Multiple Oncogenic Pathway Signatures Show Coordinate Expression Patterns in Human Prostate Tumors

BACKGROUND: Gene transcription patterns associated with activation of oncogenes Myc, c-Src, beta-catenin, E2F3, H-Ras, HER2, EGFR, MEK, Raf, MAPK, Akt, and cyclin D1, as well as of the cell cycle and of androgen signaling have been generated in previous studies using experimental models. It was not clear whether genes in these "oncogenic signatures" would show coordinate expression patterns in human prostate tumors, particularly as most of the signatures were derived from cell types other than prostate. PRINCIPAL FINDINGS: The above oncogenic pathway signatures were examined in four different gene expression profile datasets of human prostate tumors (representing approximately 250 patients in all), using both Q1-Q2 and one-sided Fisher's exact enrichment analysis methods. A significant fraction (approximately 5%) of genes up-regulated experimentally by Myc, c-Src, HER2, Akt, or androgen were co-expressed in human tumors with the oncogene or biomarker corresponding to the pathway signature. Genes down-regulated experimentally, however, did not show anticipated patterns of anti-enrichment in the human tumors. CONCLUSIONS: Significant subsets of the genes in these experimentally-derived oncogenic signatures are relevant to the study of human prostate cancer. Both molecular biologists and clinical researchers could focus attention on the relatively small number of genes identified here as having coordinate patterns that arise from both the experimental system and the human disease system

JISTIC: Identification of Significant Targets in Cancer

<p>Abstract</p> <p>Background</p> <p>Cancer is caused through a multistep process, in which a succession of genetic changes, each conferring a competitive advantage for growth and proliferation, leads to the progressive conversion of normal human cells into malignant cancer cells. Interrogation of cancer genomes holds the promise of understanding this process, thus revolutionizing cancer research and treatment. As datasets measuring copy number aberrations in tumors accumulate, a major challenge has become to distinguish between those mutations that drive the cancer versus those passenger mutations that have no effect.</p> <p>Results</p> <p>We present JISTIC, a tool for analyzing datasets of genome-wide copy number variation to identify driver aberrations in cancer. JISTIC is an improvement over the widely used GISTIC algorithm. We compared the performance of JISTIC versus GISTIC on a dataset of glioblastoma copy number variation, JISTIC finds 173 significant regions, whereas GISTIC only finds 103 significant regions. Importantly, the additional regions detected by JISTIC are enriched for oncogenes and genes involved in cell-cycle and proliferation.</p> <p>Conclusions</p> <p>JISTIC is an easy-to-install platform independent implementation of GISTIC that outperforms the original algorithm detecting more relevant candidate genes and regions. The software and documentation are freely available and can be found at: <url>http://www.c2b2.columbia.edu/danapeerlab/html/software.html</url></p

A Tissue Biomarker Panel Predicting Systemic Progression after PSA Recurrence Post-Definitive Prostate Cancer Therapy

Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy.A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model.Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence

Disease-Associated Mutations That Alter the RNA Structural Ensemble

Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble

Differential Matrix Rigidity Response in Breast Cancer Cell Lines Correlates with the Tissue Tropism

Metastasis to a variety of distant organs, such as lung, brain, bone, and liver, is a leading cause of mortality in the breast cancer patients. The tissue tropism of breast cancer metastasis has been recognized and studied extensively, but the cellular processes underlying this phenomenon, remain elusive. Modern technologies have enabled the discovery of a number of the genetic factors determining tissue tropism of malignant cells. However, the effect of these genetic differences on the cell motility and invasiveness is poorly understood. Here, we report that cellular responses to the mechanical rigidity of the extracellular matrix correlate with the rigidity of the target tissue. We tested a series of single cell populations isolated from MDA-MB-231 breast cancer cell line in a variety of assays where the extracellular matrix rigidity was varied to mimic the environment that these cells might encounter in vivo. There was increased proliferation and migration through the matrices of rigidities corresponding to the native rigidities of the organs where metastasis was observed. We were able to abolish the differential matrix rigidity response by knocking down Fyn kinase, which was previously identified as a critical component of the FN rigidity response pathway in healthy cells. This result suggests possible molecular mechanisms of the rigidity response in the malignant cells, indicating potential candidates for therapeutic interventions

