Prostate cancer is clinically heterogeneous, ranging from indolent to lethal disease. Expression profiling previously defined three subtypes of prostate cancer, one (subtype-1) linked to clinically favorable behavior, and the others (subtypes-2 and -3) linked with a more aggressive form of the disease. To explore disease heterogeneity at the genomic level, we carried out array-based comparative genomic hybridization (array CGH) on 64 prostate tumor specimens, including 55 primary tumors and 9 pelvic lymph node metastases. Unsupervised cluster analysis of DNA copy number alterations (CNA) identified recurrent aberrations, including a 6q15-deletion group associated with subtype-1 gene expression patterns and decreased tumor recurrence. Supervised analysis further disclosed distinct patterns of CNA among gene-expression subtypes, where subtype-1 tumors exhibited characteristic deletions at 5q21 and 6q15, and subtype-2 cases harbored deletions at 8p21 (NKX3-1) and 21q22 (resulting in TMPRSS2-ERG fusion). Lymph node metastases, predominantly subtype-3, displayed overall higher frequencies of CNA, and in particular gains at 8q24 (MYC) and 16p13, and loss at 10q23 (PTEN) and 16q23. Our findings reveal that prostate cancers develop via a limited number of alternative preferred genetic pathways. The resultant molecular genetic subtypes provide a new framework for investigating prostate cancer biology and explain in part the clinical heterogeneity of the disease. [Cancer Res 2007;67(18):8504-10]

Lung cancer is emerging as a paradigm for disease molecular subtyping, facilitating targeted therapy based on driving somatic alterations. Here, we perform transcriptome analysis of 153 samples representing lung adenocarcinomas, squamous cell carcinomas, large cell lung cancer, adenoid cystic carcinomas and cell lines. By integrating our data with The Cancer Genome Atlas and published sources, we analyze 753 lung cancer samples for gene fusions and other transcriptomic alterations. We show that higher numbers of gene fusions is an independent prognostic factor for poor survival in lung cancer. Our analysis confirms the recently reported CD74-NRG1 fusion and suggests that NRG1, NF1 and Hippo pathway fusions may play important roles in tumors without known driver mutations. In addition, we observe exon skipping events in c-MET, which are attributable to splice site mutations. These classes of genetic aberrations may play a significant role in the genesis of lung cancers lacking known driver mutations.

Though prostate cancer is often indolent, it is nonetheless a leading cause of cancer death. Defining the underlying molecular genetic alterations may lead to new strategies for prevention or treatment. Towards this goal, we performed array-based comparative genomic hybridization (CGH) on 86 primary prostate tumors. Among the most frequent alterations not associated with a known cancer gene, we identified focal deletions within 5q21 in 15 out of 86 (17%) cases. By high-resolution tiling array CGH, the smallest common deletion targeted just one gene, the chromatin remodeler chromodomain helicase DNA-binding protein 1 (CHD1). Expression of CHD1 was significantly reduced in tumors with deletion (P=0.03), and compared with normal prostate (P=0.04). Exon sequencing analysis also uncovered nonsynonymous mutations in 1 out of 7 (14%) cell lines (LAPC4) and in 1 out of 24 (4%) prostate tumors surveyed. RNA interference-mediated knockdown of CHD1 in two nontumorigenic prostate epithelial cell lines, OPCN2 and RWPE-1, did not alter cell growth, but promoted cell invasiveness, and in OPCN2-enhanced cell clonogenicity. Taken together, our findings suggest that CHD1 deletion may underlie cell invasiveness in a subset of prostate cancers, and indicate a possible novel role of altered chromatin remodeling in prostate tumorigenesis.

Objective: To develop a microarray-based method for noninvasive prenatal testing (NIPT) and compare it with next-generation sequencing. Methods: Maternal plasma from 878 pregnant women, including 187 trisomy cases (18 trisomy 13, 37 trisomy 18, 132 trisomy 21), was evaluated for trisomy risk. Targeted chromosomes were analyzed using Digital Analysis of Selected Regions (DANSR™) assays. DANSR products were subsequently divided between two DNA quantification methods: microarrays and next-generation sequencing. For both microarray and sequencing methodologies, the Fetal-Fraction Optimized Risk of Trisomy Evaluation (FORTE™) algorithm was used to determine trisomy risk, assay variability across samples, and compute fetal fraction variability within samples. Results: NIPT using microarrays provided faster and more accurate cell-free DNA (cfDNA) measurements than sequencing. The assay variability, a measure of variance of chromosomal cfDNA counts, was lower for microarrays than for sequencing, 0.051 versus 0.099 (p < 0.0001). Analysis time using microarrays was faster, 7.5 versus 56 h for sequencing. Additionally, fetal fraction precision was improved 1.6-fold by assaying more polymorphic sites with microarrays (p < 0.0001). Microarrays correctly classified all trisomy and nontrisomy cases. Conclusions: NIPT using microarrays delivers more accurate cfDNA analysis than next-generation sequencing and can be performed in less time.