Showing papers by "Keith A. Baggerly published in 2015"
TL;DR: This review summarizes the data collected from The Cancer Genome Atlas (TCGA) and several other genome-wide projects to identify dysregulated miRNAs in ovarian cancers and gives particular attention to TP53, BRCA1/2, CA125, HE4, and imprinted genes such as ARHI.
Abstract: MicroRNAs (miRNAs/miRs) belong to a class of small non-coding RNAs that can negatively regulate messenger RNA (mRNA) expression of target genes. miRNAs are involved in multiple aspects of ovarian cancer cell dysfunction and the phenotype of ovarian cancer cells can be modified by targeting miRNA expression. miRNA profiling has detected a number of candidate miRNAs with the potential to regulate many important biological functions in ovarian cancer, but their role still needs to be clarified, given the remarkable heterogeneity among ovarian cancers and the context dependent role of miRNAs. This review summarizes the data collected from The Cancer Genome Atlas (TCGA) and several other genome-wide projects to identify dysregulated miRNAs in ovarian cancers. Copy number variations (CNVs), epigenetic alterations, and oncogenic mutations are also discussed that impact miRNA levels in ovarian disease. Emphasis is given to the role of particular miRNAs in altering expression of genes in human ovarian cancers with the potential to provide diagnostic, prognostic and therapeutic targets. Particular attention has been given to TP53, BRCA1/2, CA125 (MUC16), HE4 (WFDC2), and imprinted genes such as ARHI (DIRAS3). Better understanding of the abnormalities in miRNA expression and downstream transcriptional and biological consequences will provide leads for more effective biomarkers and translational approaches in the management of ovarian cancer.
86 citations
TL;DR: The combination of HyperCVAD and everolimus is well tolerated and moderately effective in relapsed ALL, specifically T-ALL.
Abstract: Purpose: Previous studies suggest a potential therapeutic role for mTOR inhibition in lymphoid malignancies. This single-center phase I/II study was designed to test the safety and efficacy of the mTOR inhibitor everolimus in combination with HyperCVAD chemotherapy in relapsed/refractory acute lymphoblastic leukemia (ALL). Experimental Design: Twenty-four patients were treated; 15 received everolimus 5 mg/day and 9 received 10 mg/day with HyperCVAD. Results: The median age of patients was 25 years (range, 11–64) and median number of prior treatments was 2 (range, 1–7). Grade 3 mucositis was the dose-limiting toxicity and the maximum tolerated everolimus dose was 5 mg/day. Responses included complete remission (CR) in 6 patients (25%), CR without platelet recovery (CRp) in 1 (4%), and CR without recovery of counts (CRi) in 1 (4%), for an overall response rate of 33%. In addition, partial response (PR) was noted in 2 patients (8%). Seven of 11 patients treated in first salvage achieved CR/CRp (64%). The median OS was 29 weeks for patients in first salvage versus 15 weeks for patients in second salvage and beyond ( P ≤ 0.001). A response was noted in 5 of 10 (50%) heavily pretreated T-ALL patients (median of 4 prior salvage regimens). Everolimus significantly inhibited phosphorylation of S6RP, but this did not correlate with response. No significant decreases in p4EBP1 and pAkt levels were noted. Responders had higher everolimus dose-adjusted area under the curve ( P = 0.025) and lower clearance ( P = 0.025) than nonresponders. Conclusions: The combination of HyperCVAD and everolimus is well tolerated and moderately effective in relapsed ALL, specifically T-ALL. Clin Cancer Res; 1–11. ©2015 AACR.
49 citations
TL;DR: The frequency of recurrent hotspot mutations in 46 cancer-related genes across tumor histologies in patients with advanced cancer was determined, facilitating genomic characterization across multiple tumor lineages and identification of novel opportunities for genotype-driven trials.
