Integrated Functional, Gene Expression and Genomic Analysis for the Identification of Cancer Targets

The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi) cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer

A Magnetic Bead-Integrated Chip for the Large Scale Manufacture of Normalized esiRNAs

The chemically-synthesized siRNA duplex has become a powerful and widely used tool for RNAi loss-of-function studies, but suffers from a high off-target effect problem. Recently, endoribonulease-prepared siRNA (esiRNA) has been shown to be an attractive alternative due to its lower off-target effect and cost effectiveness. However, the current manufacturing method for esiRNA is complicated, mainly in regards to purification and normalization on a large-scale level. In this study, we present a magnetic bead-integrated chip that can immobilize amplification or transcription products on beads and accomplish transcription, digestion, normalization and purification in a robust and convenient manner. This chip is equipped to manufacture ready-to-use esiRNAs on a large-scale level. Silencing specificity and efficiency of these esiRNAs were validated at the transcriptional, translational and functional levels. Manufacture of several normalized esiRNAs in a single well, including those silencing PARP1 and BRCA1, was successfully achieved, and the esiRNAs were subsequently utilized to effectively investigate their synergistic effect on cell viability. A small esiRNA library targeting 68 tyrosine kinase genes was constructed for a loss-of-function study, and four genes were identified in regulating the migration capability of Hela cells. We believe that this approach provides a more robust and cost-effective choice for manufacturing esiRNAs than current approaches, and therefore these heterogeneous RNA strands may have utility in most intensive and extensive applications

Knowledge based identification of essential signaling from genome-scale siRNA experiments

<p>Abstract</p> <p>Background</p> <p>A systems biology interpretation of genome-scale RNA interference (RNAi) experiments is complicated by scope, experimental variability and network signaling robustness. Over representation approaches (ORA), such as the Hypergeometric or z-score, are an established statistical framework used to associate RNA interference effectors to biologically annotated gene sets or pathways. These methods, however, do not directly take advantage of our growing understanding of the interactome. Furthermore, these methods can miss partial pathway activation and may be biased by protein complexes. Here we present a novel ORA, protein interaction permutation analysis (PIPA), that takes advantage of canonical pathways and established protein interactions to identify pathways enriched for protein interactions connecting RNAi hits.</p> <p>Results</p> <p>We use PIPA to analyze genome-scale siRNA cell growth screens performed in HeLa and TOV cell lines. First we show that interacting gene pair siRNA hits are more reproducible than single gene hits. Using protein interactions, PIPA identifies enriched pathways not found using the standard Hypergeometric analysis including the FAK <it>cytoskeletal remodeling pathway</it>. Different branches of the <it>FAK </it>pathway are distinctly essential in HeLa versus TOV cell lines while other portions are uneffected by siRNA perturbations. Enriched hits belong to protein interactions associated with cell cycle regulation, anti-apoptosis, and signal transduction.</p> <p>Conclusion</p> <p>PIPA provides an analytical framework to interpret siRNA screen data by merging biologically annotated gene sets with the human interactome. As a result we identify pathways and signaling hypotheses that are statistically enriched to effect cell growth in human cell lines. This method provides a complementary approach to standard gene set enrichment that utilizes the additional knowledge of specific interactions within biological gene sets. </p

Kinome-Wide Functional Genomics Screen Reveals a Novel Mechanism of TNFα-Induced Nuclear Accumulation of the HIF-1α Transcription Factor in Cancer Cells

Hypoxia-inducible factor-1 (HIF-1) and its most important subunit, HIF-1α, plays a central role in tumor progression by regulating genes involved in cancer cell survival, proliferation and metastasis. HIF-1α activity is associated with nuclear accumulation of the transcription factor and regulated by several mechanisms including modulation of protein stability and degradation. Among recent advances are the discoveries that inflammation-induced cytokines and growth factors affect protein accumulation of HIF-1α under normoxia conditions. TNFα, a major pro-inflammatory cytokine that promotes tumorigenesis is known as a stimulator of HIF-1α activity. To improve our understanding of TNFα-mediated regulation of HIF-1α nuclear accumulation we screened a kinase-specific siRNA library using a cell imaging–based HIF-1α-eGFP chimera reporter assay. Interestingly, this systematic analysis determined that depletion of kinases involved in conventional TNFα signaling (IKK/NFκB and JNK pathways) has no detrimental effect on HIF-1α accumulation. On the other hand, depletion of PRKAR2B, ADCK2, TRPM7, and TRIB2 significantly decreases the effect of TNFα on HIF-1α stability in osteosarcoma and prostate cancer cell lines. These newly discovered regulators conveyed their activity through a non-conventional RELB-depended NFκB signaling pathway and regulation of superoxide activity. Taken together our data allow us to conclude that TNFα uses a distinct and complex signaling mechanism to induce accumulation of HIF-1α in cancer cells. In summary, our results illuminate a novel mechanism through which cancer initiation and progression may be promoted by inflammatory cytokines, highlighting new potential avenues for fighting this disease

NSC23925, Identified in a High-Throughput Cell-Based Screen, Reverses Multidrug Resistance

