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TSC2 Integrates Wnt and Energy Signals via a Coordinated Phosphorylation by AMPK and GSK3 to Regulate Cell Growth

Mutation in the TSC2 tumor suppressor causes tuberous sclerosis complex, a disease characterized by hamartoma formation in multiple tissues. TSC2 inhibits cell growth by acting as a GTPase-activating protein toward Rheb, thereby inhibiting mTOR, a central controller of cell growth. Here, we show that Wnt activates mTOR via inhibiting GSK3 without involving beta-catenin-dependent transcription. GSK3 inhibits the mTOR pathway by phosphorylating TSC2 in a manner dependent on AMPK-priming phosphorylation. Inhibition of mTOR by rapamycin blocks Wnt-induced cell growth and tumor development, suggesting a potential therapeutic value of rapamycin for cancers with activated Wnt signaling. Our results show that, in addition to transcriptional activation, Wnt stimulates translation and cell growth by activating the TSC-mTOR pathway. Furthermore, the sequential phosphorylation of TSC2 by AMPK and GSK3 reveals a molecular mechanism of signal integration in cell growth regulation.

GENOMIC LANDSCAPE OF NON-SMALL CELL LUNG CANCER IN SMOKERS AND NEVER SMOKERS

We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.

Principles for the post-GWAS functional characterization of cancer risk loci

Genome wide association studies (GWAS) have identified more than 200 mostly new common low-penetrance susceptibility loci for cancers. The predicted risk associated with each locus is generally modest (with a per-allele odds ratio typically less than 2) and so, presumably, are the functional effects of individual genetic variants conferring disease susceptibility. Perhaps the greatest challenge in the ‘post-GWAS’ era is to understand the functional consequences of these loci. Biological insights can then be translated to clinical benefits, including reliable biomarkers and effective strategies for screening and disease prevention. The purpose of this article is to propose principles for the initial functional characterization of cancer risk loci, with a focus on non-coding variants, and to define ‘post-GWAS’ functional characterization. By December 2010, there were 1,212 published GWAS studies1 reporting significant (P < 5 × 10−8) associations for 210 traits (Table 1), and the Catalog of Published GWAS states that by March 2011, 812 publications reported 3,977 SNP associations1. This is likely a small fraction of the common susceptibility loci of low penetrance that will eventually be identified. Despite these successes in identifying risk loci, the causal variant and/or the molecular basis of risk etiology has been determined for only a small fraction of these associations2–4. Plausible candidate genes can be based on proximity to risk loci, but few have so far been defined in a more systematic manner (Supplementary Table 1). Table 1 The genomic context in which a variant is found can be used as preliminary functional analysis Increased investment in post-GWAS functional characterization of risk loci5 has now been advocated across diseases and for cardiovascular disease and diabetes6. For cancer biology, the complex interplay between genetics and the environment in many cancers poses a particularly exciting challenge for post-GWAS research. Here we suggest a systematic strategy for understanding how cancer-associated variants exert their effects. We mostly refer to SNPs throughout the paper, but we recognize that other types of common genetic (for example, copy number variants) or epigenetic variation may influence risk. Our understanding of the way in which a risk variant initiates disease pathogenesis progresses from statistical association between genetic variation and trait or disease variation to functionality and causality. The functional consequences of variants in protein-coding regions causing most monogenic disorders are more readily interpreted because we know the genetic code. For non-Mendelian or multifactorial traits, most of the common DNA variants have so far mapped to non-protein–coding regions2, where our understanding of functional consequences and causality is more rudimentary. Our hypothesis is that the trait-associated alleles exert their effects by influencing transcriptional output (such as transcript levels and splicing) through multiple mechanisms. We emphasize appropriate assays and models to test the functional effects of both SNPs and genes mapping to cancer predisposition loci. Although much of what is written is applicable to alleles discovered for any trait, the section on modeling gene effects will emphasize measuring cancer-related phenotypes. At some loci, multiple, independently associated risk alleles rather than single risk alleles may be functionally responsible for the occurrence of disease. Genotyping susceptibility loci (and their correlated variants) in multiple populations with different linkage disequilibrium (LD) structures may prove effective in substantially reducing the number of potentially causative variants (that is, the same causal variant may segregate in multiple populations), as shown for the FGFR2 locus in breast cancer7, but for most loci there will remain a set of potentially causative variants that cannot be separated at the statistical level from case-control genotype data. A susceptibility locus should be re-sequenced to ascertain all genetic variation, identifying candidate functional or causal variants and identifying candidate causal genes. Ideally, the identification of a causal SNP would be the next step to reveal the molecular mechanisms of risk modification. Practically, however, it is unclear what the criteria for causality should be, particularly in non-protein–coding regions. Thus, although we propose a framework set of analyses (Box 1), we acknowledge that the techniques and methods will continue to evolve with the field. Box 1 Strategies to progress from tag SNP to mechanism Target resequencing efforts using linkage disequilibrium (LD) structure. Use other populations to refine LD regions (for example African ancestry with shorter LD and more heterogeneity). Determine expression levels of nearby genes as a function of genotype at each locus (eQTL). Characterize gene regulatory regions by multiple empirical techniques bearing in mind that these are tissue and context specific. Combine regulatory regions with risk loci using coordinates from multiple reference genomes to capture all variation within the shorter regulatory regions that correlates with the tag SNP at each locus. Multiple experimental manipulations in model systems are needed to progressively implicate transcription units (genes) in mechanisms relevant to the associated loci: Knockouts of regulatory regions in animal (difficult and may be limited by functional redundancy, but new targeting methods in rat are promising) models followed by genome-wide expression analysis. Use chromatin association methods (3C, CHIA-PET) of regulatory regions to determine the identity of target genes (compare with eQTL data). Targeted gene perturbations in somatic cell models. Explore fully genome-wide eQTL and miRNA quantitative variation correlation in relevant tissues and cells. Explore epigenetic mechanisms in the context of genome-wide genetic polymorphism. Employ cell models and tissue reconstructions to evaluate mechanisms using gene perturbations and polymorphic variants. The human cancer cell xenograft has re-emerged as a minimal in vivo validation of these models. Above all, resist the temptation to equate any partial functional evidence as sufficient. Published claims of functional relevance should be fully evaluated using the steps detailed above.

