Biomedical subjects

Holly K Dressman

Publications and source records attributed to Holly K Dressman.

At least 19 recordsLinked to original sources

PubMed2006

Genomic signatures to guide the use of chemotherapeutics.

Using in vitro drug sensitivity data coupled with Affymetrix microarray data, we developed gene expression signatures that predict sensitivity to individual chemotherapeutic drugs. Each signature was validated with response data from an independent set of cell line studies. We further show that many of these signatures can accurately predict clinical response in individuals treated with these drugs. Notably, signatures developed to predict response to individual agents, when combined, could also predict response to multidrug regimens. Finally, we integrated the chemotherapy response signatures with signatures of oncogenic pathway deregulation to identify new therapeutic strategies that make use of all available drugs. The development of gene expression profiles that can predict response to commonly used cytotoxic agents provides opportunities to better use these drugs, including using them in combination with existing targeted therapies.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2006

Assessing incomplete deprotection of microarray oligonucleotides in situ.

En masse analysis of gene structure and function by array technologies will have a lasting and profound effect on biology and medicine. This impact can be compromised by low quality of probes within arrays, which we show can be caused by incomplete removal of chemical protecting groups. To solve this quality control problem, we present a sensitive, specific and facile method to detect these groups in situ on arrays using monoclonal antibodies and existing instrumentation. Screening of microarrays with these monoclonal antibodies should guide the consideration given to data derived from these and should enhance the accuracy of the results obtained.

Antibodies, Monoclonal↗

PubMed2006

A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer.

BACKGROUND: Clinical trials have indicated a benefit of adjuvant chemotherapy for patients with stage IB, II, or IIIA--but not stage IA--non-small-cell lung cancer (NSCLC). This classification scheme is probably an imprecise predictor of the prognosis of an individual patient. Indeed, approximately 25 percent of patients with stage IA disease have a recurrence after surgery, suggesting the need to identify patients in this subgroup for more effective therapy. METHODS: We identified gene-expression profiles that predicted the risk of recurrence in a cohort of 89 patients with early-stage NSCLC (the lung metagene model). We evaluated the predictor in two independent groups of 25 patients from the American College of Surgeons Oncology Group (ACOSOG) Z0030 study and 84 patients from the Cancer and Leukemia Group B (CALGB) 9761 study. RESULTS: The lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of NSCLC. Applied to the cohorts from the ACOSOG Z0030 trial and the CALGB 9761 trial, the lung metagene model had an overall predictive accuracy of 72 percent and 79 percent, respectively. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy. CONCLUSIONS: The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

Adult↗

PubMed2006

Phase I trial of sequential low-dose 5-aza-2'-deoxycytidine plus high-dose intravenous bolus interleukin-2 in patients with melanoma or renal cell carcinoma.

PURPOSE: The silencing of gene expression through DNA methylation contributes to defects in antigen presentation and apoptosis in melanoma and renal cell cancer. To determine how a hypomethylating agent would modulate the toxicity and antitumor activity of immunotherapy, we initiated a phase I trial of 5-aza-2'-deoxycytidine (decitabine) plus high-dose interleukin 2 (IL-2). EXPERIMENTAL DESIGN: Patients received s.c. decitabine daily x 5 days on weeks 1 and 2 of a 12-week cycle. High-dose IL-2, consisting of two cycles of IL-2 600,000 IU/kg i.v. q8 hours x 14 doses separated by a 2-week break, was administered starting on week 3. Decitabine was escalated from 0.1 to 0.25 mg/kg. The hypomethylating activity of decitabine was assessed during cycle 1 by measuring hemoglobin F levels and changes in DNA methylation in peripheral blood mononuclear cells. RESULTS: Twenty-one patients with melanoma or renal cell cancer were enrolled. Decitabine did not alter the tolerability of IL-2 but caused grade 4 neutropenia in most patients. Grade 4 neutropenia lasting more than 7 days was the only dose-limiting toxicity, with a trend toward a higher incidence with increasing decitabine doses. Infection occurred in only one patient despite the high incidence of neutropenia, and granulocyte colony-stimulating factor use in several patients expedited neutrophil recovery. Decitabine augmented hemoglobin F levels and altered DNA methylation and gene expression in peripheral blood mononuclear cells in a dose-independent manner that overlapped with the administration of IL-2. Objective responses occurred in 31% of melanoma patients. CONCLUSIONS: Decitabine can be safely administered with high-dose IL-2 and may enhance the activity of IL-2 in melanoma.

