DNA copy number aberrations in small-cell lung cancer reveal activation of the focal adhesion pathway

Promises of Protein Kinase Inhibitors in Recalcitrant Small-Cell Lung Cancer: Recent Scenario and Future Possibilities

SCLC is refractory to conventional therapies; targeted therapies and immunological checkpoint inhibitor (ICI) molecules have prolonged survival only marginally. In addition, ICIs help only a subgroup of SCLC patients. Different types of kinases play pivotal roles in therapeutics-driven cellular functions. Therefore, there is a significant need to understand the roles of kinases in regulating therapeutic responses, acknowledge the existing knowledge gaps, and discuss future directions for improved therapeutics for recalcitrant SCLC. Here, we extensively review the effect of dysregulated kinases in SCLC. We further discuss the pharmacological inhibitors of kinases used in targeted therapies for recalcitrant SCLC. We also describe the role of kinases in the ICI-mediated activation of antitumor immune responses. Finally, we summarize the clinical trials evaluating the potential of kinase inhibitors and ICIs. This review overviews dysregulated kinases in SCLC and summarizes their potential as targeted therapeutic agents. We also discuss their clinical efficacy in enhancing anticancer responses mediated by ICIs.

[Potential therapeutic implication of focal adhesion kinase in small-cell lung cancer]

The molecular steps leading to small cell lung cancer (SCLC) development and progression are still poorly understood, resulting in the absence of targeted therapy and an extremely poor prognosis. Activation of Focal Adhesion Kinase (FAK) plays a key role in the invasive behavior of this cancer in vitro. Our hypothesis is that FAK could be a therapeutic target in SCLC. Our work aims to describe a mouse model to study the role of FAK and the antitumoral potential of its inhibition in SCLC in vivo.

Analysis of Breast Cancer Based on the Dysregulated Network

Breast cancer is a heterogeneous disease, and its development is closely associated with the underlying molecular regulatory network. In this paper, we propose a new way to measure the regulation strength between genes based on their expression values, and construct the dysregulated networks (DNs) for the four subtypes of breast cancer. Our results show that the key dysregulated networks (KDNs) are significantly enriched in critical breast cancer-related pathways and driver genes; closely related to drug targets; and have significant differences in survival analysis. Moreover, the key dysregulated genes could serve as potential driver genes, drug targets, and prognostic markers for each breast cancer subtype. Therefore, the KDN is expected to be an effective and novel way to understand the mechanisms of breast cancer.

Clinical Significance and Potential Role of LSM4 Overexpression in Hepatocellular Carcinoma: An Integrated Analysis Based on Multiple Databases

Background: Hepatocellular carcinoma (HCC) is a solid tumor with high recurrence rate and high mortality. It is crucial to discover available biomarkers to achieve early diagnosis and improve the prognosis. The effect of LSM4 in HCC still remains unrevealed. Our study is dedicated to exploring the expression of LSM4 in HCC, demonstrating its clinical significance and potential molecular mechanisms.

Methods: Clinical information and LSM4 expression values of HCC were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Survival analysis and receiver operating characteristic (ROC) curve analysis were applied to evaluate the prognostic and diagnostic significance of LSM4. Calculating pooled standardized mean difference (SMD) and performing summary receiver operating characteristic (sROC) curve analysis to further determine its expression status and diagnostic significance. LSM4-related co-expressed genes (CEGs) were obtained and explored their clinical significance in HCC. LSM4-associated pathways were identified through Gene set enrichment analysis (GSEA).

Results: Up-regulated LSM4 was detected in HCC tissues (SMD = 1.56, 95% CI: 1.29–1.84) and overexpressed LSM4 had excellent distinguishing ability (AUC = 0.91, 95% CI: 0.88–0.93). LSM4 was associated with clinical stage, tumor grade, and lymph node metastasis status (p < 0.05). Survival analysis showed that high LSM4 expression was related to poor overall survival (OS) of HCC patients. Cox regression analysis suggested that high LSM4 expression may be an independent risk factor for HCC. We obtained nine up-regulated CEGs of LSM4 in HCC tissues, and six CEGs had good prognostic and diagnostic significance. GSEA analysis showed that up-regulated LSM4 was closely related to the cell cycle, cell replication, focal adhesion, and several metabolism-associated pathways, including fatty acid metabolism.

Conclusion: Overexpressed LSM4 may serve as a promising diagnostic and prognostic biomarker of HCC. Besides, LSM4 may play a synergistic effect with CEGs in promoting the growth and metastasis of HCC cells via regulating crucial pathways such as cell cycle, focal adhesion, and metabolism-associated pathways.

