Phillip G. Febbo

Gene expression correlates of clinical prostate cancer behavior

Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.

Increased Expression of Genes Converting Adrenal Androgens to Testosterone in Androgen-Independent Prostate Cancer

Androgen receptor (AR) plays a central role in prostate cancer, and most patients respond to androgen deprivation therapies, but they invariably relapse with a more aggressive prostate cancer that has been termed hormone refractory or androgen independent. To identify proteins that mediate this tumor progression, gene expression in 33 androgen-independent prostate cancer bone marrow metastases versus 22 laser capture-microdissected primary prostate cancers was compared using Affymetrix oligonucleotide microarrays. Multiple genes associated with aggressive behavior were increased in the androgen-independent metastatic tumors (MMP9, CKS2, LRRC15, WNT5A, EZH2, E2F3, SDC1, SKP2, and BIRC5), whereas a candidate tumor suppressor gene (KLF6) was decreased. Consistent with castrate androgen levels, androgen-regulated genes were reduced 2- to 3-fold in the androgen-independent tumors. Nonetheless, they were still major transcripts in these tumors, indicating that there was partial reactivation of AR transcriptional activity. This was associated with increased expression of AR (5.8-fold) and multiple genes mediating androgen metabolism (HSD3B2, AKR1C3, SRD5A1, AKR1C2, AKR1C1, and UGT2B15). The increase in aldo-keto reductase family 1, member C3 (AKR1C3), the prostatic enzyme that reduces adrenal androstenedione to testosterone, was confirmed by real-time reverse transcription-PCR and immunohistochemistry. These results indicate that enhanced intracellular conversion of adrenal androgens to testosterone and dihydrotestosterone is a mechanism by which prostate cancer cells adapt to androgen deprivation and suggest new therapeutic targets.

mTOR inhibition reverses Akt-dependent prostate intraepithelial neoplasia through regulation of apoptotic and HIF-1-dependent pathways.

Loss of PTEN function leads to activation of phosphoinositide 3-kinase (PI3K) signaling and Akt. Clinical trials are now testing whether mammalian target of rapamycin (mTOR) inhibition is useful in treating PTEN-null cancers. Here, we report that mTOR inhibition induced apoptosis of epithelial cells and the complete reversal of a neoplastic phenotype in the prostate of mice expressing human AKT1 in the ventral prostate. Induction of cell death required the mitochondrial pathway, as prostate-specific coexpression of BCL2 blocked apoptosis. Thus, there is an mTOR-dependent survival signal required downstream of Akt. Bcl2 expression, however, only partially restored intraluminal cell growth in the setting of mTOR inhibition. Expression profiling showed that Hif-1α targets, including genes encoding most glycolytic enzymes, constituted the dominant transcriptional response to AKT activation and mTOR inhibition. These data suggest that the expansion of AKT-driven prostate epithelial cells requires mTOR-dependent survival signaling and activation of HIF-1α, and that clinical resistance to mTOR inhibitors may emerge through BCL2 expression and/or upregulation of HIF-1α activity.

Young Age at Diagnosis Correlates With Worse Prognosis and Defines a Subset of Breast Cancers With Shared Patterns of Gene Expression

PURPOSE Breast cancer arising in young women is correlated with inferior survival and higher incidence of negative clinicopathologic features. The biology driving this aggressive disease has yet to be defined. PATIENTS AND METHODS Clinically annotated, microarray data from 784 early-stage breast cancers were identified, and prospectively defined, age-specific cohorts (young: </= 45 years, n = 200; older: >/= 65 years, n = 211) were compared by prognosis, clinicopathologic variables, mRNA expression values, single-gene analysis, and gene set enrichment analysis (GSEA). Univariate and multivariate analyses were performed. RESULTS Using clinicopathologic variables, young women illustrated lower estrogen receptor (ER) positivity (immunohistochemistry [IHC], P = .027), larger tumors (P = .012), higher human epidermal growth factor receptor 2 (HER-2) overexpression (IHC, P = .075), lymph node positivity (P = .008), higher grade tumors (P < .0001), and trends toward inferior disease-free survival (DFS; hazard ratio = 1.32; P = .094). Using genomic expression analysis, tumors arising in young women had significantly lower ERalpha mRNA (P < .0001), ERbeta (P = .02), and progesterone receptor (PR) expression (P < .0001), but higher HER-2 (P < .0001) and epidermal growth factor receptor (EGFR) expression (P < .0001). Exploratory analysis (GSEA) revealed 367 biologically relevant gene sets significantly distinguishing breast tumors arising in young women. Combining clinicopathologic and genomic variables among tumors arising in young women demonstrated that younger age and lower ERbeta and higher EGFR mRNA expression were significant predictors of inferior DFS. CONCLUSION This large-scale genomic analysis illustrates that breast cancer arising in young women is a unique biologic entity driven by unifying oncogenic signaling pathways, is characterized by less hormone sensitivity and higher HER-2/EGFR expression, and warrants further study to offer this poor-prognosis group of women better preventative and therapeutic options.

