Dataset Information

High prognostic potential of a transcriptomic signature related to cycling hypoxia: direct application to breast cancer profiling

ABSTRACT: Purpose. Temporal and local fluctuations in oxygen levels observed within tumors represent stressful conditions requiring adaptive mechanisms that provide tumor cells with phenotypic alterations to survive and proliferate in this hostile environment. The analysis of the transcriptome associated with such cycling hypoxia could thus represent a prognostic biomarker of cancer progression. Patients and Methods. We exposed 20 cell lines derived from various tissues to repeated periods of hypoxia/reoxygenation in order to determine a transcriptomic signature of cycling hypoxia (CycHyp). We then used clinical data sets from 2,150 patients with primary breast cancer to estimate a prognostic Cox proportional hazard model and to assess the prognostic performance of the CycHyp signature on independent samples. Results. The prognostic potential of the CycHyp signature was validated in patients independently of the receptor status of the tumors (HR=1.97; p = 1.8e-12). The discriminating capacity of the CycHyp signature was further increased in the ER+ HER2- patient populations (HR = 2.34, p = 9e-12) including those with a node negative status receiving or not a treatment (HR = 3.32 and 5.51; p= 5.61e-10 and 8.15e-11, respectively). We also documented the capacity of the CycHyp signature to outperform existing prognostic gene signatures with significantly higher BCR and concordance index. We also showed that the CycHyp signature could identify ER-positive node-negative breast cancer patients at high risk based on conventional clinico-pathologic criteria but who could have been spared from chemotherapy and inversely those patients classified at low risk based on the same criteria but who presented a negative outcome. Conclusion. This study demonstrates that a gene signature derived from the transcriptomic adaptation of tumor cells to cycling hypoxia is prognostic of breast cancer and offers a unique decision making tool to complement the discrimination of breast cancer patients based on anatomo-pathological evaluation. The prognostic value of CycHyp further confirms the link between cycling hypoxia and cancer progression, and thereby paves the way for a broad applicability to evaluate cancer patient outcomes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE42416 | GEO | 2015/11/16

SECONDARY ACCESSION(S): PRJNA181352

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1Î¼g Cy3 labeled cRNA and 1 Î¼g Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.

Project description:Breast cancers contain a minority population of cancer cells characterized by CD44 expression but low or undetectable levels of CD24 (CD44+CD24-/low) that have higher tumorigenic capacity than other subtypes of cancer cells. METHODS: We compared the gene-expression profile of CD44+CD24-/low tumorigenic breast-cancer cells with that of normal breast epithelium. Differentially expressed genes were used to generate a 186-gene invasiveness gene signature (IGS), which was evaluated for its association with overall survival and metastasis-free survival in patients with breast cancer or other types of cancer. RESULTS: There was a significant association between the IGS and both overall and metastasis-free survival (P<0.001, for both) in patients with breast cancer, which was independent of established clinical and pathological variables. When combined with the prognostic criteria of the National Institutes of Health, the IGS was used to stratify patients with high-risk early breast cancer into prognostic categories (good or poor); among patients with a good prognosis, the 10-year rate of metastasis-free survival was 81%, and among those with a poor prognosis, it was 57%. The IGS was also associated with the prognosis in medulloblastoma (P=0.004), lung cancer (P=0.03), and prostate cancer (P=0.01). The prognostic power of the IGS was increased when combined with the wound-response (WR) signature. CONCLUSIONS: The IGS is strongly associated with metastasis-free survival and overall survival for four different types of tumors. This genetic signature of tumorigenic breast-cancer cells was even more strongly associated with clinical outcomes when combined with the WR signature in breast cancer. Expression profling was performed on 6 tumorigenic, 3 non tumorigenic samples of breast tumors and 3 normal breast samples on two different platforms GPL96 and GPL97. A gene signature was derived by comparing the gene expressions of 6 tumorigenic samples with 3 normal breast samples.

Dataset Information

High prognostic potential of a transcriptomic signature related to cycling hypoxia: direct application to breast cancer profiling

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets