scholarly journals Integrative Molecular Analyses of an Individual Transcription Factor-Based Genomic Model for Lung Cancer Prognosis

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Rong Yao ◽  
Leilei Zhou ◽  
Zhongying Guo ◽  
Dahong Zhang ◽  
Tiecheng Zhang
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Expression Profiling ◽  
Cox Regression ◽  
Biological Significance ◽  
Cancer Prognosis ◽  
Lung Cancer Patients ◽  
Downstream Targets ◽  
Genomic Model

Objective. Precision medicine with molecular profiles has revolutionized the management of lung cancer contributing to improved prognosis. Herein, we aimed to uncover the gene expression profiling of transcription factors (TFs) in lung cancer as well as to develop a TF-based genomic model. Methods. We retrospectively curated lung cancer patients from public databases. Through comparing mRNA expression profiling between lung cancer and normal specimens, specific TFs were determined. Thereafter, a TF genomic model was developed with univariate Cox regression and stepwise multivariable Cox analyses, which was verified through the GSE72094 dataset. Gene set enrichment analyses (GSEA) were presented. Downstream targets of TFs were predicted with ChEA, JASPAR, and MotifMap projects, and their biological significance was investigated through the clusterProfiler algorithm. Results. In the TCGA cohort, we proposed a TF-based genomic model, comprised of SATB2, HLF, and NPAS2. Lung cancer individuals were remarkably stratified into high- and low-risk groups. Survival analyses uncovered that high-risk populations presented unfavorable survival outcomes. ROCs confirmed the excellent predictive potency in patients’ prognosis. Additionally, this model was an independent prognostic indicator in accordance with multivariate analyses. The clinical implication of the model was well verified in an independent dataset. High risk score was in relation to carcinogenic pathways. Downstream targets were characterized by immune and carcinogenic activation. Conclusion. The proposed TF genomic model acts as a promising marker for estimation of lung cancer patients’ outcomes. Prospective research is required for testing the clinical utility of the model in individualized management of lung cancer.

scholarly journals Predicting brain metastasis in early stage non-small cell lung cancer patients by gene expression profiling

2020 ◽  
Vol 9 (3) ◽  
pp. 682-692
Author(s):  
Iris Kamer ◽  
Yael Steuerman ◽  
Inbal Daniel-Meshulam ◽  
Gili Perry ◽  
Shai Izraeli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Brain Metastasis ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Expression Profiling ◽  
Early Stage ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Patients

Protective effect of metformin in lung cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22063-e22063
Author(s):  
B. Gagnon ◽  
M. Roseman ◽  
G. Kasymjanova ◽  
N. MacDonald ◽  
H. Kreisman ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Human Cell Lines ◽  
Community Based ◽  
Cox Regression Analysis ◽  
Lung Cancer Patients ◽  
The Past ◽  
Jewish General Hospital

e22063 Background: Over the past decade, dozens of studies have shown that metformin not only decreases mortality in diabetics, it also significantly reduces CRP and reduces the risks of cancer in rodent and human cell lines. We report on the survival of lung cancer patients concomitantly exposed to metformin in our community-based program. Methods: 850 patients undergoing treatment from a prospectively collected pulmonary oncology database of the SMBD-Jewish General Hospital over an 8-year period were analyzed. Pilot observational study of survival was performed using Cox regression model. The factors that were included in the model were age, gender, stage, histology and metformin use. Results: 850 patients (F: M=375:475; mean age of 66) were diagnosed since 2000 and followed in pulmonary oncology outpatient clinic for NSCLC. 523 (62%) of those patients were diagnosed with adenocarcinoma; 488 (57%) were stage IIIB with pleural effusion/IV. 79(9%) patients were receiving treatment with metformin for their comorbid type 2 diabetes. The Cox regression analysis demonstrated that age, gender, stage and use of metformin were significant prognostic factors for survival. The use of metformin is associated with a 37% (HR 1.37; CI 1.01–1.84) (p=0.039) increase in survival. Conclusions: Thus, the result obtained from our model suggests that use of metformin may be associated with better survival of lung cancer patients. As this is a pilot study, we will consider alternative explanations. No significant financial relationships to disclose.

Overall survival in patients with lung cancer using a web-application-guided follow-up compared to standard modalities: Results of phase III randomized trial.

2016 ◽  
Vol 34 (18_suppl) ◽  
pp. LBA9006-LBA9006 ◽  
Author(s):  
Fabrice Denis ◽  
Claire Lethrosne ◽  
Nicolas Pourel ◽  
Olivier Molinier ◽  
Yoann Pointreau ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
High Risk ◽  
Supportive Care ◽  
Cancer Patients ◽  
Web Application ◽  
Phase Iii ◽  
P Value ◽  
Lung Cancer Patients

