ABSTRACT: Lung cancer is a devastating disease and a major therapeutic burden with poor survival rates. It is responsible for 30% of all cancer deaths. Lung cancer is strongly associated with smoking, although some subtypes are also seen in non-smokers. Tumors in the latter group are mostly adenocarcinomas with many carrying mutations in the epidermal growth factor receptor (EGFR). Survival statistics of lung cancer are grim because of its late detection and frequent local and distal metastases. Although DNA sequence information from tumors has revealed a number of frequently occurring mutations, affecting well-known tumor suppressor genes and proto-oncogenes, many of the driver mutations remain ill defined. This is likely due to the involvement of numerous rather infrequently occurring driver mutations that are difficult to distinguish from the very large number of passenger mutations detected in smoking-related lung cancers. Therefore, experimental model systems are indispensable to validate putative driver lesions and to gain insight into their mechanisms of action. Whereas a large fraction of these analyzes can be performed in cell cultures in vitro, in many cases the consequences of the mutations have to be assessed in the context of an intact organism, as this is the context in which the Mendelian selection process of the tumorigenic process took place and the advantages of particular mutations become apparent. Current mouse models for cancer are very suitable for this as they permit mimicking many of the salient features of human tumors. The capacity to swiftly re-engineer complex sets of lesions found in human tumors in mice enables us to assess the contribution of defined combinations of lesions to distinct tumor characteristics such as metastatic behavior and response to therapy. In this review we will describe mouse models of lung cancer and how they are used to better understand the disease and how they are exploited to develop better intervention strategies.
Project description:Spatial and temporal dissection of the genomic changes occurring during the evolution of human non-small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC.
Project description:BACKGROUND:Cancer is caused by genetic mutations, but not all somatic mutations in human DNA drive the emergence or growth of cancers. While many frequently-mutated cancer driver genes have already been identified and are being utilized for diagnostic, prognostic, or therapeutic purposes, identifying driver genes that harbor mutations occurring with low frequency in human cancers is an ongoing endeavor. Typically, mutations that do not confer growth advantage to tumors - passenger mutations - dominate the mutation landscape of tumor cell genome, making identification of low-frequency driver mutations a challenge. The leading approach for discovering new putative driver genes involves analyzing patterns of mutations in large cohorts of patients and using statistical methods to discriminate driver from passenger mutations. RESULTS:We propose a novel cancer driver gene detection method, QuaDMutNetEx. QuaDMutNetEx discovers cancer drivers with low mutation frequency by giving preference to genes encoding proteins that are connected in human protein-protein interaction networks, and that at the same time show low deviation from the mutual exclusivity pattern that characterizes driver mutations occurring in the same pathway or functional gene group across a cohort of cancer samples. CONCLUSIONS:Evaluation of QuaDMutNetEx on four different tumor sample datasets show that the proposed method finds biologically-connected sets of low-frequency driver genes, including many genes that are not found if the network connectivity information is not considered. Improved quality and interpretability of the discovered putative driver gene sets compared to existing methods shows that QuaDMutNetEx is a valuable new tool for detecting driver genes. QuaDMutNetEx is available for download from https://github.com/bokhariy/QuaDMutNetExunder the GNU GPLv3 license.
Project description:Lung cancer is a leading cause of cancer-related mortality in many countries. Although recent advances in targeted therapy against driver oncogenes have significantly improved patient outcome, cure of this disease is still exceptional. Although tobacco is a known cause of lung cancer, not all smokers develop lung cancer, and conversely many patients, especially Asian female patients with lung cancer, are lifetime never-smokers. Therefore, efforts to understand the basis for different susceptibilities to lung cancer among individuals with different genetic, biologic, ethnic, and social backgrounds are important to help develop effective preventive measures. Lung cancer in never-smokers has many different characteristics to lung cancer in smokers, such as adenocarcinoma predominance and high frequency of epidermal growth factor receptor (EGFR) mutation yet low number of genetic changes. Epidemiologic studies suggest that East Asians are more susceptible to smoking-unrelated lung cancer but less susceptible to smoking-related lung cancer compared with Caucasians. Mutations in the EGFR gene are more common in Asian females and never-smokers. Our case-control study suggests that EGFR mutation occurs independent of smoking, and that the apparent low frequency of EGFR mutations in smokers may be the result of dilution by smoking-related lung cancer. The frequencies of three EGFR gene polymorphisms associated with increased protein expression are significantly different between East Asians and Caucasians, favoring lower protein expression in East Asians. Although these may be associated with preferred expression of the EGFR mutant allele, it is difficult to explain the frequent EGFR mutation in Asian patients. Genome wide association studies (GWAS) revealed several loci related to lung cancer susceptibility. In the future, GWAS may identify loci that are specifically related to EGFR-targeted carcinogenesis, leading to identification of carcinogens that induce EGFR mutations and effective prevention measures.
