Genomic and transcriptional alterations in lung adenocarcinoma in relation to smoking history

Exposure to Tobacco Smoking Induces a subset of Activated Tumor-resident Tregs in Non-Small Cell Lung Cancer

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Tumor-specific smoking-induced differentially expressed genes are different in male and female patients.

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A smoking-related tumor-specific Treg subset is defined, highly expressed ADAM12.

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ADAM12⁺ CTLA4⁺ Tregs actively communicated with exhausted T cells than other Tregs.

Tobacco smoking is the major cause of non-small-cell-lung cancer (NSCLC). However, it is barely known how smoking impact the tumor immune environment (TIME) of lung cancer.

We integrated single-cell RNA-seq and bulk RNA-seq data from several studies to systematically study the impact of smoking on T cells in treatment naïve NSCLC patients. We defined a set of smoking-induced differentially expressed genes (SIDEGs) in different cells in TIME.. Specifically, we defined a smoking-related tumor-specific Treg subset, ADAM12⁺ CTLA4⁺ Tregs according to the trajectory analysis and highly express genes in cell adhesion pathways and lipid metabolism. Using independent datasets from treatment naïve patients, we found that the fraction of ADAM12⁺ CTLA4⁺ Tregs are significantly increased in patients with smoking history. Moreover, the fraction of ADAM12⁺ CTLA4⁺ Tregs are positively correlated with the fraction of exhausted T cells. Additionally, we reconstructed the spatial organization of the tumor immune microenvironment and found that ADAM12⁺ CTLA4⁺ Tregs more actively communicate with LAYN⁺CD8⁺ exhausted T cells compared with ADAM12⁻CTLA4⁺ Tregs.

Our data demonstrate that smoking induced a unique subset of tumor-specific activated Tregs which interact with exhausted T cells in the TIME. Our findings not only explained how smoking impact the TIME but also provide new targets and biomarkers for precision immunotherapy of lung cancer.

Concomitant and decoupled effects of cigarette smoke and SCAL1 upregulation on oncogenic phenotypes and ROS detoxification in lung adenocarcinoma cells

Lung cancer is the leading cause of cancer deaths worldwide, with smoking as its primary predisposing factor. Although carcinogens in cigarettes are known to cause oncogenic DNA alterations, analyses of patient cohorts revealed heterogeneous genetic aberrations with no clear driver mutations. The contribution of noncoding RNAs (ncRNAs) in the pathogenesis of lung cancer has since been demonstrated. Their dysregulation has been linked to cancer initiation and progression. A novel long noncoding RNA (lncRNA) called smoke and cancer-associated lncRNA 1 (SCAL1) was recently found upregulated in smoke-exposed adenocarcinomic alveolar epithelial cells. The present study characterized the phenotypic consequences of SCAL1 overexpression and knockdown using A549 cells as model system, with or without prior exposure to cigarette smoke extract (CSE). Increase in SCAL1 levels either by CSE treatment or SCAL1 overexpression led to increased cell migration, extensive cytoskeletal remodeling, and resistance to apoptosis. Further, SCAL1 levels were negatively correlated with intracellular levels of reactive oxygen species (ROS). In contrast, SCAL1 knockdown showed converse results for these assays. These results confirm the oncogenic function of SCAL1 and its role as a CSE-activated lncRNA that mediates ROS detoxification in A549 cells, thereby allowing them to develop resistance to and survive smoke-induced toxicity.

MARCKS cooperates with NKAP to activate NF-kB signaling in smoke-related lung cancer