Antiangiogenesis Combined with Immunotherapy to Treat Advanced Small-Cell Carcinoma of the Esophagus Resistant to Chemotherapy: According to the Guidance of Next-Generation Sequencing

A 64-year-old woman admitted to our hospital with the chief complaint of swallowing obstruction was diagnosed as relapsed small-cell carcinoma of the esophagus. Complete remission (CR) was observed after six cycles of irinotecan plus cisplatin therapy. According to the results of a next-generation sequencing analysis of the tumor specimen, anlotinib (12 mg PO q3w) was recommended. After 1 month of anlotinib treatment, the tumor decreased significantly according to computed tomography scan and gastroscopy. However, the disease progressed after 2 months of therapy. A gene analysis of the new puncture sample showed microsatellite instability and a high tumor mutation burden. Immunohistochemistry indicated positive programmed death ligand-1 expression (>1%). Because of these results, the patient was treated with anlotinib (12 mg PO q3w) in combination with toripalimab (240 mg IV drip q3w). After 3 months of therapy, CR was achieved, although progression-free survival had not been reached at the time of publication.

Cellular Heterogeneity-Adjusted cLonal Methylation (CHALM) improves prediction of gene expression

Promoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity-Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms.

CONY: A Bayesian procedure for detecting copy number variations from sequencing read depths

Copy number variations (CNVs) are genomic structural mutations consisting of abnormal numbers of fragment copies. Next-generation sequencing of read-depth signals mirrors these variants. Some tools used to predict CNVs by depth have been published, but most of these tools can be applied to only a specific data type due to modeling limitations. We develop a tool for copy number variation detection by a Bayesian procedure, i.e., CONY, that adopts a Bayesian hierarchical model and an efficient reversible-jump Markov chain Monte Carlo inference algorithm for whole genome sequencing of read-depth data. CONY can be applied not only to individual samples for estimating the absolute number of copies but also to case-control pairs for detecting patient-specific variations. We evaluate the performance of CONY and compare CONY with competing approaches through simulations and by using experimental data from the 1000 Genomes Project. CONY outperforms the other methods in terms of accuracy in both single-sample and paired-samples analyses. In addition, CONY performs well regardless of whether the data coverage is high or low. CONY is useful for detecting both absolute and relative CNVs from read-depth data sequences. The package is available at https://github.com/weiyuchung/CONY.

Role of Focal Adhesion Kinase in Small-Cell Lung Cancer and Its Potential as a Therapeutic Target

Small-cell lung cancer (SCLC) represents 15% of all lung cancers and it is clinically the most aggressive type, being characterized by a tendency for early metastasis, with two-thirds of the patients diagnosed with an extensive stage (ES) disease and a five-year overall survival (OS) as low as 5%. There are still no effective targeted therapies in SCLC despite improved understanding of the molecular steps leading to SCLC development and progression these last years. After four decades, the only modest improvement in OS of patients suffering from ES-SCLC has recently been shown in a trial combining atezolizumab, an anti-PD-L1 immune checkpoint inhibitor, with carboplatin and etoposide, chemotherapy agents. This highlights the need to pursue research efforts in this field. Focal adhesion kinase (FAK) is a non-receptor protein tyrosine kinase that is overexpressed and activated in several cancers, including SCLC, and contributing to cancer progression and metastasis through its important role in cell proliferation, survival, adhesion, spreading, migration, and invasion. FAK also plays a role in tumor immune evasion, epithelial-mesenchymal transition, DNA damage repair, radioresistance, and regulation of cancer stem cells. FAK is of particular interest in SCLC, being known for its aggressiveness. The inhibition of FAK in SCLC cell lines demonstrated significative decrease in cell proliferation, invasion, and migration, and induced cell cycle arrest and apoptosis. In this review, we will focus on the role of FAK in cancer cells and their microenvironment, and its potential as a therapeutic target in SCLC.

Increased Expression and Activation of FAK in Small-Cell Lung Cancer Compared to Non-Small-Cell Lung Cancer

INTRODUCTION

Focal adhesion kinase (FAK) plays a crucial role in cancer development and progression. FAK is overexpressed and/or activated and associated with poor prognosis in various malignancies. However, in lung cancer, activated FAK expression and its prognostic value are unknown.

METHODS

FAK and activated FAK (phospho-FAK Y397) expressions were analyzed by multiplex immunofluorescence staining in formalin-fixed paraffin-embedded tissues from 95 non-small-cell lung cancer (NSCLC) and 105 small-cell lung cancer (SCLC) patients, and 37 healthy donors. The FAK staining score was defined as the percentage (%) of FAK-stained tumor area multiplied by (×) FAK mean intensity and phospho-FAK staining score as the (% of phospho-FAK-stained area of low intensity × 1) + (% of phospho-FAK-stained area of medium intensity × 2) + (% of the phospho-FAK-stained area of high intensity × 3). FAK and phospho-FAK staining scores were compared between normal, NSCLC, and SCLC tissues. They were also tested for correlations with patient characteristics and clinical outcomes.