Project description:We sought to determine the frequency and clinical characteristics of patients with lung cancer harboring NRAS mutations. We used preclinical models to identify targeted therapies likely to be of benefit against NRAS-mutant lung cancer cells.We reviewed clinical data from patients whose lung cancers were identified at six institutions or reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) to harbor NRAS mutations. Six NRAS-mutant cell lines were screened for sensitivity against inhibitors of multiple kinases (i.e., EGFR, ALK, MET, IGF-1R, BRAF, PI3K, and MEK).Among 4,562 patients with lung cancers tested, NRAS mutations were present in 30 (0.7%; 95% confidence interval, 0.45%-0.94%); 28 of these had no other driver mutations. 83% had adenocarcinoma histology with no significant differences in gender. While 95% of patients were former or current smokers, smoking-related G:C>T:A transversions were significantly less frequent in NRAS-mutated lung tumors than KRAS-mutant non-small cell lung cancer [NSCLC; NRAS: 13% (4/30), KRAS: 66% (1772/2733), P < 0.00000001]. Five of 6 NRAS-mutant cell lines were sensitive to the MEK inhibitors, selumetinib and trametinib, but not to other inhibitors tested.NRAS mutations define a distinct subset of lung cancers (?1%) with potential sensitivity to MEK inhibitors. Although NRAS mutations are more common in current/former smokers, the types of mutations are not those classically associated with smoking.
Project description:The KRAS oncoprotein, a critical driver in 33% of lung adenocarcinoma (LUAD), has remained an elusive clinical target due to its perceived undruggable nature. The identification of dependencies borne through common co-occurring mutations are sought to more effectively target KRAS-mutant lung cancer. Approximately 20% of KRAS-mutant LUAD carry loss-of-function mutations in KEAP1, a negative regulator of the antioxidant response transcription factor NFE2L2/NRF2. We demonstrate that Keap1-deficient KrasG12D lung tumors arise from a bronchiolar cell-of-origin, lacking pro-tumorigenic macrophages observed in tumors originating from alveolar cells. Keap1 loss activates the pentose phosphate pathway, inhibition of which, using 6-AN, abrogated tumor growth. These studies highlight alternative therapeutic approaches to specifically target this unique subset of KRAS-mutant LUAD cancers.
Project description:OBJECTIVES:Lung adenocarcinoma in never-smokers accounts for 15-20% of all lung cancer. Although targetable mutations are more prevalent in these tumors, the biological and clinical importance of coexisting and/or mutually exclusive abnormalities is just emerging. This study evaluates the relationships between common genetic and epigenetic aberrations in these tumors. MATERIALS AND METHODS:Next-generation sequencing was employed to screen 20 commonly mutated cancer-driver genes in 112 lung adenocarcinomas from never-smokers. The relationship of these mutations with cancer-related methylation of 59 genes, and geographical/ethnic differences in the prevalence for mutations compared to multiple East Asian never-smoker lung adenocarcinoma cohorts was studied. RESULTS:The most common driver mutation detected in 40% (45/112) of the tumors was EGFR, followed by TP53 (18%), SETD2 (11%), and SMARCA4 (11%). Over 72% (81/112) of the cases have mutation of at least one driver gene. While 30% (34/112) of the tumors have co-mutations of two or more genes, 42% (47/112) have only one driver gene mutation. Differences in the prevalence for some of these mutations were seen between adenocarcinomas in East Asian versus US (mainly Caucasian) never-smokers including a significantly lower rate of EGFR mutation among the US patients. Interestingly, aberrant methylation of multiple cancer-related genes was significantly associated with EGFR wildtype tumors. Among 15 differentially methylated genes by EGFR mutation, 14 were more commonly methylated in EGFR wildtype compared to mutant tumors. These findings were independently validated using publicly available data. CONCLUSION:Most lung adenocarcinomas from never-smokers harbor targetable mutation/co-mutations. In the absence of EGFR mutation that drives 40% of these tumors, EGFR wildtype tumors appear to develop by acquiring aberrant promoter methylation that silences tumor-suppressor genes.
Project description:In cases of multiple lung cancers, individual tumors may represent either a primary lung cancer or both primary and metastatic lung cancers. In this study, we investigated the differences between clinical/histopathological and genomic diagnoses to determine whether they are primary or metastatic. 37 patients with multiple lung cancers were enrolled in this study. Tumor cells were selected from tissue samples using laser capture microdissection. DNA was extracted from those cells and subjected to targeted deep sequencing. In multicentric primary lung cancers, the driver mutation profile was mutually exclusive among the individual tumors, while it was consistent between metastasized tumors and the primary lesion. In 11 patients (29.7%), discrepancies were observed between genomic and clinical/histopathological diagnoses. For the lymph node metastatic lesions, the mutation profile was consistent with only one of the two primary lesions. In three of five cases with lymph node metastases, the lymph node metastatic route detected by genomic diagnosis differed from the clinical and/or pathological diagnoses. In conclusion, in patients with multiple primary lung cancers, cancer-specific mutations can serve as clonal markers, affording a more accurate understanding of the pathology of multiple lung cancers and their lymphatic metastases and thus improving both the treatment selection and outcome.