Rationale: Cigarette smoking is a major risk factor for lung cancer development and progression; however, the mechanism of how cigarette smoke activates signaling pathways in promoting cancer malignancy remains to be established. Herein, we aimed to determine the contribution of a signaling protein, myristoylated alanine-rich C kinase substrate (MARCKS), in smoke-mediated lung cancer. Methods: We firstly examined the levels of phosphorylated MARCKS (phospho-MARCKS) in smoke-exposed human lung cancer cells and specimens as well as non-human primate airway epithelium. Next, the MARCKS-interactome and its gene networks were identified. We also used genetic and pharmacological approaches to verify the functionality and molecular mechanism of smoke-induced phospho-MARCKS. Results: We observed that MARCKS becomes activated in airway epithelium and lung cancer cells in response to cigarette smoke. Functional proteomics revealed MARCKS protein directly binds to NF-κB-activating protein (NKAP). Following MARCKS phosphorylation at ser159 and ser163, the MARCKS-NKAP interaction was inhibited, leading to the activation of NF-κB signaling. In a screen of two cohorts of lung cancer patients, we confirmed that phospho-MARCKS is positively correlated with phospho-NF-κB (phospho-p65), and poor survival. Surprisingly, smoke-induced phospho-MARCKS upregulated the expression of pro-inflammatory cytokines, epithelial-mesenchymal transition, and stem-like properties. Conversely, targeting of MARCKS phosphorylation with MPS peptide, a specific MARCKS phosphorylation inhibitor, suppressed smoke-mediated NF-κB signaling activity, pro-inflammatory cytokines expression, aggressiveness and stemness of lung cancer cells. Conclusion: Our results suggest that phospho-MARCKS is a novel NF-kB activator in smoke-mediated lung cancer progression and provide a promising molecular model for developing new anticancer strategies.

Periodontal Conditions and Whole Salivary IL-17A and -23 Levels among Young Adult Cannabis sativa (Marijuana)-Smokers, Heavy Cigarette-Smokers and Non-Smokers

In the United States, prevalence of marijuana-use has doubled in the past 2 decades. The aim was to compare the periodontal conditions and whole-salivary IL-17A and IL-23 levels among young adult marijuana-smokers, heavy cigarette-smokers and non-smokers. Self-reported marijuana-smokers, heavy-cigarette-smokers, non-smokers with periodontitis and periodontally-healthy non-smokers were included. Demographic data was recorded and full-mouth plaque index (PI), bleeding on probing (BoP), probing depth (PD) and clinical attachment loss (AL), marginal bone loss (MBL) and missing teeth were recorded. Levels of IL-17A and IL-23 levels were measured in the whole saliva. p < 0.01 was considered statistically significant. Fifteen-marijuana-smokers, 15 heavy-cigarette-smokers, 16 non-smokers-with-periodontitis and 15 periodontally-healthy-non-smokers) were included. The clinicoradiographic parameters were worse among marijuana-smokers (p < 0.01), cigarette-smokers (p < 0.01) and non-smokers-with-periodontitis (p < 0.01) than periodontally-healthy-non-smokers. Marijuana- and cigarette-smokers had Stage-IV/Grade C and non-smokers with periodontitis had Stage-III/Grade-C. Salivary IL-17A and IL-23 levels were higher in marijuana-smokers than cigarette-smokers (p < 0.01) and non-smokers-with-periodontitis (p < 0.01). Whole salivary IL-17A and IL-23 levels were higher among cigarette-smokers than non-smokers with periodontitis (p < 0.01) and periodontally-healthy-individuals (p < 0.01). Marijuana- and heavy cigarette-smokers have comparable clinicoradiographic periodontal statuses. This rejects hypothesis-1. However, whole salivary immunoinflammatory response may be moderately worse in marijuana-smokers compared with heavy cigarette-smokers and non-smoker with periodontitis thereby supporting hypothesis-2.

Expression of the immunoproteasome subunit β5i in non-small cell lung carcinomas

AIM

The immunoproteasome is a specific proteasome isoform whose proteolytic activity enhances the generation of antigenic peptides to be presented by major histocompatibility complex class I molecules to CD8⁺ T cells. Physiologically, it is expressed abundantly in immune cells and is induced in somatic cells by cytokines, especially interferon-γ. Recently, variable expression of immunoproteasomes has been demonstrated in different types of cancers. However, the clinical significance of immunoproteasome expression in malignant tumours is poorly understood. In this study, we performed clinicopathological evaluation of immunoproteasome subunit β5i in non-small cell lung carcinomas (NSCLCs).

METHODS

Tumour tissues were collected from 155 patients with NSCLCs, and immunohistochemical analysis for β5i was performed in relation to the prognosis of patients.

RESULTS

High expression of β5i was found in about 20% of all NSCLCs and was found significantly more frequently (40%) in the adenocarcinoma subset. High expression of β5i was associated with a better 5-year relative survival rate in patients with pStage I to II adenocarcinoma and was also a significant and independent favourable prognostic factor in adenocarcinoma patients. In addition, when we performed in vitro analysis using NSCLC cell lines, combined treatment with the immunoproteasome-specific inhibitor ONX0914 and the proteasome inhibitor MG132 enhanced cell death in β5i-expressing NSCLC cell lines.

