Purpose: It was the aim of our study to establish an extensive panel of non-small cell lung cancer (NSCLC) xenograft models useful for the testing of novel compounds and for the identification of biomarkers. Experimental Design: Starting from102 surgical NSCLC specimens, which were obtained from primarily diagnosed patients with early-stage tumors (T 2 /T 3 ), 25 transplantable xenografts were established and used for further investigations. Results: Early passages of the NSCLC xenografts revealed a high degree of similarity with the original clinical tumor sample with regard to histology, immunohistochemistry, as well as mutation status.The chemotherapeutic responsiveness of the xenografts resembled the clinical situation in NSCLC with tumor shrinkage obtained with paclitaxel (4 of 25), gemcitabine (3 of 25), and carboplatin (3 of 25) and lower effectiveness of etoposide (1of 25) and vinorelbine (0 of 11). Twelve of 25 NSCLC xenografts were >50% growth inhibited by the anti-epidermal growth factor receptor (EGFR) antibody cetuximab and 6 of 25 by the EGFR tyrosine kinase inhibitor erlotinib. The response to the anti-EGFR therapies did not correlate with mutations in the EGFR or p53, but there was a correlation of K-ras mutations and erlotinib resistance. Protein analysis revealed a heterogeneous pattern of expression. After treatment with cetuximab, we observed a down-regulation of EGFR in 2 of 6 sensitive xenograft models investigated but never in resistant models. Conclusion: An extensive panel of patient-derived NSCLC xenografts has been established. It provides appropriate models for testing marketed as well as novel drug candidates. Additional expression studies allow the identification of stratification biomarkers for targeted therapies.

Epithelial ovarian cancer (EOC) is hallmarked by a high degree of heterogeneity. To address this heterogeneity, a classification scheme was developed based on gene expression patterns of 1538 tumours. Five, biologically distinct subgroups — Epi-A, Epi-B, Mes, Stem-A and Stem-B — exhibited significantly distinct clinicopathological characteristics, deregulated pathways and patient prognoses, and were validated using independent datasets. To identify subtype-specific molecular targets, ovarian cancer cell lines representing these molecular subtypes were screened against a genome-wide shRNA library. Focusing on the poor-prognosis Stem-A subtype, we found that two genes involved in tubulin processing, TUBGCP4 and NAT10, were essential for cell growth, an observation supported by a pathway analysis that also predicted involvement of microtubule-related processes. Furthermore, we observed that Stem-A cell lines were indeed more sensitive to inhibitors of tubulin polymerization, vincristine and vinorelbine, than the other subtypes. This subtyping offers new insights into the development of novel diagnostic and personalized treatment for EOC patients.

Despite multidisciplinary treatment for patients with advanced gastric cancer, their prognosis remains poor. Therefore, the development of novel therapeutic strategies is urgently needed, and immunotherapy utilizing anti‐programmed death 1/‐programmed death ligand‐1 mAb is an attractive approach. However, as there is limited information on how programmed death ligand‐1 is upregulated on tumor cells within the tumor microenvironment, we examined the mechanism of programmed death ligand‐1 regulation with a particular focus on interferon gamma in an in vitro setting and in clinical samples. Our in vitro findings showed that interferon gamma upregulated programmed death ligand‐1 expression on solid tumor cells through the JAK‐signal transducer and activator of transcription pathway, and impaired the cytotoxicity of tumor antigen‐specific CTL against tumor cells. Following treatment of cells with anti‐programmed death ligand‐1 mAb after interferon gamma‐pre‐treatment, the reduced anti‐tumor CTL activity by interferon gamma reached a higher level than the non‐treatment control targets. In contrast, programmed death ligand‐1 expression on tumor cells also significantly correlated with epithelial‐mesenchymal transition phenotype in a panel of solid tumor cells. In clinical gastric cancer samples, tumor membrane programmed death ligand‐1 expression significantly positively correlated with the presence of CD8‐positive T cells in the stroma and interferon gamma expression in the tumor. The results suggest that gastric cancer patients with high CD8‐positive T‐cell infiltration may be more responsive to anti‐programmed death 1/‐programmed death ligand‐1 mAb therapy.

