Pathological factors evaluating prostate cancer

Identification of recurrent fusion genes across multiple cancer types

Chromosome changes are one of the hallmarks of human malignancies. Chromosomal rearrangement is frequent in human cancers. One of the consequences of chromosomal rearrangement is gene fusions in the cancer genome. We have previously identified a panel of fusion genes in aggressive prostate cancers. In this study, we showed that 6 of these fusion genes are present in 7 different types of human malignancies with variable frequencies. Among them, the CCNH-C5orf30 and TRMT11-GRIK2 gene fusions were found in breast cancer, colon cancer, non-small cell lung cancer, esophageal adenocarcinoma, glioblastoma multiforme, ovarian cancer and liver cancer, with frequencies ranging from 12.9% to 85%. In contrast, four other gene fusions (mTOR-TP53BP1, TMEM135-CCDC67, KDM4-AC011523.2 and LRRC59-FLJ60017) are less frequent. Both TRMT11-GRIK2 and CCNH-C5orf30 are also frequently present in lymph node metastatic cancer samples from the breast, colon and ovary. Thus, detecting these fusion transcripts may have significant biological and clinical implications in cancer patient management.

Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes

Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV) were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason’s grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

High fidelity copy number analysis of formalin-fixed and paraffin-embedded tissues using Affymetrix Cytoscan HD chip

Detection of human genome copy number variation (CNV) is one of the most important analyses in diagnosing human malignancies. Genome CNV detection in formalin-fixed and paraffin-embedded (FFPE) tissues remains challenging due to suboptimal DNA quality and failure to use appropriate baseline controls for such tissues. Here, we report a modified method in analyzing CNV in FFPE tissues using microarray with Affymetrix Cytoscan HD chips. Gel purification was applied to select DNA with good quality and data of fresh frozen and FFPE tissues from healthy individuals were included as baseline controls in our data analysis. Our analysis showed a 91% overlap between CNV detection by microarray with FFPE tissues and chromosomal abnormality detection by karyotyping with fresh tissues on 8 cases of lymphoma samples. The CNV overlap between matched frozen and FFPE tissues reached 93.8%. When the analyses were restricted to regions containing genes, 87.1% concordance between FFPE and fresh frozen tissues was found. The analysis was further validated by Fluorescence In Situ Hybridization on these samples using probes specific for BRAF and CITED2. The results suggested that the modified method using Affymetrix Cytoscan HD chip gave rise to a significant improvement over most of the previous methods in terms of accuracy in detecting CNV in FFPE tissues. This FFPE microarray methodology may hold promise for broad application of CNV analysis on clinical samples.

Endothelial nitric oxide synthase gene polymorphisms and prostate cancer risk in Serbian population

Genome-wide association studies (GWAS) have identified over 46 SNPs associated with human prostate cancer (PCa). Some studies have shown correlation of the nitric oxide synthase (NOS) NOS3 gene polymorphisms with the risk and/or progression of PCa. This study aimed to evaluate the association of NOS3 gene polymorphisms (-786T>C, -764A>G, -714G>T, -690C>T, -649G>A and 894G>T) with PCa risk and progression. 150 patients with PCa, 150 patients with BPH and 100 age-matched healthy controls were recruited in this study. Genotyping of promoter polymorphisms was performed by bi-directional DNA sequencing, and for 894G>T by RFLP analysis. There was no significant association between the alleles and genotypes of these genetic variants and PCa risk. For -786T>C polymorphism, we found that C allele is associated with absence of metastases, assuming dominant genetic model (P = 0.049; OR, 0.50; 95% CI, 0.25-1.00). It was found that, compared with NOS3 -690C>T variant CC genotype, CT and TT genotypes confer decreased risk of developing metastases (dominant model, P = 0.015, OR, 0.24; 95% CI, 0.07-0.88) and show association with low clinical tumour stage, compared with stages T3 and T4 (dominant model, P = 0.046, OR, 0.20; 95% CI, 0.04-1.02). Genetic variants -764A>G, -714G>T, -649G>A were not detected in our study group. There is evidence of an inverse correlation of the NOS3 894G>T minor allele with high serum PSA (>20 ng/ml) (dominant model, P = 0.013, OR, 0.37; 95% CI, 0.17-0.82). Our results suggest that NOS3 gene polymorphisms are genetic susceptibility factors for the progression of PCa and patient outcome.