CONCLUSION

The expression of immunoproteasome can be explored as both a prognostic factor and a potential therapeutic target in NSCLCs. Since immunoproteasomes have crucial role in the antigen presentation, further studies may help to provide essential knowledge for therapeutic strategies in anticancer immunotherapy.

Identification and validation of smoking-related genes in lung adenocarcinoma using an in vitro carcinogenesis model and bioinformatics analysis

Background

Lung cancer is one of the most common carcinomas in the world, and lung adenocarcinoma (LUAD) is the most lethal and most common subtype of lung cancer. Cigarette smoking is the most leading risk factor of lung cancer, but it is still unclear how normal lung cells become cancerous in cigarette smokers. This study aims to identify potential smoking-related biomarkers associated with the progression and prognosis of LUAD, as well as their regulation mechanism using an in vitro carcinogenesis model and bioinformatics analysis.

Results

Based on the integration analysis of four Gene Expression Omnibus (GEO) datasets and our mRNA sequencing analysis, 2 up-regulated and 11 down-regulated genes were identified in both S30 cells and LUAD. By analyzing the LUAD dataset in The Cancer Gene Analysis (TCGA) database, 3 of the 13 genes, viz., glycophorin C (GYPC), NME/NM23 nucleoside diphosphate kinase 1 (NME1) and slit guidance ligand 2 (SLIT2), were found to be significantly correlated with LUAD patients’ smoking history. The expression levels of GYPC, NME1 and SLIT2 in S30 cells and lung cancer cell lines were validated by quantitative PCR, immunofluorescence, and western blot assays. Besides, these three genes are associated with tumor invasion depth, and elevated expression of NME1 was correlated with lymph node metastasis. The enrichment analysis suggested that these genes were highly correlated to tumorigenesis and metastasis-related biological processes and pathways. Moreover, the increased expression levels of GYPC and SLIT2, as well as decreased expression of NME1 were associated with a favorable prognosis in LUAD patients. Furthermore, based on the multi-omics data in the TCGA database, these genes were found to be regulated by DNA methylation.

Conclusion

In conclusion, our observations indicated that the differential expression of GYPC, NME1 and SLIT2 may be regulated by DNA methylation, and they are associated with cigarette smoke-induced LUAD, as well as serve as prognostic factors in LUAD patients.

Genetic and microenvironmental differences in non-smoking lung adenocarcinoma patients compared with smoking patients

Background

Non-smoking-related lung adenocarcinoma (LUAD) has its own characteristics. Genetic and microenvironmental differences in smoking and non-smoking LUAD patients were analyzed to elucidate the oncogenesis of non-smoking-related LUAD, which will improve our understanding of the underlying molecular mechanism and be of clinical use in the future.

Methods

The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) databases were used for clinical and genomic information. Various bioinformatics tools were used to analyze differences in somatic mutations, RNA and microRNA (miRNA) expression, immune infiltration, and stemness indices. GO, KEGG, and GSVA analyses were performed with R. A merged protein-protein interaction (PPI) network was constructed and analyzed. A miRNA-differentially expressed gene network was constructed with miRNet. qRT-PCR was used for validation of 4 most significantly differently expressed genes and 2 miRNAs in tumor samples obtained from 20 pairs of non-smoking and smoking patients.

Results

Five hundred and one patients with LUAD were obtained, including 210 in the non-smoking group and 292 in the smoking group. A total of 174 significantly altered somatic mutations were detected, including mutations in tumor protein p53 and epidermal growth factor receptor, which were downregulated in non-smoking-related LUAD. At the RNA level, 231 significantly differentially expressed genes were obtained; 124 were upregulated and 107 downregulated in the non-smoking group. GSVA analysis revealed 42 significant pathways. Other functional and enrichment analyses of somatic mutations and RNA expression levels revealed that these genes were significantly enriched in receptor activity regulation and receptor binding. Differences in microenvironments including immune infiltration (e.g., CD8⁺ T cells and resting mast cells) and stemness indices were also found between groups. A 79-pair interaction was found between differentially expressed genes and miRNAs, of which miR-335-5p and miR-34a-5p were located in the center. Twenty-one genes, including vitronectin, neurotensin, and neuronatin, were differentially expressed in both non-smoking LUAD patients and DMSO-treated A549 cells. And the different expression of neurotensin, neuronatin, trefoil factor family2, regenerating family member 4, miR-377-5p, miR-34a were verified with the same tendency in our own samples.