LBA9006 Background: We developed a web-application for an early detection of symptomatic relapse, complications and early supportive care in high-risk lung cancer patients between visits. A dynamical analysis of the weekly self-reported symptoms automatically triggered physician visit. Methods: We performed a national multi-institutional phase 3 prospective randomized study to compare web-application follow-up (experimental arm) for which patient’s self-scored symptoms that were weekly sent (between planned visits) to the oncologist and a clinical routine assessment with a CT-scan (every 3-6 months or at investigator’s discretion - standard arm). High risk lung cancer patients without progression and with a 0-2 performance status (PS) after an initial treatment were included. Maintenance chemotherapy or TKI therapy were allowed. In the experimental arm, an email alert was sent to the oncologist when some predefined clinical criteria were fulfilled: an imaging was then quickly prescribed. Early supportive cares were provided if adequate. The primary endpoint was to detect an improvement of 12% in 9 months survival in favor of the experimental arm (α = 5%, β = 20%, unilateral test). The boundary for declaring superiority with respect to overall survival at the pre-planned interim analysis was a p-value of less than 0.006. The PS at relapse, the quality of life (QOL) and cost-effectiveness were also investigated. Results: 121 patients were included in the intent-to-test survival analysis (90% were stage III/IV, median age: 65 y): 60 (61) in the experimental (standard) arms with equivalent baseline characteristics. Median follow-up was 9 months. Median overall survival in months was 19 (11.8), p=0.0014 (n  =  121; HR  =  0.33; 95 % CI, 0.16-0.67) and the PS at the first relapse was 0-1 for 81.5% (35.3%) of the patients (p<0.001) in the experimental (standard) arm. Conclusions: This trial shows a significant survival improvement using Web-application-guided follow-up that allowed better PS at relapse, earlier supportive care and reduction of routine imaging. QOL and cost analysis results will be presented during the meeting. Clinical trial information: NCT02361099.

Potentially malignant oral disorders and high-risk habits in liver cirrhosis and lung cancer patients

Oral Diseases ◽  
2014 ◽  
Vol 21 (3) ◽  
pp. 373-377 ◽  
Author(s):  
I Salarić ◽  
I Povrzanović ◽  
D Brajdić ◽  
I Lukšić ◽  
D Macan
Keyword(s):  
Lung Cancer ◽  
Liver Cirrhosis ◽  
High Risk ◽  
Cancer Patients ◽  
Lung Cancer Patients ◽  
Potentially Malignant

scholarly journals The Dual Effect of CD28 on The Prognosis of Lung Cancer Based On Nomograms: A Comprehensive Analysis of The Tumor Immune Microenvironment

2020 ◽  
Author(s):  
dantong sun ◽  
Lu Tian ◽  
Tiantian Bian ◽  
Han Zhao ◽  
Junyan Tao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Multivariate Analyses ◽  
Cancer Prognosis ◽  
Immune Microenvironment ◽  
Dual Effect ◽  
Internal Validation ◽  
Lung Cancer Patients ◽  
Tumor Immune Microenvironment

Abstract Background Lung cancer has ranked first in China in recent years, and TIME-related molecules may serve as biomarkers for the prognosis of lung cancer. Nomograms are widely used tools for the evaluation of prognosis in malignancies. We performed this study to construct nomograms based on TIME for predicting the prognosis of lung cancer. Methods Univariate and multivariate analyses were performed to estimate prognosis. TIME-related variables and basic clinical characteristics were included in the nomograms. Discrimination and calibration were used for the internal validation of the nomograms. Patients in our center and in the TCGA database were involved in the construction of the nomograms. Results Both LUAD and lung cancer patients with a higher expression of CD28 had a shorter DFS (P = 0.0011; P = 0.0001) but a longer OS (P = 0.0001; P = 0.0282). Nomograms for the DFS of young LUAD patients and the OS of LUAD and lung cancer patients were constructed. The established nomograms provide an easy way to estimate prognosis. Patients may obtain not only probabilities for disease progression and 1-year, 3-year or 5-year survival but also a precise and individualized follow-up regimen. Conclusion TIME-related variables are closely associated with the prognosis of lung cancer patients, especially young LUAD patients. CD28, which has a dual effect on lung cancer prognosis, may be a novel biomarker for not only the prognosis of lung cancer but also sensitivity to immunotherapy. Nomograms based on TIME may be a novel way to predict the prognosis of lung cancer.

scholarly journals Clinical Impact of Association Between Diabets and Lung Cancer

2019 ◽  
Vol 70 (4) ◽  
pp. 1149-1151 ◽  
Author(s):  
Laura Mazilu ◽  
Dana Lucia Stanculeanu ◽  
Andreea Daniela Gheorghe ◽  
Adrian Paul Suceveanu ◽  
Irinel Raluca Parepa ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Lung Cancer ◽  
Cancer Patients ◽  
Negative Impact ◽  
Cancer Prognosis ◽  
Lung Cancer Patients ◽  
High Prevalence ◽  
Cancer Outcome ◽  
The Impact

The main objective of this analysis is to evaluate the impact of lung cancer and diabetes association on cancer treatment and outcome of lung cancer patients. Lung cancer, as well as diabetes mellitus, are two diseases with very high prevalence. Lung cancer, despite the improvement in diagnosis and therapeutic methods, is still the 1st cause of cancer-related deaths. The influence of diabetes on cancer patients survival is well established among patients with hepatic, pancreatic or breast cancer. Diabetes implication on lung cancer outcome is not well known. Several studies reported a negative impact, whereas other studies reported a better prognosis for these patients. Our study took place in the Oncology Department of the Clinical Emergency Hospital of Constanta, Romania. 80 patients with diagnosis of non-small cell lung cancer were elected to participate in this study; 29 patients had also diabetes. Selected patients were divided in 2 groups, one group of lung cancer and diabetes, and one group without diabetes. Features of the patients among both groups were analyzed. Our study showed that preexisting diabetes is an unfavorable factor, and has influence on lung cancer prognosis, treatment adhesion and quality of life. To amend the outcome of patients with lung cancer, a better evaluation of patients� co-morbidities, including diabetes mellitus, is required.

Sign in / Sign up

Export Citation Format

Share Document