Adult↗

PubMed2006

Toxicogenomic studies of the rat brain at an early time point following acute sarin exposure.

We have studied sarin-induced global gene expression patterns at an early time point (2 h: 0.5 x LD50) using Affymetrix Rat Neurobiology U34 chips and male Sprague-Dawley rats. A total of 46 genes showed statistically significant alterations from control levels. Three gene categories contained more of the altered genes than any other groups: ion channel (8 genes) and calcium channel and binding proteins (6 genes). Alterations were also found in the following gene groups: ATPases and ATP-based transporters (4), growth factors (4), G-protein-coupled receptor pathway-related molecules (3), neurotransmission and neurotransmitter transporters (3), cytoskeletal and cell adhesion molecules (2), hormones (2), mitochondria-associated proteins (2), myelin proteins (2), stress-activated molecules (2), cytokine (1), caspase (1), GABAnergic (1), glutamergic (1), immediate early gene (1), prostaglandin (1), transcription factor (1), and tyrosine phosphorylation molecule (1). Persistent alteration of the following genes also were noted: Arrb1, CaMKIIa, CaMKIId, Clcn5, IL-10, c-Kit, and Plp1, suggesting altered GPCR, kinase, channel, and cytokine pathways. Selected genes from the microarray data were further validated using relative RT-PCR. Some of those genes (GFAP, NF-H, CaMKIIa, Calm, and MBP) have been shown by other laboratories and ours, to be involved in the pathogenesis of sarin-induced pathology and organophosphate-induced delayed neurotoxicity (OPIDN). Induction of both proapoptotic (Bcl2l11, Casp6) and antiapoptotic (Bcl-X) genes, besides suppression of p21, suggest complex cell death/protection-related mechanisms operating early on. Principal component analysis (PCA) of the expression data confirmed that the changes in gene expression are a function of sarin exposure, since the control and treatment groups separated clearly. Our model (based on current and previous studies) indicates that both degenerative and regenerative pathways are activated early and contribute to the level of neurodegeneration at a later time, leading to neuro-pathological alterations.

Animals↗

PubMed2006

ALK1 signalling analysis identifies angiogenesis related genes and reveals disparity between TGF-beta and constitutively active receptor induced gene expression.

BACKGROUND: TGF-beta1 is an important angiogenic factor involved in the different aspects of angiogenesis and vessel maintenance. TGF-beta signalling is mediated by the TbetaRII/ALK5 receptor complex activating the Smad2/Smad3 pathway. In endothelial cells TGF-beta utilizes a second type I receptor, ALK1, activating the Smad1/Smad5 pathway. Consequently, a perturbance of ALK1, ALK5 or TbetaRII activity leads to vascular defects. Mutations in ALK1 cause the vascular disorder hereditary hemorrhagic telangiectasia (HHT). METHODS: The identification of ALK1 and not ALK5 regulated genes in endothelial cells, might help to better understand the development of HHT. Therefore, the human microvascular endothelial cell line HMEC-1 was infected with a recombinant constitutively active ALK1 adenovirus, and gene expression was studied by using gene arrays and quantitative real-time PCR analysis. RESULTS: After 24 hours, 34 genes were identified to be up-regulated by ALK1 signalling. Analysing ALK1 regulated gene expression after 4 hours revealed 13 genes to be up- and 2 to be down-regulated. Several of these genes, including IL-8, ET-1, ID1, HPTPeta and TEAD4 are reported to be involved in angiogenesis. Evaluation of ALK1 regulated gene expression in different human endothelial cell types was not in complete agreement. Further on, disparity between constitutively active ALK1 and TGF-beta1 induced gene expression in HMEC-1 cells and primary HUVECs was observed. CONCLUSION: Gene array analysis identified 49 genes to be regulated by ALK1 signalling and at least 14 genes are reported to be involved in angiogenesis. There was substantial agreement between the gene array and quantitative real-time PCR data. The angiogenesis related genes might be potential HHT modifier genes. In addition, the results suggest endothelial cell type specific ALK1 and TGF-beta signalling.

Activin Receptors, Type II↗

PubMed2006

Gene expression profiles of multiple breast cancer phenotypes and response to neoadjuvant chemotherapy.

