A P53-Deficiency Gene Signature Predicts Recurrence Risk of Patients with Early-Stage Lung Adenocarcinoma

Abstract We present a gene signature distinguishing invasive and indolent tumors among early-stage lung adenocarcinoma (esLUAD). An Invasiveness Score estimated using the gene signature was strongly associated with survival of esLUAD patients in multiple independent cohorts and with the invasiveness phenotype in lung cancer cell lines. Regulatory network analysis identified aurora kinase as one of master regulators of the gene signature and perturbation of aurora kinases in vitro and in vivo reduced tumor invasion. Our study suggests aurora kinases as a novel target for treating early-stage invasive lung adenocarcinoma.

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Integration of mRNA and microRNA profiles as prognostic and predictive markers in lung adenocarcinoma

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.7522 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. 7522-7522

Author(s):

J. H. Strickler ◽

W. Mostertz ◽

W. Kim ◽

K. Walters ◽

M. Stevenson ◽

...

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Cell Lines ◽

Cisplatin Resistance ◽

Early Stage ◽

Gene Signature ◽

Discovery Cohort ◽

Risk Of Recurrence ◽

Increased Risk

7522 Background: Lung adenocarcinoma (ADC) is a distinct biologic entity with unique gene amplifications (Weir B, Nature 2008). Yet, comprehensive transcriptomic analysis, including microRNAs, specific to lung ADC are lacking. Methods: Using mRNA expression data from a discovery cohort of 154 patients with histologically proven early stage (I and II) lung ADC, signatures of oncogenic pathway and tumor microenvironment status were applied and further organized by hierarchical clustering to develop a metagene model. Further, using in vitro assays in a large cohort of lung ADC cell lines (n = 42) with corresponding mRNA and microRNA data, novel microRNAs associated with a poor prognosis and their relationship to cisplatin resistance was elucidated. Results: In the discovery cohort of 154 patients with early stage disease, activation of oncogenic pathways associated with wound healing (angiogenesis), chromosomal instability, and STAT signaling were associated with an increased risk of recurrence (p<0.001). Utilizing the extremes of survival to identify cohorts of patients as high and low risk phenotypes, using bayesian regression, a 100 gene signature (‘metagene') that captured the diversity of signaling pathways unique to patients at increased risk of recurrence was identified and validated in an independent cohort (n = 364) of lung ADC samples with 78.3% accuracy. Kaplan Meier survival analysis and multivariate analysis further confirmed the independent prognostic value of the 100 gene signature (p= 0.007). Using in vitro cell proliferation assays, predicted high risk lung ADC cell lines were identified as being more resistant to cisplatin therapy than those predicted to be low risk (p=0.001). In a novel manner, we also identified several microRNAs (miR-215, miR-98, miR- 643, let-7b, miR-665, miR-629) associated with a high risk of recurrence and more importantly cisplatin resistance. Conclusions: mRNA and microRNA profiles reflect unique aspects of individual tumors and may characterize histology-specific tumor heterogeneity in lung ADC, providing an opportunity to better characterize the oncogenic process and refine therapeutic options. No significant financial relationships to disclose.

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Prognostic gene signatures for lung adenocarcinoma using digital multiplexed gene expression in formalin-fixed paraffin embedded tissue.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.e20050 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. e20050-e20050

Author(s):

