-295G20.2 serves as a potential therapeutic target in LUAD.

Impact of the STK11/KRAS co-mutation on the response to immunotherapy in a real-world pan-cancer cohort

INTRODUCTION

Immune checkpoint inhibitors are highly effective in treating various cancers. We analyzed the significance of the KRAS/STK11 co-mutation in relation to the efficacy of immune checkpoint inhibitors in pan-cancer patient cohort.

METHODS

We analyzed data from open-access research: MSK-IMPACT (molecular profiling data from patients receiving systemic antitumor therapy) and MSK-TMB (molecular profiling data from patients receiving immune checkpoint inhibitors). In both studies, high throughput sequencing was used for molecular profiling.

RESULTS

A total of 10,336 patients receiving antitumor therapy (MSK-IMPACT study) and 1661 patients receiving immune checkpoint inhibitors (MSK-TMB study) were included in the analysis. Co-mutation STK11/KRAS was found in 156 (1.5%) and 46 (2.8%) patients in the two studies, respectively. Most patients with the STK11/KRAS co-mutation had non-small cell lung cancer (83% and 85% in the two studies, respectively). Among non-small cell lung cancer patients, the STK11 mutation was associated with a worse outcome for patients receiving systemic antitumor therapy, but not immune checkpoint inhibition therapy (HR for OS 1.90 [95% CI 1.36-2.65] and 1.44 [95% CI 0.88-2.37]). Co-mutation STK11/KRAS was also not associated with patient outcome in any of the studies (HR for OS 0.93 [95% CI 0.56-1.52] and 1.09 [95% CI 0.54-2.19]). High tumor mutational burden was associated with better outcome in the cohort of patients receiving immune checkpoint inhibitors. An analogous analysis among patients in the pan-cancer cohort (excluding patients with non-small cell lung cancer) showed STK11 mutations and high tumor mutational burden have a predictive role for the efficacy of immune checkpoint inhibitors, but not STK11/KRAS co-mutation.

CONCLUSIONS

Co-mutation STK11/KRAS is common among patients with non-small cell lung cancer and is not an independent predictive marker for the efficacy of immune checkpoint inhibitors. Further studies are required to clarify the role of STK11 mutations in immune checkpoint inhibitor treatment response.

Morphometric analysis of nuclear shape irregularity as a novel predictor of programmed death-ligand 1 expression in lung squamous cell carcinoma

Immune checkpoint inhibitor (ICI) therapy has been established as one of the key treatment strategies for lung squamous cell carcinoma (LUSQ). The status of programmed death-ligand 1 (PD-L1) in tumor cells and/or immune cells using immunohistochemistry has been primarily used as a surrogate marker for determining ICI treatment; however, when the tissues to be examined are small, false-negative results could be unavoidable due to the heterogeneity of PD-L1 immunoreactivity. To overcome this practical limitation, we attempted to explore the status of nuclear atypia evaluated using morphometry as a potential predictor of PD-L1 status in LUSQ. We correlated the parameters related to nuclear atypia with PD-L1 status using two different cohorts of LUSQ patients (95 cases from The Cancer Genome Atlas database and 30 cases from the Miyagi Cancer Center). Furthermore, we studied the gene mutation status to elucidate the genetic profile of PD-L1 predictable cases. The results revealed that nuclear atypia, especially morphometric parameters related to nuclear shape irregularity, including aspect ratio, circularity, roundness, and solidity, were all significantly associated with PD-L1 status. Additionally, LUSQ cases with high PD-L1 expression and pronounced nuclear atypia were significantly associated with C10orf71 and COL14A1 mutations compared with those with low PD-L1 expression and mild nuclear atypia. We demonstrated for the first time that nuclear shape irregularity could represent a novel predictor of PD-L1 expression in LUSQ. Including the morphometric parameters related to nuclear atypia in conjunction with PD-L1 status could help determine an effective ICI therapeutic strategy; however, further investigation is required.

Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

PURPOSE

To explore whether patients with BRCA1/2-mutated or homologous recombination deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial.

PATIENTS AND METHODS

Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. Programmed death-ligand 1 (PD-L1) status of tumor-infiltrating immune cells (IC) was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥ 16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates.

RESULTS

Among biomarker-evaluable samples, 22% (234/1,050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1,024) had TMB ≥10 mut/Mb, and 0.3% (3/1,022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on ICs) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors.

CONCLUSIONS

Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors. See related commentary by Al-Rawi et al., p. 1645.