PURPOSE: Breast cancer is a heterogeneous disease, and markers for disease subtypes and therapy response remain poorly defined. For that reason, we employed a prospective neoadjuvant study in locally advanced breast cancer to identify molecular signatures of gene expression correlating with known prognostic clinical phenotypes, such as inflammatory breast cancer or the presence of hypoxia. In addition, we defined molecular signatures that correlate with response to neoadjuvant chemotherapy. EXPERIMENTAL DESIGN: Tissue was collected under ultrasound guidance from patients with stage IIB/III breast cancer before four cycles of neoadjuvant liposomal doxorubicin paclitaxel chemotherapy combined with local whole breast hyperthermia. Gene expression analysis was done using Affymetrix U133 Plus 2.0 GeneChip arrays. RESULTS: Gene expression patterns were identified that defined the phenotypes of inflammatory breast cancer as well as tumor hypoxia. In addition, molecular signatures were identified that predicted the persistence of malignancy in the axillary lymph nodes after neoadjuvant chemotherapy. This persistent lymph node signature significantly correlated with disease-free survival in two separate large populations of breast cancer patients. CONCLUSIONS: Gene expression signatures have the capacity to identify clinically significant features of breast cancer and can predict which individual patients are likely to be resistant to neoadjuvant therapy, thus providing the opportunity to guide treatment decisions.

Breast Neoplasms↗

PubMed2005

Gene expression profiles of the rat brain both immediately and 3 months following acute sarin exposure.

We have studied sarin-induced global gene expression patterns at an early time point (15 min; 0.5xLD50) and a later time point (3 months; 1xLD50) using Affymetrix: Rat Neurobiology U34 chips in male, Sprague-Dawley rats and have identified a total of 65 (early) and 38 (late) genes showing statistically significant alterations from control levels at 15 min and 3 months, respectively. At the early time point, those that are classified as ion channel, cytoskeletal and cell adhesion molecules, in addition to neuropeptides and their receptors predominated over all other groups. The other groups included: cholinergic signaling, calcium channel and binding proteins, transporters, chemokines, GABAnergic, glutamatergic, aspartate, catecholaminergic, nitric oxide synthase, purinergic, and serotonergic signaling molecules. At the late time point, genes that are classified as calcium channel and binding proteins, cytoskeletal and cell adhesion molecules and GABAnergic signaling molecules were most prominent. Seven molecules (Ania-9, Arrb-1, CX-3C, Gabab-1d, Nos-2a, Nrxn-1b, PDE2) were identified that showed altered persistent expression in both time points. Selected genes from each of these time points were further validated using semi quantitative RT-PCR approaches. Some of the genes that were identified in the present study have been shown to be involved in organophosphate-induced neurotoxicity by both other groups as well as ours. Principal component analysis (PCA) of the expression data from both time points was used for comparative analysis of the gene expression, which indicated that the changes in gene expression were a function of dose and time of euthanasia after the treatment. Our model also predicts that besides dose and duration of post-treatment period, age and possibly other factors may be playing important roles in the regulation of pathways, leading to the neurotoxicity.

Animals↗

PubMed2005

Molecular profile and partial functional analysis of novel endothelial cell-derived growth factors that regulate hematopoiesis.

Recent progress has been made in the identification of the osteoblastic cellular niche for hematopoietic stem cells (HSCs) within the bone marrow (BM). Attempts to identify the soluble factors that regulate HSC self-renewal have been less successful. We have demonstrated that primary human brain endothelial cells (HUBECs) support the ex vivo amplification of primitive human BM and cord blood cells capable of repopulating non-obese diabetic/severe combined immunodeficient repopulating (SCID) mice (SCID repopulating cells [SRCs]). In this study, we sought to characterize the soluble hematopoietic activity produced by HUBECs and to identify the growth factors secreted by HUBECs that contribute to this HSC-supportive effect. Extended noncontact HUBEC cultures supported an eight-fold increase in SRCs when combined with thrombopoietin, stem cell factor, and Flt-3 ligand compared with input CD34(+) cells or cytokines alone. Gene expression analysis of HUBEC biological replicates identified 65 differentially expressed, nonredundant transcripts without annotated hematopoietic activity. Gene ontology studies of the HUBEC transcriptome revealed a high concentration of genes encoding extracellular proteins with cell-cell signaling function. Functional analyses demonstrated that adrenomedullin, a vasodilatory hormone, synergized with stem cell factor and Flt-3 ligand to induce the proliferation of primitive human CD34(+)CD38(-)lin(-) cells and promoted the expansion of CD34(+) progenitors in culture. These data demonstrate the potential of primary HUBECs as a reservoir for the discovery of novel secreted proteins that regulate human hematopoiesis.

