scholarly journals Hypoxic-immune Model Based on Lung Squamous Cell Carcinoma Reveals the Effects of Inflammation and Hypoxia on Drug Resistance, CD8 Cell Depletion and Prognosis

2021 ◽  
Author(s):  
Kang Sun ◽  
Zhiqiang Zhang ◽  
Dongqin Wang ◽  
Hongyu Ma ◽  
Chaoqun Lian ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Cell Depletion ◽  
Personalized Treatment

Abstract Background: Lung squamous cell carcinoma (LUSC) is a malignant tumor with high mortality and poor prognosis. More evidence shows that hypoxia and the immune environment play an essential role in cancer progression, but the specific impact on lung squamous cell carcinoma is unclear. This study mainly establishes immune and hypoxia risk models to predict the prognosis of patients and formulates personalized treatment plans for patients according to the specific conditions of hypoxia regulation and immune invasion in high-risk groups. Results: Based on the combined use of multiple data, 380 hypoxia and immune co-related genes (HMGs) were obtained， to establish the risk model of immune and hypoxia. Through the use of comprehensive analysis methods, the model has a high predictive value. The survival rate of the high-risk group is low, and the CD8-T cell depletion factor is widely distributed in high-risk groups. It has a large number of neutrophils and low CD8 cells. In addition, hypoxia, inflammation, and drug resistance-related pathways are also abundant in high-risk groups. We also found that high-risk patients were generally resistant to chemotherapeutic drugs. Finally, we constructed a competing endogenous RNA (CeRNA) network closely related to risk genes, including 9 mRNAs, 10 MicroRNAs (miRNAs), and 16 long non-coding RNAs (lncRNAs). Conclusions:This study specifically analyzed the effects of hypoxia regulation and immune Infiltration on the prognosis of patients. It provided a new idea for patients to improve the prognosis and personalized treatment.

Prognostic significance of eight immune-related genes on survival in patients with lung squamous cell carcinoma

2021 ◽  
Vol 15 (4) ◽  
pp. 295-306
Author(s):  
Hansheng Wu ◽  
Shujie Huang ◽  
Weitao Zhuang ◽  
Guibin Qiao
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Related Gene ◽  
Immune Related Gene ◽  
Immune Related Genes

Aim: To build a valid prognostic model based on immune-related genes for lung squamous cell carcinoma (LUSC). Materials & methods: Differential expression of immune-related genes between LUSC and normal specimens from TCGA dataset and underlying molecular mechanisms were systematically analyzed. Constructing and validating the high-risk and low-risk groups for LUSC survival. Results: The immune-related gene-based prognostic index (IRGPI) could predict the overall survival in patients with different clinicopathological characteristics. Functional enrichment analysis of differential expression of immune-related gene signature indicated distinctive molecular pathways between high-risk and low-risk groups. Conclusion: Analysis of IRGs in LUSC enable us to stratify patients into distinct risk groups, which may help to screen LUSC patients at risk and decision making on follow-up therapeutic intervention.

scholarly journals Potential Biomarkers for Predicting the Overall Survival of Lung squamous cell carcinoma: A analysis of Ferroptosis-Related lncRNAs

2021 ◽  
Author(s):  
zixuan Wu ◽  
Xuyan Huang ◽  
Min-jie Cai ◽  
Peidong Huang ◽  
Zunhui Guan
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Abstract Background In 502 Lung squamous cell carcinoma (LUSC) samples from The Cancer Genome Atlas (TCGA) datasets, the predictive significance of ferroptosis-related long non-coding RNAs (lncRNAs) was investigated. In LUSC, we meant to express how ferroptosis-associated lncRNAs interact with immune cell infiltration. Methods Gene expression enrichment was investigated using gene set enrichment analysis in the Kyoto Encyclopedia of Genes and Genomes. The prognostic model was constructed using Lasso regression. To better understand immune cell infiltration in different risk groups and its relationship to clinical outcome, researchers analyzed by modifications in the tumor microenvironment (TME) and immunological association. The expression of lncRNA was intimately connected to that of ferroptosis, according to co-expression analyses. Ferroptosis-related lncRNAs were shown to be partially overexpressed in high-risk patients in the absence of additional clinical signs, suggesting that they may be incorporated into a prediction model to predict LUSC prognosis. GSEA revealed the immunological and tumor-related pathways in the low-risk group. Results According to TCGA, CCR and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of C10orf55, AC016924.1, AL161431.1, LUCAT1, AC104248.1, and MIR3945HG were likewise different in the two risk groups. Conclusion LncRNAs linked to ferroptosis are connected to the occurrence and development of LUSC. With the use of matching prognostic models, the prognosis of LUSC patients can be predicted. In LUSC, ferroptosis-related lncRNAs and immune cell infiltration in the TME might be novel therapeutic targets that should be investigated further.

