Identification of Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Li, Na; Wang, Jiahong; Zhan, Xianquan

doi:10.3389/fimmu.2021.752643

Cited by 23 publications

(23 citation statements)

References 57 publications

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“…Generally, the nomogram exerted a medium accuracy on predicting OS of LUSC, displaying a better overall net benefit than the T, N stating system for predicting 1-and 3-year OS rate. Although in terms of validity, this ATIRE-based nomogram did not display a superior performance compared to previously published gene-expression-based nomograms as shown by the Harrell's C-indexes, given an amount of gene-expression-based nomograms exerted Harrell's C-indexes ranging from 0.65-0.85 [44][45][46][47][48][49]. However, in terms of determination reliability, quantification of AITRE level is more stable and reliable than that of gene expression.…”

Section: Discussioncontrasting

confidence: 68%

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

Liu

Deng

et al. 2022

BMC Cancer

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Background Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival. Methods To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs’ effect on transcriptome expression were analyzed. Results Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways. Conclusions This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

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Section: Discussioncontrasting

confidence: 68%

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

Liu

Deng

et al. 2022

BMC Cancer

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“…Furthermore, we compared the performance of the present signature with those of the other previously reported gene signatures in LUSC. The RMS curve showed that the performance of the present signature was similar to that of the other four signatures ( Supplementary Figure S3C ) ( Huang et al, 2021 ; Li et al, 2021 ; Li et al, 2022 ; Zhai et al, 2022 ). These results suggest that the CSRG signature can serve as a candidate prognostic biomarker for survival in patients with stage I–III LUSC.…”

Section: Resultssupporting

confidence: 57%

Determination of a prediction model for therapeutic response and prognosis based on chemokine signaling-related genes in stage I–III lung squamous cell carcinoma

et al. 2022

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Background: The chemokine signaling pathway plays an essential role in the development, progression, and immune surveillance of lung squamous cell carcinoma (LUSC). Our study aimed to systematically analyze chemokine signaling-related genes (CSRGs) in LUSC patients with stage I–III disease and develop a prediction model to predict the prognosis and therapeutic response.Methods: A total of 610 LUSC patients with stage I–III disease from three independent cohorts were included in our study. Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses were used to develop a CSRG-related signature. GSVA and GSEA were performed to identify potential biological pathways. The ESTIMATE algorithm, ssGSEA method, and CIBERSORT analyses were applied to explore the correlation between the CSRG signature and the tumor immune microenvironment. The TCIA database and pRRophetic algorithm were utilized to predict responses to immunochemotherapy and targeted therapy.Results: A signature based on three CSRGs (CCL15, CXCL7, and VAV2) was developed in the TCGA training set and validated in the TCGA testing set and GEO external validation sets. A Kaplan–Meier survival analysis revealed that patients in the high-risk group had significantly shorter survival than those in the low-risk group. A nomogram combined with clinical parameters was established for clinical OS prediction. The calibration and DCA curves confirmed that the prognostic nomogram had good discrimination and accuracy. An immune cell landscape analysis demonstrated that immune score and immune-related functions were abundant in the high-risk group. Interestingly, the proportion of CD8 T-cells was higher in the low-risk group than in the high-risk group. Immunotherapy response prediction indicated that patients in the high-risk group had a better response to CTLA-4 inhibitors. We also found that patients in the low-risk group were more sensitive to first-line chemotherapeutic treatment and EGFR tyrosine kinase inhibitors. In addition, the expression of genes in the CSRG signature was validated by qRT‒PCR in clinical tumor specimens.Conclusion: In the present study, we developed a CSRG-related signature that could predict the prognosis and sensitivity to immunochemotherapy and targeted therapy in LUSC patients with stage I–III disease. Our study provides an insight into the multifaceted role of the chemokine signaling pathway in LUSC and may help clinicians implement optimal individualized treatment for patients.

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“…The most frequent histological subtype of lung cancer corresponds to LUAD, while the minority correspond to LUSC. Recent studies are shedding light into the numerous differences between them that would require the identification of biomarkers of response with discriminating values for each histology independently ( 47, 62, 63 ). Indeed, plasma FKN had positive predictive value only for LUAD treated with ICB in our discovery cohort.…”

Section: Discussionmentioning

confidence: 99%

Potent clinical predictive and systemic adjuvant therapeutic value of plasma fractalkine in PD-L1/PD-1 blockade immunotherapy for lung cancer

Bocanegra

Fernández

Ajona

et al. 2022

Preprint

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Recent studies highlight the importance of baseline functional immunity for efficacious immune checkpoint blockade therapies. Extensive systemic immune profiling was performed in a discovery cohort of 112 non-small cell lung cancer patients undergoing PD-L1/PD-1 blockade immunotherapy. Responders showed high baseline phenotypic diversity of myeloid cell types in peripheral blood, in which elevated activated monocytic cells and decreased granulocytic phenotypes were potent prognostic factors. A high-throughput profiling of soluble factors in plasma was carried out that identified fractalkine (FKN), a chemokine involved in adhesion and chemotactic attraction of immune cells, as a biomarker of myeloid cell diversity in human patients and in murine models, which was found significantly increased in objective responders. Secreted FKN inhibited adenocarcinoma and squamous cell carcinoma growth in vivo through a prominent contribution of systemic effector NK cells, enhanced tumor infiltration with immunostimulatory immune cells and inhibition of MDSCs within tumors. A synergy between FKN and PD-L1/PD-1 blockade immunotherapy was found in murine lung cancer models refractory to anti-PD-L1/anti-PD-1 treatment. Transcriptional data from human lung adenocarcinoma samples independently confirmed the data from the discovery cohort. Importantly, recombinant FKN and tumor expressed-FKN were efficacious in delaying tumor growth in vivo with significant abscopal effects, indicating a potential therapeutic use of FKN in combination with immunotherapies.

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Identification of Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Cited by 23 publications

References 57 publications

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

Determination of a prediction model for therapeutic response and prognosis based on chemokine signaling-related genes in stage I–III lung squamous cell carcinoma

Potent clinical predictive and systemic adjuvant therapeutic value of plasma fractalkine in PD-L1/PD-1 blockade immunotherapy for lung cancer

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