Immunotherapy for Metastatic Non-Small Cell Lung Cancer: Therapeutic Advances and Biomarkers

Immunotherapy has revolutionized the treatment paradigm of non-small cell lung cancer and improved patients' prognosis. Immune checkpoint inhibitors have quickly become standard frontline treatment for metastatic non-oncogene addicted disease, either as a single agent or in combination strategies. However, only a few patients have long-term benefits, and most of them do not respond or develop progressive disease during treatment. Thus, the identification of reliable predictive and prognostic biomarkers remains crucial for patient selection and guiding therapeutic choices. In this review, we provide an overview of the current strategies, highlighting the main clinical challenges and novel potential biomarkers.

Metabolic Tumor Volume Measured by 18F-FDG PET/CT is Associated with the Survival of Unresectable Hepatocellular Carcinoma Treated with PD-1/PD-L1 Inhibitors Plus Molecular Targeted Agents

Purpose

The combination of PD-1/PD-L1 inhibitors and molecular targeted agents showed promising efficacy for unresectable hepatocellular carcinoma (uHCC). This study aimed to investigate the prognostic value of metabolic parameters from ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) in patients with uHCC underwent the combined therapies.

Patients and Methods

Patients with uHCC treated with a combination of immunotherapy and targeted therapy who underwent baseline ¹⁸F-FDG PET/CT between July 2018 and December 2021 were recruited retrospectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake values (SUV_max), and clinical and biological parameters were recorded. A multivariate prediction model was developed for overall survival (OS) using these parameters together with clinical prognostic factors.

Results

Seventy-seven patients were finally included. The median OS was 16.8 months. We found that a high MTV (≥39.65 cm³ as the median value) was significantly associated with OS (P<0.05). In multivariate analyses for OS, a high MTV, high Eastern Cooperative Oncology Group performance status (ECOG-PS, ≥1), Child-Pugh (B-C) grade, and the presence of bone metastasis were significantly associated with poor OS (HR 1.371, HR 3.73, HR 15.384, and HR 2.994, all P<0.05, respectively). A multivariate prognostic model including MTV and prognostic factors, such as ECOG-PS, Child-Pugh grade, and bone metastasis, further improved the identification of different OS subgroups.

Conclusion

High MTV is an adverse prognostic factor in patients with uHCC treated with a combination of immunotherapy and molecular targeted agents. Integrating PET/CT parameters with clinical prognostic factors could help to personalize immunotherapy.

Cell adhesion molecules and immunotherapy in advanced non-small cell lung cancer: Current process and potential application

Advanced non-small cell lung cancer (NSCLC) is a severe disease and still has high mortality rate after conventional treatment (e.g., surgical resection, chemotherapy, radiotherapy and targeted therapy). In NSCLC patients, cancer cells can induce immunosuppression, growth and metastasis by modulating cell adhesion molecules of both cancer cells and immune cells. Therefore, immunotherapy is increasingly concerned due to its promising anti-tumor effect and broader indication, which targets cell adhesion molecules to reverse the process. Among these therapies, immune checkpoint inhibitors (mainly anti-PD-(L)1 and anti-CTLA-4) are most successful and have been adapted as first or second line therapy in advanced NSCLC. However, drug resistance and immune-related adverse reactions restrict its further application. Further understanding of mechanism, adequate biomarkers and novel therapies are necessary to improve therapeutic effect and alleviate adverse effect.

Pan-cancer analysis of tumor mutation burden sensitive tumors reveals tumor-specific subtypes and hub genes related to immune infiltration

BACKGROUND

High tumor mutation burden (TMB) failed to serve as a favorable prognostic biomarker for immunotherapy across all tumors. This study aimed to explore TMB-sensitive tumors on a pan-cancer level and construct their immune infiltration phenotypes in TMB-high groups.

METHODS

Pan-cancer patients were separated into TMB-high and TMB-low groups based on the median TMB values per tumor. TMB-related genes were identified using differently expressed genes (DEGs) and differently mutated genes (DMGs) between the above two TMB groups. CIBERSORT algorithm was used to estimate the abundance of 22 tumor immune infiltrating cells (TIICs). Consensus clustering analysis was applied to predict molecular subtypes. Cox regression analysis was performed to evaluate the correlations between hub genes and TIICs and immunomodulator genes.

