scholarly journals Bioinformatic Analysis Revealing Mitotic Spindle Assembly regulated NDC80 and MAD2L1 as Prognostic Biomarkers in Non-Small Cell Lung Cancer Development

2020 ◽  
Author(s):  
Rong Wei ◽  
Ziyue Wang ◽  
Yaping Zhang ◽  
Bin Wang ◽  
Ningning Shen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Small Cell ◽  
Prognostic Indicators ◽  
Pathological Features ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Key Genes

Abstract Background Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. Results Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed. Conclusions Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.

scholarly journals Bioinformatic Analysis Revealing Mitotic Spindle Assembly regulated NDC80 and MAD2L1 as Prognostic Biomarkers in Non-Small Cell Lung Cancer Development

2020 ◽  
Author(s):  
Rong Wei ◽  
Ziyue Wang ◽  
Yaping Zhang ◽  
Bin Wang ◽  
Ningning Shen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Small Cell ◽  
Prognostic Indicators ◽  
Pathological Features ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Key Genes

Abstract Background Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. Results Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed. Conclusions Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.

scholarly journals Bioinformatic Analysis Revealing Mitotic Spindle Assembly regulated NDC80 and MAD2L1 as Prognostic Biomarkers in Non-Small Cell Lung Cancer Development

2020 ◽  
Author(s):  
Rong Wei ◽  
Ziyue Wang ◽  
Yaping Zhang ◽  
Bin Wang ◽  
Ningning Shen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Small Cell ◽  
Prognostic Indicators ◽  
Pathological Features ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Key Genes

Abstract Background Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data.Results Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed.Conclusions Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.

Correlation between anemia before treatment with survival in patients with advanced non-small cell lung cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 18211-18211
Author(s):  
S. R. Bella ◽  
M. E. Richardet ◽  
P. Gomez Storniolo ◽  
P. Celiz ◽  
A. Lingua ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Hemoglobin Level ◽  
Small Cell Lung ◽  
Cox Regression Analysis

18211 Background: Prognostic factors identified in advanced non small cell lung cancer are: age, gender, PS, h. SWOG univariable analysis in patients with chemotheraphy; confirmed these factors and show a relationship between the hemoglobin level and the overall survival; in addition the metastasic site number and cisplatin- based chemotheraphy (7). To analyse and compare the hemoglobin level before cisplatin- based chemotheraphy with survival in patients with advanced non- small cell lung cancer. Methods: Retrospective study conducted at the IONC of the 179 clinical record were analized, over a 5 year period. The collected data were: age, gender, PS, histologic type, stage, chemotheraphy cycles number, smooke history, number and metastasic site. We analyzed median and overal survival using Kaplan Meier, and the anemia as a prognostic implication factor with univariable and multivariable Cox regression analysis. Istologic type and TNM (1–6). Results: The mean age was 59 (40–79); 146 (81.5%) male and 33 (18.5%) women; histological types found were squamous cell carcinomas in 66 (37%), and adenocarcinoma in 113 (63%); stage IIIB in 61 (34%) and IV in 118 (66%). 147 (82%) were smokers and 32 (18%) were never smokers. All the patients had PS 0–1. Median overall survival time was 11.53 months and 13.88 months in the haemoglobin level < or > 11 gr/ 100 ml, respectively. (p=0.3). In univariable Cox regression analysis, smoking rates and chemotheraphy cycles number were predictors of survival (p=0.05 y p=0.018, respectively). Hemoglobine (p=0.55). In multivariable Cox regression analysis, only the number of cycles was predictor of survival (p=0.026). Hemoglobine (p=0.34). Conclusions: In our experience, a greater survival tendency was observed in patients with advanced non- small cell lung cancer who presented levels of Hemoglobine greater than 11 gr/dl, previous to cisplatin- based chemotherapy without statistical significance. [Table: see text]

scholarly journals The Baseline Serum Uric Acid as an Indicator of Chemotherapy-Related Adverse Reaction and Mortality in Aged Males with Stage IIIB or IV Non-Small Cell Lung Cancer

2021 ◽  
Author(s):  
Xiaoyan Chen ◽  
Lisha Hou ◽  
Jianqun Li ◽  
Yanjiao Shen ◽  
Fucha Tan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bone Marrow ◽  
Uric Acid ◽  
Regression Analysis ◽  
Cox Regression ◽  
Small Cell ◽  
Bone Marrow Suppression ◽  
Stage Iiib ◽  
Small Cell Lung ◽  
Cox Regression Analysis