Conclusions

Non-smoking LUAD patients, compared to smokers, have different characteristics in terms of somatic mutation, gene, and miRNA expression and the microenvironment, indicating a diverse mechanism of oncogenesis.

Multiple genome pattern analysis and signature gene identification for the Caucasian lung adenocarcinoma patients with different tobacco exposure patterns

Background

When considering therapies for lung adenocarcinoma (LUAD) patients, the carcinogenic mechanisms of smokers are believed to differ from those who have never smoked. The rising trend in the proportion of nonsmokers in LUAD urgently requires the understanding of such differences at a molecular level for the development of precision medicine.

Methods

Three independent LUAD tumor sample sets—TCGA, SPORE and EDRN—were used. Genome patterns of expression (GE), copy number variation (CNV) and methylation (ME) were reviewed to discover the differences between them for both smokers and nonsmokers. Tobacco-related signature genes distinguishing these two groups of LUAD were identified using the GE, ME and CNV values of the whole genome. To do this, a novel iterative multi-step selection method based on the partial least squares (PLS) algorithm was proposed to overcome the high variable dimension and high noise inherent in the data. This method can thoroughly evaluate the importance of genes according to their statistical differences, biological functions and contributions to the tobacco exposure classification model. The kernel partial least squares (KPLS) method was used to further optimize the accuracies of the classification models.

Results

Forty-three, forty-eight and seventy-five genes were identified as GE, ME and CNV signatures, respectively, to distinguish smokers from nonsmokers. Using only the gene expression values of these 43 GE signature genes, ME values of the 48 ME signature genes or copy numbers of the 75 CNV signature genes, the accuracies of TCGA training and SPORE/EDRN independent validation datasets all exceed 76%. More importantly, the focal amplicon in Telomerase Reverse Transcriptase in nonsmokers, the broad deletion in ChrY in male nonsmokers and the greater amplification of MDM2 in female nonsmokers may explain why nonsmokers of both genders tend to suffer LUAD. These pattern analysis results may have clear biological interpretation in the molecular mechanism of tumorigenesis. Meanwhile, the identified signature genes may serve as potential drug targets for the precision medicine of LUAD.

Clinical features and therapeutic options in non-small cell lung cancer patients with concomitant mutations of EGFR, ALK, ROS1, KRAS or BRAF

Background

Although oncogenic driver mutations were thought to be mutually exclusive in non‐small cell lung cancer (NSCLC), certain tumors harbor co‐occurring mutations and represent a rare molecular subtype. The evaluation of the clinical features and therapeutic response associated with this NSCLC subtype will be vital for understanding the heterogeneity of treatment response and improving the management of these patients.

Methods

This retrospective study included 3774 samples from patients diagnosed with NSCLC. All samples were screened for EGFR, ALK, ROS1, KRAS, and BRAF mutation using the amplification‐refractory mutation system. The relationship between concomitant driver mutations and clinicopathologic characteristics, and patient clinical outcomes were evaluated.

Results

Sixty‐three (1.7%) samples had more than one driver gene mutation. Among these, 43 were coalterations with an EGFR mutation, 20 with an ALK rearrangement, and eight with an ROS1 rearrangement. Except for ROS1 concomitant mutations that were more frequent in male patients (87.5%, P = 0.020), the clinicopathological features of the concomitant mutation patients were not significantly different from those harboring a single EGFR, ALK, or ROS1 mutation. Furthermore, first‐line EGFR‐TKI treatment did not significantly improve the progression‐free survival (PFS) of patients harboring EGFR concomitant mutation, compared to patients harboring a single EGFR mutation. However, for EGFR concomitant mutation patients, TKI therapy was more effective than chemotherapy (median PFS of 10.8 vs 5.2 months, P = 0.023). Lastly, KRAS mutations did not influence the EGFR‐TKI therapy treatment effect.

Conclusion

In this study, concomitant mutations were found in 1.7% of the NSCLC. EGFR‐TKI therapy was more effective than chemotherapy for patients harboring EGFR concomitant mutation, and ROS1 concomitant mutations were more frequent in male patients. For patients harboring coalterations with an ALK or ROS1 rearrangement, we should be cautious when considering the therapeutic options.

