Genome-wide DNA methylation measurements in prostate tissues uncovers novel prostate cancer diagnostic biomarkers and transcription factor binding patterns.

BACKGROUND: Current diagnostic tools for prostate cancer lack specificity and sensitivity for detecting very early lesions. DNA methylation is a stable genomic modification that is detectable in peripheral patient fluids such as urine and blood plasma that could serve as a non-invasive diagnostic biomarker for prostate cancer. METHODS: We measured genome-wide DNA methylation patterns in 73 clinically annotated fresh-frozen prostate cancers and 63 benign-adjacent prostate tissues using the Illumina Infinium HumanMethylation450 BeadChip array. We overlaid the most significantly differentially methylated sites in the genome with transcription factor binding sites measured by the Encyclopedia of DNA Elements consortium. We used logistic regression and receiver operating characteristic curves to assess the performance of candidate diagnostic models. RESULTS: We identified methylation patterns that have a high predictive power for distinguishing malignant prostate tissue from benign-adjacent prostate tissue, and these methylation signatures were validated using data from The Cancer Genome Atlas Project. Furthermore, by overlaying ENCODE transcription factor binding data, we observed an enrichment of enhancer of zeste homolog 2 binding in gene regulatory regions with higher DNA methylation in malignant prostate tissues. CONCLUSIONS: DNA methylation patterns are greatly altered in prostate cancer tissue in comparison to benign-adjacent tissue. We have discovered patterns of DNA methylation marks that can distinguish prostate cancers with high specificity and sensitivity in multiple patient tissue cohorts, and we have identified transcription factors binding in these differentially methylated regions that may play important roles in prostate cancer development.

Genomic regulation of invasion by STAT3 in triple negative breast cancer.

Breast cancer is a heterogeneous disease comprised of four molecular subtypes defined by whether the tumor-originating cells are luminal or basal epithelial cells. Breast cancers arising from the luminal mammary duct often express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth receptor 2 (HER2). Tumors expressing ER and/or PR are treated with anti-hormonal therapies, while tumors overexpressing HER2 are targeted with monoclonal antibodies. Immunohistochemical detection of ER, PR, and HER2 receptors/proteins is a critical step in breast cancer diagnosis and guided treatment. Breast tumors that do not express these proteins are known as "triple negative breast cancer" (TNBC) and are typically basal-like. TNBCs are the most aggressive subtype, with the highest mortality rates and no targeted therapy, so there is a pressing need to identify important TNBC tumor regulators. The signal transducer and activator of transcription 3 (STAT3) transcription factor has been previously implicated as a constitutively active oncogene in TNBC. However, its direct regulatory gene targets and tumorigenic properties have not been well characterized. By integrating RNA-seq and ChIP-seq data from 2 TNBC tumors and 5 cell lines, we discovered novel gene signatures directly regulated by STAT3 that were enriched for processes involving inflammation, immunity, and invasion in TNBC. Functional analysis revealed that STAT3 has a key role regulating invasion and metastasis, a characteristic often associated with TNBC. Our findings suggest therapies targeting STAT3 may be important for preventing TNBC metastasis.

RNA sequencing of pancreatic adenocarcinoma tumors yields novel expression patterns associated with long-term survival and reveals a role for ANGPTL4.

BACKGROUND: Pancreatic adenocarcinoma patients have low survival rates due to late-stage diagnosis and high rates of cancer recurrence even after surgical resection. It is important to understand the molecular characteristics associated with survival differences in pancreatic adenocarcinoma tumors that may inform patient care. RESULTS: RNA sequencing was performed for 51 patient tumor tissues extracted from patients undergoing surgical resection, and expression was associated with overall survival time from diagnosis. Our analysis uncovered 323 transcripts whose expression correlates with survival time in our pancreatic patient cohort. This genomic signature was validated in an independent RNA-seq dataset of 68 additional patients from the International Cancer Genome Consortium. We demonstrate that this transcriptional profile is largely independent of markers of cellular division and present a 19-transcript predictive model built from a subset of the 323 transcripts that can distinguish patients with differing survival times across both the training and validation patient cohorts. We present evidence that a subset of the survival-associated transcripts is associated with resistance to gemcitabine treatment in vitro, and reveal that reduced expression of one of the survival-associated transcripts, Angiopoietin-like 4, impairs growth of a gemcitabine-resistant pancreatic cancer cell line. CONCLUSIONS: Gene expression patterns in pancreatic adenocarcinoma tumors can distinguish patients with differing survival outcomes after undergoing surgical resection, and the survival difference could be associated with the intrinsic gemcitabine sensitivity of primary patient tumors. Thus, these transcriptional differences may impact patient care by distinguishing patients who would benefit from a non-gemcitabine based therapy.

Recurrent read-through fusion transcripts in breast cancer.

Read-through fusion transcripts that result from the splicing of two adjacent genes in the same coding orientation are a recently discovered type of chimeric RNA. We sought to determine if read-through fusion transcripts exist in breast cancer. We performed paired-end RNA-seq of 168 breast samples, including 28 breast cancer cell lines, 42 triple negative breast cancer primary tumors, 42 estrogen receptor positive (ER+) breast cancer primary tumors, and 56 non-malignant breast tissue samples. We analyzed the sequencing data to identify breast cancer associated read-through fusion transcripts. We discovered two recurrent read-through fusion transcripts that were identified in breast cancer cell lines, confirmed across breast cancer primary tumors, and were not detected in normal tissues (SCNN1A-TNFRSF1A and CTSD-IFITM10). Both fusion transcripts use canonical splice sites to join the last splice donor of the 5' gene to the first splice acceptor of the 3' gene, creating an in-frame fusion transcript. Western blots indicated that the fusion transcripts are translated into fusion proteins in breast cancer cells. Custom small interfering RNAs targeting the CTSD-IFITM10 fusion junction reduced expression of the fusion transcript and reduced breast cancer cell proliferation. Read-through fusion transcripts between adjacent genes with different biochemical functions represent a new type of recurrent molecular defect in breast cancer that warrant further investigation as potential biomarkers and therapeutic targets. Both breast cancer associated fusion transcripts identified in this study involve membrane proteins (SCNN1A-TNFRSF1A and CTSD-IFITM10), which raises the possibility that they could be breast cancer-specific cell surface markers.