Asuka Nakata

A Novel Serum 4-microRNA Signature for Lung Cancer Detection

The aim of this study was to identify differentially-expressed miRNAs in the serum of non-small cell lung cancer (NSCLC) patients that might be a clinically-useful tool for lung cancer early detection. We performed miRNA expression profile analysis using TaqMan OpenArray Human panel in a discovery set of 70 serum samples obtained at lung tumor resection and 22 non-cancer subjects (NC). Selected serum miRNAs were then validated by quantitative PCR using an independent validation set of serum samples from LC patients (n = 84) and NC (n = 23). Sixty miRNAs were significantly up-regulated and 31 were down-regulated in the serum from NSCLC patients versus NC (adjusted p < 0.001). Four miRNAs (miR-193b, miR-301, miR-141 and miR-200b) were selected for validating their diagnostic value in an independent cohort. In the discovery set, the ROC plot derived from the combination of these miRNAs yielded an area under the curve (AUC) of 0.985 (95% CI 0.961–1.000, p < 0.001). In the test set, this miRNA signature exhibited an AUC of 0.993 (95% CI 0.979–1.000, p < 0.001). In conclusion, we identified a serum 4-miRNA signature that discriminated with high accuracy lung cancer patients from NC. Further prospective validation of this miRNA signature is warranted.

Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma

Purpose To identify stage I lung adenocarcinoma patients with a poor prognosis who will benefit from adjuvant therapy. Patients and Methods Whole gene expression profiles were obtained at 19 time points over a 48-hour time course from human primary lung epithelial cells that were stimulated with epidermal growth factor (EGF) in the presence or absence of a clinically used EGF receptor tyrosine kinase (RTK)-specific inhibitor, gefitinib. The data were subjected to a mathematical simulation using the State Space Model (SSM). “Gefitinib-sensitive” genes, the expressional dynamics of which were altered by addition of gefitinib, were identified. A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort. The predictive ability of the risk scoring model was examined in independent cohorts of surgical specimens of lung cancer. Results The risk scoring model enabled the identification of high-risk stage IA and IB cases in another North American cohort for overall survival (OS) with a hazard ratio (HR) of 7.16 (P = 0.029) and 3.26 (P = 0.0072), respectively. It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively. Conclusion The set of 139 gefitinib-sensitive genes includes many genes known to be involved in biological aspects of cancer phenotypes, but not known to be involved in EGF signaling. The present result strongly re-emphasizes that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis. Trial Registration The Gene Expression Omnibus (GEO) GSE31210

A comparative study of statistical methods used to identify dependencies between gene expression signals

One major task in molecular biology is to understand the dependency among genes to model gene regulatory networks. Pearsons correlation is the most common method used to measure dependence between gene expression signals, but it works well only when data are linearly associated. For other types of association, such as non-linear or non-functional relationships, methods based on the concepts of rank correlation and information theory-based measures are more adequate than the Pearsons correlation, but are less used in applications, most probably because of a lack of clear guidelines for their use. This work seeks to summarize the main methods (Pearsons, Spearmans and Kendalls correlations; distance correlation; Hoeffdings D: measure; Heller-Heller-Gorfine measure; mutual information and maximal information coefficient) used to identify dependency between random variables, especially gene expression data, and also to evaluate the strengths and limitations of each method. Systematic Monte Carlo simulation analyses ranging from sample size, local dependence and linear/non-linear and also non-functional relationships are shown. Moreover, comparisons in actual gene expression data are carried out. Finally, we provide a suggestive list of methods that can be used for each type of data set.

Recent understanding of the molecular mechanisms for the efficacy and resistance of EGF receptor-specific tyrosine kinase inhibitors in non-small cell lung cancer

Introduction: The epidermal growth factor receptor (EGFR) and its family members are involved in many aspects of tumor biological processes. Aberrant activation of the EGFR tyrosine kinase by mutations or protein overexpression is observed in various types of human cancer, including lung cancer. EGFR tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib and erlotinib, are highly effective in lung cancer patients who harbor active mutations in the EGFR gene. However, patients who are initially sensitive to EGFR-TKIs eventually relapse within few years. Areas covered: Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and is associated with a high frequency of EGFR mutations. This review describes the EGFR mutations that determine the sensitivity to EGFR-TKIs and the current understanding of the molecular mechanisms of acquired resistance to EGFR-TKIs in NSCLC. Furthermore, the authors describe recent strategies developed to overcome acquired resistance using second-generation EGFR-TKIs and combination therapies with several molecular-targeting drugs. Expert opinion: Although recent findings have contributed to our understanding of the mechanism of acquired resistance and helped the development of novel strategies to overcome such resistance, the underlying mechanisms are complex and additional research is necessary to develop effective therapeutic strategies for individual patients with lung cancer.