Histopathological Imaging⁻Environment Interactions in Cancer Modeling

Histopathological imaging has been routinely conducted in cancer diagnosis and recently used for modeling other cancer outcomes/phenotypes such as prognosis. Clinical/environmental factors have long been extensively used in cancer modeling. However, there is still a lack of study exploring possible interactions of histopathological imaging features and clinical/environmental risk factors in cancer modeling. In this article, we explore such a possibility and conduct both marginal and joint interaction analysis. Novel statistical methods, which are “borrowed” from gene–environment interaction analysis, are employed. Analysis of The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) data is conducted. More specifically, we examine a biomarker of lung function as well as overall survival. Possible interaction effects are identified. Overall, this study can suggest an alternative way of cancer modeling that innovatively combines histopathological imaging and clinical/environmental data.

Patients with SMARCA4-deficient thoracic sarcoma and severe skeletal-related events

OBJECTIVES

SMARCA4-deficient thoracic sarcoma(DTS) is a recently identified new entity of thoracic malignancies characterized by inactivation of SMARCA4. Patients with SMARCA4-DTS have a particulary aggresive clinical course and no effective treatments. However, the detailed clinical features of SMARCA4-DTS remain unclear. Here, we report the clinical courses and molecular profiles of two cases of SMARCA4-DTS.

MATERIALS AND METHODS

We experienced strikingly similar two patients of SMARCA4-DTS. The clinicopathologic features were reviewed, and detailed immunohistochemical and comprehensive cancer panel analysis with next generation sequencing confirmed the diagnosis.

RESULTS

Our cases had many clinical and radiological observations characteristic of SMARCA4-DTS in common. Immunohistochemical staing showed complete loss of SMARCA4 in tumor cells. Loss of function mutations were detected in SMARCA4. We found that severe SREs comprise a new significant clinical feature of SMARCA4-DTS.

CONCLUSION

Integrated clinico-radiologic-pathologic-genetic diagnosis is essential for SMARCA4-DTS and physicians should pay attention to severe SREs during the clinical course of this disease.

Integrative Genomic Analyses Identifies GGA2 as a Cooperative Driver of EGFR-Mediated Lung Tumorigenesis

INTRODUCTION

Targeted therapies for lung adenocarcinoma (LUAD) have improved patient outcomes; however, drug resistance remains a major problem. One strategy to achieve durable response is to develop combination-based therapies that target both mutated oncogenes and key modifiers of oncogene-driven tumorigenesis. This is based on the premise that mutated oncogenes, although necessary, are not sufficient for malignant transformation. We aimed to uncover genetic alterations that cooperate with mutant EGFR during LUAD development.

METHODS

We performed integrative genomic analyses, combining copy number, gene expression and mutational information for over 500 LUAD tumors. Co-immunoprecipitation and Western blot analysis were performed in LUAD cell lines to confirm candidate interactions while RNA interference and gene overexpression were used for in vitro and in vivo functional assessment.

RESULTS

We identified frequent amplifications/deletions of chromosomal regions affecting the activity of genes specifically in the context of EGFR mutation, including amplification of the mutant EGFR allele and deletion of dual specificity phosphatase 4 (DUSP4), which have both previously been reported. In addition, we identified the novel amplification of a segment of chromosome arm 16p in mutant-EGFR tumors corresponding to increased expression of Golgi Associated, Gamma Adaptin Ear Containing, ARF Binding Protein 2 (GGA2), which functions in protein trafficking and sorting. We found that GGA2 interacts with EGFR, increases EGFR protein levels and modifies EGFR degradation after ligand stimulation. Furthermore, we show that overexpression of GGA2 enhances EGFR mediated transformation while GGA2 knockdown reduces the colony and tumor forming ability of EGFR mutant LUAD.

CONCLUSIONS

These data suggest that overexpression of GGA2 in LUAD tumors results in the accumulation of EGFR protein and increased EGFR signaling, which helps drive tumor progression. Thus, GGA2 plays a cooperative role with EGFR during LUAD development and is a potential therapeutic target for combination-based strategies in LUAD.