Abstract Objective: To evaluate the accuracy of baselineserum uric acid(BSUA) in estimating adverse effects (AE) and all-cause mortality (ACM) in older males with stage IIIB or IV non-small cell lung cancer (NSCLC) diagnosis.Study design:This is a single-center retrospective examination, conducted at the West China Hospital, Sichuan University in Chengdu, Sichuan Province, China, between the duration of January 2010 and December 2017.Primary outcome and measures:: All patients data was obtained based on medical reports and mortality information was gathered via telephone interviews. BUSA was assessed prior to chemotherapy. Additionally, the end points of this study included chemotherapy-mediated AE and ACM. Binarylogistic regression analysis was used to explore the correlation between BSUA and AE. Lastly, Cox regression analysis was utilized to examine theimpactof BSUA on ACM.Results: 317 male patients with NSCLC were eligible for this study. Within this population, 18.3% had stage IIIB and 81.7% had stage IV NSCLC. Moreover, 81.39% suffered from adenocarcinoma lung cancer (ACLC), whereas 18.61% suffered from squamous cell carcinoma lung cancer (SCCLC). As of March 1, 2019, 257 (81.07%) patients expired. Following the initial chemotherapeutic course, short-term AE like bone marrow suppression, all infection, liver dysfunction, and digestive reactions, wereobserved in 13.25%, 7.26%, 5.36%, and 4.1% of cases, respectively. Upon normalizing with confounding factors, the adjustedlogistic regression model demonstrated thatthe moderate BSUA was independently linked to a lower risk of bone marrow suppression (OR=0.407,95% CI:0.178-0.931; p=0.033).Moreover, based on the Cox regression analysis, moderate BSUAwas also independently correlated with a low mortality risk (HR=0.705,95% CI:0.518-0.959; p=0.026).Conclusion：In males patients withstage IIIB or IV NSCLC, BSUA is intimately linked to chemotherapy-driven AE and ACM.

scholarly journals The Baseline Serum Uric Acid as an Indicator of Chemotherapy-related Adverse Reaction and Mortality in Aged Males with Stage IIIB or IV Non-small Cell Lung Cancer

2021 ◽  
Author(s):  
Xiaoyan Chen ◽  
Lisha Hou ◽  
Jianqun Li ◽  
Yanjiao Shen ◽  
Birong Dong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bone Marrow ◽  
Regression Analysis ◽  
Cox Regression ◽  
Small Cell ◽  
Bone Marrow Suppression ◽  
Stage Iiib ◽  
Small Cell Lung ◽  
Baseline Serum ◽  
Cox Regression Analysis

Abstract Objective: To evaluate the accuracy of baseline serum uric acid (BSUA) in estimating adverse effects (AE) and all-cause mortality (ACM) in older males with stage IIIB or IV non-small cell lung cancer (NSCLC) diagnosis.Methods: All patients data was obtained based on medical reports and mortality information was gathered via telephone interviews. BUSA was assessed prior to chemotherapy. Additionally, the end points of this study included chemotherapy-mediated AE and ACM. Binary logistic regression analysis was used to explore the correlation between BSUA and AE. Lastly, Cox regression analysis was utilized to examine the impact of BSUA on ACM.Results: 317 male patients with NSCLC were eligible for this study. Within this population, 18.3% had stage IIIB and 81.7% had stage IV NSCLC. Moreover, 81.39% suffered from adenocarcinoma lung cancer (ACLC), whereas 18.61% suffered from squamous cell carcinoma lung cancer (SCCLC). As of March 1, 2019, 257 (81.07%) patients expired. Following the initial chemotherapeutic course, short-term AE like bone marrow suppression, all infection, liver dysfunction, and digestive reactions, were observed in 13.25%, 7.26%, 5.36%, and 4.1% of cases, respectively. Upon normalizing with confounding factors, the adjusted logistic regression model demonstrated that the moderate BSUA was independently linked to a lower risk of bone marrow suppression (OR=0.407,95% CI:0.178-0.931; p=0.033). Moreover, based on the Cox regression analysis, moderate BSUA was also independently correlated with a low mortality risk (HR=0.705, 95% CI:0.518-0.959; p=0.026).Conclusion：In males patients with stage IIIB or IV NSCLC, BSUA is intimately linked to chemotherapy-driven AE and ACM.

scholarly journals Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Qing Ma ◽  
Kai Geng ◽  
Ping Xiao ◽  
Lili Zeng
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Nsclc Patients

Background. Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases. Methods. The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature. Results. WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT. Conclusion. We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.

scholarly journals Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chenlu Li ◽  
Jingjing Pan ◽  
Jing Luo ◽  
Xupeng Chen
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Risk Scores ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Nsclc Patients