A Major Lung Cancer Susceptibility Locus Maps to Chromosome 6q23–25

Lung cancer is a major cause of death in the United States and other countries. The risk of lung cancer is greatly increased by cigarette smoking and by certain occupational exposures, but familial factors also clearly play a major role. To identify susceptibility genes for familial lung cancer, we conducted a genomewide linkage analysis of 52 extended pedigrees ascertained through probands with lung cancer who had several first-degree relatives with the same disease. Multipoint linkage analysis, under a simple autosomal dominant model, of all 52 families with three or more individuals affected by lung, throat, or laryngeal cancer, yielded a maximum heterogeneity LOD score (HLOD) of 2.79 at 155 cM on chromosome 6q (marker D6S2436). A subset of 38 pedigrees with four or more affected individuals yielded a multipoint HLOD of 3.47 at 155 cM. Analysis of a further subset of 23 multigenerational pedigrees with five or more affected individuals yielded a multipoint HLOD score of 4.26 at the same position. The 14 families with only three affected relatives yielded negative LOD scores in this region. A predivided samples test for heterogeneity comparing the LOD scores from the 23 multigenerational families with those from the remaining families was significant (P=.007). The 1-HLOD multipoint support interval from the multigenerational families extends from C6S1848 at 146 cM to 164 cM near D6S1035, overlapping a genomic region that is deleted in sporadic lung cancers as well as numerous other cancer types. Parametric linkage and variance-components analysis that incorporated effects of age and personal smoking also supported linkage in this region, but with somewhat diminished support. These results localize a major susceptibility locus influencing lung cancer risk to 6q23-25.

Wildtype Kras2 can inhibit lung carcinogenesis in mice

Although the ras genes have long been established as proto-oncogenes, the dominant role of activated ras in cell transformation has been questioned. Previous studies have shown frequent loss of the wildtype Kras2 allele in both mouse and human lung adenocarcinomas. To address the possible tumor suppressor role of wildtype Kras2 in lung tumorigenesis, we have carried out a lung tumor bioassay in heterozygous Kras2-deficient mice. Mice with a heterozygous Kras2 deficiency were highly susceptible to the chemical induction of lung tumors when compared to wildtype mice. Activating Kras2 mutations were detected in all chemically induced lung tumors obtained from both wildtype and heterozygous Kras2-deficient mice. Furthermore, wildtype Kras2 inhibited colony formation and tumor development by transformed NIH/3T3 cells and a mouse lung tumor cell line containing an activated Kras2 allele. Allelic loss of wildtype Kras2 was found in 67% to 100% of chemically induced mouse lung adenocarcinomas that harbor a mutant Kras2 allele. Finally, an inverse correlation between the level of wildtype Kras2 expression and extracellular signal–regulated kinase (ERK) activity was observed in these cells. These data strongly suggest that wildtype Kras2 has tumor suppressor activity and is frequently lost during lung tumor progression.

Bnip3 Mediates the Hypoxia-induced Inhibition on Mammalian Target of Rapamycin by Interacting with Rheb

The mammalian target of rapamycin (mTOR) is a central controller of cell growth, and it regulates translation, cell size, cell viability, and cell morphology. mTOR integrates a wide range of extracellular and intracellular signals, including growth factors, nutrients, energy levels, and stress conditions. Rheb, a Ras-related small GTPase, is a key upstream activator of mTOR. In this study, we found that Bnip3, a hypoxia-inducible Bcl-2 homology 3 domain-containing protein, directly binds Rheb and inhibits the mTOR pathway. Bnip3 decreases Rheb GTP levels in a manner depending on the binding to Rheb and the presence of the N-terminal domain. Both knockdown and overexpression experiments show that Bnip3 plays an important role in mTOR inactivation in response to hypoxia. Moreover, Bnip3 inhibits cell growth in vivo by suppressing the mTOR pathway. These observations demonstrate that Bnip3 mediates the inhibition of the mTOR pathway in response to hypoxia.

