Use of a proliferation-based mRNA signature to predict outcome in early-stage non-small cell lung adenocarcinoma.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 7023-7023
Author(s):  
Carmen Behrens ◽  
Francesca Lombardi ◽  
Susanne Wagner ◽  
Junya Fujimoto ◽  
Maria G Raso ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Multivariate Analysis ◽  
Lung Adenocarcinoma ◽  
Quantitative Pcr ◽  
Prognostic Value ◽  
Early Stage ◽  
Treatment Decisions ◽  
Cancer Center ◽  
Data Set ◽  
Ffpe Samples

7023 Background: Adjuvant treatment of patients with early-stage lung adenocarcinoma is based on post-surgical pathological staging and patient performance status. Disparate outcomes within each staging group suggest that additional prognostic markers could improve our understanding of risk-benefit and potentially lead to better treatment decisions. A proliferation-based, mRNA expression profile was applied to public microarray data of surgically treated lung adenocarcinomas and a cohort of FFPE samples to test its potential prognostic utility. Methods: Public expression data (Director’s Consortium, DC) were derived from Affymetrix HG-U133A arrays. Clinical FFPE samples were assayed by quantitative PCR. A cell cycle progression (CCP) score was calculated from the expression average of 31 cell cycle genes normalized by 15 housekeeper genes. The prognostic value of the CCP score to predict stage I and II patient outcomes was evaluated by Cox proportional hazards analysis with disease-related death as the primary outcome measure. Results: In 256 DC cases, the CCP score was a significant predictor of death in univariate (p=0.0001) and multivariate analysis (p=0.001, HR 1.57, 95%CI 1.20-2.05) using age, stage, gender, smoking status and treatment as covariates. Similarly, in a second data set (GSE31210, n=204) the CCP score was highly associated with death (univariate, p=0.001; multivariate analysis, p=0.003, HR 1.81, 95% CI 1.24-2.66). Using quantitative PCR, the signature was applied to 381 FFPE samples with a median follow-up of 5 years collected at the MD Anderson Cancer Center and the European Institute for Oncology. In the presence of clinical covariates (as above and tumor size and pleural invasion), the CCP score remained the most significant predictor of death in univariate (p=0.0003) and multivariate analysis (p=0.007, HR 1.50, 95% CI 1.11-2.02). Conclusions: A 46 gene mRNA signature is a significant predictor of disease-related death in early-stage lung adenocarcinoma, providing independent prognostic value in the presence of clinical variables. This molecular predictor of cancer survival will be studied in additional cohorts for its ability to impact clinical treatment decisions.

scholarly journals Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7821 ◽  
Author(s):  
Xiaoming Zhang ◽  
Jing Zhuang ◽  
Lijuan Liu ◽  
Zhengguo He ◽  
Cun Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Prognostic Value ◽  
Early Stage ◽  
Expression Profiles ◽  
Diagnostic Value ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Data Set

Background Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening. Methods First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA). Results Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer. Conclusion Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

scholarly journals Alterations in Cell Cycle Genes in Early Stage Lung Adenocarcinoma Identified by Expression Profiling

2003 ◽  
Vol 2 (3) ◽  
pp. 291-298 ◽  
Author(s):  
Sunil Singhal ◽  
Kunjilata Amin ◽  
Robert Kruklitis ◽  
Peter DeLong ◽  
Michael E. Friscia ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
Expression Profiling ◽  
Early Stage ◽  
Cell Cycle Genes

Prognostic value and therapeutic implications of expanded molecular testing for resected early stage lung adenocarcinoma

Lung Cancer ◽  
2020 ◽  
Vol 143 ◽  
pp. 60-66 ◽  
Author(s):  
Peter J. Kneuertz ◽  
David P. Carbone ◽  
Desmond M. D’Souza ◽  
Konstantin Shilo ◽  
Mahmoud Abdel-Rasoul ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Early Stage ◽  
Molecular Testing ◽  
Therapeutic Implications

scholarly journals Prognostic value of OCT4A and SPP1C transcript variant co-expression in early-stage lung adenocarcinoma

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Seijiro Koshimune ◽  
Mitsuko Kosaka ◽  
Nobuhiko Mizuno ◽  
Hiromasa Yamamoto ◽  
Tomoyuki Miyamoto ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Value ◽  
Early Stage ◽  
Transcript Variant

scholarly journals Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Pancheng Wu ◽  
Yi Zheng ◽  
Yanyu Wang ◽  
Yadong Wang ◽  
Naixin Liang
Keyword(s):  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Prognostic Signature ◽  
Training Set ◽  
Validation Data ◽  
Data Set ◽  
Screening Programs ◽  
Immune Signature ◽  
Immune Related Genes

Abstract Background The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD. Methods The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts. Results A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design. Conclusions Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

scholarly journals P3.16-06 Does Comprehensive Mutation Analysis Add Prognostic Value in Resected Early Stage Lung Adenocarcinoma?

2018 ◽  
Vol 13 (10) ◽  
pp. S1005
Author(s):  
P. Kneuertz ◽  
D. Carbone ◽  
L. Luo ◽  
D. D'Souza ◽  
S. Moffatt-Bruce ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mutation Analysis ◽  
Prognostic Value ◽  
Early Stage

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

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.

HER2-low and gastric cancer: A prognostic biomarker?

