Clonal evolution in breast cancer revealed by single nucleus genome sequencing.

Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.

Optimized Prediction of Extreme Treatment Outcomes in Ovarian Cancer.

Ovarian cancer is the fifth leading cause of death among female cancers. Front-line therapy for ovarian cancer is platinum-based chemotherapy. However, the response of patients is highly nonuniform. The TCGA database of serous ovarian carcinomas shows that ~10% of patients respond poorly to platinum-based chemotherapy, with tumors relapsing in seven months or less. Another 10% or so enjoy disease-free survival of three years or more. The objective of the present research is to identify a small number of highly predictive biomarkers that can distinguish between the two extreme responders and then extrapolate to all patients. This is achieved using the lone star algorithm that is specifically developed for biological applications. Using this algorithm, we are able to identify biomarker panels of 25 genes (of 12,000 genes) that can be used to classify patients into one of the three groups: super responders, medium responders, and nonresponders. We are also able to determine a discriminant function that can divide the entire patient population into two classes, such that one group has a clear survival advantage over the other. These biomarkers are developed using the TCGA Agilent platform data and cross-validated on the TCGA Affymetrix platform data, as well as entirely independent data from Tothill et al. The P-values on the training data are extremely small, sometimes below machine zero, while the P-values on cross-validation are well below the widely accepted threshold of 0.05.

Clinically relevant microRNAs in ovarian cancer.

microRNAs (miRNAs/miRs) belong to a class of small noncoding RNAs that can negatively regulate messenger RNA (mRNA) expression of target genes. miRNAs are involved in multiple aspects of ovarian cancer cell dysfunction and the phenotype of ovarian cancer cells can be modified by targeting miRNA expression. miRNA profiling has detected a number of candidate miRNAs with the potential to regulate many important biologic functions in ovarian cancer, but their role still needs to be clarified, given the remarkable heterogeneity among ovarian cancers and the context-dependent role of miRNAs. This review summarizes the data collected from The Cancer Genome Atlas (TCGA) and several other genome-wide projects to identify dysregulated miRNAs in ovarian cancers. Copy number variations (CNVs), epigenetic alterations, and oncogenic mutations are also discussed that affect miRNA levels in ovarian disease. Emphasis is given to the role of particular miRNAs in altering expression of genes in human ovarian cancers with the potential to provide diagnostic, prognostic, and therapeutic targets. Particular attention has been given to TP53, BRCA1/2, CA125 (MUC16), HE4 (WFDC2), and imprinted genes such as ARHI (DIRAS3). A better understanding of the abnormalities in miRNA expression and downstream transcriptional and biologic consequences will provide leads for more effective biomarkers and translational approaches in the management of ovarian cancer.

Most expression and splicing changes in myotonic dystrophy type 1 and type 2 skeletal muscle are shared with other muscular dystrophies.

The prevailing pathomechanistic paradigm for myotonic dystrophy (DM) is that aberrant expression of embryonic/fetal mRNA/protein isoforms accounts for most aspects of the pleiotropic phenotype. To identify aberrant isoforms in skeletal muscle of DM1 and DM2 patients, we performed exon-array profiling and RT-PCR validation on the largest DM sample set to date, including Duchenne, Becker and tibial muscular dystrophy (NMD) patients as disease controls, and non-disease controls. Strikingly, most expression and splicing changes in DM patients were shared with NMD controls. Comparison between DM and NMD identified almost no significant differences. We conclude that DM1 and DM2 are essentially identical for dysregulation of gene expression, and DM expression changes represent a subset of broader spectrum dystrophic changes. We found no evidence for qualitative splicing differences between DM1 and DM2. While some DM-specific splicing differences exist, most of the DM splicing differences were also seen in NMD controls. SSBP3 exon 6 missplicing was observed in all diseased muscle and led to reduced protein. We conclude there is no widespread DM-specific spliceopathy in skeletal muscle and suggest that missplicing in DM (and NMD) may not be the driving mechanism for the muscle pathology, since the same pathways show expression changes unrelated to splicing.

Molecular biomarkers of residual disease after surgical debulking of high-grade serous ovarian cancer.

PURPOSE: Residual disease following primary cytoreduction is associated with adverse overall survival in patients with epithelial ovarian cancer. Accurate identification of patients at high risk of residual disease has been elusive, lacking external validity and prompting many to undergo unnecessary surgical exploration. Our goal was to identify and validate molecular markers associated with high rates of residual disease. METHODS: We interrogated two publicly available datasets from chemonaïve primary high-grade serous ovarian tumors for genes overexpressed in patients with residual disease and significant at a 10% false discovery rate (FDR) in both datasets. We selected genes with wide dynamic range for validation in an independent cohort using quantitative RT-PCR to assay gene expression, followed by blinded prediction of a patient subset at high risk for residual disease. Predictive success was evaluated using a one-sided Fisher exact test. RESULTS: Forty-seven probe sets met the 10% FDR criterion in both datasets. These included FABP4 and ADH1B, which tracked tightly, showed dynamic ranges >16-fold and had high expression levels associated with increased incidence of residual disease. In the validation cohort (n = 139), FABP4 and ADH1B were again highly correlated. Using the top quartile of FABP4 PCR values as a prespecified threshold, we found 30 of 35 cases of residual disease in the predicted high-risk group (positive predictive value = 86%) and 54 of 104 among the remaining patients (P = 0.0002; OR, 5.5). CONCLUSION: High FABP4 and ADH1B expression is associated with significantly higher risk of residual disease in high-grade serous ovarian cancer. Patients with high tumoral levels of these genes may be candidates for neoadjuvant chemotherapy.

Tumour angiogenesis regulation by the miR-200 family.

The miR-200 family is well known to inhibit the epithelial-mesenchymal transition, suggesting it may therapeutically inhibit metastatic biology. However, conflicting reports regarding the role of miR-200 in suppressing or promoting metastasis in different cancer types have left unanswered questions. Here we demonstrate a difference in clinical outcome based on miR-200's role in blocking tumour angiogenesis. We demonstrate that miR-200 inhibits angiogenesis through direct and indirect mechanisms by targeting interleukin-8 and CXCL1 secreted by the tumour endothelial and cancer cells. Using several experimental models, we demonstrate the therapeutic potential of miR-200 delivery in ovarian, lung, renal and basal-like breast cancers by inhibiting angiogenesis. Delivery of miR-200 members into the tumour endothelium resulted in marked reductions in metastasis and angiogenesis, and induced vascular normalization. The role of miR-200 in blocking cancer angiogenesis in a cancer-dependent context defines its utility as a potential therapeutic agent.