Risk for nicotine dependence and lung cancer is conferred by mRNA expression levels and amino acid change in CHRNA5

Nicotine dependence risk and lung cancer risk are associated with variants in a region of chromosome 15 encompassing genes encoding the nicotinic receptor subunits CHRNA5, CHRNA3 and CHRNB4. To identify potential biological mechanisms that underlie this risk, we tested for cis-acting eQTLs for CHRNA5, CHRNA3 and CHRNB4 in human brain. Using gene expression and disease association studies, we provide evidence that both nicotine-dependence risk and lung cancer risk are influenced by functional variation in CHRNA5. We demonstrated that the risk allele of rs16969968 primarily occurs on the low mRNA expression allele of CHRNA5. The non-risk allele at rs16969968 occurs on both high and low expression alleles tagged by rs588765 within CHRNA5. When the non-risk allele occurs on the background of low mRNA expression of CHRNA5, the risk for nicotine dependence and lung cancer is significantly lower compared to those with the higher mRNA expression. Together, these variants identify three levels of risk associated with CHRNA5. We conclude that there are at least two distinct mechanisms conferring risk for nicotine dependence and lung cancer: altered receptor function caused by a D398N amino acid variant in CHRNA5 (rs16969968) and variability in CHRNA5 mRNA expression.

IκB kinase ε and TANK-binding kinase 1 activate AKT by direct phosphorylation

AKT activation requires phosphorylation of the activation loop (T308) by 3-phosphoinositide-dependent protein kinase 1 (PDK1) and the hydrophobic motif (S473) by the mammalian target of rapamycin complex 2 (mTORC2). We recently observed that phosphorylation of the AKT hydrophobic motif was dramatically elevated, rather than decreased, in mTOR knockout heart tissues, indicating the existence of other kinase(s) contributing to AKT phosphorylation. Here we show that the atypical IκB kinase ε and TANK-binding kinase 1 (IKKε/TBK1) phosphorylate AKT on both the hydrophobic motif and the activation loop in a manner dependent on PI3K signaling. This dual phosphorylation results in a robust AKT activation in vitro. Consistently, we found that growth factors can induce AKT (S473) phosphorylation in Rictor−/− cells, and this effect is insensitive to mTOR inhibitor Torin1. In IKKε/TBK1 double-knockout cells, AKT activation by growth factors is compromised. We also observed that TBK1 expression is elevated in the mTOR knockout heart tissues, and that TBK1 is required for Ras-induced mouse embryonic fibroblast transformation. Our observations suggest a physiological function of IKKε/TBK1 in AKT regulation and a possible mechanism of IKKε/TBK1 in oncogenesis by activating AKT.

Familial Aggregation of Common Sequence Variants on 15q24-25.1 in Lung Cancer

Three recent genome-wide association studies identified associations between markers in the chromosomal region 15q24-25.1 and the risk of lung cancer. We conducted a genome-wide association analysis to investigate associations between single-nucleotide polymorphisms (SNPs) and the risk of lung cancer, in which we used blood DNA from 194 case patients with familial lung cancer and 219 cancer-free control subjects. We identified associations between common sequence variants at 15q24-25.1 (that spanned LOC123688 [a hypothetical gene], PSMA4, CHRNA3, CHRNA5, and CHRNB4) and lung cancer. The risk of lung cancer was more than fivefold higher among those subjects who had both a family history of lung cancer and two copies of high-risk alleles rs8034191 (odds ratio [OR] = 7.20, 95% confidence interval [CI] = 2.21 to 23.37) or rs1051730 (OR = 5.67, CI = 2.21 to 14.60, both of which were located in the 15q24-25.1 locus, than among control subjects. Thus, further research to elucidate causal variants in the 15q24-25.1 locus that are associated with lung cancer is warranted.

Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing

Lung cancer is the leading cause of cancer-related death, with non-small cell lung cancer (NSCLC) being the predominant form of the disease. Most lung cancer is caused by the accumulation of genomic alterations due to tobacco exposure. To uncover its mutational landscape, we performed whole-exome sequencing in 31 NSCLCs and their matched normal tissue samples. We identified both common and unique mutation spectra and pathway activation in lung adenocarcinomas and squamous cell carcinomas, two major histologies in NSCLC. In addition to identifying previously known lung cancer genes (TP53, KRAS, EGFR, CDKN2A and RB1), the analysis revealed many genes not previously implicated in this malignancy. Notably, a novel gene CSMD3 was identified as the second most frequently mutated gene (next to TP53) in lung cancer. We further demonstrated that loss of CSMD3 results in increased proliferation of airway epithelial cells. The study provides unprecedented insights into mutational processes, cellular pathways and gene networks associated with lung cancer. Of potential immediate clinical relevance, several highly mutated genes identified in our study are promising druggable targets in cancer therapy including ALK, CTNNA3, DCC, MLL3, PCDHIIX, PIK3C2B, PIK3CG and ROCK2.