Abstract Background Non-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of these patients. Methods Gene expression profiles of 1026 NSCLC patients were collected from The Cancer Genome Atlas (TCGA) datasets with their corresponding clinical and somatic mutation data. Based on immune infiltration scores, molecular clustering classification was performed to identify immune subtypes in NSCLC. After the functional enrichment analysis of subtypes, hub genes were further screened using univariate Cox, Lasso, and multivariate Cox regression analysis, and the risk score was defined to construct the prognostic model. Other microarray data and corresponding clinical information of 603 NSCLC patients from the GEO datasets were applied to conduct random forest models for the prognosis of NSCLC with 100 runs of cross-validation. Finally, external datasets with immunotherapy and chemotherapy were further applied to explore the significance of risk-scores in clinical immunotherapy response for NSCLC patients. Results Compared with Subtype-B, the Subtype-A, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration scores and up-regulation of immunotherapy markers. In addition, we found and validated an eleven -gene signatures for better application of distinguishing high- and low-risk NSCLC patients and predict patients’ prognosis and therapeutical response to immunotherapy. Furthermore, combined with other clinical characteristics based on multivariate Cox regression analysis, we successfully constructed and validated a nomogram to effectively predict the survival rate of NSCLC patients. External immunotherapy and chemotherapy cohorts validated the patients with higher risk-scores exhibited significant therapeutic response and clinical benefits. Conclusion These results demonstrated the immunological and prognostic heterogeneity within NSCLC and provided a new clinical application in predicting the prognosis and benefits of immunotherapy for the disease.

Prognostic role of pretreatment lung immune prognostic index in extensive-stage small-cell lung cancer treated with platinum plus etoposide chemotherapy

2021 ◽  
pp. 1-9
Author(s):  
Weixiang Qi ◽  
Shengguang Zhao ◽  
Jiayi Chen
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Prognostic Index ◽  
Small Cell ◽  
Small Cell Lung ◽  
Prognostic Role ◽  
Cox Regression Analysis ◽  
Extensive Stage

BACKGROUND: To investigate the prognostic role of lung immune prognostic index LIPI in extensive-stage small-cell lung cancer (ES-SCLC) patients treated with platinum plus etoposide chemotherapy. METHODS: Data were obtained from two randomized controlled trials (NCT00119613 and NCT00363415). Overall survival (OS) and progression-free survival (PFS) was assessed according to LIPI score through Kaplan-Meier analysis. Univariate and multivariate Cox-regression analysis were performed to investigate predictors for OS and PFS. RESULTS: A total of 911 patients with ES-SCLC treated with platinum plus etoposide chemotherapy (CT) were included for analysis. The median age at diagnosis was 62 years, and 760 (83.4%) had performance status of 1 or less. 1-year OS for ES-SCLC with poor, intermediate, and good LIPI was 20%, 30% and 31%, respectively, and 1-year PFS was 7%, 15% and 21%, respectively. Cox-regression analysis showed that the PFS and OS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores (HR 1.81, 95% CI: 1.38–2.36; p< 0.001 and HR 1.35, 95% CI: 1.07–1.72, p= 0.012), while no significant difference was observed between intermediate and poor LIPI groups in terms of OS (HR 1.01, 95% CI: 0.82–1.23, p= 0.82), but not for PFS (HR 1.27, 95% CI: 1.00–1.61, p= 0.048). In addition, LIPI score was significantly associated with disease control rate and objective response rate (both p< 0.0001). CONCLUSION: Prognosis of patients with pretreatment LIPI score of 2 is poorer than those with LIPI score of 0–1 among ES-SCLC who received first-line platinum plus etoposide chemotherapy; Further studies are still recommended to confirm our findings in prospective studies.

Efficacy and toxicity hypofractionated radiotherapy for centrally located non-small cell lung cancer

2021 ◽  
pp. 1-4
Author(s):  
Tanzeel Janjua ◽  
Fei Sun ◽  
Katy Clarke ◽  
Pete Dickinson ◽  
Kevin Franks ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Early Stage ◽  
Performance Status ◽  
Small Cell ◽  
Small Cell Lung ◽  
Early Stage Lung Cancer ◽  
Cox Regression Analysis

Abstract Aim: Centrally located early-stage non-small cell lung cancer in patients who are unfit for surgery are treated with fractionated radiotherapy. We present the outcomes of a moderately hypofractionated accelerated dose regimen of 50 Gy in 15 fractions from a single centre in the UK. Materials and methods: Electronic case notes and radiotherapy records of lung cancer patients treated between January 2014 and December 2016 were retrospectively reviewed. Adult Comorbidity Evaluation-27 score was used to evaluate comorbidities. Mean lung doses and percentage of lung receiving more than 20 Gy were calculated for all patients. Survival outcomes were estimated using Kaplan–Meier curves. Results: Fifty-three patients were included in the study; the median follow-up was 20.2 months. 87% of patients had stage I disease. There was no 30-day post-treatment mortality. Ninety-day mortality rate after radiotherapy was 3.8%. Grade 2 pneumonitis was seen in five patients while no grade 3 or 4 pneumonitis was observed. The median progression-free survival (PFS) and overall survival (OS) were 18.5 months and 28.2 months, respectively. The estimated 1 and 2 years PFS were 62.3% and 41.3%, respectively, and OS were 77.4% and 56.6%, respectively. Worsening performance status was associated with worse survival on cox regression analysis. Disease relapsed in 36% of patients. 7.5% of patients with relapsed disease had infield recurrence. Findings: 50 Gy in 15 fractions radiotherapy for central early-stage lung cancer is a feasible choice that requires further randomised trials.

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