Project description:BACKGROUND: Evidence strongly suggests that spontaneous doublet mutations in normal mouse tissues generally arise from chronocoordinate events. These chronocoordinate mutations sometimes reflect "mutation showers", which are multiple chronocoordinate mutations spanning many kilobases. However, little is known about mutagenesis of doublet and multiplet mutations (domuplets) in human cancer. Lung cancer accounts for about 25% of all cancer deaths. Herein, we analyze the epidemiology of domuplets in the EGFR and TP53 genes in lung cancer. The EGFR gene is an oncogene in which doublets are generally driver plus driver mutations, while the TP53 gene is a tumor suppressor gene with a more typical situation in which doublets derive from a driver and passenger mutation. METHODOLOGY/PRINCIPAL FINDINGS: EGFR mutations identified by sequencing were collected from 66 published papers and our updated EGFR mutation database (www.egfr.org). TP53 mutations were collected from IARC version 12 (www-p53.iarc.fr). For EGFR and TP53 doublets, no clearly significant differences in race, ethnicity, gender and smoking status were observed. Doublets in the EGFR and TP53 genes in human lung cancer are elevated about eight- and three-fold, respectively, relative to spontaneous doublets in mouse (6% and 2.3% versus 0.7%). CONCLUSIONS/SIGNIFICANCE: Although no one characteristic is definitive, the aggregate properties of doublet and multiplet mutations in lung cancer are consistent with a subset derived from chronocoordinate events in the EGFR gene: i) the eight frameshift doublets (present in 0.5% of all patients with EGFR mutations) are clustered and produce a net in-frame change; ii) about 32% of doublets are very closely spaced (< or =30 nt); and iii) multiplets contain two or more closely spaced mutations. TP53 mutations in lung cancer are very closely spaced (< or =30 nt) in 33% of doublets, and multiplets generally contain two or more very closely spaced mutations. Work in model systems is necessary to confirm the significance of chronocoordinate events in lung and other cancers.
Project description:Lung cancer is still responsible for the highest number of cancer deaths worldwide. Despite this fact, significant progress has been made in the treatment of non-small cell lung cancer (NSCLC). Specifically, efforts to identify and treat genetic alterations (gene mutations, gene fusions, gene amplification events, etc.) that result in oncogenic drivers are now standard of care (EGFR and ALK) or an intense area of research. The most prevalent oncogenic drivers have likely already been identified; thus, there is now a focus on subgroups of tumors with less common genetic alterations. Interestingly, as we explore these less common mutations, we are discovering that many occur across other tumor types (i.e., non-lung cancer), further justifying their study. Furthermore, many studies have demonstrated that by searching broadly for multiple genetic alterations in large subsets of patients they are able to identify potentially targetable alterations in the majority of patients. Although individually, the rare oncogenic drivers subgroups may seem to occur too infrequently to justify their exploration, the fact that the majority of patients with NSCLC harbor a potentially actionable driver mutation within their tumors and the fact that different types of cancers often have the same oncogenic driver justifies this approach.
Project description:Although non-small-cell lung cancer is a leading cause of cancer-related deaths, the molecular characterization and classification of its genetic alterations has drastically changed treatment options and overall survival within the last few decades. In particular, tyrosine kinase inhibitors targeting specific molecular alterations, among other MET, have greatly improved the prognosis of non-small-cell lung cancer patients. Here, we compare the genomic background of a subset of non-small-cell lung cancer cases harboring either a MET high-level amplification (n = 24) or a MET exon 14 skipping mutation (n = 26), using next-generatison sequencing, fluorescence in situ hybridization, immunohistochemistry, and Nanostring nCounter® technology. We demonstrate that the MET-amplified cohort shows a higher genetic instability, compared with the mutant cohort (p < 0.001). Furthermore, MET mutations occur at high allele frequency and in the presence of co-occurring TP53 mutations (n = 7), as well as MDM2 (n = 7), CDK4 (n = 6), and HMGA2 (n = 5) co-amplifications. No other potential driver mutation has been detected. Conversely, in the MET-amplified group, we identify co-occurring pathogenic NRAS and KRAS mutations (n = 5) and a significantly higher number of TP53 mutations, compared with the MET-mutant cohort (p = 0.048). Of note, MET amplifications occur more frequently as subclonal events. Interestingly, despite the significantly (p = 0.00103) older age at diagnosis of stage IIIb/IV of MET-mutant patients (median 77 years), compared with MET high-level amplified patients (median 69 years), MET-mutant patients with advanced-stage tumors showed a significantly better prognosis at 12 months (p = 0.04). In conclusion, the two groups of MET genetic alterations differ, both clinically and genetically: our data strongly suggest that MET exon 14 skipping mutations represent an early driver mutation. In opposition, MET amplifications occur usually in the background of other strong genetic events and therefore MET amplifications should be interpreted in the context of each tumor's genetic background, rather than as an isolated driver event, especially when considering MET-specific treatment options.