Multidrug resistance (MDR) is a major factor which contributes to the failure of cancer chemotherapy, and numerous efforts have been attempted to overcome MDR. To date, none of these attempts have yielded a tolerable and effective therapy to reverse MDR; thus, identification of new agents would be useful both clinically and scientifically.To identify small molecule compounds that can reverse chemoresistance, we developed a 96-well plate high-throughput cell-based screening assay in a paclitaxel resistant ovarian cancer cell line. Coincubating cells with a sublethal concentration of paclitaxel in combination with each of 2,000 small molecule compounds from the National Cancer Institute Diversity Set Library, we identified a previously uncharacterized molecule, NSC23925, that inhibits Pgp1 and reverses MDR1 (Pgp1) but does not inhibit MRP or BCRP-mediated MDR. The cytotoxic activity of NSC23925 was further evaluated using a panel of cancer cell lines expressing Pgp1, MRP, and BCRP. We found that at a concentration of >10 microM NSC23925 moderately inhibits the proliferation of both sensitive and resistant cell lines with almost equal activity, but its inhibitory effect was not altered by co-incubation with the Pgp1 inhibitor, verapamil, suggesting that NSC23925 itself is not a substrate of Pgp1. Additionally, NSC23925 increases the intracellular accumulation of Pgp1 substrates: calcein AM, Rhodamine-123, paclitaxel, mitoxantrone, and doxorubicin. Interestingly, we further observed that, although NSC23925 directly inhibits the function of Pgp1 in a dose-dependent manner without altering the total expression level of Pgp1, NSC23925 actually stimulates ATPase activity of Pgp, a phenomenon seen in other Pgp inhibitors.The ability of NSC23925 to restore sensitivity to the cytotoxic effects of chemotherapy or to prevent resistance could significantly benefit cancer patients

Population genomics of the critically endangered kākāpō

Summary The kākāpō is a flightless parrot endemic to New Zealand. Once common in the archipelago, only 201 individuals remain today, most of them descending from an isolated island population. We report the first genome-wide analyses of the species, including a high-quality genome assembly for kākāpō, one of the first chromosome-level reference genomes sequenced by the Vertebrate Genomes Project (VGP). We also sequenced and analyzed 35 modern genomes from the sole surviving island population and 14 genomes from the extinct mainland population. While theory suggests that such a small population is likely to have accumulated deleterious mutations through genetic drift, our analyses on the impact of the long-term small population size in kākāpō indicate that present-day island kākāpō have a reduced number of harmful mutations compared to mainland individuals. We hypothesize that this reduced mutational load is due to the island population having been subjected to a combination of genetic drift and purging of deleterious mutations, through increased inbreeding and purifying selection, since its isolation from the mainland ∼10,000 years ago. Our results provide evidence that small populations can survive even when isolated for hundreds of generations. This work provides key insights into kākāpō breeding and recovery and more generally into the application of genetic tools in conservation efforts for endangered species

High Expression of Wee1 Is Associated with Poor Disease-Free Survival in Malignant Melanoma: Potential for Targeted Therapy

Notoriously resistant malignant melanoma is one of the most increasing forms of cancer worldwide; there is thus a precarious need for new treatment options. The Wee1 kinase is a major regulator of the G2/M checkpoint, and halts the cell cycle by adding a negative phosphorylation on CDK1 (Tyr15). Additionally, Wee1 has a function in safeguarding the genome integrity during DNA synthesis. To assess the role of Wee1 in development and progression of malignant melanoma we examined its expression in a panel of paraffin-embedded patient derived tissue of benign nevi and primary- and metastatic melanomas, as well as in agarose-embedded cultured melanocytes. We found that Wee1 expression increased in the direction of malignancy, and showed a strong, positive correlation with known biomarkers involved in cell cycle regulation: Cyclin A (p<0.0001), Ki67 (p<0.0001), Cyclin D3 (p = 0.001), p21Cip1/WAF1 (p = 0.003), p53 (p = 0.025). Furthermore, high Wee1 expression was associated with thicker primary tumors (p = 0.001), ulceration (p = 0.005) and poor disease-free survival (p = 0.008). Transfections using siWee1 in metastatic melanoma cell lines; WM239WTp53, WM45.1MUTp53 and LOXWTp53, further support our hypothesis of a tumor promoting role of Wee1 in melanomas. Whereas no effect was observed in LOX cells, transfection with siWee1 led to accumulation of cells in G1/S and S phase of the cell cycle in WM239 and WM45.1 cells, respectively. Both latter cell lines displayed DNA damage and induction of apoptosis, in the absence of Wee1, indicating that the effect of silencing Wee1 may not be solely dependent of the p53 status of the cells. Together these results reveal the importance of Wee1 as a prognostic biomarker in melanomas, and indicate a potential role for targeted therapy, alone or in combination with other agents

Identifying Causal Genes and Dysregulated Pathways in Complex Diseases

In complex diseases, various combinations of genomic perturbations often lead to the same phenotype. On a molecular level, combinations of genomic perturbations are assumed to dys-regulate the same cellular pathways. Such a pathway-centric perspective is fundamental to understanding the mechanisms of complex diseases and the identification of potential drug targets. In order to provide an integrated perspective on complex disease mechanisms, we developed a novel computational method to simultaneously identify causal genes and dys-regulated pathways. First, we identified a representative set of genes that are differentially expressed in cancer compared to non-tumor control cases. Assuming that disease-associated gene expression changes are caused by genomic alterations, we determined potential paths from such genomic causes to target genes through a network of molecular interactions. Applying our method to sets of genomic alterations and gene expression profiles of 158 Glioblastoma multiforme (GBM) patients we uncovered candidate causal genes and causal paths that are potentially responsible for the altered expression of disease genes. We discovered a set of putative causal genes that potentially play a role in the disease. Combining an expression Quantitative Trait Loci (eQTL) analysis with pathway information, our approach allowed us not only to identify potential causal genes but also to find intermediate nodes and pathways mediating the information flow between causal and target genes. Our results indicate that different genomic perturbations indeed dys-regulate the same functional pathways, supporting a pathway-centric perspective of cancer. While copy number alterations and gene expression data of glioblastoma patients provided opportunities to test our approach, our method can be applied to any disease system where genetic variations play a fundamental causal role