Project description:Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis. Long non-coding RNAs (lncRNAs), as a new, relatively unstudied class of transcripts, provide a rich opportunity to identify both functional drivers and cancer-type specific biomarkers. However, despite the potential importance of lncRNAs to the cancer field, no comprehensive survey of lncRNA expression across various cancers has been reported. We used 3'-End Sequencing for Expression Quantification (3SEQ) to quantify transcript abundance across 64 solid tumors representing 17 diagnostic subtypes of adenocarcinomas, squamous cell carcinomas, and sarcomas. We identified hundreds of transcripts from among the known 1,065 lncRNAs surveyed that show variability in transcript levels between the tumor types, and therefore, make potential biomarker candidates. We discovered 1,071 novel intergenic transcribed regions and demonstrate that these show similar patterns of variability between tumor types. We find that many of these differentially expressed cancer transcripts are also expressed in normal tissues. One such novel transcript specifically expressed in breast tissue was further evaluated using RNA in situ hybridization on a panel of breast tumors and shown to correlate with low tumor grade and estrogen receptor expression, thereby representing a potentially important new breast cancer biomarker. This study provides the first large survey of lncRNA expression within a panel of solid cancers and also identifies a number of novel transcribed regions differentially expressed across distinct cancer types that represent candidate biomarkers for future research. 3SEQ was performed on 64 formalin-fixed, paraffin-embedded (FFPE) human tumors representing 17 diagnostic cancer subtypes. Duplicate libraries were prepared for two of the tumors (ESS STT5520 and LMS STT516). 3SEQ was also performed on 27 normal human tissue samples. RNA-Seq was performed on 6 breast cancer cell lines for the examination of the breast-specific transcript on chr10. Series supplementary files: 'GSE28866_raw_counts_54511_peaks_cancer_and_normal.txt': Raw_counts: Total 3SEQ reads in each peak for each sample. File includes read counts for 54,511 peaks for the 66 cancer libraries and the 27 normal libraries. 'GSE28866_36048_normalized_peaks_cancer_and_normal.txt': Normalized_peaks: Normalized 3SEQ expression data for the 36,048 filtered peaks for the 66 cancer libraries and the 27 normal libraries. Peaks were classified as coding, lncRNA (Rinn, Bartel, Hughes, Gencode_lnc), other known transcripts (ref_known_Gencode_nc, all_mrna, other known), downstream, intron, promoter, or novel_intergenic. Peaks determined to be differentially expressed in one of the 17 cancer subtypes using a series of 2-Class SAM analyses are noted along with the type of cancer showing upregulation. Expression data was normalized using the sequencing depth of each sample by scaling the data using the mean value of each sample. Data was further compressed to reduce outliers by taking the square root of each value.

Project description:Personalized biological insights into heterogeneous tumors, such as breast cancer could improve clinical management. While genomic analysis has contributed significantly towards dissecting breast cancer heterogeneity, limitations in clinical application are partly rooted in the inter-tumor variability arising from a largely uncharacterized interactive exchange between diverse cell types in the tumor microenvironment. Here we first identified a common response signature to stromal coculture across breast cancer of varying clinicopathologic phenotypes. Proximity to fibroblasts resulted in gene transcript alterations of >2-fold for 107 probe sets, collectively designated as Fibroblast Triggered Gene Expression in Tumor (FTExT). Prominent features of tumor cell response included transcript repression related to biofunctions encompassing inflammatory signaling, cell movement, cell death, and cell growth and proliferation. In an evaluation of intertumor heterogeneity, the FTExT classifier stratified moderate and high histopathologic grade breast cancer according to clinical outcome (dataset 1, n=401, p=0.031; dataset 2, n=200, p=0.013), delineating a novel phenotype of stromal crosstalk underlying the prognostic potential of tumor grade. Extending correlative data through functional analysis of stromal-epithelial cocultures of both malignant and nonmalignant derivation, significant differences in cell cycle regulation, rate of proliferation, resistance to therapy-induced apoptosis, and growth arrest were observed in FTExT-based subgroups. Instead of a stromal impact that is uniformly cancer promoting, our data demonstrate striking variability in tumor cell response that directly contributes to contrasting functional aggressiveness of malignant breast tissue. Our findings uniquely reveal dynamically interacting paracrine components underlying the molecular and functional heterogeneity of breast cancer, thus presenting novel opportunities for tumor targeting.