Consensus of gene expression phenotypes and prognostic risk predictors in primary lung adenocarcinoma

Transcriptional profiling of lung adenocarcinomas has identified numerous gene expression phenotype (GEP) and risk prediction (RP) signatures associated with patient outcome. However, classification agreement between signatures, underlying transcriptional programs, and independent signature validation are less studied. We classified 2395 transcriptional adenocarcinoma profiles, assembled from 17 public cohorts, using 11 GEP and seven RP signatures, finding that 16 signatures were associated with patient survival in the total cohort and in multiple individual cohorts. For significant signatures, total cohort hazard ratios were ~2 in univariate analyses (mean=1.95, range=1.4-2.6). Strong classification agreement between signatures was observed, especially for predicted low-risk patients by adenocarcinoma-derived signatures. Expression of proliferation-related genes correlated strongly with GEP subtype classifications and RP scores, driving the gene signature association with prognosis. A three-group consensus definition of samples across 10 GEP classifiers demonstrated aggregation of samples with specific smoking patterns, gender, and EGFR/KRAS mutations, while survival differences were only significant when patients were divided into low- or high-risk. In summary, our study demonstrates a consensus between GEPs and RPs in lung adenocarcinoma through a common underlying transcriptional program. This consensus generalizes reported problems with current signatures in a clinical context, stressing development of new adenocarcinoma-specific single sample predictors for clinical use.

Elucidating the genomic architecture of Asian EGFR-mutant lung adenocarcinoma through multi-region exome sequencing

EGFR-mutant lung adenocarcinomas (LUAD) display diverse clinical trajectories and are characterized by rapid but short-lived responses to EGFR tyrosine kinase inhibitors (TKIs). Through sequencing of 79 spatially distinct regions from 16 early stage tumors, we show that despite low mutation burdens, EGFR-mutant Asian LUADs unexpectedly exhibit a complex genomic landscape with frequent and early whole-genome doubling, aneuploidy, and high clonal diversity. Multiple truncal alterations, including TP53 mutations and loss of CDKN2A and RB1, converge on cell cycle dysregulation, with late sector-specific high-amplitude amplifications and deletions that potentially beget drug resistant clones. We highlight the association between genomic architecture and clinical phenotypes, such as co-occurring truncal drivers and primary TKI resistance. Through comparative analysis with published smoking-related LUAD, we postulate that the high intra-tumor heterogeneity observed in Asian EGFR-mutant LUAD may be contributed by an early dominant driver, genomic instability, and low background mutation rates.

EGFR mutant lung adenocarcinoma (LUAD) exhibit diverse clinical outcomes in response to targeted therapies. Here the authors show that these LUADs involve a complex genomic landscape with high intratumor heterogeneity, providing insights into the evolutionary trajectory of oncogene-driven LUAD and potential mediators of EGFR TKI resistance.

Integrative CAGE and DNA Methylation Profiling Identify Epigenetically Regulated Genes in NSCLC

Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of cancer driver mutations have been identified; however, relevant epigenetic regulation involved in tumorigenesis has only been fragmentarily analyzed. Epigenetically regulated genes have a great theranostic potential, especially in tumors with no apparent driver mutations. Here, epigenetically regulated genes were identified in lung cancer by an integrative analysis of promoter-level expression profiles from Cap Analysis of Gene Expression (CAGE) of 16 non-small cell lung cancer (NSCLC) cell lines and 16 normal lung primary cell specimens with DNA methylation data of 69 NSCLC cell lines and 6 normal lung epithelial cells. A core set of 49 coding genes and 10 long noncoding RNAs (lncRNA), which are upregulated in NSCLC cell lines due to promoter hypomethylation, was uncovered. Twenty-two epigenetically regulated genes were validated (upregulated genes with hypomethylated promoters) in the adenocarcinoma and squamous cell cancer subtypes of lung cancer using The Cancer Genome Atlas data. Furthermore, it was demonstrated that multiple copies of the REP522 DNA repeat family are prominently upregulated due to hypomethylation in NSCLC cell lines, which leads to cancer-specific expression of lncRNAs, such as RP1-90G24.10, AL022344.4, and PCAT7. Finally, Myeloma Overexpressed (MYEOV) was identified as the most promising candidate. Functional studies demonstrated that MYEOV promotes cell proliferation, survival, and invasion. Moreover, high MYEOV expression levels were associated with poor prognosis.Implications: This report identifies a robust list of 22 candidate driver genes that are epigenetically regulated in lung cancer; such genes may complement the known mutational drivers.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/15/10/1354/F1.large.jpg Mol Cancer Res; 15(10); 1354-65. ©2017 AACR.