scholarly journals Comprehensive profiling of genomic and transcriptomic differences between risk groups of lung adenocarcinoma and lung squamous cell carcinoma

2021 ◽  
Author(s):  
Talip Zengin ◽  
Tuğba Önal-Süzek
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cox Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Low Risk

AbstractLung cancer is the second frequently diagnosed cancer type and responsible for the highest number of cancer deaths worldwide. Lung adenocarcinoma and lung squamous cell carcinoma are subtypes of non-small cell lung cancer which has the highest frequency of lung cancer cases. We aimed to analyze genomic and transcriptomic variations including simple nucleotide variations (SNVs), copy number variations (CNVs) and differential expressed genes (DEGs) in order to find key genes and pathways for diagnostic and prognostic prediction for lung adenocarcinoma and lung squamous cell carcinoma. We performed univariate cox model and then lasso regularized cox model with leave-one-out cross-validation using TCGA gene expression data in tumor samples. We generated a 35-gene signature and a 33-gene signature for prognostic risk prediction based on the overall survival time of the patients with LUAD and LUSC, respectively. When we clustered patients into high-risk and low-risk groups, the survival analysis showed highly significant results with high prediction power for both training and test datasets. Then we characterized the differences including significant SNVs, CNVs, DEGs, active subnetworks, and the pathways. We described the results for the risk groups and cancer subtypes separately to identify specific genomic alterations between both high-risk groups and cancer subtypes. Both LUAD and LUSC high-risk groups have more down-regulated immune pathways and upregulated metabolic pathways. On the other hand, low-risk groups have both upregulated and downregulated genes on cancer-related pathways. Both LUAD and LUSC have important gene alterations such as CDKN2A and CDKN2B deletions with different frequencies. SOX2 amplification occurs in LUSC and PSMD4 amplification in LUAD. EGFR and KRAS mutations are mutually exclusive in LUAD samples. EGFR, MGA, SMARCA4, ATM, RBM10, and KDM5C genes are mutated only in LUAD but not in LUSC. CDKN2A, PTEN, and HRAS genes are mutated only in LUSC samples. Low-risk groups of both LUAD and LUSC, tend to have a higher number of SNVs, CNVs, and DEGs. The signature genes and altered genes have the potential to be used as diagnostic and prognostic biomarkers for personalized oncology.

scholarly journals Development and validation of an individualized immune prognostic model in stage I–III lung squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Stage I ◽  
Tissue Samples ◽  
Mutation Burden

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.

A Four-gene Autophagy-related Prognostic Signature and Its Association With Immune Landscape in Lung Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Lumeng Luo ◽  
Minghe Lv ◽  
Xuan Li ◽  
Tiankui Qiao ◽  
Kuaile Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Immune Suppression ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk

Abstract Background: Recent advances in immune checkpoint inhibitors (ICIs) have dramatically changed the therapeutic strategy against lung squamous cell carcinoma (LUSC). In the era of immunotherapy, effective biomarkers to better predict outcomes and inform treatment decisions for patients diagnosed with LUSC are urgently needed. We hypothesized that immune contexture of LUSC is potentially dictated by tumor intrinsic events, such as autophagy. Thus, we attempted to construct an autophagy-related risk signature and examine its prediction value for immune phenotype in LUSC.Method: The expression profile of LUSC was obtained from the cancer genome atlas (TCGA) database and the profile of autophagy-related genes (ARGs) was extracted. The survival‑related ARGs (sARGs) was screened out through survival analyses. Random forest was performed to select the sARGs and construct a prognostic risk signature based on these sARGs. The signature was further validated by receiver operating characteristic (ROC) analysis and Cox regression. GEO dataset was used as an independent testing dataset. Patients were divided into high-risk and low-risk group based on the risk score. Then, gene set enrichment analysis (GSEA) was conducted between the two groups. The Single-Sample GSEA (ssGSEA) was introduced to quantify the relative infiltration of immune cells. The correlations between risk score and several main immune checkpoints were examined. And the ESTIMATE algorithm was used to calculate the estimate/immune/stromal scores of the LUSC. Results: Four ARGs (CFLAR, RGS19, PINK1 and CTSD) with the most significant prognostic values were enrolled to construct the risk signature. Patients in high-risk group had better prognosis than the low-risk group (P < 0.0001 in TCGA; P < 0.01 in GEO) and considered as an independent prognosis factor. We also found that high-risk group indicated an immune-suppression status and had higher levels of infiltrating regulatory T cells and macrophages, which are correlated with worse outcome. Besides, risk score showed a significantly positive correlation with the expression of PD-1 and CTLA4, as well as estimate score and immune score.Conclusion: This study established a novel autophagy-related four-gene prognostic risk signature, and the autophagy-related scores are associated with immune landscape of LUSC, with higher score indicating a stronger immune-suppression status.