Ping Wei ◽

Xiang Du

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Expression Analysis ◽

Gene Expression Analysis ◽

Early Stage ◽

Gene Signature ◽

Risk Scores ◽

Cancer Center ◽

Microarray Gene Expression ◽

Nsclc Patients

e20050 Background: The outcome after resection of non-small-cell lung cancer (NSCLC) patients are poor, even in the early stage, there still has 35-50% recurrence rates. Current staging methods are not inadequate for predicting the outcome of NSCLC patients. Methods: 396 lung adenocarcinoma specimens were obtained for this study, of whom 78 frozen specimens (corhort1) and 223 FFPE specimens (corhort2) were from Shanghai Cancer Center, Fudan University and 85 FFPE specimens (independent corhort) were from Shanghai Pulmonary Hospital. The RNA was extracted from corhort1 and used in the microarray gene expression analysis to derive prognostic associated genes. The digital multiplexed technology (Nanostring) was then used to determine the expression of these genes in FFPE-derived RNA from corhort2. For validation, we used the random patients from the independent corhort. Results: Through microarray assay, the top 18 survival and 19 metastasis associated gene were chosen to digital multiplexed gene expression analysis using FFPE-derived RNA from corhort2. Four genes that correlated with the survival were then identified by risk scores. Kaplan-Meier analysis showed that patients of high risk scores had longer OS and DFS compared with patients of low risk scores in the corhort2. The four-gene signature was an independent predictor of OS and DFS. We validated the four-gene model in the independent corhort. Conclusions: Our results suggest that the four gene signature is a new biomarker for the prognosis of patients with NSCLC, enabling more accurate prediction of prognosis.

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Reverse engineering a predictive signature characterized by proliferation, DNA damage, and immune escape from stage I lung adenocarcinoma recurrence

Acta Biochimica et Biophysica Sinica ◽

10.1093/abbs/gmaa036 ◽

2020 ◽

Vol 52 (6) ◽

pp. 638-653

Author(s):

Jiannan Yao ◽

Xinying Xue ◽

Dongfeng Qu ◽

C Benedikt Westphalen ◽

Yang Ge ◽

...

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Immune Escape ◽

Early Stage ◽

Gene Signature ◽

Response To Therapy ◽

Stage I ◽

Cox Regression Analysis ◽

Patients At Risk

Abstract Identifying early-stage cancer patients at risk for progression is a major goal of biomarker research. This report describes a novel 19-gene signature (19-GCS) that predicts stage I lung adenocarcinoma (LAC) recurrence and response to therapy and performs comparably in pancreatic adenocarcinoma (PAC), which shares LAC molecular traits. Kaplan–Meier, Cox regression, and cross-validation analyses were used to build the signature from training, test, and validation sets comprising 831 stage I LAC transcriptomes from multiple independent data sets. A statistical analysis was performed using the R language. Pathway and gene set enrichment were used to identify underlying mechanisms. 19-GCS strongly predicts overall survival and recurrence-free survival in stage I LAC (P=0.002 and P<0.001, respectively) and in stage I–II PAC (P<0.0001 and P<0.0005, respectively). A multivariate cox regression analysis demonstrated the independence of 19-GCS from significant clinical factors. Pathway analyses revealed that 19-GCS high-risk LAC and PAC tumors are characterized by increased proliferation, enhanced stemness, DNA repair deficiency, and compromised MHC class I and II antigen presentation along with decreased immune infiltration. Importantly, high-risk LAC patients do not appear to benefit from adjuvant cisplatin while PAC patients derive additional benefit from FOLFIRINOX compared with gemcitabine-based regimens. When validated prospectively, this proof-of-concept biomarker may contribute to tailoring treatment, recurrence reduction, and survival improvements in early-stage lung and pancreatic cancers.

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The prognostic value of a Methylome-based Malignancy Density Scoring System to predict recurrence risk in early-stage Lung Adenocarcinoma

Theranostics ◽

10.7150/thno.44229 ◽

2020 ◽

Vol 10 (17) ◽

pp. 7635-7644

Author(s):

Lu Yang ◽

Jing Zhang ◽

Guangjian Yang ◽

Haiyan Xu ◽

Jing Lin ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Scoring System ◽

Prognostic Value ◽

Early Stage ◽

Recurrence Risk

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Development and validation of a hypoxia-related gene signature to predict overall survival in early-stage lung adenocarcinoma patients

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835920937904 ◽

2020 ◽

Vol 12 ◽

pp. 175883592093790

Author(s):

Jing Sun ◽

Tianyu Zhao ◽

Di Zhao ◽

Xin Qi ◽

Xuanwen Bao ◽

...