RESULTS

Nine TMB-sensitive tumors were identified by high-frequency of TMB-related genes. A total of 126 tumor-specific hub genes (1 in BLCA, 19 in BRCA, 4 in COAD, 4 in HNSC, 25 in LUAD, 2 in LUSC, 27 in SKCM, 37 in STAD, and 7 UCEC) were identified. In five out of nine TMB-sensitive tumors, the molecular subtypes based on hub gene expression were characterized by TMB values, prognostic values and tumor-specific TIICs levels. In TMB-high groups, hub genes associated immune infiltration phenotypes were constructed with key TIICs and immunomodulators spanning TMB-sensitive tumors.

CONCLUSIONS

Our tumor-specific analysis revealed hub genes associated immune infiltration features may serve as potential therapeutic targets and prognostic markers of immunotherapy, providing the potential underlying mechanism of immune infiltration in TMB-high groups across TMB-sensitive tumors.

Characterization of Necroptosis-Related Molecular Subtypes and Therapeutic Response in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high morbidity and mortality and is usually associated with therapeutic resistance and poor prognosis because of individual biological heterogeneity. There is an unmet need to screen for reliable parameters, especially immunotherapy-related biomarkers to predict the patient’s outcomes. Necroptosis is a special caspase-independent form of necrotic cell death associated with the pathogenesis, progression, and prognosis of multiple tumors but the potential connection between necroptosis-related genes (NRGs) and LUAD still remains unclear. In this study, we expounded mutational and transcriptional alterations of 67 NRGs in 522 LUAD samples and proposed a consensus-clustering subtype of these patients into two cohorts with distinct immunological and clinical prognosis characteristics. Cluster B patients were associated with a better prognosis and characterized by relatively lower expression of NRGs, higher immune scores in the tumor microenvironment (TME), more mild clinical stages, and downregulated expression of immunotherapy checkpoints. Subsequently, the NRG score was further established to predict the overall survival (OS) of LUAD patients using univariate Cox, LASSO, and multivariate Cox regression analyses. The immunological characteristics and potential predictive capability of NRG scores were further validated by 583 LUAD patients in external datasets. In addition to better survival and immune-activated conditions, low-NRG-score cohorts exhibited a significant positive correlation with the mRNA stem index (mRNAsi) and tumor mutation burden (TMB) levels. Combined with classical clinical characteristics and NRG scores, we successfully defined a novel necroptosis-related nomogram to accurately predict the 1/3/5-year survival rate of individual LUAD patients, and the potential predictive capability was further estimated and validated in multiple test datasets with high AUC values. Integrated transcriptomic analysis helps us seek vital NRGs and supplements a novel clinical application of NRG scores in predicting the overall survival and therapeutic benefits for LUAD patients.

A Bioinformatic Analysis: The Overexpression and Prognostic Potential of GPX7 in Lower-Grade Glioma

Purpose

Glutathione peroxidase-7 (GPX7) is a newly discovered non-selenium-containing protein with glutathione peroxidase activity, which mainly protects the organism from oxidative damage and is very important for basic biology studies. This study aims to reveal the expression pattern of GPX7 and its prognosis potential from a pan-cancer perspective.

Methods

Expression levels of GPX7 in human tumor tissues and normal tissues were evaluated using Human Protein Atlas (HPA), the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and UALCAN databases. The prognostic potential of GPX7 for 33 TCGA tumors was evaluated by Kaplan–Meier analysis and Cox regression analysis. Subsequently, the Chinese Glioma Genome Atlas (CGGA) dataset was used to further verify the expression of GPX7 and its prognostic potential in glioma. We explored the correlation between GPX7 and immune infiltration, tumor mutational burden (TMB) and microsatellite instability (MSI). Furthermore, a nomogram lower-grade glioma (LGG) was constructed to verify the prognostic outcome of patients. Finally, the relationship between GPX7 and treatment regimens for LGG was also explored.

Results

GPX7 was overexpressed in multiple tumors. Elevated expression of GPX7 was associated with poor prognosis of LGG patients (OS hazard ratio (HR) = 1.044, P < 0.0001; DFS HR = 1.035, P < 0.0001; PFS HR = 1.045, P < 0.0001). GPX7 was proved to be an independent prognostic factor of LGG through univariate and multivariate Cox analysis. The nomogram confirmed a better predictability (Concordance index (C-index): 0.845; 95% CI, 0.825–0.865). GPX7 was positively correlated with TMB in LGG. GPX7 expression was negatively correlated with half-maximal inhibitory concentration (IC50) of temozolomide (TMZ) (\documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over \rho } $$ \end{document}_spearman= −0.59, P =1.3e-48).