scholarly journals Development and Validation of an E2F-Related Gene Signature to Predict Prognosis of Patients With Lung Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Cailian Wang ◽  
Xuyu Gu ◽  
Xiuxiu Zhang ◽  
Min Zhou ◽  
Yan Chen
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Decision Tree ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Related Gene ◽  
Risk Patients

BackgroundLung squamous cell carcinoma (LUSC) generally correlates with poor clinical prognoses due to the lack of available prognostic biomarkers. This study is designed to identify a potential biomarker significant for the prognosis and treatment of LUSC, so as to provide a scientific basis for clinical treatment decisions.MethodsGenomic changes in LUSC samples before and after radiation were firstly discussed to identify E2 factor (E2F) pathway of prognostic significance. A series of bioinformatics analyses and statistical methods were combined to construct a robust E2F-related prognostic gene signature. Furthermore, a decision tree and a nomogram were established according to the gene signature and multiple clinicopathological characteristics to improve risk stratification and quantify risk assessment for individual patients.ResultsIn our investigated cohorts, the E2F-related gene signature we identified was capable of predicting clinical outcomes and therapeutic responses in LUSC patients, besides, discriminative to identify high-risk patients. Survival analysis suggested that the gene signature was independently prognostic for adverse overall survival of LUSC patients. The decision tree identified the strong discriminative performance of the gene signature in risk stractification for overall survival while the nomogram demonstrated a high accuracy.ConclusionThe E2F-related gene signature may help distinguish high-risk patients so as to formulate personalized treatment strategy in LUSC patients.

scholarly journals Ferroptosis-related gene signature predicts the prognosis in Oral squamous cell carcinoma patients

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hongyu Li ◽  
Xiliu Zhang ◽  
Chen Yi ◽  
Yi He ◽  
Xun Chen ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Status ◽  
Risk Group ◽  
Risk Groups ◽  
Gene Signature ◽  
High Risk Group

Abstract Background The prognosis of oral squamous cell carcinoma (OSCC) patients is difficult to predict or describe due to its high-level heterogeneity and complex aetiologic factors. Ferroptosis is a novel form of iron-dependent cell death that is closely related to tumour growth and progression. This study aims to clarify the predictive value of ferroptosis-related genes (FRGs) on the overall survival(OS) of OSCC patients. Methods The mRNA expression profile of FRGs and clinical information of patients with OSCC were collected from the TCGA database. Candidate differentially expressed ferroptosis-related genes (DE-FRGs) were identified by analysing differences between OSCC and adjacent normal tissues. A gene signature of prognosis-related DE-FRGs was established by univariate Cox analysis and LASSO analysis in the training set. Patients were then divided into high- and low-risk groups according to the cut-off value of risk scores, A nomogram was constructed to quantify the contributions of gene signature and clinical parameters to OS. Then several bioinformatics analyses were used to verify the reliability and accuracy of the model in the validation set. Finally, single-sample gene set enrichment analysis (ssGSEA) was also performed to reveal the underlying differences in immune status between different risk groups. Results A prognostic model was constructed based on 10 ferroptosis-related genes. Patients in high-risk group had a significantly worse OS (p < 0.001). The gene signature was verified as an independent predictor for the OS of OSCC patients (HR > 1, p < 0.001). The receiver operating characteristic curve displayed the favour predictive performance of the risk model. The prediction nomogram successfully quantified each indicator’s contribution to survival and the concordance index and calibration plots showed its superior predictive capacity. Finally, ssGSEA preliminarily indicated that the poor prognosis in the high-risk group might result from the dysregulation of immune status. Conclusion This study established a 10-ferroptosis-releated gene signature and nomogram that can be used to predict the prognosis of OSCC patients, which provides new insight for future anticancer therapies based on potential FRG targets.

Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma

2020 ◽  
pp. 1-11
Author(s):  
Nan Lee ◽  
Xuelian Xia ◽  
Hui Meng ◽  
Weiliang Zhu ◽  
Xiankai Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk ◽  
Risk Patients

BACKGROUND: DNA methylation plays a vital role in modulating genomic function and warrants evaluation as a biomarker for the diagnosis and treatment of lung squamous cell carcinoma (LUSC). OBJECTIVE: In this study, we aimed to identify effective potential biomarkers for predicting prognosis and drug sensitivity in LUSC. METHODS: A univariate Cox proportional hazards regression analysis, a random survival forests-variable hunting (RSFVH) algorithm, and a multivariate Cox regression analysis were adopted to analyze the methylation profile of patients with LUSC included in public databases: The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO). RESULTS: A methylated region consisting of 3 sites (cg06675147, cg07064331, cg20429172) was selected. Patients were divided into a high-risk group and a low-risk group in the training dataset. High-risk patients had shorter overall survival (OS) (hazard ratio [HR]: 2.72, 95% confidence interval [CI]: 1.82–4.07, P< 0.001) compared with low-risk patients. The accuracy of the prognostic signature was validated in the test and validation cohorts (TCGA, n= 94; GSE56044, n= 23). Gene set variation analysis (GSVA) showed that activity in the cell cycle/mitotic, ERBB, and ERK/MAPK pathways was higher in the high-risk compared with the low-risk group, which may lead to differences in OS.Interestingly, we observed that patients in the high-risk group were more sensitive to gemcitabine and docetaxel than the low-risk group, which is consistent with results of the GSVA. CONCLUSION: We report novel methylation sites that could be used as powerful tools for predicting risk factors for poorer survival in patients with LUSC.

Evaluation of the in vitro Chemosensitivity and Correlation with Clinical Outcomes in Lung Cancer using the ATP-TCA

2018 ◽  
Vol 18 (1) ◽  
pp. 139-145 ◽  
Author(s):  
Zhiyao Chen ◽  
Shichao Zhang ◽  
Sheng Ma ◽  
Chang Li ◽  
Chun Xu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Drug Resistance ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Clinical Outcomes ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Lung Cancer Patients ◽  
In Vitro Chemosensitivity

Background and Objective: Multiple drug resistance (MDR) to chemotherapeutic agents often leads to a failure to respond to chemotherapy. We utilized an in vitro chemosensitivity test to identify sensitive and effective chemotherapeutic drugs and further elucidated the correlation between the in vivo chemosensitivity and clinical outcomes. Methods: Here, we evaluated the in vitro chemosensitivity and MDR of 120 lung cancer patients to eight singledrug chemotherapies and of 291 lung cancer patients to seven chemotherapy regimens using an ATP-based tumor chemosensitivity assay (ATP-TCA). Additionally, the chemosensitivity profiles of lung adenocarcinoma patients (284 cases) and lung squamous cell carcinoma patients (90 cases) to these single-drug and chemotherapy regimens were compared. Furthermore, the correlations between the chemosensitivity and clinical outcomes were investigated in 16 stage III squamous cell carcinoma patients. Results and Conclusion: PTX (51.7%), TXT (43.3%), GEM (12.5%), PTX+DDP (62.5%), TXT+L-OHP (54.3%) and VP-16+DDP (16.2%) had the highest in vitro chemosensitivity rates. Approximately 31.7% of patients developed resistance to all eight single-drug chemotherapies, and 25.8% of patients displayed resistance to all seven chemotherapy regimens. In addition, lung squamous cell carcinoma was significantly more sensitive to GEM and MTA+DDP than lung adenocarcinoma (P<0.05). Further analysis showed that patients with higher drug sensitivity tended to have longer disease-free survival (18 months vs. 8.5 months) than patients displaying drug resistance (P<0.05). These results suggest that the implementation of in vitro drug susceptibility testing before chemotherapy can effectively prevent the occurrence of primary drug resistance and inappropriate drug treatment.

scholarly journals Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of esophageal squamous cell carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mingdi Liu ◽  
Faping Li ◽  
Bin Liu ◽  
Yongping Jian ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment

Abstract Background As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC). Methods ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC. Results Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. Conclusions Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.

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