Oncogenic Fusion Gene CD74-NRG1 Confers Cancer Stem Cell–like Properties in Lung Cancer through a IGF2 Autocrine/Paracrine Circuit

The CD74-Neuregulin1 (NRG1) fusion gene was recently identified as novel driver of invasive mucinous adenocarcinoma, a malignant form of lung cancer. However, the function of the CD74-NRG1 fusion gene in adenocarcinoma pathogenesis and the mechanisms by which it may impart protumorigenic characteristics to cancer stem cells (CSC) is still unclear. In this study, we found that the expression of the CD74-NRG1 fusion gene increased the population of lung cancer cells with CSC-like properties. CD74-NRG1 expression facilitated sphere formation not only of cancer cells, but also of nonmalignant lung epithelial cells. Using a limiting dilution assay in a xenograft model, we further show that the CD74-NRG1 fusion gene enhanced tumor initiation. Mechanistically, we found that CD74-NRG1 expression promoted the phosphorylation of ErbB2/3 and activated the PI3K/Akt/NF-κB signaling pathway. Furthermore, the expression of the secreted insulin-like growth factor 2 (IGF2) and phosphorylation of its receptor, IGF1R, were enhanced in an NF-κB-dependent manner in cells expressing CD74-NRG1. These findings suggest that CD74-NRG1-induced NF-κB activity promotes the IGF2 autocrine/paracrine circuit. Moreover, inhibition of ErbB2, PI3K, NF-κB, or IGF2 suppressed CD74-NRG1-induced tumor sphere formation. Therefore, our study provides a preclinical rationale for developing treatment approaches based on these identified pathways to suppress CSC properties that promote tumor progression and recurrence.

Elevated β-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs.

There is a high death rate of lung cancer patients. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are effective in some lung adenocarcinoma patients with EGFR mutations. However, a significant number of patients show primary and acquire resistance to EGFR-TKIs. Although the Akt kinase is commonly activated due to various resistance mechanisms, the key targets of Akt remain unclear. Here, we show that the Akt-β-catenin pathway may be a common resistance mechanism. We analyzed gene expression profiles of gefitinib-resistant PC9M2 cells that were derived from gefitinib-sensitive lung cancer PC9 cells and do not have known resistance mechanisms including EGFR mutation T790M. We found increased expression of Axin, a β-catenin target gene, increased phosphorylation of Akt and GSK3, accumulation of β-catenin in the cytoplasm/nucleus in PC9M2 cells. Both knockdown of β-catenin and treatment with a β-catenin inhibitor at least partially restored gefitinib sensitivity to PC9M2 cells. Lung adenocarcinoma tissues derived from gefitinib-resistant patients displayed a tendency to accumulate β-catenin in the cytoplasm. We provide a rationale for combination therapy that includes targeting of the Akt-β-catenin pathway to improve the efficacy of EGFR-TKIs.

Pyruvate kinase M2, but not M1, allele maintains immature metabolic states of murine embryonic stem cells

The M2 isoform of pyruvate kinase, the final rate-limiting enzyme of aerobic glycolysis, is expressed during embryonic development. In contrast, the M1 isoform is expressed in differentiated cells due to alternative splicing. Here we investigated murine embryonic stem cells (ESCs) with Pkm1 or Pkm2 knock-in alleles. Pkm1 allele knock-in resulted in excessive oxidative phosphorylation and induced the formation of cysteine-thiol disulfide-dependent complexes of forkhead box class-O (FOXO) transcription factors, which resulted in altered endoderm differentiation. In contrast, Pkm2 knock-in induced synthesis of a methylation-donor, S-adenosylmethionine, and increased unsaturated eicosanoid groups, which contributed to the redox control and maintenance of ESC undifferentiated status. Because PKM2 is also a critical enzyme for the cancer-specific Warburg effect, our results demonstrate an important role for the Pkm2 allele in establishing intracellular redox conditions and modulating PKM1-dependent oxidative phosphorylation events to achieve an appropriate ESC differentiation program.

