Background Despite more aggressive screening across all demographics and gradual declines in mortality related to prostate cancer (PCa) in the United States, disparities among populations persist. A substantial proportion of African American men (AAM) have a higher overall incidence, earlier age of onset, increased proportion of clinically advanced disease, and increased bone metastases and mortality from PCa compared to European American men (EAM). Limited early evidence indicates that underlying causes for disparities may be observed in tumor-specific gene expression programs. Methods This study used microarray-based methods to measure expression levels for 517 genes that were previously associated with PCa in archived formalin-fixed paraffin embedded (FFPE) specimens; testing the hypothesis that gene expression features of functional consequence to cancer distinguish PCa from AAM and EAM. A t test was conducted comparing AAM to EAM expression levels for each probe on the array. Results Analysis of 639 tumor samples (270 AAM, 369 EAM) showed that 95 genes were overexpressed specifically in PCa from AAM relative to EAM and 132 were overexpressed in PCa from EAM relative to AAM. Furthermore, systems-level analyses highlight the relevant signaling pathways and functions associated with the EAM- or AAM-specific overexpressed gene sets, for example, inflammation and lipid metabolism. Conclusions Results here bring further understanding to the potential for molecular differences for PCa in AAM versus EAM. Impact The results support the notion that therapeutic benefits will be realized when targeted treatments are designed to acknowledge and address a greater spectrum of PCa subtypes and molecular distinctions.
Among breast cancer patients, those diagnosed with the triple-negative breast cancer (TNBC) subtype have the worst prog-nosis. TNBC does not express estrogen receptor-alpha, progesterone receptor, or the HER2 oncogene; therefore, TNBC lacks targets for molecularly-guided therapies. The concept that EGFR oncogene inhibitor drugs could be used as targeted treatment against TNBC has been put forth based on estimates that 30–60% of TNBC express high levels of EGFR. However, results from clinical trials testing EGFR inhibitors, alone or in combination with cytotoxic chemotherapy, did not improve patient outcomes. Results herein offer an explanation as to why EGFR inhibitors failed TNBC patients and support how combining a select antioxidant and an EGFR-specific small molecule kinase inhibitor (SMKI) could be an effective, novel therapeutic strategy. Treatment with CAT-SKL—a re-engineered protein form of the antioxidant enzyme catalase—inhibited cancer stem-like cells (CSCs), and treatment with the EGFR-specific SMKI erlotinib inhibited non-CSCs. Thus, combining the antioxidant CAT-SKL with erlotinib targeted both CSCs and bulk cancer cells in cultures of EGFR-expressing TNBC-derived cells. We also report evidence that the mechanism for CAT-SKL inhibition of CSCs may depend on antioxidant-induced downregulation of a short alternative mRNA splicing variant of the methyl-CpG binding domain 2 gene, isoform MBD2c.
Obesity is a risk factor for triple‐negative breast cancer ( TNBC ) incidence and poor outcomes, but the underlying molecular biology remains unknown. We previously identified in TNBC cell cultures that expression of epigenetic reader methyl‐CpG‐binding domain protein 2 ( MBD 2), specifically the alternative mRNA splicing variant MBD variant 2 ( MBD 2_v2), is dependent on reactive oxygen species ( ROS ) and is crucial for maintenance and expansion of cancer stem cell‐like cells ( CSC s). Because obesity is coupled with inflammation and ROS , we hypothesized that obesity can fuel an increase in MBD 2_v2 expression to promote the tumor‐initiating CSC phenotype in TNBC cells in vivo . Analysis of TNBC patient datasets revealed associations between high tumor MBD 2_v2 expression and high relapse rates and high body mass index ( BMI ). Stable gene knockdown/overexpression methods were applied to TNBC cell lines to elucidate that MBD 2_v2 expression is governed by ROS ‐dependent expression of serine‐ and arginine‐rich splicing factor 2 ( SRSF 2). We employed a diet‐induced obesity ( DIO ) mouse model that mimics human obesity to investigate whether obesity causes increased MBD 2_v2 expression and increased tumor initiation capacity in inoculated TNBC cell lines. MBD 2_v2 and SRSF 2 levels were increased in TNBC cell line‐derived tumors that formed more frequently in DIO mice relative to tumors in lean control mice. Stable MBD 2_v2 overexpression increased the CSC fraction in culture and increased TNBC cell line tumor initiation capacity in vivo . SRSF 2 knockdown resulted in decreased MBD 2_v2 expression, decreased CSC s in TNBC cell cultures, and hindered tumor formation in vivo . This report describes evidence to support the conclusion that MBD 2_v2 expression is induced by obesity and drives TNBC cell tumorigenicity, and thus provides molecular insights into support of the epidemiological evidence that obesity is a risk factor for TNBC . The majority of TNBC patients are obese and rising obesity rates threaten to further increase the burden of obesity‐linked cancers, which reinforces the relevance of this report.