RESULTS

The median follow-up time after the first treatment was 42.5 months and 6.4 months for NSCLC and SCLC patients, respectively. FAK and phospho-FAK staining scores were significantly higher in lung cancer than in normal lung and significantly higher in SCLC compared to NSCLC tissues (p < 0.01). Moreover, the ratio between phospho-FAK and FAK staining scores was significantly higher in SCLC than in NSCLC tissues (p < 0.01). However, FAK and activated FAK expression in lung cancer did not correlate with recurrence-free and overall survival in NSCLC and SCLC patients.

CONCLUSIONS

Total FAK and activated FAK expressions are significantly higher in lung cancer than in normal lung, and significantly higher in SCLC compared to NSCLC, but are not prognostic biomarkers in this study.

Therapeutic Potential of Focal Adhesion Kinase Inhibition in Small Cell Lung Cancer

Small cell lung cancer (SCLC) has a poor prognosis. Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase regulating cell proliferation, survival, migration, and invasion, which is overexpressed and/or activated in several cancers, including SCLC. We wanted to determine whether FAK contributes to SCLC aggressive behavior. We first evaluated the effect of FAK small-molecule inhibitor PF-573,228 in NCI-H82, NCI-H146, NCI-H196, and NCI-H446 SCLC cell lines. PF-573,228 (0.1-5 μmol/L) inhibited FAK activity by decreasing phospho-FAK (Tyr397), without modifying total FAK expression. PF-573,228 decreased proliferation, decreased DNA synthesis, induced cell-cycle arrest in G₂-M phases, and increased apoptosis in all cell lines. PF-573,228 also decreased motility in adherent cell lines. To make sure that these effects were not off-target, we then used a genetic method to inhibit FAK in NCI-H82 and NCI-H446, namely stable transduction with FAK shRNA and/or FAK-related nonkinase (FRNK), a splice variant lacking the N-terminal and kinase domains. Although FAK shRNA transduction decreased total and phospho-FAK (Tyr397) expression, it did not affect proliferation, DNA synthesis, or progression through cell cycle. However, restoration of FAK-targeting (FAT) domain (attached to focal adhesion complex where it inhibits pro-proliferative proteins such as Rac-1) by FRNK transduction inhibited proliferation, DNA synthesis, and induced apoptosis. Moreover, although FAK shRNA transduction increased active Rac1 level, FRNK reexpression in cells previously transduced with FAK shRNA decreased it. Therefore, FAK appears important in SCLC biology and targeting its kinase domain may have a therapeutic potential, while targeting its FAT domain should be avoided to prevent Rac1-mediated protumoral activity.

MIMPFC: Identifying miRNA-mRNA regulatory modules by combining phase-only correlation and improved rough-fuzzy clustering

MicroRNAs (miRNAs) play a key role in gene expression and regulation in various organisms. They control a wide range of biological processes and are involved in several types of cancers by causing mRNA degradation or translational inhibition. However, the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With the accumulation of the expression data of miRNAs and mRNAs, many computational methods have been proposed to predict miRNA-mRNA regulatory relationship. However, most existing methods require the number of modules predefined that may be difficult to determine beforehand. Here, we propose a novel computational method to discover miRNA-mRNA regulatory modules by combining Phase-only correlation and improved rough-Fuzzy Clustering (MIMPFC). The proposed method is evaluated on three heterogeneous datasets, and the obtained results are further validated through relevant literatures, biological significance and functional enrichment analysis. The analysis results show that the identified modules are highly correlated with the biological conditions. A large part of the regulatory relationships found by MIMPFC has been confirmed in the experimentally verified databases. It demonstrates that the modules found by MIMPFC are biologically significant.

Comparative analysis of gene expression profiles of hip articular cartilage between non-traumatic necrosis and osteoarthritis

