A 10-Gene Yin Yang Expression Ratio Signature for Stage IA and IB Non–Small Cell Lung Cancer

Xu, Wayne; Jia, Gaofeng; Davie, James R.; Murphy, Leigh C.; Kratzke, Robert A.; Banerji, Shantanu

doi:10.1016/j.jtho.2016.07.023

Cited by 16 publications

(19 citation statements)

References 36 publications

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“…FOXM1 and PPARα) can be used to build signatures for TNBC. One hundred and fourteen genes from the Yin (133) pathways and 66 genes from the list of Yang (71) pathways were then used in the YMR signature [ 20 – 22 ] and tested against the METABRIC dataset. All the 126 patients from the METABRIC dataset were separated into high risk and low risk groups using a median value of 1.00 and then survival curves over 10 years for the treated and untreated patients were generated.…”

Section: Resultsmentioning

confidence: 99%

“…The “core” genes from the Yin pathways were the Yin genes and the “core” genes of the Yang pathways were the Yang genes. The Yin Yang gene expression mean ratio (YMR) signature [ 20 – 22 ] was tested using the TNBC samples of the TCGA and METABRIC datasets by the R package Survcomp.…”

Section: Methodsmentioning

confidence: 99%

“…In this study, we explored the pathways that are upregulated and downregulated in TNBC with respect to normal breast tissue samples. We hypothesized these up- and down-regulated pathways represent two opposing effects (Yin and Yang) that determine the cancer outcome [ 20 – 22 ]. These Yin and Yang pathways could help identify potential therapeutic targets for TNBC.…”

Section: Introductionmentioning

confidence: 99%

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The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC)

et al. 2018

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BackgroundTriple Negative Breast Cancers (TNBCs) lack the appropriate targets for currently used breast cancer therapies, conferring an aggressive phenotype, more frequent relapse and poorer survival rates. The biological heterogeneity of TNBC complicates the clinical treatment further. We have explored and compared the biological pathways in TNBC and other subtypes of breast cancers, using an in silico approach and the hypothesis that two opposing effects (Yin and Yang) pathways in cancer cells determine the fate of cancer cells. Identifying breast subgroup specific components of these opposing pathways may aid in selecting potential therapeutic targets as well as further classifying the heterogeneous TNBC subtype.MethodsGene expression and patient clinical data from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used for this study. Gene Set Enrichment Analysis (GSEA) was used to identify the more active pathways in cancer (Yin) than in normal and the more active pathways in normal (Yang) than in cancer. The clustering analysis was performed to compare pathways of TNBC with other types of breast cancers. The association of pathway classified TNBC sub-groups to clinical outcomes was tested using Cox regression model.ResultsAmong 4729 curated canonical pathways in GSEA database, 133 Yin pathways (FDR < 0.05) and 71 Yang pathways (p-value <0.05) were discovered in TNBC. The FOXM1 is the top Yin pathway while PPARα is the top Yang pathway in TNBC. The TNBC and other types of breast cancers showed different pathways enrichment significance profiles. Using top Yin and Yang pathways as classifier, the TNBC can be further subtyped into six sub-groups each having different clinical outcomes.ConclusionWe first reported that the FOMX1 pathway is the most upregulated and the PPARα pathway is the most downregulated pathway in TNBC. These two pathways could be simultaneously targeted in further studies. Also the pathway classifier we performed in this study provided insight into the TNBC heterogeneity.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3939-4) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC)

et al. 2018

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“…Although it has been shown in different studies that a specific gene set can predict the prognosis of cancer patients [20,21], the number of genes in a model is often beyond practical need [22] or of immune irrelevance [23], making translational feasibility low. With the development of tumour immunotherapy, the role of the immune system in the development of cancer has once again been taken into consideration.…”