Identification of CD15 as a Marker for Tumor-Propagating Cells in a Mouse Model of Medulloblastoma

The growth of many cancers depends on self-renewing cells called cancer stem cells or tumor-propagating cells (TPCs). In human brain tumors, cells expressing the stem cell marker CD133 have been implicated as TPCs. Here we show that tumors from a model of medulloblastoma, the Patched mutant mouse, are propagated not by CD133(+) cells but by cells expressing the progenitor markers Math1 and CD15/SSEA-1. These cells have a distinct expression profile that suggests increased proliferative capacity and decreased tendency to undergo apoptosis and differentiation. CD15 is also found in a subset of human medulloblastomas, and tumors expressing genes similar to those found in murine CD15(+) cells have a poorer prognosis. Thus, CD15 may represent an important marker for TPCs in medulloblastoma.

A 17-gene Assay to Predict Prostate Cancer Aggressiveness in the Context of Gleason Grade Heterogeneity, Tumor Multifocality, and Biopsy Undersampling

BACKGROUND Prostate tumor heterogeneity and biopsy undersampling pose challenges to accurate, individualized risk assessment for men with localized disease. OBJECTIVE To identify and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology. DESIGN, SETTING, AND PARTICIPANTS Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). OUTCOME MEASURES AND STATISTICAL ANALYSIS The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. RESULTS AND LIMITATIONS Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3.0; p=0.003) at surgical pathology. GPS predicted high-grade and/or high-stage disease after controlling for established clinical factors (p<0.005) such as an OR of 2.1 (95% CI, 1.4-3.2) when adjusting for Cancer of the Prostate Risk Assessment score. A limitation of the validation study was the inclusion of men with low-volume intermediate-risk PCa (Gleason score 3+4), for whom some providers would not consider AS. CONCLUSIONS Genes representing multiple biological pathways discriminate PCa aggressiveness in biopsy tissue despite tumor heterogeneity, multifocality, and limited sampling at time of biopsy. The biopsy-based 17-gene GPS improves prediction of the presence or absence of adverse pathology and may help men with PCa make more informed decisions between AS and immediate treatment. PATIENT SUMMARY Prostate cancer (PCa) is often present in multiple locations within the prostate and has variable characteristics. We identified genes with expression associated with aggressive PCa to develop a biopsy-based, multigene signature, the Genomic Prostate Score (GPS). GPS was validated for its ability to predict men who have high-grade or high-stage PCa at diagnosis and may help men diagnosed with PCa decide between active surveillance and immediate definitive treatment.

Prostate intraepithelial neoplasia induced by prostate restricted Akt activation: The MPAKT model

To determine whether Akt activation was sufficient for the transformation of normal prostate epithelial cells, murine prostate restricted Akt kinase activity was generated in transgenic mice (MPAKT mice). Akt expression led to p70S6K activation, prostatic intraepithelial neoplasia (PIN), and bladder obstruction. mRNA expression profiles from MPAKT ventral prostate revealed similarities to human cancer and an angiogenic signature that included three angiogenin family members, one of which was found elevated in the plasma of men with prostate cancer. Thus, the MPAKT model may be useful in studying the role of Akt in prostate epithelial cell transformation and in the discovery of molecular markers relevant to human disease.

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.

An Animal Model of MYC-Driven Medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in children. Patients whose tumors exhibit overexpression or amplification of the MYC oncogene (c-MYC) usually have an extremely poor prognosis, but there are no animal models of this subtype of the disease. Here, we show that cerebellar stem cells expressing Myc and mutant Trp53 (p53) generate aggressive tumors following orthotopic transplantation. These tumors consist of large, pleiomorphic cells and resemble human MYC-driven MB at a molecular level. Notably, antagonists of PI3K/mTOR signaling, but not Hedgehog signaling, inhibit growth of tumor cells. These findings suggest that cerebellar stem cells can give rise to MYC-driven MB and identify a novel model that can be used to test therapies for this devastating disease.

Neoadjuvant Docetaxel before Radical Prostatectomy in Patients with High-Risk Localized Prostate Cancer

Purpose: To determine the clinical, pathologic, and molecular effects of neoadjuvant docetaxel chemotherapy in high-risk localized prostate cancer. Experimental Design: Patients with biopsy Gleason scores of 8 to 10, serum prostate-specific antigen levels >20 ng/mL, and/or clinical stage T3 disease received weekly docetaxel (36 mg/m2) for 6 months, followed by radical prostatectomy, and were monitored with weekly visits, serum prostate-specific antigen measurements, and endorectal magnetic resonance imaging (MRI). Frozen tumor specimens were collected for microarray analysis. Results: The 19 patients enrolled received 82% of the planned chemotherapy. Toxicity was mild to moderate; fatigue and taste disturbance were common. Prostate-specific antigen declines of >50% were seen in 11 of 19 patients (58%; 95% confidence interval, 33-80%) and endorectal MRI showed maximum tumor volume reduction of at least 25% in 13 of 19 patients (68%; 95% confidence interval, 47-85%) and at least 50% in 4 patients (21%; 95% confidence interval, 6-46%). Sixteen patients completed chemotherapy and had radical prostatectomy; none achieved pathologic complete response. Microarray analysis identified coordinate up-regulation of genes involved in androgen metabolism associated with docetaxel therapy. Specifically, RNA expression for genes that decrease cellular levels of bioactive androgens was coordinately increased in response to chemotherapy. Conclusions: Neoadjuvant docetaxel administered for 6 months before radical prostatectomy is feasible, well tolerated, and often results in prostate-specific antigen declines of >50% and decreased tumor volume on endorectal MRI. No pathologic complete responses were observed. Altered androgen metabolism may partially account for the noted declines in prostate-specific antigen and be a mechanism for chemotherapy resistance.