Hip cartilage destruction is consistently observed in the non-traumatic osteonecrosis of femoral head (NOFH) and accelerates its bone necrosis. The molecular mechanism underlying the cartilage damage of NOFH remains elusive. In this study, we conducted a systematically comparative study of gene expression profiles between NOFH and osteoarthritis (OA). Hip articular cartilage specimens were collected from 12 NOFH patients and 12 controls with traumatic femoral neck fracture for microarray (n=4) and quantitative real-time PCR validation experiments (n=8). Gene expression profiling of articular cartilage was performed using Agilent Human 4×44K Microarray chip. The accuracy of microarray experiment was further validated by qRT-PCR. Gene expression results of OA hip cartilage were derived from previously published study. Significance Analysis of Microarrays (SAM) software was applied for identifying differently expressed genes. Gene ontology (GO) and pathway enrichment analysis were conducted by Gene Set Enrichment Analysis software and DAVID tool, respectively. Totally, 27 differently expressed genes were identified for NOFH. Comparing the gene expression profiles of NOFH cartilage and OA cartilage detected 8 common differently expressed genes, including COL5A1, OGN, ANGPTL4, CRIP1, NFIL3, METRNL, ID2 and STEAP1. GO comparative analysis identified 10 common significant GO terms, mainly implicated in apoptosis and development process. Pathway comparative analysis observed that ECM-receptor interaction pathway and focal adhesion pathway were enriched in the differently expressed genes of both NOFH and hip OA. In conclusion, we identified a set of differently expressed genes, GO and pathways for NOFH articular destruction, some of which were also involved in the hip OA. Our study results may help to reveal the pathogenetic similarities and differences of cartilage damage of NOFH and hip OA.

Targeting Focal Adhesion Kinase Suppresses the Malignant Phenotype in Rhabdomyosarcoma Cells

Despite the tremendous advances in the treatment of childhood solid tumors, rhabdomyosarcoma (RMS) continues to provide a therapeutic challenge. Children with metastatic or relapsed disease have a disease-free survival rate under 30%. Focal adhesion kinase (FAK) is a nonreceptor tyrosine kinase that is important in many facets of tumorigenesis. Signaling pathways both upstream and downstream to FAK have been found to be important in sarcoma tumorigenesis, leading us to hypothesize that FAK would be present in RMS and would impact cellular survival. In the current study, we showed that FAK was present and phosphorylated in pediatric alveolar and embryonal RMS tumor specimens and cell lines. We also examined the effects of FAK inhibition upon two RMS cell lines utilizing parallel approaches including RNAi and small molecule inhibitors. FAK inhibition resulted in decreased cellular survival, invasion, and migration and increased apoptosis. Furthermore, small molecule inhibition of FAK led to decreased tumor growth in a nude mouse RMS xenograft model. The findings from this study will help to further our understanding of the regulation of tumorigenesis in RMS and may provide desperately needed novel therapeutic strategies for these difficult-to-treat tumors.

Proteomic Profiling Identifies PTK2/FAK as a Driver of Radioresistance in HPV-negative Head and Neck Cancer

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) is commonly treated with radiotherapy, and local failure after treatment remains the major cause of disease-related mortality. To date, human papillomavirus (HPV) is the only known clinically validated, targetable biomarkers of response to radiation in HNSCC.

EXPERIMENTAL DESIGN

We performed proteomic and transcriptomic analysis of targetable biomarkers of radioresistance in HPV-negative HNSCC cell lines in vitro, and tested whether pharmacologic blockade of candidate biomarkers sensitized cells to radiotherapy. Candidate biomarkers were then investigated in several independent cohorts of patients with HNSCC.

RESULTS

Increased expression of several targets was associated with radioresistance, including FGFR, ERK1, EGFR, and focal adhesion kinase (FAK), also known as PTK2. Chemical inhibition of PTK2/FAK, but not FGFR, led to significant radiosensitization with increased G2-M arrest and potentiated DNA damage. PTK2/FAK overexpression was associated with gene amplification in HPV-negative HNSCC cell lines and clinical tumors. In two independent cohorts of patients with locally advanced HPV-negative HNSCC, PTK2/FAK amplification was highly associated with poorer disease-free survival (DFS; P = 0.012 and 0.034). PTK2/FAK mRNA expression was also associated with worse DFS (P = 0.03). Moreover, both PTK2/FAK mRNA (P = 0.021) and copy number (P = 0.063) were associated with DFS in the Head and Neck Cancer subgroup of The Cancer Genome Atlas.

CONCLUSIONS

Proteomic analysis identified PTK2/FAK overexpression is a biomarker of radioresistance in locally advanced HNSCC, and PTK2/FAK inhibition radiosensitized HNSCC cells. Combinations of PTK2/FAK inhibition with radiotherapy merit further evaluation as a therapeutic strategy for improving local control in HPV-negative HNSCC. Clin Cancer Res; 22(18); 4643-50. ©2016 AACR.

Integrated analyses of copy number variations and gene differential expression in lung squamous-cell carcinoma

Background

Although numerous efforts have been made, the pathogenesis underlying lung squamous-cell carcinoma (SCC) remains unclear. This study aimed to identify the CNV-driven genes by an integrated analysis of both the gene differential expression and copy number variation (CNV).