Project description:Personalized biological insights into heterogeneous tumors, such as breast cancer could improve clinical management. While genomic analysis has contributed significantly towards dissecting breast cancer heterogeneity, limitations in clinical application are partly rooted in the inter-tumor variability arising from a largely uncharacterized interactive exchange between diverse cell types in the tumor microenvironment. Here we first identified a common response signature to stromal coculture across breast cancer of varying clinicopathologic phenotypes. Proximity to fibroblasts resulted in gene transcript alterations of >2-fold for 107 probe sets, collectively designated as Fibroblast Triggered Gene Expression in Tumor (FTExT). Prominent features of tumor cell response included transcript repression related to biofunctions encompassing inflammatory signaling, cell movement, cell death, and cell growth and proliferation. In an evaluation of intertumor heterogeneity, the FTExT classifier stratified moderate and high histopathologic grade breast cancer according to clinical outcome (dataset 1, n=401, p=0.031; dataset 2, n=200, p=0.013), delineating a novel phenotype of stromal crosstalk underlying the prognostic potential of tumor grade. Extending correlative data through functional analysis of stromal-epithelial cocultures of both malignant and nonmalignant derivation, significant differences in cell cycle regulation, rate of proliferation, resistance to therapy-induced apoptosis, and growth arrest were observed in FTExT-based subgroups. Instead of a stromal impact that is uniformly cancer promoting, our data demonstrate striking variability in tumor cell response that directly contributes to contrasting functional aggressiveness of malignant breast tissue. Our findings uniquely reveal dynamically interacting paracrine components underlying the molecular and functional heterogeneity of breast cancer, thus presenting novel opportunities for tumor targeting. 10 tumor samples cocultured with fibroblast were profiled in their gene expression with microarrays, and compared with 7 tumor samples cultured without fibroblast. Immortalized tumor cell lines of varying histologic grade were developed and maintained in a growth median as described in Dairkee, et al., Oncogene, 2007. In the coculture set up, epithelial cells were seeded in 6-well plates, and fibroblasts in 0.4 μm inserts with hanging geometry (BD Biosciences, Franklin Lakes, NJ) at a 3:1 ratio in a common pool of growth medium for 3-day harvests. Controls were comprised of each epithelial sample maintained in the absence of fibroblast-seeded inserts under the same culture conditions.

Project description:Current prognostic factors are insufficient for precise risk-discrimination in breast cancer patients with low grade breast tumors, which, in disagreement with theoretical prognosis, occasionally form early lymph node metastasis. To identify markers for this group of patients, we employed iTRAQ-2DLC-MS/MS proteomics to 24 lymph node positive and 24 lymph node negative grade 1 luminal A primary breast tumors. Another group of 48 high-grade tumors (luminal B, triple negative, Her-2 subtypes) was also analyzed to investigate marker specificity for grade 1 luminal A tumors. From the total of 4405 proteins identified (FDR<5%), the top 65 differentially expressed together with 30 previously identified and control markers were analyzed also at transcript level. Increased levels of carboxypeptidase B1 (CPB1), PDZ and LIM domain protein 2 (PDLIM2) and ring finger protein 25 (RNF25) were associated specifically with lymph node positive grade 1 tumors, whereas stathmin 1 (STMN1) and thymosin beta 10 (TMSB10) associated with aggressive tumor phenotype also in high grade tumors at both protein and transcript level. For CPB1, these differences were also observed by immunohistochemical analysis on tissue microarrays. Upregulation of putative biomarkers in lymph node positive (vs. negative) luminal A tumors was validated by gene expression analysis of an independent published dataset (N=343) for CPB1 (p=0.00155), PDLIM2 (p=0.02027) and RELA (p=0.00015). Moreover, statistically significant connections with patient survival were identified in another public dataset (N=1678). Our findings indicate unique pro-metastatic mechanisms in grade 1 tumors that can include up-regulation of CPB1, activation of NF-κB pathway and changes in cell survival and cytoskeleton. These putative biomarkers have potential to identify the specific minor sub-population of breast cancer patients with low grade tumors who are at higher than expected risk of recurrence and who would benefit from more intensive follow-up and may require more personalized therapy.

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Transcriptional profiling of lncRNAs and novel transcribed regions across a diverse panel of archived human cancers

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