Abstract 168: Cancer stem-like properties and drug resistance are dependent on purine synthetic metabolism mediated by the mitochondrial enzyme MTHFD2

Tumor recurrence is attributable to cancer stem-like cells (CSCs), the metabolic mechanisms of which currently remain obscure. Here, we uncovered the critical role of folate-mediated one-carbon (1C) metabolism involving mitochondrial methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and its downstream purine synthesis pathway. MTHFD2 knockdown greatly reduced tumorigenesis and stem-like properties, which were associated with purine nucleotide deficiency, and caused marked accumulation of 5-aminoimidazole carboxamide ribonucleotide (AICAR)—the final intermediate of the purine synthesis pathway. Lung cancer cells with acquired resistance to the targeted drug gefitinib exhibited increased stem-like properties and enhanced expression of MTHFD2. MTHFD2 knockdown or treatment with AICAR reduced the stem-like properties and restored gefitinib sensitivity in gefitinib-resistant cancer cells. Thus, MTHFD2-mediated mitochondrial 1C metabolism appears critical for cancer stem-like properties and resistance to drugs including gefitinib through consumption of AICAR, leading to depletion of the intracellular pool of AICAR. Because CSCs are dependent on MTHFD2, therapies targeting MTHFD2 may eradicate tumors and prevent recurrence. Citation Format: Noriko Gotoh, Tatsunori Nishimura, Asuka Nakata, Shin-ichi Horike, Susumu Kohno, Chiaki Takahashi, Tomoyoshi Soga, Arinobu Tojo. Cancer stem-like properties and drug resistance are dependent on purine synthetic metabolism mediated by the mitochondrial enzyme MTHFD2 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 168.

Abstract LB-99: EGF receptor tyrosine kinase defines critical prognostic genes of stage IA lung adenocarcinoma

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Non-small cell lung cancer (NSCLC) is the commonest and the most fatal histological subtype of lung cancer. About 10-30% of patients diagnosed as stage IA (the earliest stage of a lung tumor, smaller than three centimeters in diameter with no evidence of regional lymph node and/or regional metastasis) and submitted to surgery die due to recurrence. Therefore, the identification of prognostic biomarkers for stage IA lung adenocarcinoma with poor prognosis is of great importance to select patients who will be benefited by adjuvant therapy. To the best of our knowledge, there is not a set of genes that identifies these patients. It is known that epidermal growth factor (EGF) signaling pathway is closely related to aggressive phenotypes of lung and other cancers. EGFR tyrosine kinase-specific inhibitor, namely gefitinib is expected to alter the gene expression patterns caused by EGFR tyrosine kinase activity. We performed microarray assays in order to obtain the entire gene expression time course profile of human primary lung epithelial cells that were stimulated with EGF in both the presence and absence of gefitinib. The time courses are composed of 19 time points along 48 hours. The data were subjected to a mathematical analysis, namely the State Space Model (SSM) in order to select genes with gene expressions altered by gefitinib. One hundred thirty nine genes were identified. These genes were used as expression signatures to train a risk scoring model that classifies patients in high- or low-risk (risk of dying in five years). This model was trained by using a data set composed of 253 North American patients with lung adenocarcinomas. Then, the predictive ability of the risk scoring model was examined in two independent cohorts composed of North American and Japanese patients. The model enabled the statistically significant identification of high-risk stage IA lung adenocarcinoma in both cohorts, with hazard ratios (HRs) for death of 7.16 (P=0.029) for North American and 10.98 (P=0.008) for Japanese. The set of 139 genes altered by gefitinib includes several ones that are involved in biological aspects of cancer phenotypes but are yet unknown to be involved in EGF signaling. This result strongly re-emphasizes that EGF signaling status underlies aggressive phenotype of cancer cells, and also suggests the first set of genes that are useful for the identification of stage IA lung adenocarcinoma patients with poor prognosis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-99. doi:1538-7445.AM2012-LB-99