Background: Comprehensive molecular oncogenomic and microRNA (miRNA) profiling of tumors can provide tumor specific oncogenomic and miRNA signatures which can be useful to improve diagnostic accuracy, refine prognostic and predictive capabilities, and may serve as therapeutic targets. In prostate cancer (PCa) such a comprehensive analysis has not been reported. Design: DNA and RNA obtained from scant amounts of fresh frozen PCa tumor tissue samples (n=36) were profiled by (1) Mutation analysis: Sequenom Massarray & OncoCarta VI panel that profiles 238 common cancer mutations in 19 oncogenes (known predictors of response or resistance to targeted therapies);(2) Whole-genome gene expression Microarrays: Illumina Chip;(3) Single Nucleotide Polymorphisms (SNP) with genome-wide coverage:Illumina Omni microarrays. (4)miRNA analysis was done on RNA from FFPE PCa tumor tissues (n=126) using RT-PCR. Data was statistically analyzed & correlated with clinical & pathologic variables. Results: Massarray analysis identified a MET oncogene mutation, variant T992I, in a 49 year old patient with Gleason score 7 (4+3) tumor. Of the 47,224 genes analyzed by gene expression microarrays, 74 genes were significant predictors of high tumor grade by ordinal regression analysis (p<0.0001). TGIF1 was the most significant gene. Of the 731,442 SNP's analyzed, 638 significantly predicted high tumor grade by logistic regression analysis (p<0.0001). There was significant interaction between gene and SNPs in 531 SNP/gene pairs (p<0.05). Ingenuity Pathway analysis revealed the significant predictor genes (p<0.05) were involved in biological pathways for Gene Expression, Cell Cycle, Cancer,” “Inflammatory Response, Cell Death, Infection Mechanism & Cellular Assembly, Organization, Gene Expression, Cancer. P53 gene was found to be at the center hub of significant predicting pathways. Loss of miR-34a expression was found in PCa tissues consistent with the central role of p53. Conclusions: Using high throughput genomic profiling & miRNA analysis of small amounts of fresh-frozen and FFPE PCa tumor samples, we identified clinically relevant hot spot mutation in MET oncogene and several significant genes & SNPs to predict tumor grade. P53 gene is at the center hub of all significant pathways. Loss of miR-34a was consistent with p53 function in PCa. MET oncogene mutation is a novel finding, not previously reported in PCa against which small molecule inhibitors are under development. These molecular signatures may have a significant clinical impact on improving diagnostic and predictive capabilities & in designing targeted therapies to achieve the goal of personalized medicine. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4599. doi:1538-7445.AM2012-4599
An attractive application of expression technologies is to predict drug efficacy or safety using expression data of biomarkers. To evaluate the performance of various classification methods for building predictive models, we applied these methods on six expression datasets. These datasets were from studies using microarray technologies and had either two or more classes. From each of the original datasets, two subsets were generated to simulate two scenarios in biomarker applications. First, a 50-gene subset was used to simulate a candidate gene approach when it might not be practical to measure a large number of genes/biomarkers. Next, a 2000-gene subset was used to simulate a whole genome approach. We evaluated the relative performance of several classification methods by using leave-one-out cross-validation and bootstrap cross-validation. Although all methods perform well in both subsets for a relative easy dataset with two classes, differences in performance do exist among methods for other datasets. Overall, partial least squares discriminant analysis (PLS-DA) and support vector machines (SVM) outperform all other methods. We suggest a practical approach to take advantage of multiple methods in biomarker applications.