Conclusion

GPX7 was upregulated in multiple tumors, and it was a potential prognostic biomarker in LGG. High-expressed GPX7 can predict the sensitivity of TMZ in LGG patients.

Predictive value of tumor mutational burden for immunotherapy in non-small cell lung cancer: A systematic review and meta-analysis

Background

Immunotherapy has emerged as a promising treatment for non-small cell lung cancer (NSCLC). Yet, some patients cannot benefit from immunotherapy, and reliable biomarkers for selecting sensitive patients are needed. Herein, we performed a meta-analysis to evaluate the predictive value of tumor mutational burden (TMB) in NSCLC patients treated with immunotherapy.

Methods

Eligible studies were comprehensively searched from electronic databases prior to August 31, 2021. Meta-analyses of high TMB versus low TMB as well as immunotherapy versus chemotherapy in patients with high/low TMB were conducted. Hazard ratio (HR) with corresponding 95% confidence interval (95%CI) for progression-free survival (PFS) and overall survival (OS) and odds ratio (OR) with 95%CI for objective response rate (ORR) were calculated.

Results

A total of 31 datasets (3437 patients) and 6 randomized controlled trials (3662 patients) were available for meta-analyses of high TMB versus low TMB and immunotherapy versus chemotherapy, respectively. High TMB predicted significantly favorable PFS (HR = 0.54, 95%CI: 0.46–0.63, P<0.001) and OS (HR = 0.70, 95%CI: 0.57–0.87, P = 0.001), and higher ORR (OR = 3.14, 95%CI: 2.28–4.34, P<0.001) compared with low TMB. In patients with high TMB, immunotherapy was associated with improved PFS (HR = 0.62, 95%CI: 0.53–0.72), OS (HR = 0.67, 95%CI: 0.57–0.79) and ORR (OR = 2.35, 95%CI: 1.74–3.18) when compared with chemotherapy. However, in patients with low TMB, immunotherapy seemed to predict inferior PFS (HR = 1.20, 95%CI: 1.02–1.41) and ORR (OR = 0.61, 95%CI: 0.44–0.84) and have no OS benefit (HR = 0.88, 95%CI: 0.74–1.05) as compared with chemotherapy.

Conclusion

This meta-analysis demonstrates more clinical benefits concerning treatment response and survival outcomes in high-TMB NSCLC patients who are treated with immunotherapy. TMB is a promising biomarker for discriminating NSCLC patients who can benefit more from immunotherapy.

Predictive Efficacy of Blood-Based Tumor Mutation Burden Assay for Immune Checkpoint Inhibitors Therapy in Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background

In non-small cell lung cancer (NSCLC) patients treated by immune checkpoint inhibitors (ICIs), tumor mutation burden (TMB) has been found to have predictive potential for survival. When compared to TMB detection in tissue (tTMB), detecting TMB in the blood (bTMB) has practical advantages; yet, the results of various studies are conflicting. The question of whether bTMB can be utilized as a predictive biomarker is becoming increasingly contentious. To confirm the predictive efficacy of bTMB, researchers did a systematic review and meta-analysis to look into the relationship between ICIs and bTMB.

Method

From the inception to March 2021, Cochrane Library, PubMed, EMBASE and other databases were systematically searched. The predictive value of bTMB in ICIs, or the efficacy of ICIs against chemotherapy, was studied. The results were presented as pooled ratio rate (RR) and hazard ratio (HR) with 95% confidence intervals for the Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Subgroup analysis, heterogeneity analyses, and sensitivity analysis were also performed.

Results

A total of 2,610 NSCLC patients were studied in seven trials. There were no significant differences in OS (HR = 1.09; 95% CI: 0.62–1.91, P = 0.774) or PFS (HR = 0.73; 95% CI: 0.20–2.65, P = 0.629) between high and low bTMB groups in the ICIs cohort. When ICIs were compared to chemotherapy, ICIs were found to enhance OS (HR = 0.74; 95% CI: 0.59–0.92, P = 0.006), but the improvement in PFS and ORR was only a numerical trend (PFS: HR = 0.83; 95% CI: 0.63–1.09, P = 0.173; ORR: RR = 0.92, 95% CI: 0.77–1.10, P = 0.372). NSCLC patients treated with ICIs in the high bTMB group had better survival benefits than chemotherapy patients in terms of OS (HR = 0.63; 95% CI: 0.51–0.76, P <0.001), PFS (HR = 0.63; 95% CI: 0.52–0.76, P <0.001), and ORR (RR = 1.86; 95% CI: 1.32–2.62, P <0.001), while in the low TMB group, the results were no different or even reversed (OS: HR = 0.89; 95% CI: 0.64–1.24, P = 0.485; PFS: HR = 1.21, 95% CI: 0.93–1.58, P = 0.154; ORR: RR = 0.68, 95% CI: 0.54–0.85, P = 0.001).

