Gene signature for predicting prognosis of patients with solid tumors
Inventors
Wang, Xin Wei • Roessler, Stephanie K.
Assignees
US Department of Health and Human Services
Publication Number
US-8735082-B2
Publication Date
2014-05-27
Expiration Date
2029-11-10
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Abstract
Disclosed herein is a driver gene signature for predicting survival in patients with solid tumors, such as hepatocellular carcinoma (HCC) and breast cancer. The gene signature includes ten tumor-associated genes, SH2D4A, CCDC25, ELP3, DLC1, PROSC, SORBS3, HNRPD, PAQR3, PHF17 and DCK. A decrease in DNA copy number or mRNA expression of SH2D4A, CCDC25, ELP3, DLC1, PROSC and SORBS3 in solid tumors is associated with a poor prognosis, while a decrease in DNA copy number or mRNA expression of HNRPD, PAQR3, PHF17 and DCK in solid tumors is associated with a good prognosis. Thus, provided herein is a method of predicting the prognosis of a patient diagnosed with HCC or breast cancer by detecting expression of one of more tumor-associated genes in a tumor sample and comparing expression of the one or more tumor-associated genes in the tumor sample to a control. Also provided is a method of treating a patient diagnosed with HCC or breast cancer by administering a therapeutically effective amount of an agent that alters expression or activity of one or more of the disclosed tumor-associated genes. Further provided are arrays comprising probes or antibodies specific for a plurality of tumor-associated genes or proteins.
Core Innovation
The invention discloses a driver gene signature consisting of ten tumor-associated genes—SH2D4A, CCDC25, ELP3, DLC1, PROSC, SORBS3, HNRPD, PAQR3, PHF17, and DCK—for predicting survival in patients with solid tumors such as hepatocellular carcinoma (HCC) and breast cancer. The signature links a decrease in DNA copy number or mRNA expression of SH2D4A, CCDC25, ELP3, DLC1, PROSC, and SORBS3 in solid tumors with poor prognosis and a decrease in DNA copy number or mRNA expression of HNRPD, PAQR3, PHF17, and DCK with good prognosis. Methods are provided for predicting prognosis by detecting expression of one or more of these tumor-associated genes in tumor samples compared to controls, as well as methods of treatment by administering agents that alter expression or activity of these genes. Arrays comprising probes or antibodies specific for these tumor-associated genes or proteins are also disclosed.
The problem addressed by this invention arises from the high heterogeneity and genomic instability of solid tumors, such as HCC and breast cancer, which lead to numerous genomic aberrations that do not contribute to tumor progression (‘passenger’ mutations). Differentiating functionally relevant ‘driver’ mutations from passenger mutations is critical because these ‘driver’ genes provide ideal targets for prognosis prediction and therapeutic development. Despite high genomic instability and diverse pathways leading to tumor development, the molecular mechanisms underlying HCC progression remain poorly understood, and existing treatment options, including surgical resection, are limited by late-stage presentation and ineffective systemic chemotherapy.
This invention solves the problem by applying integrative genomics combining arrayCGH and gene expression profiling to identify functionally relevant driver genes linked to clinical outcomes in solid tumors. The identified 10-gene driver signature, located on chromosome 4q and 8p, distinguishes poor prognosis from good prognosis subgroups in HCC and is also predictive in breast cancer patients with mixed nodal status. The gene signature provides a tumor-specific prognostic tool and identifies potential novel tumor suppressor genes (e.g., SH2D4A and SORBS3) that can be targeted therapeutically to inhibit tumor growth and progression.
Claims Coverage
The patent contains two independent claims focused on methods of detecting expression of multiple tumor-associated genes to predict poor prognosis in subjects diagnosed with breast cancer or hepatocellular carcinoma.
Method of detecting tumor-associated gene expression indicative of poor prognosis in breast cancer
Detecting a decrease in expression of SH2D4A, CCDC25, ELP3, DLC1, PROSC, and SORBS3 and an increase in expression of HNRPD, PAQR3, PHF17, and DCK in a breast tumor sample relative to a control to indicate poor prognosis.
Method of detecting tumor-associated gene expression indicative of poor prognosis in hepatocellular carcinoma (HCC)
Detecting a decrease in expression of SH2D4A, CCDC25, ELP3, DLC1, PROSC, and SORBS3 or an increase in expression of HNRPD, PAQR3, PHF17, and DCK in a liver tumor sample relative to a control to indicate poor prognosis.
The claims cover methods of prognosticating breast cancer and HCC by measuring specific patterns of decreased or increased expression of a ten-gene tumor-associated signature, involving both downregulated and upregulated genes relative to controls, providing a tumor-specific prognostic marker.
Stated Advantages
The gene signature serves as an independent and significant predictor of survival in HCC and breast cancer patients.
It allows for tumor-specific prognosis, distinguishing better and worse clinical outcomes based on tumor gene expression.
Identification of novel tumor suppressor genes, such as SH2D4A and SORBS3, provides potential targets for therapeutic intervention.
The disclosure provides potential utility for personalized treatment by enabling genotype-specific therapies.
Documented Applications
Predicting prognosis of patients diagnosed with hepatocellular carcinoma (HCC) or breast cancer by detecting expression of tumor-associated genes in tumor samples.
Treating patients with HCC, breast cancer, or other solid tumors (e.g., lung, esophageal, colon cancer) by administering agents that modulate expression or activity of the ten tumor-associated genes.
Identifying therapeutic agents for treatment of solid tumors by screening candidate agents for their ability to modulate expression or activity of the tumor-associated genes.
Use of arrays comprising probes or antibodies specific for the tumor-associated genes or proteins for prognosis and research.
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