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16086-e16086
Author(s):  
Bruno Cezar de Mendonça Uchôa ◽  
Rafaela Pirolli ◽  
Luciana Beatriz Mendes Gomes Siqueira ◽  
Francisca Giselle Rocha Moura ◽  
Ana Paula Rondina Correa ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Multivariate Analysis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Statistical Significance ◽  
Gastroesophageal Junction ◽  
Rank Test ◽  
Cancer Center ◽  
First Line

e16086 Background: The role of HER2 positive (HER2+) as a prognostic biomarker for gastric/gastroesophageal junction cancer (G-GEJC) is controversial. Recently, the HER2-low (HER2l) concept has emerged and proved to predict response to trastuzumab deruxtecan in metastatic scenario. Data on HER2l prognostic value are missing. Methods: All consecutive patients with metastatic G-GEJC, tested for HER2 in the primary tumor or in the metastatic tissue before initiating first-line therapy at A.C. Camargo Cancer Center, were retrospectively recruited. The primary objective was to compare the overall survival (OS: from the metastasis diagnosis to death by any cause) between HER2l and HER2 negative (HER2-) populations. Secondarily, we aimed to compare the first-line progression-free survival (PFS) between HER2l and HER2-, to analyze prognostic factors associated with OS and to compare the OS between HER2+ and HER2l/HER2-. The HER2 immunohistochemistry (IHC) tests were performed with the Ventana anti-HER2/neu kit, by specialized gastrointestinal pathologists of the study center, using the AJCC HER2 scoring criteria for gastric cancer. In situ hybridization (ISH) was done when IHC 2+ was detected. HER2+ were IHC 3+ or 2+ amplified by ISH; HER2l, 1+ or 2+ non-amplified; HER-, 0+. Kaplan-Meier curves, Log-Rank test and Cox regression were used for survival analysis. Cox regression was used for uni and multivariate analysis. Results: From June, 2008 to July, 2020, 398 patients were included (48 HER2+; 103 HER2l; 247 HER2-). The median follow-up was 31 months (m). Median age at diagnosis was 58 years; the majority were men (62.8%), caucasian (50.8%), with gastric (81% vs 19% GEJ), diffuse (50.3%), de novo metastatic (57.0%) tumors. In comparison to HER2l/HER2-, HER2+ group had superior rates of men, GEJC, intestinal subtype and non-visceral metastasis. Central nervous system metastases were uncommon, and proportionally higher in HER2+ tumors (HER2+: 6.2%; HER2l: 2.9%; HER2-: 2.0%; p = 0.27). There were no imbalances between HER2l and HER2- groups. The median OS was similar for HER2l and HER2- (13m for both; HR 1.0, 95%CI 0.76-1.31; p = 1.0), as it was the PFS (5m for both; HR 0.84, 95%CI 0.65-1.08; p = 0.18). These results did not vary on dependence of IHC + (0 vs 1 + vs 2+). HER2+ tumors had a superior median OS (17m vs 13m for HER2l/HER2-; HR 0.70, 95%CI 0.49-0.99; p = 0.046). When ungrouping HER2l/HER2-, this numerical difference remains, with a loss of statistical significance (17m vs 13m vs 13m; HR 0.87, 95%CI 0.74-1.02; p = 0.12). HER2+, > 1 line of treatment and metastasectomy were predictive for improved OS in multivariate analysis. HER2l was neither predictive for OS nor PFS. Conclusions: Although HER2-low emerged as a new predictive biomarker in metastatic gastric cancer, its prognostic value could not be proved in this study, with an absence of impact in OS. HER2+, however, was associated with improved survival.

scholarly journals Lepidic component identifies a subgroup of lung adenocarcinoma with a distinctive prognosis: a multicenter propensity-matched analysis

2020 ◽  
Vol 12 ◽  
pp. 175883592098284
Author(s):  
Erjia Zhu ◽  
Chenyang Dai ◽  
Huikang Xie ◽  
Hang Su ◽  
Xuefei Hu ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Survival Rates ◽  
Prognostic Impact ◽  
Data Set ◽  
Cox Regression Analysis ◽  
T Stage ◽  
Kaplan Meier ◽  
T Classification

Background: Our aim was to investigate the prognostic impact of the lepidic component on T stage in patients with lung adenocarcinoma (LUAD). Methods: A retrospective data set including 863 cases of LUAD with lepidic component and 856 cases without lepidic component was used to identify matched lepidic-positive and lepidic-negative cohorts ( n = 376 patients per group) using a propensity-score matching. Primary outcome variables included recurrence-free survival (RFS) and overall survival (OS). Prognostic factors were assessed by Cox regression analysis and Kaplan–Meier estimates. Results: Multivariate analysis revealed that lepidic component presence was an independent prognostic factor for prolonged RFS ( p < 0.001) and OS ( p < 0.001). Furthermore, lepidic ratio (LR) >25% or ⩽25% were confirmed to be independent prolonged survival predictors. No survival differences were observed between patients with LUAD with LR >25% or ⩽25% (RFS p = 0.333; OS p = 0.078). The 5-year OS rates of patients with LUAD with a lepidic component were 90% regardless of the T stage, and these survival rates were significantly better than those of patients with LUAD without a lepidic component in the corresponding T stage. Multivariate analysis confirmed that T stage was associated with survival only in patients with LUAD without a lepidic component. Conclusions: Lepidic component presence identifies a LUAD subgroup with an excellent prognosis independent of the LR, pathological T classification. Considering the lepidic component presence may improve prognostic predictions for patients with LUAD.

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