Results

A higher burden of the CNVs was found in 10–50 kb length. The 16 CNV-driven genes mainly located in chr 1 and chr 3 were enriched in immune response [e.g. complement factor H (CFH) and Fc fragment of IgG, low affinity IIIa, receptor (FCGR3A)], starch and sucrose metabolism [e.g. amylase alpha 2A (AMY2A)]. Furthermore, 38 TFs were screened for the 9 CNV-driven genes and then the regulatory network was constructed, in which the GATA-binding factor 1, 2, and 3 (GATA1, GATA2, GATA3) jointly regulated the expression of TP63.

Conclusions

The above CNV-driven genes might be potential contributors to the development of lung SCC.

ENVE: a novel computational framework characterizes copy-number mutational landscapes in colorectal cancers from African American patients

Reliable detection of somatic copy-number alterations (sCNAs) in tumors using whole-exome sequencing (WES) remains challenging owing to technical (inherent noise) and sample-associated variability in WES data. We present a novel computational framework, ENVE, which models inherent noise in any WES dataset, enabling robust detection of sCNAs across WES platforms. ENVE achieved high concordance with orthogonal sCNA assessments across two colorectal cancer (CRC) WES datasets, and consistently outperformed a best-in-class algorithm, Control-FREEC. We subsequently used ENVE to characterize global sCNA landscapes in African American CRCs, identifying genomic aberrations potentially associated with CRC pathogenesis in this population. ENVE is downloadable at https://github.com/ENVE-Tools/ENVE.

Classification of lung cancer using ensemble-based feature selection and machine learning methods

Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), squamous cell lung cancer (SQCLC) as well as large cell lung cancer. Many previous studies demonstrated that DNA methylation has emerged as potential lung cancer-specific biomarkers. However, whether there exists a set of DNA methylation markers simultaneously distinguishing such three types of lung cancers remains elusive. In the present study, ROC (Receiving Operating Curve), RFs (Random Forests) and mRMR (Maximum Relevancy and Minimum Redundancy) were proposed to capture the unbiased, informative as well as compact molecular signatures followed by machine learning methods to classify LADC, SQCLC and SCLC. As a result, a panel of 16 DNA methylation markers exhibits an ideal classification power with an accuracy of 86.54%, 84.6% and a recall 84.37%, 85.5% in the leave-one-out cross-validation (LOOCV) and independent data set test experiments, respectively. Besides, comparison results indicate that ensemble-based feature selection methods outperform individual ones when combined with the incremental feature selection (IFS) strategy in terms of the informative and compact property of features. Taken together, results obtained suggest the effectiveness of the ensemble-based feature selection approach and the possible existence of a common panel of DNA methylation markers among such three types of lung cancer tissue, which would facilitate clinical diagnosis and treatment.

FAK inhibition abrogates the malignant phenotype in aggressive pediatric renal tumors

Despite the tremendous advances in the treatment of childhood kidney tumors, there remain subsets of pediatric renal tumors that continue to pose a therapeutic challenge, mainly malignant rhabdoid kidney tumors and nonosseous renal Ewing sarcoma. Children with advanced, metastatic, or relapsed disease have a poor disease-free survival rate. Focal adhesion kinase (FAK) is a nonreceptor tyrosine kinase that is important in many facets of tumor development and progression. FAK has been found in other pediatric solid tumors and in adult renal cellular carcinoma, leading to the hypothesis that FAK contributes to pediatric kidney tumors and would affect cellular survival. In the current study, FAK was present and phosphorylated in pediatric kidney tumor specimens. Moreover, the effects of FAK inhibition upon G401 and SK-NEP-1 cell lines were examined using a number of parallel approaches to block FAK, including RNA interference and small-molecule FAK inhibitors. FAK inhibition resulted in decreased cellular survival, invasion and migration, and increased apoptosis. Furthermore, small-molecule inhibition of FAK led to decreased SK-NEP-1 xenograft growth in vivo. These data deepen the knowledge of the tumorigenic process in pediatric renal tumors, and provide desperately needed therapeutic strategies and targets for these rare, but difficult to treat, malignancies.

IMPLICATIONS

This study provides a fundamental understanding of tumorigenesis in difficult to treat renal tumors and provides an impetus for new avenues of research and potential for novel, targeted therapies.

Separate enrichment analysis of pathways for up- and downregulated genes

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Co-expression network analysis identifies Spleen Tyrosine Kinase (SYK) as a candidate oncogenic driver in a subset of small-cell lung cancer

Background

Oncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types.