Gene Expression Profiling of Large Cell Lung Cancer Links Transcriptional Phenotypes to the New Histological WHO 2015 Classification

INTRODUCTION

Large cell lung cancer (LCLC) and large cell neuroendocrine carcinoma (LCNEC) constitute a small proportion of NSCLC. The WHO 2015 classification guidelines changed the definition of the debated histological subtype LCLC to be based on immunomarkers for adenocarcinoma and squamous cancer. We sought to determine whether these new guidelines also translate into the transcriptional landscape of lung cancer, and LCLC specifically.

METHODS

Gene expression profiling was performed by using Illumina V4 HT12 microarrays (Illumina, San Diego, CA) on samples from 159 cases (comprising all histological subtypes, including 10 classified as LCLC WHO 2015 and 14 classified as LCNEC according to the WHO 2015 guidelines), with complimentary mutational and immunohistochemical data. Derived transcriptional phenotypes were validated in 199 independent tumors, including six WHO 2015 LCLCs and five LCNECs.

RESULTS

Unsupervised analysis of gene expression data identified a phenotype comprising 90% of WHO 2015 LCLC tumors, with characteristics of poorly differentiated proliferative cancer, a 90% tumor protein p53 gene (TP53) mutation rate, and lack of well-known NSCLC oncogene driver alterations. Validation in independent data confirmed aggregation of WHO 2015 LCLCs in the specific phenotype. For LCNEC tumors, the unsupervised gene expression analysis suggested two different transcriptional patterns corresponding to a proposed genetic division of LCNEC tumors into SCLC-like and NSCLC-like cancer on the basis of TP53 and retinoblastoma 1 gene (RB1) alteration patterns.

CONCLUSIONS

Refined classification of LCLC has implications for diagnosis, prognostics, and therapy decisions. Our molecular analyses support the WHO 2015 classification of LCLC and LCNEC tumors, which herein follow different tumorigenic paths and can accordingly be stratified into different transcriptional subgroups, thus linking diagnostic immunohistochemical staining-driven classification with the transcriptional landscape of lung cancer.

Identification of feature genes for smoking-related lung adenocarcinoma based on gene expression profile data

This study aimed to identify the genes and pathways associated with smoking-related lung adenocarcinoma. Three lung adenocarcinoma associated datasets (GSE43458, GSE10072, and GSE50081), the subjects of which included smokers and nonsmokers, were downloaded to screen the differentially expressed feature genes between smokers and nonsmokers. Based on the identified feature genes, we constructed the protein-protein interaction (PPI) network and optimized feature genes using closeness centrality (CC) algorithm. Then, the support vector machine (SVM) classification model was constructed based on the feature genes with higher CC values. Finally, pathway enrichment analysis of the feature genes was performed. A total of 213 down-regulated and 83 up-regulated differentially expressed genes were identified. In the constructed PPI network, the top ten nodes with higher degrees and CC values included ANK3, EPHA4, FGFR2, etc. The SVM classifier was constructed with 27 feature genes, which could accurately identify smokers and nonsmokers. Pathways enrichment analysis for the 27 feature genes revealed that they were significantly enriched in five pathways, including proteoglycans in cancer (EGFR, SDC4, SDC2, etc.), and Ras signaling pathway (FGFR2, PLA2G1B, EGFR, etc.). The 27 feature genes, such as EPHA4, FGFR2, and EGFR for SVM classifier construction and cancer-related pathways of Ras signaling pathway and proteoglycans in cancer may play key roles in the progression and development of smoking-related lung adenocarcinoma.