Abstract: // Genevieve M. Boland 1,2 , Sarina A. Piha-Paul 3 , Vivek Subbiah 3 , Mark Routbort 4 , Shelley M. Herbrich 5 , Keith Baggerly 6 , Keyur P. Patel 4 , Lauren Brusco 3 , Chacha Horombe 7 , Aung Naing 3 , Siqing Fu 3 , David S. Hong 3 , Filip Janku 3 , Amber Johnson 7 , Russell Broaddus 8 , Raja Luthra 4 , Kenna Shaw 7 , John Mendelsohn 7 , Gordon B. Mills 7,9 and Funda Meric-Bernstam 2,3,7 1 Division of Surgical Oncology, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA 2 Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 3 Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 4 Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 5 Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 6 Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 7 Department of Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 8 Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 9 Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA Correspondence to: Funda Meric-Bernstam, email: // Keywords : genomic sequencing, actionable genes Received : November 10, 2014 Accepted : April 23, 2015 Published : May 08, 2015 Abstract Purpose: We determined the frequency of recurrent hotspot mutations in 46 cancer-related genes across tumor histologies in patients with advanced cancer. Methods: We reviewed data from 500 consecutive patients who underwent genomic profiling on an IRB-approved prospective clinical protocol in the Phase I program at the MD Anderson Cancer Center. Archival tumor DNA was tested for 740 hotspot mutations in 46 genes (Ampli-Seq Cancer Panel; Life Technologies, CA). Results: Of the 500 patients, 362 had at least one reported mutation/variant. The most common likely somatic mutations were within TP53 (36%), KRAS (11%), and PIK3CA (9%) genes. Sarcoma (20%) and kidney (30%) had the lowest proportion of likely somatic mutations detected, while pancreas (100%), colorectal (89%), melanoma (86%), and endometrial (75%) had the highest. There was high concordance in 62 patients with paired primary tumors and metastases analyzed. 151 (30%) patients had alterations in potentially actionable genes. 37 tumor types were enrolled; both rare actionable mutations in common tumor types and actionable mutations in rare tumor types were identified. Conclusion: Multiplex testing in the CLIA environment facilitates genomic characterization across multiple tumor lineages and identification of novel opportunities for genotype-driven trials .
46 citations
TL;DR: Tumors with CSN6/COP1 deregulation may have growth advantage by regulating p27 degradation and subsequent impact on p27 targeted genes, and the negative impact of COP1 on p 27 stability contributes to elevating expression of genes that are suppressed through p27 mediation.
Abstract: The COP9 signalosome subunit 6 (CSN6), which is involved in ubiquitin-mediated protein degradation, is overexpressed in many types of cancer. CSN6 is critical in causing p53 degradation and malignancy, but its target in cell cycle progression is not fully characterized. Constitutive photomorphogenic 1 (COP1) is an E3 ubiquitin ligase associating with COP9 signalosome to regulate important target proteins for cell growth. p27 is a critical G1 CDK inhibitor involved in cell cycle regulation, but its upstream regulators are not fully characterized. Here, we show that the CSN6-COP1 link is regulating p27(Kip1) stability, and that COP1 is a negative regulator of p27(Kip1). Ectopic expression of CSN6 can decrease the expression of p27(Kip1), while CSN6 knockdown leads to p27(Kip1) stabilization. Mechanistic studies show that CSN6 interacts with p27(Kip1) and facilitates ubiquitin-mediated degradation of p27(Kip1). CSN6-mediated p27 degradation depends on the nuclear export of p27(Kip1), which is regulated through COP1 nuclear exporting signal. COP1 overexpression leads to the cytoplasmic distribution of p27, thereby accelerating p27 degradation. Importantly, the negative impact of COP1 on p27 stability contributes to elevating expression of genes that are suppressed through p27 mediation. Kaplan-Meier analysis of tumor samples demonstrates that high COP1 expression was associated with poor overall survival. These data suggest that tumors with CSN6/COP1 deregulation may have growth advantage by regulating p27 degradation and subsequent impact on p27 targeted genes.
28 citations
TL;DR: Rhabdoid clear-cell renal cell carcinoma is transcriptomically distinct and shows a high rate of SETD2 and BAP1 mutations and a low rate of PBRM1 mutations, which are often discordant across different morphologic regions, whereas the gene expression program is relatively stable.
25 citations
TL;DR: SULT1A1 protein levels in cell lysates from 18 leukemia cell lines reliably predicted the susceptibility of the cell lines to NSC-743380 and can be used as a biomarker for identification of N SC- 743380 responders.