Different combinations of genetic and environmental risk factors are known to contribute to the complex etiology of ischemic heart disease (IHD) in different subsets of individuals. We employed the Patient Rule-Induction Method (PRIM) to select the combination of risk factors and risk factor values that identified each of 16 mutually exclusive partitions of individuals having significantly different levels of risk of IHD. PRIM balances two competing objectives: (1) finding partitions where the risk of IHD is high and (2) maximizing the number of IHD cases explained by the partitions. A sequential PRIM analysis was applied to data on the incidence of IHD collected over 8 years for a sample of 5,455 unrelated individuals from the Copenhagen City Heart Study (CCHS) to assess the added value of variation in two candidate susceptibility genes beyond the traditional, lipid and body mass index risk factors for IHD. An independent sample of 362 unrelated individuals also from the city of Copenhagen was used to test the model obtained for each of the hypothesized partitions.
African American men (AAM) are at higher risk of being diagnosed with prostate cancer (PCa) and are at higher risk of dying from the disease compared to European American men (EAM). We sought to better understand PCa molecular diversity that may be underlying these disparities. We performed RNA‐sequencing analysis on high‐grade PCa to identify genes showing differential tumor versus noncancer adjacent tissue expression patterns unique to AAM or EAM. We observed that interleukin‐6 (IL‐6) was upregulated in the nonmalignant adjacent tissue in AAM, but in EAM IL‐6 expression was higher in PCa tissue. Enrichment analysis identified that genes linked to the function of TP53 were overrepresented and downregulated in PCa tissue from AAM. These RNA‐sequencing results informed our subsequent investigation of a diverse PCa cell line panel. We observed that PCa cell lines that are TP53 wild‐type, which includes cell lines derived from AAM (MDA‐PCa‐2b and RC77T), did not express detectable IL‐6 mRNA. IL‐6 treatment of these cells downregulated wild‐type TP53 protein and induced mRNA and protein expression of the epigenetic reader methyl CpG binding domain protein 2 (MBD2), specifically the alternative mRNA splicing variant MBD2_v2. Further investigation validated that upregulation of this short isoform promotes self‐renewal and expansion of PCa cancer stem‐like cells (CSCs). In conclusion, this report contributes to characterizing gene expression patterns in high‐grade PCa and adjacent noncancer tissues from EAM and AAM. The results we describe here advance what is known about the biology associated with PCa race disparities and the molecular signaling of CSCs.
Background The appropriate management of the neck in patients with regionally advanced head and neck cancer remains controversial. The purpose of this study was to retrospectively analyze our institutional experience with up-front neck dissection followed by definitive chemoradiotherapy. Methods Fifty-five patients with radiographic evidence of large or necrotic lymph nodes underwent up-front neck dissection followed by definitive chemoradiation. Results The 5-year overall survival (OS) and progression-free survival (PFS) rates were estimated at 71.3% and 64.7%, respectively. There were 2 failures in the dissected neck, for a control rate of 96.7%. There were 7 locoregional failures and 12 distant failures, for locoregional and distant control rates of 87.3% and 78.2%, respectively. Conclusion Up-front neck dissection followed by chemoradiotherapy resulted in excellent locoregional control, OS, and PFS. Utilization of this strategy should be considered in carefully selected patients with regionally advanced head and neck cancer.
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