Mutational and gene fusion analyses of primary large cell and large cell neuroendocrine lung cancer

Large cell carcinoma with or without neuroendocrine features (LCNEC and LC, respectively) constitutes 3-9% of non-small cell lung cancer but is poorly characterized at the molecular level. Herein we analyzed 41 LC and 32 LCNEC (including 15 previously reported cases) tumors using massive parallel sequencing for mutations in 26 cancer-related genes and gene fusions in ALK, RET, and ROS1. LC patients were additionally subdivided into three immunohistochemistry groups based on positive expression of TTF-1/Napsin A (adenocarcinoma-like, n = 24; 59%), CK5/P40 (squamous-like, n = 5; 12%), or no marker expression (marker-negative, n = 12; 29%). Most common alterations were TP53 (83%), KRAS (22%), MET (12%) mutations in LCs, and TP53 (88%), STK11 (16%), and PTEN (13%) mutations in LCNECs. In general, LCs showed more oncogene mutations compared to LCNECs. Immunomarker stratification of LC revealed oncogene mutations in 63% of adenocarcinoma-like cases, but only in 17% of marker-negative cases. Moreover, marker-negative LCs were associated with inferior overall survival compared with adenocarcinoma-like tumors (p = 0.007). No ALK, RET or ROS1 fusions were detected in LCs or LCNECs. Together, our molecular analyses support that LC and LCNEC tumors follow different tumorigenic paths and that LC may be stratified into molecular subgroups with potential implications for diagnosis, prognostics, and therapy decisions.

Comparative genetic analysis of a rare synchronous collision tumor composed of malignant pleural mesothelioma and primary pulmonary adenocarcinoma

Background

Although asbestos acts as a potent carcinogen in pleural mesothelial and pulmonary epithelial cells, it still remains unclear whether asbestos causes specific and characteristic gene alterations in these different kinds of target cells, because direct comparison in an identical patient is not feasible. We experienced a rare synchronous collision tumor composed of malignant pleural mesothelioma (MPM) and primary pulmonary adenocarcinoma (PAC) in a 77-year-old man with a history of long-term smoking and asbestos exposure, and compared the DNA copy number alteration (CNA) and somatic mutation in these two independent tumors.

Methods

Formalin-fixed paraffin-embedded (FFPE) tissues of MPM and PAC lesions from the surgically resected specimen were used. Each of these MPM and PAC lesions exhibited a typical histology and immunophenotype. CNA analysis using SNP array was performed using the Illumina Human Omni Express-12_FFPE (Illumina, San Diego, CA, USA) with DNA extracts from each lesion. Somatic mutation analysis using next-generation sequencing was performed using the TruSeq Amplicon Cancer Panel (Illumina).

Results

The CNA analysis demonstrated a marked difference in the frequency of gain and loss between MPM and PAC. In PAC, copy number (CN) gain was detected more frequently and widely than CN loss, whereas in MPM there was no such obvious difference. PAC did not harbor CNAs that have been identified in asbestos-associated lung cancer, but did harbor some of the CNAs associated with smoking. MPM exhibited CN loss at 9p21.2-3, which is the most common genetic alteration in mesothelioma.

Conclusion

In this particular case, asbestos exposure may not have played a primary role in PAC carcinogenesis, but cigarette smoking may have contributed more to the occurrence of CN gains in PAC. This comparative genetic analysis of two different lesions with same amount of asbestos exposure and cigarette smoke exposure has provided information on differences in the cancer genome related to carcinogenesis.

Genome-wide DNA methylation analysis of lung carcinoma reveals one neuroendocrine and four adenocarcinoma epitypes associated with patient outcome

PURPOSE

Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer remains unclear.

EXPERIMENTAL DESIGN

Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors, including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), 1 adenosquamous cancer, 5 large cell carcinomas, 9 large cell neuroendocrine carcinomas (LCNEC), and 3 small-cell carcinomas (SCLC). Unsupervised bootstrap clustering was performed to identify DNA methylation subgroups, which were validated in 695 adenocarcinomas and 122 SqCCs. Subgroups were characterized by clinicopathologic factors, whole-exome sequencing data, and gene expression profiles.

RESULTS

Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, remaining four epitypes were associated with unsupervised and supervised gene expression phenotypes, and differences in molecular features, including global hypomethylation, promoter hypermethylation, genomic instability, expression of proliferation-associated genes, and mutations in KRAS, TP53, KEAP1, SMARCA4, and STK11. Furthermore, these epitypes were associated with clinicopathologic features such as smoking history and patient outcome.

CONCLUSIONS

Our findings highlight one neuroendocrine and four adenocarcinoma epitypes associated with molecular and clinicopathologic characteristics, including patient outcome. This study demonstrates the possibility to further subgroup lung cancer, and more specifically adenocarcinomas, based on epigenetic/molecular classification that could lead to more accurate tumor classification, prognostication, and tailored patient therapy.