Adrenomedullin↗

PubMed2005

Oncogenic pathway signatures in human cancers as a guide to targeted therapies.

The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.

Animals↗

PubMed2005

Gene-expression patterns predict phenotypes of immune-mediated thrombosis.

Antiphospholipid antibody syndrome (APS) is a complex autoimmune thrombotic disorder with defined clinical phenotypes. Although not all patients with elevated antiphospholipid antibody (aPLA) levels develop complications, the severity of these potential events mandates aggressive and extended lifelong anti-thrombotic therapy. One hundred twenty-nine patients (57 patients with APS and venous thromboembolism [VTE], 32 patients with VTE without aPLA, 32 patients with aPLA only, and 8 healthy patients) were enrolled. RNA from peripheral-blood collection was used for DNA microarray analysis. Patterns of gene expression that characterize APS as well as thrombosis in the presence of aPLA were identified by hierarchical clustering and binary regression methods. Gene-expression profiles identify and predict individuals with APS from patients with VTE without aPLA. Importantly, similar methods identified expression profiles that accurately predicted those patients with aPLA at high risk for thrombotic events. All profiles were validated in independent cohorts of patients. The ability to predict APS, but more importantly, those patients at risk for venous thrombosis, represents a paradigm for a genomic approach that can be applied to other populations of patients with venous thrombosis, providing for more effective clinical management of disease, while also reflecting the possible underlying biologic processes.

Adult↗

PubMed2005

Distinctions in the specificity of E2F function revealed by gene expression signatures.

The E2F family of transcription factors provides essential activities for coordinating the control of cellular proliferation and cell fate. Both E2F1 and E2F3 proteins have been shown to be particularly important for cell proliferation, whereas the E2F1 protein has the capacity to promote apoptosis. To explore the basis for this specificity of function, we used DNA microarray analysis to probe for the distinctions in the two E2F activities. Gene expression profiles that distinguish either E2F1- or E2F3-expressing cells from quiescent cells are enriched in genes encoding cell cycle and DNA replication activities, consistent with many past studies. E2F1 profile is also enriched in genes known to function in apoptosis. We also identified patterns of gene expression that specifically differentiate the activity of E2F1 and E2F3; this profile is enriched in genes known to function in mitosis. The specificity of E2F function has been attributed to protein interactions mediated by the marked box domain, and we now show that chimeric E2F proteins generate expression signatures that reflect the origin of the marked box, thus linking the biochemical mechanism for specificity of function with specificity of gene activation.

Animals↗

PubMed2005

Gene expression changes and signaling events associated with the direct antimelanoma effect of IFN-gamma.

IFN-gamma plays a role in the response to melanoma indirectly through its effect on the immune system and directly through its antiproliferative and proapoptotic effects on melanoma cells. To understand the molecular basis for the direct antimelanoma effect of IFN-gamma, we studied IFN-induced changes in gene expression and signaling among three human melanoma cell lines (DM6, DM93, and 501mel). These were resistant to the antimelanoma effect of IFN-alpha, and only DM6 cells exhibited growth inhibition and apoptosis with IFN-gamma. Through DNA microarray analysis, we found that the antimelanoma effect of IFN-gamma in DM6 was associated with the down-regulation of multiple genes involved in G-protein signaling and phospholipase C activation (including Rap2B and calpain 3) as well as the down-regulation of genes involved in melanocyte/melanoma survival (MITF and SLUG), apoptosis inhibition (Bcl2A1 and galectin-3), and cell cycling (CDK2). The antimelanoma effect of IFN-gamma was also associated with the up-regulation of the proapoptotic dependence receptor UNC5H2 and the Wnt inhibitor Dkk-1. Whereas both IFNs were able to activate Stat1 in all cell lines, the delayed activation of the extracellular signal-regulated kinase, p38, and c-Jun NH2-terminal kinase mitogen-activated protein kinases occurred only in DM6 with IFN-gamma, and the effect of IFN-gamma on cell growth and survival as well as gene expression in DM6 was dependent on the coordinate activation of MEK1 and p38. These findings provide new insights into the signaling events and gene expression changes associated with growth inhibition and apoptosis in melanoma and may thereby assist in identifying new targets for the treatment of melanoma.

Antineoplastic Agents↗

PubMed2005

Gene expression profiling and genetic markers in glioblastoma survival.