Keyword(s):

Overall Survival ◽

Risk Factor ◽

Decision Tree ◽

Risk Stratification ◽

Lung Adenocarcinoma ◽

Early Stage ◽

Staging System ◽

Gene Signature ◽

Significant Heterogeneity ◽

Related Gene

Background: Patients with early-stage lung adenocarcinoma (LUAD) exhibit significant heterogeneity in overall survival. The current tumour-node-metastasis staging system is insufficient to provide precise prediction for prognosis. Methods: We quantified the levels of various hallmarks of cancer and identified hypoxia as the primary risk factor for overall survival in early-stage LUAD. Different bioinformatic and statistical methods were combined to construct a robust hypoxia-related gene signature for prognosis. Furthermore, a decision tree and a nomogram were constructed based on the gene signature and clinicopathological features to improve risk stratification and quantify risk assessment for individual patients. Results: The hypoxia-related gene signature discriminated high-risk patients at an early stage in our investigated cohorts. Survival analyses demonstrated that our gene signature served as an independent risk factor for overall survival. The decision tree identified risk subgroups powerfully, and the nomogram exhibited high accuracy. Conclusions: Our study might contribute to the optimization of risk stratification for survival and personalized management of early-stage LUAD.

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High concordance of 70-gene recurrence risk signature and 80-gene molecular subtyping signature between core needle biopsy and surgical resection specimen in early-stage breast cancer

10.1101/2021.05.28.21257887 ◽

2021 ◽

Author(s):

Jennifer A Crozier ◽

Julie Barone ◽

Pat Whitworth ◽

Abraham Cheong ◽

Robert Maganini ◽

...

Keyword(s):

Breast Cancer ◽

Strong Correlation ◽

Early Stage ◽

Recurrence Risk ◽

Gene Signature ◽

Early Stage Breast Cancer ◽

Molecular Subtyping ◽

Core Needle ◽

High Concordance ◽

Good Concordance

Introduction: With an increase in neoadjuvant therapy recommendations for most early-stage breast cancer patients due to the COVID-19 pandemic, it has become increasingly imperative to ensure that molecular diagnostic assays provide reliable results from preoperative core needle biopsies. Therefore, the objective of this study was to determine the concordance of MammaPrint results (70-gene signature) and BluePrint results (80-gene signature) between core needle biopsies (CNB) and surgical resection (SR) specimens using prospectively collected matched tissues from patients enrolled in the FLEX trial (NCT03053193). Methods: We analyzed 113 matched CNB and SR tumor specimens from women with early-stage breast cancer enrolled in the FLEX trial. Each patient enrolled in the trial receives a MammaPrint recurrence risk classification test with or without BluePrint molecular subtyping. Concordance of MammaPrint is reported using overall percentage agreement, positive predictive value (PPV, High Risk), negative predictive value (NPV, Low Risk), and Cohens kappa coefficient. Additionally, correlations between sample types are reported using Pearson correlation coefficient. Results: We found good concordance for MammaPrint results between CNB and SR tumor samples (90.3%, k = 0.803), with a 95.1% NPV and 84.6% PPV. There was also a strong correlation of MammaPrint indices between CNB and SR specimens (r = 0.94). In addition to our primary objective, we determined the concordance of BluePrint subtyping in the matched tumor samples, and found excellent concordance (98.2%) and strong correlation of BluePrint scores within each subtype. Conclusion: CNB samples demonstrated overall high concordance with paired SR samples for MammaPrint risk classification, ensuring that physicians are provided with accurate prognostic information for therapy decisions based on testing of core biopsy tissue. Further, BluePrint molecular subtyping also had good concordance between the sample types, outperforming concordance rates based on traditional IHC based classification. Overall, with an increase in neoadjuvant therapy, physicans and patients can be assured that MammaPrint and BluePrint provide reliable results that guide timely and appropriate therapies using preoperative CNB specimens.

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Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-related Genes and Construction of the Risk Score for Prognostication in Early-stage Lung Adenocarcinoma

10.21203/rs.3.rs-125302/v1 ◽

2020 ◽

Author(s):

Bingzhou Guo ◽

Hongliang Zhang ◽

Jinliang Wang ◽

Rilige Wu ◽

Junyan Zhang ◽

...