Abstract: // Xiao Huang 1,* , Mengru Cao 1,7,* , Li Wang 1 , Shuhong Wu 1 , Xiaoying Liu 1 , Hongyu Li 1 , Hui Zhang 1 , Rui-Yu Wang 2 , Xiaoping Sun 3 , Caimiao Wei 4 , Keith A. Baggerly 5 , Jack A. Roth 1 , Michael Wang 6 , Stephen G. Swisher 1 and Bingliang Fang 1 1 Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 2 Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 3 Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 4 Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 5 Department of Bioinformatics and Computation Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 6 Department of Lymphoma, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 7 The Fourth Department of Medicine Oncology, Harbin Medical University Cancer Hospital, Harbin, China * These authors contributed equally to this work Correspondence: Bingliang Fang, email: // Keywords : Cancer, drug development, biomarker, sulfotransferase, SULT1A1, personalized therapy Received : September 05, 2014 Accepted : November 15, 2014 Published : November 16, 2014 Abstract The small molecule anticancer agent NSC-743380 modulates functions of multiple cancer-related pathways and is highly active in a subset of cancer cell lines in the NCI-60 cell line panel. It also has promising in vivo anticancer activity. However, the mechanisms underlying NSC-743380’s selective anticancer activity remain uncharacterized. To determine biomarkers that may be used to identify responders to this novel anticancer agent, we performed correlation analysis on NSC-743380’s anticancer activity and the gene expression levels in NCI-60 cell lines and characterized the functions of the top associated genes in NSC-743380–mediated anticancer activity. We found sulfotransferase SULT1A1 is causally associated with NSC-743380’s anticancer activity. SULT1A1 was expressed in NSC-743380–sensitive cell lines but was undetectable in resistant cancer cells. Ectopic expression of SULT1A1 in NSC743380 resistant cancer cells dramatically sensitized the resistant cells to NSC-743380. Knockdown of the SULT1A1 in the NSC-743380 sensitive cancer cell line rendered it resistance to NSC-743380. The SULT1A1 protein levels in cell lysates from 18 leukemia cell lines reliably predicted the susceptibility of the cell lines to NSC-743380. Thus, expression of SULT1A1 in cancer cells is required for NSC-743380’s anticancer activity and can be used as a biomarker for identification of NSC-743380 responders.
12 citations
01 Oct 2015
TL;DR: Sarcomatoid clear cell renal cell carcinoma is molecularly distinct from non‐sarcom atoidclear cell renalcell carcinoma, with its genetic programming largely shared by its biphasic morphological components.
Abstract: Sarcomatoid transformation, wherein an epithelioid carcinomatous tumour component coexists with a sarcomatoid histology, is a predictor of poor prognosis in clear cell renal cell carcinoma. Our understanding of sarcomatoid change has been hindered by the lack of molecular examination. Thus, we sought to characterize molecularly the biphasic epithelioid and sarcomatoid components of sarcomatoid clear cell renal cell carcinoma and compare them to non-sarcomatoid clear cell renal cell carcinoma. We examined the transcriptome of the epithelioid and sarcomatoid components of advanced stage sarcomatoid clear cell renal cell carcinoma (n=43) and non-sarcomatoid clear cell renal cell carcinoma (n=37) from independent discovery and validation cohorts using the cDNA microarray and RNA-seq platforms. We analyzed DNA copy number profiles, generated using SNP arrays, from patients with sarcomatoid clear cell renal cell carcinoma (n=10) and advanced non-sarcomatoid clear cell renal cell carcinoma (n=155). The epithelioid and sarcomatoid components of sarcomatoid clear cell renal cell carcinoma had similar gene expression and DNA copy number signatures that were, however, distinct from those of high-grade, high-stage non-sarcomatoid clear cell renal cell carcinoma. Prognostic clear cell renal cell carcinoma gene expression profiles were shared by the biphasic components of sarcomatoid clear cell renal cell carcinoma and the sarcomatoid component showed a partial epithelial-to-mesenchymal transition signature. Our genome-scale microarray-based transcript data were validated in an independent set of sarcomatoid and non-sarcomatoid clear cell renal cell carcinomas using RNA-seq. Sarcomatoid clear cell renal cell carcinoma is molecularly distinct from non-sarcomatoid clear cell renal cell carcinoma, with its genetic programming largely shared by its biphasic morphological components. These data explain why a low percentage of sarcomatoid histology augurs a poor prognosis; suggest the need to modify the pathological grading system and introduce the potential for candidate biomarkers to detect sarcomatoid change preoperatively without specifically sampling the histological sarcomatoid component.