Survivin expression in oral squamous cell carcinoma

A series of 110 cases of oral squamous cell carcinoma (SCC) together with six lymph node and one distant metastatic lesions was analysed for expression of survivin, a recent apoptosis inhibitor, by immunohistochemistry and Western blotting. In total, 91 cases (82.7%) of carcinoma and all metastasis (seven cases, 100%) were positive for survivin expression, with weighted survivin scores ranging from 1 to 4. In contrast, normal oral epithelium did not express survivin. There was no significant correlation between survivin expression and age, sex, tumour size, the presence of lymph node and distant metastases. Survivin expression was increased in poorly differentiated tumours, even if differences were not statistically significant. In contrast, when analysed for prognostic significance, patients with low survivin expression had statistically significant better survival rates than the group with high survivin expression (P < 0.05). These data suggest that survivin expression may identify cases of oral SCC with more aggressive and invasive phenotype

Identification of Prognostic Molecular Features in the Reactive Stroma of Human Breast and Prostate Cancer

Primary tumor growth induces host tissue responses that are believed to support and promote tumor progression. Identification of the molecular characteristics of the tumor microenvironment and elucidation of its crosstalk with tumor cells may therefore be crucial for improving our understanding of the processes implicated in cancer progression, identifying potential therapeutic targets, and uncovering stromal gene expression signatures that may predict clinical outcome. A key issue to resolve, therefore, is whether the stromal response to tumor growth is largely a generic phenomenon, irrespective of the tumor type or whether the response reflects tumor-specific properties. To address similarity or distinction of stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to compare the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Invasive breast and prostate cancer-associated stroma was observed to display distinct transcriptomes, with a limited number of shared genes. Interestingly, both breast and prostate tumor-specific dysregulated stromal genes were observed to cluster breast and prostate cancer patients, respectively, into two distinct groups with statistically different clinical outcomes. By contrast, a gene signature that was common to the reactive stroma of both tumor types did not have survival predictive value. Univariate Cox analysis identified genes whose expression level was most strongly associated with patient survival. Taken together, these observations suggest that the tumor microenvironment displays distinct features according to the tumor type that provides survival-predictive value

Small molecules targeted to the microtubule–Hec1 interaction inhibit cancer cell growth through microtubule stabilization

Highly expressed in cancer protein 1 (Hec1) is a subunit of the kinetochore (KT)-associated Ndc80 complex, which ensures proper segregation of sister chromatids at mitosis by mediating the interaction between KTs and microtubules (MTs). HEC1 mRNA and protein are highly expressed in many malignancies as part of a signature of chromosome instability. These properties render Hec1 a promising molecular target for developing therapeutic drugs that exert their anticancer activities by producing massive chromosome aneuploidy. A virtual screening study aimed at identifying small molecules able to bind at the Hec1–MT interaction domain identified one positive hit compound and two analogs of the hit with high cytotoxic, pro-apoptotic and anti-mitotic activities. The most cytotoxic analog (SM15) was shown to produce chromosome segregation defects in cancer cells by inhibiting the correction of erroneous KT–MT interactions. Live cell imaging of treated cells demonstrated that mitotic arrest and segregation abnormalities lead to cell death through mitotic catastrophe and that cell death occurred also from interphase. Importantly, SM15 was shown to be more effective in inducing apoptotic cell death in cancer cells as compared to normal ones and effectively reduced tumor growth in a mouse xenograft model. Mechanistically, cold-induced MT depolymerization experiments demonstrated a hyper-stabilization of both mitotic and interphase MTs. Molecular dynamics simulations corroborate this finding by showing that SM15 can bind the MT surface independently from Hec1 and acts as a stabilizer of both MTs and KT–MT interactions. Overall, our studies represent a clear proof of principle that MT-Hec1-interacting compounds may represent novel powerful anticancer agents

Evidence That SOX2 Overexpression Is Oncogenic in the Lung

BACKGROUND: SOX2 (Sry-box 2) is required to maintain a variety of stem cells, is overexpressed in some solid tumors, and is expressed in epithelial cells of the lung. METHODOLOGY/PRINCIPAL FINDINGS: We show that SOX2 is overexpressed in human squamous cell lung tumors and some adenocarcinomas. We have generated mouse models in which Sox2 is upregulated in epithelial cells of the lung during development and in the adult. In both cases, overexpression leads to extensive hyperplasia. In the terminal bronchioles, a trachea-like pseudostratified epithelium develops with p63-positive cells underlying columnar cells. Over 12-34 weeks, about half of the mice expressing the highest levels of Sox2 develop carcinoma. These tumors resemble adenocarcinoma but express the squamous marker, Trp63 (p63). CONCLUSIONS: These findings demonstrate that Sox2 overexpression both induces a proximal phenotype in the distal airways/alveoli and leads to cancer