Results

We derived an SCLC-specific classifier from weighted gene co-expression network analysis (WGCNA) of a lung cancer dataset. The classifier, termed SCLC-specific hub network (SSHN), robustly separates SCLC from other lung cancer types across multiple datasets and multiple platforms, including RNA-seq and shotgun proteomics. The classifier was also conserved in SCLC cell lines. SSHN is enriched for co-expressed signaling network hubs strongly associated with the SCLC phenotype. Twenty of these hubs are actionable kinases with oncogenic potential, among which spleen tyrosine kinase (SYK) exhibits one of the highest overall statistical associations to SCLC. In patient tissue microarrays and cell lines, SCLC can be separated into SYK-positive and -negative. SYK siRNA decreases proliferation rate and increases cell death of SYK-positive SCLC cell lines, suggesting a role for SYK as an oncogenic driver in a subset of SCLC.

Conclusions

SCLC treatment has thus far been limited to chemotherapy and radiation. Our WGCNA analysis identifies SYK both as a candidate biomarker to stratify SCLC patients and as a potential therapeutic target. In summary, WGCNA represents an alternative strategy to large scale sequencing for the identification of potential oncogenic drivers, based on a systems view of signaling networks. This strategy is especially useful in cancer types where no actionable mutations have emerged.

Epidemiology of lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines

BACKGROUND

Ever since a lung cancer epidemic emerged in the mid-1900 s, the epidemiology of lung cancer has been intensively investigated to characterize its causes and patterns of occurrence. This report summarizes the key findings of this research.

METHODS

A detailed literature search provided the basis for a narrative review, identifying and summarizing key reports on population patterns and factors that affect lung cancer risk.

RESULTS

Established environmental risk factors for lung cancer include smoking cigarettes and other tobacco products and exposure to secondhand tobacco smoke, occupational lung carcinogens, radiation, and indoor and outdoor air pollution. Cigarette smoking is the predominant cause of lung cancer and the leading worldwide cause of cancer death. Smoking prevalence in developing nations has increased, starting new lung cancer epidemics in these nations. A positive family history and acquired lung disease are examples of host factors that are clinically useful risk indicators. Risk prediction models based on lung cancer risk factors have been developed, but further refinement is needed to provide clinically useful risk stratification. Promising biomarkers of lung cancer risk and early detection have been identified, but none are ready for broad clinical application.

CONCLUSIONS

Almost all lung cancer deaths are caused by cigarette smoking, underscoring the need for ongoing efforts at tobacco control throughout the world. Further research is needed into the reasons underlying lung cancer disparities, the causes of lung cancer in never smokers, the potential role of HIV in lung carcinogenesis, and the development of biomarkers.

FAK Inhibition Decreases Hepatoblastoma Survival Both In Vitro and In Vivo

Hepatoblastoma is the most frequently diagnosed liver tumor of childhood, and children with advanced, metastatic or relapsed disease have a disease-free survival rate under 50%. Focal adhesion kinase (FAK) is a nonreceptor tyrosine kinase that is important in many facets of tumor development and progression. FAK has been found in other pediatric solid tumors and in adult hepatocellular carcinoma, leading us to hypothesize that FAK would be present in hepatoblastoma and would impact its cellular survival. In the current study, we showed that FAK was present and phosphorylated in human hepatoblastoma tumor specimens. We also examined the effects of FAK inhibition upon hepatoblastoma cells using a number of parallel approaches to block FAK including RNAi and small molecule FAK inhibitors. FAK inhibition resulted in decreased cellular survival, invasion, and migration and increased apoptosis. Further, small molecule inhibition of FAK led to decreased tumor growth in a nude mouse xenograft model of hepatoblastoma. The findings from this study will help to further our understanding of the regulation of hepatoblastoma tumorigenesis and may provide desperately needed novel therapeutic strategies and targets for aggressive, recurrent, or metastatic hepatoblastomas.

Overexpression of focal adhesion kinase correlates with increased lymph node metastasis and poor prognosis in non-small-cell lung cancer

BACKGROUND

The aim of this study was to investigate whether focal adhesion kinase (FAK) overexpression correlates with lymph node metastases and prognosis.

METHODS

The protein expression of FAK was investigated in 153 paraffin-embedded tissues by immunohistochemical analysis and then correlated with various clinicopathologic parameters. FAK mRNA level was detected with quantitative RT-PCR in 57 NSCLC frozen tissues and 20 normal matched tissues.

RESULTS

Immunohistochemistry showed FAK overexpression was significantly associated with positive lymph node metastasis and more advanced disease stage of NSCLCs and adenocarcinoma subtype; real-time PCR also indicated a statistically significant correlation between increased FAK mRNA level and the presence of nodal metastases. Moreover, in survival analysis, FAK overexpression was significantly associated with worse overall survival.