12 citations
TL;DR: A mechanistic principle emerging from this analysis was sensitivity of EOC to miRNA‐mediated release of cell fate specification programs, loss of which may be a prerequisite for development of this disease.
Abstract: Large-scale molecular annotation of epithelial ovarian cancer (EOC) indicates remarkable heterogeneity in the etiology of that disease. This diversity presents a significant obstacle against intervention target discovery. However, inactivation of miRNA biogenesis is commonly associated with advanced disease. Thus, restoration of miRNA activity may represent a common vulnerability among diverse EOC oncogenotypes. To test this, we employed genome-scale, gain-of-function, miRNA mimic toxicity screens in a large, diverse spectrum of EOC cell lines. We found that all cell lines responded to at least some miRNA mimics, but that the nature of the miRNA mimics provoking a response was highly selective within the panel. These selective toxicity profiles were leveraged to define modes of action and molecular response indicators for miRNA mimics with tumor-suppressive characteristics in vivo. A mechanistic principle emerging from this analysis was sensitivity of EOC to miRNA-mediated release of cell fate specification programs, loss of which may be a prerequisite for development of this disease.
8 citations
TL;DR: A small number of highly predictive biomarkers are identified that can distinguish between the two extreme responders and then extrapolate to all patients, achieved using the lone star algorithm that is specifically developed for biological applications.
Abstract: Ovarian cancer is the fifth leading cause of death among female cancers. Front-line therapy for ovarian cancer is platinum-based chemotherapy. However, the response of patients is highly nonuniform. The TCGA database of serous ovarian carcinomas shows that ~10% of patients respond poorly to platinum-based chemotherapy, with tumors relapsing in seven months or less. Another 10% or so enjoy disease-free survival of three years or more. The objective of the present research is to identify a small number of highly predictive biomarkers that can distinguish between the two extreme responders and then extrapolate to all patients. This is achieved using the lone star algorithm that is specifically developed for biological applications. Using this algorithm, we are able to identify biomarker panels of 25 genes (of 12,000 genes) that can be used to classify patients into one of the three groups: super responders, medium responders, and nonresponders. We are also able to determine a discriminant function that can divide the entire patient population into two classes, such that one group has a clear survival advantage over the other. These biomarkers are developed using the TCGA Agilent platform data and cross-validated on the TCGA Affymetrix platform data, as well as entirely independent data from Tothill et al. The P-values on the training data are extremely small, sometimes below machine zero, while the P-values on cross-validation are well below the widely accepted threshold of 0.05.
8 citations
TL;DR: Yang et al. as discussed by the authors developed a novel immunoassay for quantitating TP53-specific autoantibody (AAb) in small volumes (2 uL) of serum.