Despite the strikingly grave prognosis for older patients with glioblastomas, significant variability in patient outcome is experienced. To explore the potential for developing improved prognostic capabilities based on the elucidation of potential biological relationships, we did analyses of genes commonly mutated, amplified, or deleted in glioblastomas and DNA microarray gene expression data from tumors of glioblastoma patients of age >50 for whom survival is known. No prognostic significance was associated with genetic changes in epidermal growth factor receptor (amplified in 17 of 41 patients), TP53 (mutated in 11 of 41 patients), p16INK4A (deleted in 15 of 33 patients), or phosphatase and tensin homologue (mutated in 15 of 41 patients). Statistical analysis of the gene expression data in connection with survival involved exploration of regression models on small subsets of genes, based on computational search over multiple regression models with cross-validation to assess predictive validity. The analysis generated a set of regression models that, when weighted and combined according to posterior probabilities implied by the statistical analysis, identify patterns in expression of a small subset of genes that are associated with survival and have value in assessing survival risks. The dominant genes across such multiple regression models involve three key genes-SPARC (Osteonectin), Doublecortex, and Semaphorin3B-which play key roles in cellular migration processes. Additional analysis, based on statistical graphical association models constructed using similar computational analysis methods, reveals other genes which support the view that multiple mediators of tumor invasion may be important prognostic factor in glioblastomas in older patients.

Aged↗

PubMed2005

Patterns of gene expression that characterize long-term survival in advanced stage serous ovarian cancers.

PURPOSE: A better understanding of the underlying biology of invasive serous ovarian cancer is critical for the development of early detection strategies and new therapeutics. The objective of this study was to define gene expression patterns associated with favorable survival. EXPERIMENTAL DESIGN: RNA from 65 serous ovarian cancers was analyzed using Affymetrix U133A microarrays. This included 54 stage III/IV cases (30 short-term survivors who lived <3 years and 24 long-term survivors who lived >7 years) and 11 stage I/II cases. Genes were screened on the basis of their level of and variability in expression, leaving 7,821 for use in developing a predictive model for survival. A composite predictive model was developed that combines Bayesian classification tree and multivariate discriminant models. Leave-one-out cross-validation was used to select and evaluate models. RESULTS: Patterns of genes were identified that distinguish short-term and long-term ovarian cancer survivors. The expression model developed for advanced stage disease classified all 11 early-stage ovarian cancers as long-term survivors. The MAL gene, which has been shown to confer resistance to cancer therapy, was most highly overexpressed in short-term survivors (3-fold compared with long-term survivors, and 29-fold compared with early-stage cases). These results suggest that gene expression patterns underlie differences in outcome, and an examination of the genes that provide this discrimination reveals that many are implicated in processes that define the malignant phenotype. CONCLUSIONS: Differences in survival of advanced ovarian cancers are reflected by distinct patterns of gene expression. This biological distinction is further emphasized by the finding that early-stage cancers share expression patterns with the advanced stage long-term survivors, suggesting a shared favorable biology.

Case-Control Studies↗

PubMed2005

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Gene Expression Profiling↗

PubMed2004

Prediction of optimal versus suboptimal cytoreduction of advanced-stage serous ovarian cancer with the use of microarrays.

OBJECTIVE: The purpose of this study was to define gene expression patterns that are associated with the optimal versus suboptimal debulking of advanced-stage serous ovarian cancers. STUDY DESIGN: RNA from 44 advanced serous ovarian cancers (19 optimal, 25 suboptimal) was evaluated with microarrays that contain >22,000 genes. Genes were screened on the basis of their association with debulking status to obtain the top 120 differentially expressed genes. These genes were then used to develop a predictive model for debulking status, which was subjected to out-of-sample cross validation. RESULTS: We found that patterns of expression of 32 genes can distinguish between optimal and suboptimal debulking with 72.7% predictive accuracy. An analysis of the data that were based on clusters of co-ordinately expressed genes resulted in only a marginal improvement in predictive accuracy (75%). CONCLUSION: These data support the hypothesis that favorable survival that is associated with optimal debulking of advanced ovarian cancers is due to, at least in part, the underlying biologic characteristics of these cancers.

Biomarkers, Tumor↗

PubMed2004

Gene expression patterns that characterize advanced stage serous ovarian cancers.

OBJECTIVE: To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis. METHODS: Using genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR). RESULTS: Hierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively. CONCLUSION: Global expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making.

Apoptosis Regulatory Proteins↗