The Warburg effect describes the increased utilization of glycolysis rather than oxidative phosphorylation by tumour cells for their energy requirements under physiological oxygen conditions. This effect has been the basis for much speculation on the survival advantage of tumour cells, tumourigenesis and the microenvironment of tumours. More recently, studies have begun to reveal how the Warburg effect could influence drug efficacy and how our understanding of tumour energetics could be exploited to improve drug development. In particular, evidence is emerging demonstrating how better modelling of the tumour metabolic microenvironment could lead to a better prediction of drug efficacy and the identification of new combination strategies. This review will provide details of the current understanding of the complex interplay between glucose metabolism and pharmacology and discuss opportunities for utilizing the Warburg effect in future drug development.

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.

The cancer stem cell hypothesis may explain why conventional chemotherapies are unable to fully eradicate cancers. In this study, we examined both the prognostic and predictive significance of putative cancer stem cell markers in colorectal cancer. In this study, immunohistochemistry for three candidate cancer stem cell markers (CD133, Oct-4 and Sox-2) and for six other postulated prognostic markers (CK7, CK20, Cox-2, Ki-67, p27 and p53) were performed using tissue microarrays containing 501 primary colorectal cancer cases. Receiveroperating characteristic analysis was used to determine cut-off scores for positive protein expression. Multivariate analysis revealed that positive expression for CD133 and Oct-4 was associated with significantly worse survival in patients treated by surgery alone (P ¼ 0.023 and Po0.001, respectively) and in patients treated with 5-fluorouracil-based chemotherapy (P ¼ 0.001 and P ¼ 0.021, respectively). Stage III patients with negative CD133 expression showed an apparent survival benefit from 5-fluorouracil treatment (P ¼ 0.002), but not those with positive CD133 expression. Positive expression of CD133 was also associated with poorer clinical response to chemotherapy in stage IV patients (P ¼ 0.006). In summary, the putative cancer stem cell markers CD133 and Oct-4 showed strong prognostic significance in colorectal cancer. Our results show for the first time that CD133 þ colorectal tumors are more resistant to 5-fluorouracil-based chemotherapy.

Recent developments in high-throughput sequence capture methods and next-generation sequencing technologies have now made exome sequencing a viable approach to elucidate the genetic basis of Mendelian disorders with hitherto unknown etiology. In addition, exome sequencing is increasingly being employed as a diagnostic tool for specific genetic diseases, particularly in the context of those disorders characterized by significant genetic and phenotypic heterogeneity, for example, Charcot-Marie-Tooth disease and congenital disorders of glycosylation. Such disorders are challenging to interrogate with conventional polymerase chain reaction-Sanger sequencing methods, because of the inherent difficulty in prioritizing candidate genes for diagnostic testing. Here, we explore the value of exome sequencing as a diagnostic tool and discuss whether exome sequencing can come to serve a dual role in diagnosis and discovery. We summarize the current status of exome sequencing, the technical challenges facing it, and its adaptation to diagnostics, and make recommendations for the use of exome sequencing as a routine diagnostic tool. Finally, we discuss pertinent ethical concerns, such as the use of exome sequencing data, originally generated in a diagnostic context, in research investigations.

The most common risk factor for developing hepatocellular carcinoma (HCC) is chronic infection with hepatitis B virus (HBV). To better understand the evolutionary forces driving HCC we performed a near saturating transposon mutagenesis screen in a mouse HBV model of HCC. This screen identified 21 candidate early stage drivers, and a bewildering number (2860) of candidate later stage drivers, that were enriched for genes mutated, deregulated, or that function in signaling pathways important for human HCC, with a striking 1199 genes linked to cellular metabolic processes. Our study provides a comprehensive overview of the genetic landscape of HCC.