Synthetic lethality is an appealing technique for selectively targeting cancer cells which have acquired molecular changes that distinguish them from normal cells. High-throughput RNAi-based screens have been successfully used to identify synthetic lethal pathways with well-characterized tumor suppressors and oncogenes. The recent identification of metabolic tumor suppressors suggests that the concept of synthetic lethality can be applied to selectively target cancer metabolism as well.
Chemotherapy of advanced pancreatic cancer has mainly been gemcitabine-based for the past 15 years, with only limited effect. Recently, combination therapy that also targets checkpoint kinase 1 (CHK1) has become an attractive option. The central role of CHK1 in many DNA-damage response pathways, however, may result in undesired cytotoxicity in normal cells, causing side effects. We were searching for other target molecules of similar function that may be more specific and thus better suited for combination therapy. To this end a negative selection RNAi screen was performed in cell lines with small hairpin RNA molecules targeting over 10,000 genes. Genes that were found to be synthetically lethal with gemcitabine and whose proteins act upstream of CHK1 were characterised in more detail. In particular, the inhibition of RAD17 potentiated gemcitabine cytotoxicity in the pancreatic cancer cell lines BxPC-3 and MiaPaca-2 and in the primary cell line JoPaca-1 that closely resembles primary tumour tissue. Further analysis showed that the synergistic effect of RAD17 knockdown and gemcitabine leads to forced mitotic entry of cells arrested in S phase by gemcitabine treatment, resulting in asymmetric DNA distribution during anaphase followed by DNA fragmentation and finally cell death by mitotic catastrophe. Our data suggest RAD17 as a novel target protein for gemcitabine combination therapy supplementing or complementing inhibition of CHK1. In contrast to CHK1, RAD17 knockdown by itself does not lead to abnormal DNA segregation, suggesting a more specific action.
Breast cancer stem cells are suspected to be responsible for tumour recurrence, metastasis formation as well as chemoresistance. Consequently, great efforts have been made to understand the molecular mechanisms underlying cancer stem cell maintenance. In order to study these rare cells in-vitro, they are typically enriched via mammosphere culture. Here we developed a mammosphere-based negative selection shRNAi screening system suitable to analyse the involvement of thousands of genes in the survival of cells with cancer stem cell properties.
Vertebrate mitochondria use stop codons UAA and UAG decoded by the release factor (RF) MTRF1L and two reassigned arginine codons, AGA and AGG. A second highly conserved RF-like factor, MTRF1, which evolved from a gene duplication of an ancestral mitochondrial RF1 and not a RF2, is a good candidate for recognizing the nonstandard codons. MTRF1 differs from other RFs by having insertions in the two external loops important for stop codon recognition (tip of helix alpha5 and recognition loop) and by having key substitutions that are involved in stop codon interactions in eubacterial RF/ribosome structures. These changes may allow recognition of the larger purine base in the first position of AGA/G and, uniquely for RFs, only of G at position 2. In contrast, residues that support A and G recognition in the third position in RF1 are conserved as would be required for recognition of AGA and AGG. Since an assay with vertebrate mitochondrial ribosomes has not been established, we modified Escherichia coli RF1 at the helix alpha5 and recognition loop regions to mimic MTRF1. There was loss of peptidyl-tRNA hydrolysis activity with standard stop codons beginning with U (e.g., UAG), but a gain of activity with codons beginning with A (AAG in particular). A lower level of activity with AGA could be enhanced by solvent modification. These observations imply that MTRF1 has the characteristics to recognize A as the first base of a stop codon as would be required to decode the nonstandard codons AGA and AGG.
RNAi screens via pooled short hairpin RNAs (shRNAs) have recently become a powerful tool for the identification of essential genes in mammalian cells. In the past years, several pooled large-scale shRNA screens have identified a variety of genes involved in cancer cell proliferation. All of those studies employed microarray analysis, utilizing either the shRNAs half hairpin sequence or an additional shRNA-associated 60 nt barcode sequence as a molecular tag. Here we describe a novel method to decode pooled RNAi screens, namely barcode tiling array analysis, and demonstrate how this approach can be used to precisely quantify the abundance of individual shRNAs from a pool.
Standard cancer cell lines do not model the intratumoural heterogeneity situation sufficiently. Clonal selection leads to a homogeneous population of cells by genetic drift. Heterogeneity of tumour cells, however, is particularly critical for therapeutically relevant studies, since it is a prerequisite for acquiring drug resistance and reoccurrence of tumours. Here, we report the isolation of a highly tumourigenic primary pancreatic cancer cell line, called JoPaca-1 and its detailed characterization at multiple levels. Implantation of as few as 100 JoPaca-1 cells into immunodeficient mice gave rise to tumours that were histologically very similar to the primary tumour. The high heterogeneity of JoPaca-1 was reflected by diverse cell morphology and a substantial number of chromosomal aberrations. Comparative whole-genome sequencing of JoPaca-1 and BxPC-3 revealed mutations in genes frequently altered in pancreatic cancer. Exceptionally high expression of cancer stem cell markers and a high clonogenic potential in vitro and in vivo was observed. All of these attributes make this cell line an extremely valuable model to study the biology of and pharmaceutical effects on pancreatic cancer.
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