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The rapamycin-regulated gene expression signature determines prognosis for breast cancer.

ABSTRACT: Mammalian target of rapamycin (mTOR) is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes) may also be used to simulate a biologic process or effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer.Colony formation and sulforhodamine B (IC50 < 1 nM) assays, and xenograft animals showed that MDA-MB-468 cells were sensitive to treatment with rapamycin. The comparison of in vitro and in vivo gene expression data identified a signature, termed rapamycin metagene index (RMI), of 31 genes upregulated by rapamycin treatment in vitro as well as in vivo (false discovery rate of 10%). In the Miller dataset, RMI did not correlate with tumor size or lymph node status. High (>75th percentile) RMI was significantly associated with longer survival (P = 0.015). On multivariate analysis, RMI (P = 0.029), tumor size (P = 0.015) and lymph node status (P = 0.001) were prognostic. In van 't Veer study, RMI was not associated with the time to develop distant metastasis (P = 0.41). In the Wang dataset, RMI predicted time to disease relapse (P = 0.009).Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment.

SUBMITTER: Akcakanat A

PROVIDER: S-EPMC2761377 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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The rapamycin-regulated gene expression signature determines prognosis for breast cancer.

Akcakanat Argun A Zhang Li L Tsavachidis Spiridon S Meric-Bernstam Funda F

Molecular cancer 20090924

<h4>Background</h4>Mammalian target of rapamycin (mTOR) is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes) may also be used to simulate a biologic process or effects of a drug treatment. In this study, we tested ...[more]

PMID: 19778445

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Project description:Previous studies have revealed that upregulation of interleukin 15 receptor ? (IL15RA) contributes to improved prognosis of breast cancer. The present study aimed to elucidate the molecular mechanisms underlying the antitumor effect induced by IL15RA upregulation, and to identify a gene signature capable of predicting the survival of patients with breast cancer. Using paired gene expression and methylation data of breast cancer samples from The Cancer Genome Atlas data portal, differentially expressed genes (DEGs) were identified in hypermethylated and hypomethylated IL15RA breast cancer samples. Furthermore, a gene signature-based risk-scoring model was developed according to the Cox regression coefficients of survival-associated DEGS. The gene signature was applied to classify patients with breast cancer and hypermethylated IL15RA into two risk groups via Kaplan-Meier survival analysis of overall survival (OS) time. Functional enrichment analysis was conducted to decipher the biological roles of the DEGs between the two risk groups. A total of 326 DEGs were present in the hypomethylation and hypermethylation samples compared with in the normal samples. A four-gene signature [SH3 and cysteine rich domain 2 (STAC2), proline rich 11 (PRR11), homeobox C11 (HOXC11) and nucleolar and spindle associated protein 1 (NUSAP1)] was identified as able to successfully separate patients with breast cancer and hypermethylated IL15RA into two risk groups with significantly different OS time. The signature revealed similar predictive performance in an independent set. Significant enrichment of the 'receptor interaction' and 'cell adhesion molecules (CAM)' pathways, which involved the DEGs, occurred between the two risk groups. These findings suggested that IL15RA may participate in the regulation of STAC2, PRR11, HOXC11, NUSAP1, and 'ECM-receptor interaction' and 'cell adhesion molecules' pathways, and therefore in the suppression of breast cancer development and progression. The four-gene signature may have potential prognostic value for breast cancer.

Project description:A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher's exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with lower 12-gene scores in GSE39582, the subgroup receiving ACT showed significantly longer OS time compared with those who received no ACT (Log Rank p = 0.021), while there is no obvious difference between counterparts among patients with higher 12-gene scores (Log Rank p = 0.12). Besides COAD, our 12-gene signature is multifunctional in several other cancer types including kidney cancer, lung cancer, uveal and skin melanoma, brain cancer, and pancreatic cancer. Functional classification showed that seven of the twelve genes are involved in immune system function and regulation, so our 12-gene signature could potentially be used to guide decisions about adjuvant therapy for patients with stage II/III and pMMR COAD.

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The rapamycin-regulated gene expression signature determines prognosis for breast cancer.

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The rapamycin-regulated gene expression signature determines prognosis for breast cancer.

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