CONCLUSIONS

FAK overexpression is a promising pathological factor to predict aggressive behavior and prognosis in patients with NSCLC, particularly in the adenocarcinoma subtype.

FAK inhibition decreases cell invasion, migration and metastasis in MYCN amplified neuroblastoma

Neuroblastoma, the most common extracranial solid tumor of childhood, is responsible for over 15 % of pediatric cancer deaths. We have shown that neuroblastoma cell lines overexpress focal adhesion kinase (FAK), a non-receptor protein tyrosine kinase that controls a number of tumorigenic pathways. In this study, we hypothesized that inhibition of FAK would result in decreased cellular migration and invasion in neuroblastoma cell lines, and decrease metastasis in a murine model. We utilized non-isogenic and isogenic MYCN human neuroblastoma cell lines and parallel methods of FAK inhibition. Cell viability, migration, and invasion assays were employed to assess the effects of FAK inhibition in vitro. A nude mouse model was utilized to determine the effects of FAK inhibition on in vivo liver metastasis. FAK knockdown with siRNA resulted in decreased invasion and migration in neuroblastoma cell lines, and the effects of siRNA-induced FAK inhibition were more pronounced in MYCN amplified cell lines. In addition, abrogation of FAK with a small molecule inhibitors resulted in decreased cell survival, migration and invasion in neuroblastoma cell lines, again most pronounced in cell lines with MYCN amplification. Finally, small molecule FAK inhibition in a nude mouse model resulted in a significant decrease in metastatic tumor burden in SK-N-BE(2) injected animals. We believe that FAK plays an important role in maintaining and propagating the metastatic phenotype of neuroblastoma cells, and this driver role is exaggerated in cell lines that overexpress MYCN. FAK inhibition warrants further investigation as a potential therapeutic target in the treatment of aggressive neuroblastoma.

An RNA interference lethality screen of the human druggable genome to identify molecular vulnerabilities in epithelial ovarian cancer

Targeted therapies have been used to combat many tumor types; however, few have effectively improved the overall survival in women with epithelial ovarian cancer, begging for a better understanding of this deadly disease and identification of essential drivers of tumorigenesis that can be targeted effectively. Therefore, we used a loss-of-function screening approach to help identify molecular vulnerabilities that may represent key points of therapeutic intervention. We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting over 6,000 druggable genes and studied their effects on growth and/or survival of epithelial ovarian cancer (EOC) cell lines. The top 300 “hits” affecting the viability of A1847 cells were rescreened across additional EOC cell lines and non-tumorigenic, human immortalized ovarian epithelial cell lines. Fifty-three gene candidates were found to exhibit effects in all tumorigenic cell lines tested. Extensive validation of these hits refined the list to four high quality candidates (HSPA5, NDC80, NUF2, and PTN). Mechanistic studies show that silencing of three genes leads to increased apoptosis, while HSPA5 silencing appears to alter cell growth through G1 cell cycle arrest. Furthermore, two independent gene expression studies show that NDC80, NUF2 and PTN were significantly aberrantly overexpressed in serous adenocarcinomas. Overall, our functional genomics results integrated with the genomics data provide an important unbiased avenue towards the identification of prospective therapeutic targets for drug discovery, which is an urgent and unmet clinical need for ovarian cancer.

Anti-angiogenic effects of thioridazine involving the FAK-mTOR pathway

Thioridazine is a type of anti-psychotic drug that also includes anti-tumor activity. In this study, we assessed the effects of thioridazine, as a novel anti-angiogenic agent, on the suppression of angiogenesis-mediated cell proliferation. Thioridazine was found to inhibit growth in ovarian cancer cells (OVCAR-3 and 2774), but did not possess any inhibitory effects on normal cell types such as HOSE-E6E7, MCF-10A, MRC-5, and BEAS-2B. Thioridazine also suppressed vascular endothelial growth factor (VEGF)-stimulated HUVEC migration in a dose-time-dependent manner. We also showed that being treated with thioridazine inhibited VEGF-stimulated proliferation, invasion, and capillary-like structure tube formation in vitro. Thioridazine suppressed phosphorylation of the signaling regulators downstream of the focal adhesion kinase (FAK) through αvβ3 integrin, which also include Akt, phosphoinositide-dependent protein kinase 1 (PDK-1), mammalian target of rapamycin (mTOR), ribosomal protein S6 kinase (p70S6K), but had no effect on VEGF-stimulated extracellular signal-regulated kinase (ERK) phosphorylation. We found the molecular mechanism of thioridazine to be a novel anti-angiogenic protein. These results provide evidence for the regulation of endothelial cell functions that are relevant to angiogenesis through the suppression of the αvβ3/FAK/mTOR signaling pathway.

Dickkopf-1 (DKK-1) interrupts FAK/PI3K/mTOR pathway by interaction of carbonic anhydrase IX (CA9) in tumorigenesis

Recently, we found that carbonic anhydrase IX (CA9) modulates tumor-associated cell migration and invasion, and then identified dickkopf-1 (DKK-1) as a novel CA9-interacting protein. In this study, we have determined the binding regions that are required for interaction between CA9 and DKK-1 through in vitro and in vivo. The N-terminal domain of CA9 is participated to interact with the Val(60)-Tyr(168) site of DKK-1. We also observed that DKK-1 inhibits endothelial cell angiogenesis of CA9 in tumorigenesis. Furthermore, induction of CA9-mediated mTOR phosphorylation and angiogenesis was significantly inhibited by over-expression of DKK-1. Taken together, these findings identify DKK-1 as a potential factor in the regulation of CA9 cellular homeostasis and also suggest a new possible role for DKK1-1 in tumorigenesis.

Pituitary adenylate cyclase-activating polypeptide causes increased tyrosine phosphorylation of focal adhesion kinase and paxillin

The effects of pituitary adenylate cyclase-activating polypeptide (PACAP) on tyrosine phosphorylation of focal adhesion kinase (FAK) and paxillin were investigated using lung cancer cells. Addition of PACAP-27 or PACAP-38 but not vasoactive intestinal peptide to NCI-H838 or NCI-H1299 human lung cancer cells significantly increased the tyrosine phosphorylation of FAK or paxillin. The increase in FAK or paxillin tyrosine phosphorylation caused by addition of PACAP-27 to NCI-H838 cells was inhibited by PACAP(6-38), a PAC1-receptor (R) antagonist. The increase in FAK or paxillin tyrosine phosphorylation caused by 100 nM PACAP-27 was maximal 2 min after addition to NCI-H838 cells. The effects of PACAP at stimulating FAK and paxillin tyrosine phosphorylation were reversed by cytochalasin D and genistein which inhibit actin polymerization and tyrosine kinase activity, respectively. The effects of PACAP at stimulating FAK and paxillin tyrosine phosphorylation were reversed by U-73122 but not H89 which inhibit phospholipase C and protein kinase A, respectively. The results show that PAC1-R regulates FAK and paxillin tyrosine phosphorylation in lung cancer cells as a result of increased phosphatidylinositol turnover but not adenylyl cylase stimulation.

Identification of single- and multiple-class specific signature genes from gene expression profiles by group marker index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases.

Expression of focal adhesion kinase in small-cell lung carcinoma

BACKGROUND

The focal adhesion kinase (FAK) is a non-receptor tyrosine kinase linked to tumor growth, invasion, and metastasis. FAK is overexpressed and associated with prognosis in many cancers, but its prognostic value in small-cell lung carcinoma (SCLC) is unknown and was the focus of this study.

METHODS

Total FAK expression was analyzed via immunohistochemistry in tissue microarrays consisting of formalin-fixed, paraffin-embedded SCLC specimens from 85 patients. FAK staining scores were tested for correlations with pathological characteristics and clinical outcomes. Phospho-paxillin was also tested in 35 of the 85 specimens to evaluate whether FAK expression was associated with downstream signaling.

RESULTS

Specific FAK expression was localized to the cytoplasm of 78/85 (92%) SCLCs. FAK expression was scored low in 11 (13%), moderate in 17 (20%), and high in 50 (59%) SCLCs. FAK staining scores treated as continuous variables did not correlate with SCLC disease stage, response to therapy, recurrence/progression-free survival, or overall survival. Moreover, total FAK expression did not correlate with phospho-paxillin Tyr(118) expression.

CONCLUSIONS

Total FAK is strongly expressed in a majority of SCLC tumors. However, the expression evaluated via immunohistochemistry is not a prognostic factor in patients with SCLC.

Acquisition of Genetic Aberrations by Activation-Induced Cytidine Deaminase (AID) during Inflammation-Associated Carcinogenesis

Genetic abnormalities such as nucleotide alterations and chromosomal disorders that accumulate in various tumor-related genes have an important role in cancer development. The precise mechanism of the acquisition of genetic aberrations, however, remains unclear. Activation-induced cytidine deaminase (AID), a nucleotide editing enzyme, is essential for the diversification of antibody production. AID is expressed only in activated B lymphocytes under physiologic conditions and induces somatic hypermutation and class switch recombination in immunoglobulin genes. Inflammation leads to aberrant AID expression in various gastrointestinal organs and increased AID expression contributes to cancer development by inducing genetic alterations in epithelial cells. Studies of how AID induces genetic disorders are expected to elucidate the mechanism of inflammation-associated carcinogenesis.