Abstract: Detection of ovarian cancer in early stage could improve mortality from the disease by 10-30%. Most attempts to utilize serum biomarkers for early detection of ovarian cancer have focused on CA125. As CA125 is expressed by only 80% of ovarian cancers, multiple biomarkers will be required to detect ovarian cancers that fail to express the antigen. In studies with preclinical samples to date, no biomarker has been consistently elevated prior to CA125. Detecting an autologous immune response to tumor associated antigens might provide improved lead time. TP53 is mutated and overexpressed in virtually all high grade serous ovarian cancers. Autoantibodies reactive with wtTP53 have been reported in approximately 15% of ovarian cancers at the time of conventional diagnosis, but most reports have studied a limited number of cases and preclinical sera have not previously been tested. We have developed a novel immunoassay for quantitating TP53-specific autoantibody (AAb) in small volumes (2 uL) of serum. Samples from the MD Anderson Cancer Center Tissue Bank (MDACC), the MDACC Ovarian SPORE NROS screening study, the Australian Ovarian Cancer Study (AOCS) and the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) were used for discovery and validation. Assay cut-offs were determined by including less than 2% false positive samples in each control group (98% specificity of the assay). Elevated titers of TP53 AAb were detected in 13 of 50 sera (26%) from MDACC patients with stage III-IV ovarian cancer and in 4 of 216 sera (1.9%) from healthy controls from the NROS study. Using the same cut-off we detected TP53 AAb in 28 of 108 cases (25.9%), 7 of 109 benign controls (6.4%) and 10 of 464 normal controls (2.1%) from the AOCS study. TP53 AAb was found in 3 of 12 cases (25.0%) in early stage (I/II) and 22 of 90 cases (24.4%) in late stage (III/IV). To further validate the result in the AOCS, we analyzed 2,471 serial serum samples from the UKCTOCS trial. Elevated TP53 AAb was found in 18 of 87 cases (20.7%) and 8 of 435 normal controls (1.8%). Increased titers were detected in 6 of 32 cases (18.8%) in early stage and 12 of 55 cases (21.8%) in late stage. Positivity was found in 11 of 49 cases (22.5%) detected with rising CA125 and 7 of 38 (18.4%) cases not detected with rising CA125. TP53 AAb titers rose prior to CA125 in 7 of 11 cases (63.6%). In 11 TP53 AAb (+) and CA125 (-) cases, TP53 AAb titers rose a mean of 13.5 months and a median of 5 months prior to CA125. In 7 TP53 AAb (+) and CA125 (-) cases, titers rose a mean of 33 months and a median of 29 months prior to cancer diagnosis. Consequently, quantitative assessment of TP53 AAb titers holds promise for earlier detection of ovarian cancer in combination with CA125. Citation Format: Wei-Lei Yang, Archana Simmons, Zhen Lu, Keith Baggerly, Karen Lu, Alex Gentry-Maharaj, Usha Menon, Ian Jacobs, Robert C. Bast. TP53 autoantibody can detect CA125 screen negative ovarian cancer cases and can be elevated prior to CA125 in preclinical ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2838. doi:10.1158/1538-7445.AM2015-2838
3 citations
TL;DR: The hypothesis that clinically defined aggressive variant PCs also share relevant biology with small cell carcinoma (SCC) is supported to support the hypothesis that clinical defined aggressive variants also sharerelevant biology with SCC.
Abstract: 149 Background: Unusually aggressive PC behavior is linked to small cell carcinoma (SCC) morphology. We observed SCC clinical features in association with morphologically heterogeneous PC and, in a prospective clinical trial (NCT00514540), also with chemotherapy responsiveness. Our previous studies in patient derived xenografts (PDX) revealed a distinct molecular profile for SCC. Here we sought to support the hypothesis that clinically defined aggressive variant PCs also share relevant biology with SCC. Methods: 59 PC samples, and 8 PDX, from 42 men registered to NCT00514540 were stained for RB, p53, AR, NKX3-1, ASCL1, AURKA, UBE2C and Ki67. Labeling indices (LI) were calculated as the ratio of positive epithelial cells to total of epithelial cells, at 200x. We determined copy number alterations (CNA) by Onco Scan® in 36 of 59 samples and 8 PDX lines. We used Western Blot and qRT-PCR to expand pathway analyses and their associations in PDX models. Results: Donor patients were similar to non-donor patients...
TL;DR: These findings provide a new understanding of ovarian cancer metastasis and identify a potentially important target for therapeutic intervention.