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Risk Group ◽

Early Stage ◽

Gene Signature ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Cox Analysis ◽

Random Survival Forest

Abstract Background: N6-methyladenosine (m6A) RNA modification play critical roles in tumorigenesis because it can change gene expression and even the function in multiple levels including the regulation of degradation, subcellular localization, splicing and local conformation changes of RNA transcripts. In this study, we aim to conduct comprehensive investigation on m6A RNA methylation regulators and m6A-related genes and their association with prognosis in early-stage Lung adenocarcinoma (LUAD). Methods: The relevant datasets which were used to analyze 21 m6A RNA methylation regulators and 887 m6A-related genes in m6Avar were downloaded from Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate cox regression analysis, random survival forest analysis, Kaplan-Meier anylysis, STRING and multivariate cox analysis were carried out on the datasets, and a risk prognostic model based on five feature genes was constructed.Results: Respectively, we treated GSE31210 (n=226) as training set, GSE50081 (n=128) and TCGA data (n=461) as test set. By performing univariable cox regression and random survival forest algorithm in the training group, five prognosis-related genes including DENND1A, KBTBD6, KIF4A, BMPER, and YTHDC2 were screened out, which could divide LUAD patients into low-risk group and high-risk group (log rank P < 0.001). The predictive efficacy of these genes was confirmed in the test group GSE50081 (log rank P < 0.01) and TCGA datasets (log rank P < 0.001). Cox analysis showed that this five-gene signature was an independent risk factor in LUAD. Further, genes in the signature were also external validated using online database. YTHDC2 played vital role of readers in m6A methylation.Conclusion: The findings of this study suggested that associated with m6A-related genes and m6A RNA methylation regulators, five-gene signature was reliable prognostic indicator for LUAD patients, indicating a clinical application prospect to serve as a potential therapeutic target.

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Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma

10.21203/rs.3.rs-148623/v1 ◽

2021 ◽

Author(s):

Bingzhou Guo ◽

Hongliang Zhang ◽

Jinliang Wang ◽

Rilige Wu ◽

Junyan Zhang ◽

...

Keyword(s):

Gene Expression ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Risk Group ◽

Early Stage ◽

Gene Signature ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Cox Analysis ◽

Random Survival Forest

Abstract BackgroundN6-methyladenosine (m6A) RNA modification play critical roles in tumorigenesis because it can change gene expression and even the function in multiple levels including the regulation of degradation, subcellular localization, splicing and local conformation changes of RNA transcripts. In this study, we aim to conduct comprehensive investigation on m6A RNA methylation regulators and m6A-related genes and their association with prognosis in early-stage Lung adenocarcinoma (LUAD). MethodsThe relevant datasets which were used to analyze 21 m6A RNA methylation regulators and 887 m6A-related genes in m6Avar were downloaded from Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA) databases. Univariate cox regression analysis, random survival forest analysis, Kaplan-Meier anylysis, STRING and multivariate cox analysis were carried out on the datasets, and a risk prognostic model based on five feature genes was constructed.ResultsRespectively, we treated GSE31210 (n=226) as training set, GSE50081 (n=128) and TCGA data (n=461) as test set. By performing univariable cox regression and random survival forest algorithm in the training group, five prognosis-related genes including DENND1A, KBTBD6, KIF4A, BMPER, and YTHDC2 were screened out, which could divide LUAD patients into low-risk group and high-risk group (log rank P < 0.001). The predictive efficacy of these genes was confirmed in the test group GSE50081 (log rank P < 0.01) and TCGA datasets (log rank P < 0.001). Cox analysis showed that this five-gene signature was an independent risk factor in LUAD. Further, genes in the signature were also external validated using online database. YTHDC2 played vital role of readers in m6A methylation.ConclusionThe findings of this study suggested that associated with m6A-related genes and m6A RNA methylation regulators, five-gene signature was reliable prognostic indicator for LUAD patients, indicating a clinical application prospect to serve as a potential therapeutic target.

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