Evolving transcriptomic fingerprint based on genome-wide data as prognostic tools in prostate cancer

Differential Expression of Genes for Ubiquitin Ligases in Medulloblastoma Subtypes

Using publically available datasets on gene expression in medulloblastoma (MB) subtypes, we selected genes for ubiquitin ligases and identified statistically those that best predicted each of the four major MB subgroups as separate disease entities. We identify a gene coding for an ubiquitin ligase, ZNRF3, whose overexpression alone can predict the WNT subgroup for 100% in the Pfister dataset. For the SHH subgroup, we identify a gene for a regulatory subunit of the protein phosphatase 2A (PP2A), PPP2R2C, as the major predictor among the E3 ligases genes. The ubiquitin and ubiquitin-like conjugation database (UUCD) lists PPP2R2C as coding for a Cullin Ring ubiquitin ligase adaptor. For group 3 MBs, the best ubiquitin ligase predictor was PPP2R2B, a gene which codes for another regulatory subunit of the PP2A holoenzyme. For group 4, the best E3 gene predictors were MID2, ZBTB18, and PPP2R2A, which codes for a third PP2A regulatory subunit. Heatmap analysis of the E3 gene data shows that expression of ten genes for ubiquitin ligases can be used to classify MBs into the four major consensus subgroups. This was illustrated by analysis of gene expression of ubiquitin ligases of the Pfister dataset and confirmed in the dataset of Cavalli. We conclude that genes for ubiquitin ligases can be used as genetic markers for MB subtypes and that the proteins coded for by these genes should be investigated as subtype specific therapeutic targets for MB.

Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer

BACKGROUND

We examined the ability of a biopsy-based 22-marker genomic classifier (GC) to predict for distant metastases after radiation and a median of 6 months of androgen deprivation therapy (ADT).

METHODS

We studied 100 patients with intermediate-risk (55%) and high-risk (45%) prostate cancer who received definitive radiation plus a median of 6 months of ADT (range 3-39 months) from 2001-2013 at a single center and had available biopsy tissue. Six to ten 4 micron sections of the needle biopsy core with the highest Gleason score and percentage of tumor involvement were macrodissected for RNA extraction. GC scores (range, 0.04-0.92) were determined. The primary end point of the study was time to distant metastasis. Median follow-up was 5.1 years. There were 18 metastases during the study period.

RESULTS

On univariable analysis (UVA), each 0.1 unit increase in GC score was significantly associated with time to distant metastasis (hazard ratio: 1.40 (1.10-1.84), P=0.006) and remained significant after adjusting for clinical variables on multivariable analysis (MVA) (adjusted hazard ratio: 1.36 (1.04-1.83), P=0.024). The c-index for 5-year distant metastasis was 0.45 (95% confidence interval: 0.27-0.64) for Cancer of the Prostate Risk Assessment score, 0.63 (0.40-0.78) for National Comprehensive Cancer Network (NCCN) risk groups, and 0.76 (0.57-0.89) for the GC score. Using pre-specified GC risk categories, the cumulative incidence of metastasis for GC>0.6 reached 20% at 5 years after radiation (P=0.02).

CONCLUSIONS

We believe this is the first demonstration of the ability of the biopsy-based GC score to predict for distant metastases after definitive radiation and ADT for intermediate- and high-risk prostate cancer. Patients with the highest GC risk (GC>0.6) had high rates of metastasis despite multi-modal therapy suggesting that they could potentially be candidates for treatment intensification and/or enrollment in clinical trials of novel therapy.

Observed correlation between the expression levels of catalytic subunit, Cβ2, of cyclic adenosine monophosphate-dependent protein kinase and prostate cancer aggressiveness

BACKGROUND

Today overtreatment of indolent prostate cancers and undertreatment of aggressive prostate cancer are a major concern for patients, their families, and the health care system. New biomarkers distinguishing indolent and aggressive prostate cancer are needed to improve precision medicine. In prostate cancer, protein kinase A (PKA) is known to activate the androgen receptor and published data indicate that PKA subunits can act as predictive markers for response to radiation and chemotherapy. We have previously shown that the catalytic subunit, Cβ2, of PKA is up-regulated in prostate cancer and we would in this study investigate the potential of Cβ2 to become a prognostic biomarker in prostate cancer.

METHODS

Data were sampled from a total of 241 patients from 3 independent cohorts. We measured and compared Cβ2 messenger RNA (mRNA) levels in prostate tumor and nontumor samples (n = 22), and exon levels in a cohort of 50 tumor samples, as well as acquiring mRNA data from the publicly available database The cancer genome atlas (n = 169).

RESULTS

Cβ2 mRNA was up-regulated in prostate cancer in all 3 cohorts, measured by 3 different methods. Furthermore, the relative Cβ2 mRNA expression levels were lower in prostate cancer samples with Gleason score 8 to 10 compared with samples with Gleason score<8 (P = 0.004). Finally, low expression of Cβ2 mRNA in prostate cancer biopsies correlated with poor survival (hazard ratio = 0.20; 95% CI: 0.048-0.86; P = 0.031), adjusted for risk group and age.

CONCLUSIONS

We suggest that Cβ2 mRNA expression may be used as a biomarker together with established prognostic markers to more precisely predict aggressiveness in patients diagnosed with prostate cancer.

Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens

Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed, paraffin-embedded biopsy specimens has many unique challenges. Herein, we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers in diagnostic prostate needle core biopsy specimens. One-hundred fifty-eight samples from diagnostic needle core biopsy specimens (BX) and radical prostatectomies (RPs) were collected from 33 patients at three hospitals; each patient provided up to six tumor and benign samples. Genome-wide transcriptomic profiles were generated using Affymetrix Human Exon arrays for comparison of gene expression alterations and prognostic signatures between the BX and RP samples. A sufficient amount of RNA (>100 ng) was obtained from all RP specimens (n = 77) and from 72 of 81 of BX specimens. Of transcriptomic features detected in RP, 95% were detectable in BX tissues and demonstrated a high correlation (r = 0.96). Likewise, an expression signature pattern validated on RPs (Decipher prognostic test) showed correlation between BX and RP (r = 0.70). Of matched BX and RP pairs, 25% showed discordant molecular subtypes. Genome-wide exon arrays yielded data of comparable quality from biopsy and RP tissues. The high concordance of tumor-associated gene expression changes between BX and RP samples provides evidence for the adequate performance of the assay platform with samples from prostate needle biopsy specimens with limited tumor volume.