Abstract: Purpose:The purpose of this study was to identify molecular predictors of residual disease (RD) in high grade serous ovarian cancer (HGSC) and further understand their role in promoting cancer metastasis. Method:The current study analyzed Affymetrix gene expression data of 504 HGSC cases from The Cancer Genome Atlas (TCGA) data to identify differentially expressed genes in tumors from patients with no gross residual disease after surgery (NRD) or presence of RD following initial debulking surgery. It was followed by qRT-PCR analysis of tumor samples for validation purposes. RPPA data of 354 patients from TCGA were analyzed. Immunohistochemical analysis was performed on the patient samples to determine the expression at the protein level (cancer versus stromal cells). Gene array was carried out after overexpressing the selected gene in ovarian cancer cells and the data was analyzed by Ingenuity Pathway Analysis (IPA). In vitro (migration and invasion) and in vivo (orthotopic mouse models) assays were used to determine the biological roles of gene(s) identified from the above analyses. Results: In TCGA data set, 97/107 (90.6%) of the patients with high expression of FABP4 gene had residual disease. In the validation cohort, among the 35 patients predicted to be at high risk for residual disease, 30 (86%) did have residual disease. In contrast, only 54 of the 104 patients with FABP4 values below the decision threshold (52%) had incomplete resection (p = 0.0002). RPPA analysis indicated that expression of FABP4 was positively correlated (Spearman correlation analysis) with expression of several other proteins known to increase tumor cell infiltration and metastasis such as JNK2 (p = 0.194), transglutaminase (p = 0.199), c-kit (p = 0.173), fibronectin (p = 0.364), PKC-A (p = 0.178), collagen-6 (p = 0.197) and paxillin (p = 0.239). It was negatively correlated with E-cadherin (p = -0.246) and claudin-7 (p = -0.201) expression. Immunohistochemical analysis confirmed that apart from endothelial cells and adipocytes, cancer cells also express significant amount of FABP4. In vitro assays showed significant reduction in invasion and migration after silencing FABP4 in HGSC cell lines (p Conclusion:These findings provide a new understanding of ovarian cancer metastasis and identify a potentially important target for therapeutic intervention. Citation Format: Kshipra M. Gharpure, Susan L. Tucker, Shelley M. Herbrich, Anna K. Unruh, Alpa M. Nick, Erin K. Crane, Robert L. Coleman, Jamie Guenthoer, Heather J. Dalton, Sherry Y. Wu, Rajesha Rupaimoole, Gabriel Lopez-Berestein, Bulent Ozpolat, Cristina Ivan, Wei Hu, Keith Baggerly, Anil Sood. Mechanistic and functional implications of FABP4 in ovarian cancer metastasis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2273. doi:10.1158/1538-7445.AM2015-2273
TL;DR: A prospective clinical trial of platinum doublets gave confidence that clinically defined AVPCa also shares chemotherapy sensitivity with SCC, irrespective of morphology, and this work screens for links between the clinical phenotype and molecular profile of AV PCa and corresponding PDX.
Abstract: 5055 Background: AVPCa shares clinical features with small cell carcinoma (SCC) such as resistance to androgen signaling inhibition and frequent visceral metastases. A prospective clinical trial of...
08 Feb 2015
TL;DR: This paper proposes and validate another gene-based signature that can divide patients into two classes, such that there is a clear survival advantage of one group over the other.
Abstract: The TCGA ovarian cancer database shows that about 10% of patients respond poorly to platinum-based chemotherapy, with tumors relapsing in seven months or less. At the other extreme, another 10% or so enjoy disease-free survival of three years or more [1]. At present there are more than a dozen prognostic signatures that claim to predict the survival prospects of a patient based on her genetic profile. Yet, according to [2], none of these signatures performs significantly better than pure guessing. Accordingly, in this paper the objective is to propose and validate another gene-based signature. TCGA ovarian cancer data is analyzed using the “lone star” algorithm [3] that is specifically developed for identifying a small number of highly predictive features from a very large set. Using this algorithm, we are able to identify a biomarker panel of 25 genes (out of 12,000) that can be used to classify patients into one of three groups: super-responders (SR), medium responders (MR), and non-responders (NR). We are also able to determine a discriminant function that can divide patients into two classes, such that there is a clear survival advantage of one group over the other. This signature is developed using the TCGA Agilent platform data, and cross-validated on the TCGA Affymetrix platform data, as well as entirely independent data due to Tothill et al. [4]. The P-value on the training data is below machine zero, while the P-values on cross-validation are well below the widely accepted threshold of 0.05.