Conclusions

TMB could predict the enhanced survival benefit of NSCLC patients treated with ICIs; however the role of bTMB is limited at this stage. For NSCLC patients with high TMB, ICIc may be a better option than chemotherapy.

The Prognostic Value of ctDNA and bTMB on Immune Checkpoint Inhibitors in Human Cancer

Background

Circulating tumor DNA (ctDNA) levels and blood tumor mutation burden (bTMB) have a significant impact on the prognosis of tumor patients. However, their prognostic role in immune checkpoint inhibitors (ICIs) in cancer patients is still unclear.

Methods

We used the Review Manager software (version 5.3) to perform a meta-analysis based on the published literature to explore the prognostic value of ctDNA and bTMB in patients receiving immunotherapy. We extracted the hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS) for each included study and their respective 95% confidence intervals (CIs) and p-values for analysis.

Results

Thirteen studies were included in the meta-analysis. Higher ctDNA levels were significantly associated with shorter OS (HR = 3.35, 95%CI = 2.49–4.51, p < 0.00001) and PFS (HR = 3.28, 95%CI = 2.47–4.35, p < 0.00001). The results of ctDNA subgroup analysis showed that high posttreatment ctDNA levels significantly correlated with shorter OS in cancer patients receiving ICIs (HR = 5.09, 95%CI = 1.43–18.07, p = 0.01). Moreover, patients with ctDNA clearance had better OS (HR = 4.94, 95%CI = 2.96–8.26, p < 0.00001). Patients with high posttreatment ctDNA levels had shorter PFS (HR = 3.00, 95%CI = 2.02–4.46, p < 0.00001) and those with ctDNA clearance had longer PFS (HR = 4.61, 95%CI = 2.78–7.65, p < 0.00001). However, there was no statistically significant difference in the OS benefits between a high and a low bTMB after ICI therapy (HR = 0.68, 95%CI = 0.33–1.37, p = 0.28).

Conclusions

The host immune system and tumor burden together determine whether cancer patients can benefit from ICI therapy. Our systematic review and meta-analysis revealed for the first time that the levels of pretreatment and posttreatment ctDNA and the clearance of ctDNA can independently be used as prognostic factors for antitumor immunotherapy, while bTMB cannot. In conclusion, ctDNA levels have great potential as an assistant tool for radiological assessments to make clinical therapeutic decisions. The prognostic utility of bTMB still requires further exploration.

Analyzing the characteristics of immune cell infiltration in lung adenocarcinoma via bioinformatics to predict the effect of immunotherapy

Recent studies have shown that tumor immune cell infiltration (ICI) is associated with immunotherapy sensitivity and the prognosis of lung adenocarcinoma (LUAD). However, the immunoinfiltrative landscape of LUAD has not been elucidated. We propose two computational algorithms to unravel the ICI landscape to evaluate the efficacy of immunotherapy in LUAD patients. The raw data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed. After merging these datasets and removing the batch differences, we used the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm to obtain the immune cell content of all the samples. The unsupervised consistency clustering algorithm was used to analyze the ICI subtypes, and three subgroups were obtained. In addition, the unsupervised consistency clustering algorithm was used to analyze the differentially expressed genes (DEGs) of the ICI subtypes and obtain three ICI gene clusters. Finally, the ICI score was determined by using principal component analysis (PCA) for the gene signature. The ICI score of LUAD patients ranged from - 32.26 to 12.89 and represents the prognosis and the response to immunotherapy. High ICI scores were characterized by the T cell receptor signaling pathway, B cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity, suggesting that some immune cells were activated and had increased activity, which may be the cause of the better prognosis for patients with high ICI scores. Additionally, patients with higher ICI scores showed a significant immune therapeutic advantage and clinical benefit. This study shows that the ICI score may be a potent prognostic biomarker and predictor of therapy with immune checkpoint inhibitors.