scholarly journals Identification of novel immunomodulators in lung squamous cell carcinoma based on transcriptomic data

2021 ◽  
Vol 19 (2) ◽  
pp. 1843-1860
Author(s):  
Xin Lin ◽  
◽  
Xingyuan Li ◽  
Binqiang Ma ◽  
Lihua Hang ◽  
...  

<abstract> <p>Cells in the tumor microenvironment are well known for their role in cancer development and prognosis. The processes of genetic changes and possible remodeling in the tumor microenvironment of lung squamous cell carcinoma, on the other hand, are mainly unclear. In this investigation, 1164 immunological differentially expressed genes (DEGs) were shown to have predictive significance. A prognostic model with high prediction accuracy was constructed using these genes and survival data. There were 1020 upregulated genes and 144 downregulated genes found, with 57 genes found to be important in the development of LUSC. We used least absolute shrinkage and selection operator (LASSO) regression analysis to determine the risk profiles of 9 genes based on the expression values of 57 prognosis-related genes. The AUCs of the developed prognostic model for predicting patient survival at 1, 3, and 5 years were 0.66, 0.61, and 0.63, respectively, based on the training data. For immune-correlation analysis in this survival model, we chose IGLC7, which was seen to predict patient survival with high accuracy. The effects on immune cells and synergistic effects with other immunomodulators were then investigated. We discovered that IGLC7 is involved in immune response and inflammatory activity using gene ontology analysis and genomic sequence variance analysis (GSVA), with a potential effect, especially on B cells and T cells. In conclusion, IGLC7 expression levels are related to the malignancy of LUSC based on the constructed prognostic model and can thus be a therapeutic target for patients with LUSC. Furthermore, IGLC7 may work in concert with other immune checkpoint members to regulate the immune microenvironment of LUSC. These discoveries might lead to a fresh understanding of the complicated interactions between cancer cells and the tumor microenvironment, particularly the population of immune cells, and a novel approach to future immunotherapeutic treatments for patients with LUSC.</p> </abstract>

2020 ◽  
Author(s):  
Xiao Chen ◽  
Rui Li ◽  
Yun-Hong Yin ◽  
Xiao Liu ◽  
Xi-Jia Zhou ◽  
...  

Abstract Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  

AbstractLung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I–III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I–III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I–III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Liyan Hou ◽  
Yingbo Li ◽  
Ying Wang ◽  
Dongqiang Xu ◽  
Hailing Cui ◽  
...  

In this study, we investigated the potential prognostic value of ubiquitin-conjugating enzyme E2D1 (UBE2D1) RNA expression in different histological subtypes of non-small-cell lung cancer (NSCLC). A retrospective study was performed by using molecular, clinicopathological, and survival data in the Cancer Genome Atlas (TCGA)—Lung Cancer. Results showed that both lung adenocarcinoma (LUAD) (N=514) and lung squamous cell carcinoma (LUSC) (N=502) tissues had significantly elevated UBE2D1 RNA expression compared to the normal tissues (p<0.001 and p=0.036, respectively). UBE2D1 RNA expression was significantly higher in LUAD than in LUSC tissues. Increased UBE2D1 RNA expression was independently associated with shorter OS (HR: 1.359, 95% CI: 1.031–1.791, p=0.029) and RFS (HR: 1.842, 95% CI: 1.353–2.508, p<0.001) in LUAD patients, but not in LUSC patients. DNA amplification was common in LUAD patients (88/551, 16.0%) and was associated with significantly upregulated UBE2D1 RNA expression. Based on these findings, we infer that UBE2D1 RNA expression might only serve as an independent prognostic indicator of unfavorable OS and RFS in LUAD, but not in LUSC.


2021 ◽  
Author(s):  
Katie E. Blise ◽  
Shamilene Sivagnanam ◽  
Grace L. Banik ◽  
Lisa M. Coussens ◽  
Jeremy Goecks

ABSTRACTRecent research has provided compelling evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors correlates with survival and response to therapy in numerous cancer types. Here, we report results of a quantitative single-cell spatial analysis of the TiME of primary and recurrent human head and neck squamous cell carcinoma (HNSCC) tumors, that builds upon our initial longitudinal study of these same HNSCCs that annotated immune complexity at near single cell resolution. Herein, we extended multiple spatial algorithms to quantify spatial landscapes of immune cells within TiMEs. Most notably, we report that spatial compartmentalization, rather than mixing, between neoplastic tumor cells and immune cells is associated with longer patient survival, as well as revealing mesenchymal spatial cellular neighborhoods and their association with improved patient outcomes. Results reported herein are concordant with studies in other tumor types, thus indicating that cellular heterogeneity within tumors trends with spatial TiME features, and are likely prognostic for patient survival.


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