Section: Discussionmentioning

confidence: 99%

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Shi

Dong

et al. 2020

J Transl Med

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Background: Tumour cells interfere with normal immune functions by affecting the expression of some immunerelated genes, which play roles in the prognosis of cancer patients. In recent years, immunotherapy for tumours has been widely studied, but a practical prognostic model based on immune-related genes in lung adenocarcinoma comparable to existing model has not been established and reported. Methods: We first obtained publicly accessible lung adenocarcinoma RNA expression data from The Cancer Genome Atlas (TCGA) for differential gene expression analysis and then filtered immune-related genes based on the ImmPort database. By using the lasso algorithm and multivariate Cox Proportional-Hazards (CoxPH) regression analysis, we identified candidate genes for model development and validation. The robustness of the model was further examined by comparing the model with three established gene models. Results: Gene expression data from a total of 524 lung adenocarcinoma patients from TCGA were used for model development. We identified four biomarkers (MAP3K8, CCL20, VEGFC, and ANGPTL4) that could predict overall survival in lung adenocarcinoma (HR = 1.98, 95% CI 1.48 to 2.64, P = 4.19e−06) and this model could be used as a classifier for the evaluation of low-risk and high-risk groups. This model was validated with independent microarray data and was highly comparable with previously reported gene expression signatures for lung adenocarcinoma prognosis. Conclusions: In this study, we identified a practical and robust four-gene prognostic model based on an immune gene dataset with cross-platform compatibility. This model has potential value in improving TNM staging for survival predictions in patients with lung adenocarcinoma. Impact: The study provides a method of immune relevant gene prognosis model and the identification of immune gene classifier for the prediction of lung adenocarcinoma prognosis with RNA sequencing and microarray compatibility.

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“…Given the unsatisfactory survival rates, many researchers have been searching for possible methods that could help predict the outcome of stage I patients, such as analysis of the standard uptake value (SUVmax) in positron emission tomography or carcinoembryonic antigen (CEA) serum levels [19, 20], or detection of genetic alterations [21–23], epigenetic modifications [15, 24], and gene-expression profiles [25–27]. However, few studies have explored the molecular status of histologically normal-appearing surgical margins [13–15, 21, 28].…”

Section: Discussionmentioning

confidence: 99%

Detection of oncogenic mutations in resected bronchial margins by next-generation sequencing indicates early relapse in stage IA lung adenocarcinoma patients

Zou

Liu

et al. 2017

Oncotarget

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Stage I non-small cell lung cancer (NSCLC) patients experience a relatively high rate of recurrence, ranging from about 30-35%. We hypothesized that this elevated risk of recurrence is due to the presence of tumor cells at bronchial margins which was undetected by conventional light microscopy. Patients with clinical stage IA (T1N0M0) NSCLC were enrolled in this study, which included 8 early-relapse(ER) and 6 no-relapse(NR) patients. Primary tumor, bronchial margin, and normal lung tissues were collected and sent to a central site for targeted next-generation sequencing analysis. All of the patients were lung adenocarcinoma. Gene mutations were identified in all tumor tissue samples (100%). Oncogenic mutations were identified in 87.5%(7/8) bronchial margins of early relapse patients, whereas only 16.7%(1/6) no-relapse (NR) patient of marginal tissue had identified gene mutation. Additionally, concordance between primary tumor and bronchial margins was relatively high, with 4 of 8 (50%) ER patients having at least one identical mutation. Moreover, according to the gene mutation status in marginal tissue, 87.5% (7/8) of patients with at least one gene mutation in the bronchial margins had local recurrence or metastasis, whereas only 16.7% (1/6) of patients without any mutation detected had signs of relapse, the recurrence rate was significantly higher than that of the negative mutation margin group ((p (log-rank) = 0.023). The existence of oncogenic mutations in bronchial margins may represent occult residual tumor and elevated risk of recurrence in early stage NSCLC patients. Thus, assessing molecular status in bronchial margins may help identify patients who might benefit from extensive surgery or adjuvant treatment.

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A 10-Gene Yin Yang Expression Ratio Signature for Stage IA and IB Non–Small Cell Lung Cancer

Abstract: The YMR signature has great potential for guiding clinical management for NSCLC, particularly early-stage disease. The signature appears more reproducible than older signatures and functions using a variety of common gene expression platforms.

Cited by 16 publications

References 36 publications

The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC)

The exploration of contrasting pathways in Triple Negative Breast Cancer (TNBC)

IRGS: an immune-related gene classifier for lung adenocarcinoma prognosis

Detection of oncogenic mutations in resected bronchial margins by next-generation sequencing indicates early relapse in stage IA lung adenocarcinoma patients

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