A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification.

Usually, the clustering process is the first step in several data analyses. Clustering allows identify patterns we did not note before and helps raise new hypotheses. However, one challenge when analyzing empirical data is the presence of covariates, which may mask the obtained clustering structure. For example, suppose we are interested in clustering a set of individuals into controls and cancer patients. A clustering algorithm could group subjects into young and elderly in this case. It may happen because the age at diagnosis is associated with cancer. Thus, we developed CEM-Co, a model-based clustering algorithm that removes/minimizes undesirable covariates' effects during the clustering process. We applied CEM-Co on a gene expression dataset composed of 129 stage I non-small cell lung cancer patients. As a result, we identified a subgroup with a poorer prognosis, while standard clustering algorithms failed.

MUSASHI-2 confers resistance to third-generation EGFR-tyrosine kinase inhibitor osimertinib in lung adenocarcinoma.

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are effective in patients with non-small-cell lung cancer (NSCLC) harboring EGFR mutations. However, due to acquired resistance to EGFR-TKIs, even patients on third-generation osimertinib have a poor prognosis. Resistance mechanisms are still not fully understood. Here, we demonstrate that the increased expression of MUSASHI-2 (MSI2), an RNA-binding protein, is a novel mechanism for resistance to EGFR-TKIs. We found that after a long-term exposure to gefitinib, the first-generation EGFR-TKI lung cancer cells harboring the EGFR-TKI-sensitive mutations became resistant to both gefitinib and osimertinib. Although other mutations in EGFR were not found, expression levels of Nanog, a stemness core protein, and activities of aldehyde dehydrogenase (ALDH) were increased, suggesting that cancer stem-like properties were increased. Transcriptome analysis revealed that MSI2 was among the stemness-related genes highly upregulated in EGFR-TKI-resistant cells. Knockdown of MSI2 reduced cancer stem-like properties, including the expression levels of Nanog, a core stemness factor. We demonstrated that knockdown of MSI2 restored sensitivity to osimertinib or gefitinib in EGFR-TKI-resistant cells to levels similar to those of parental cells in vitro. An RNA immunoprecipitation (RIP) assay revealed that antibodies against MSI2 were bound to Nanog mRNA, suggesting that MSI2 increases Nanog expression by binding to Nanog mRNA. Moreover, overexpression of MSI2 or Nanog conferred resistance to osimertinib or gefitinib in parental cells. Finally, MSI2 knockdown greatly increased the sensitivity to osimertinib in vivo. Collectively, our findings provide proof of principle that targeting the MSI2-Nanog axis in combination with EGFR-TKIs would effectively prevent the emergence of acquired resistance.

Xenografts derived from patients with head and neck cancer recapitulate patient tumour properties.

Rodent models mimic the heterogeneity of head and neck cancer (HNC) malignancies and are used to investigate HNC-associated biomarkers and evaluate drug responses. To assess the utility of patient-derived xenografts (PDXs) as an HNC model, 18 tumour samples were obtained from surgical specimens of patients with HNC and implanted into non-obese diabetic severe combined immunodeficient mice. The histological features of PDXs and corresponding patient samples were compared. Furthermore, the present study investigated how PDX responses to anticancer drugs mimic patient clinical responses, as well as the expression of adenosine triphosphate-binding cassette transporters through chemotherapy in an HNC-PDX model. A total of five PDXs from patients with HNC exhibiting high correspondence with histopathological features of the original patient samples were established (establishment rate, 28%). The responses of three PDXs to cisplatin were associated with clinical responses of the patients. ABC transporter expression was augmented in one PDX model after anticancer drug treatment, but not in PBS-treated passaged PDXs. PDX models exhibited similar biological and chemosensitive characteristics to those of the primary tumours. PDXs could be a useful preclinical tool to test novel therapeutic agents and identify novel targets and biomarkers in HNC.

MCM10 compensates for Myc-induced DNA replication stress in breast cancer stem-like cells.

Cancer stem-like cells (CSCs) induce drug resistance and recurrence of tumors when they experience DNA replication stress. However, the mechanisms underlying DNA replication stress in CSCs and its compensation remain unclear. Here, we demonstrate that upregulated c-Myc expression induces stronger DNA replication stress in patient-derived breast CSCs than in differentiated cancer cells. Our results suggest critical roles for mini-chromosome maintenance protein 10 (MCM10), a firing (activating) factor of DNA replication origins, to compensate for DNA replication stress in CSCs. MCM10 expression is upregulated in CSCs and is maintained by c-Myc. c-Myc-dependent collisions between RNA transcription and DNA replication machinery may occur in nuclei, thereby causing DNA replication stress. MCM10 may activate dormant replication origins close to these collisions to ensure the progression of replication. Moreover, patient-derived breast CSCs were found to be dependent on MCM10 for their maintenance, even after enrichment for CSCs that were resistant to paclitaxel, the standard chemotherapeutic agent. Further, MCM10 depletion decreased the growth of cancer cells, but not of normal cells. Therefore, MCM10 may robustly compensate for DNA replication stress and facilitate genome duplication in cancer cells in the S-phase, which is more pronounced in CSCs. Overall, we provide a preclinical rationale to target the c-Myc-MCM10 axis for preventing drug resistance and recurrence of tumors.

Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer.

Triple negative breast cancer (TNBC) is currently the only major breast tumor subtype without effective targeted therapy and, as a consequence, usually presents a poor outcome. Due to its more aggressive phenotype, there is an urgent clinical need to identify novel biomarkers that discriminate individuals with poor prognosis. We hypothesize that miRNAs can be used to this end because they are involved in the initiation and progression of tumors by altering the expression of their target genes. To identify a prognostic biomarker in TNBC, we analyzed the miRNA expression of a cohort composed of 185 patients diagnosed with TNBC using penalized Cox regression models. We identified a four-biomarker signature based on miR-221, miR-1305, miR-4708, and RMDN2 expression levels that allowed for the subdivision of TNBC into high- or low-risk groups (Hazard Ratio - HR = 0.32; 95% Confidence Interval - CI = 0.11-0.91; p = 0.03) and are also statistically associated with survival outcome in subgroups of postmenopausal status (HR = 0.19; 95% CI = 0.04-0.90; p= 0.016), node negative status (HR = 0.12; 95% CI = 0.01-1.04; p = 0.026), and tumors larger than 2cm (HR = 0.21; 95% CI = 0.05-0.81; p = 0.021). This four-biomarker signature was significantly associated with TNBC as an independent prognostic factor for survival.

Cancer stem-like properties and gefitinib 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, caused by elevated expression of components of the ß-catenin pathway, 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 these gefitinib-resistant cancer cells. Moreover, overexpression of MTHFD2 in gefitinib-sensitive lung cancer cells conferred resistance to gefitinib. 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.

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 ß-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-ß-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 ß-catenin target gene, increased phosphorylation of Akt and GSK3, accumulation of ß-catenin in the cytoplasm/nucleus in PC9M2 cells. Both knockdown of ß-catenin and treatment with a ß-catenin inhibitor at least partially restored gefitinib sensitivity to PC9M2 cells. Lung adenocarcinoma tissues derived from gefitinib-resistant patients displayed a tendency to accumulate ß-catenin in the cytoplasm. We provide a rationale for combination therapy that includes targeting of the Akt-ß-catenin pathway to improve the efficacy of EGFR-TKIs.

NEURONAL DEVELOPMENT. Glycerophospholipid regulation of modality-specific sensory axon guidance in the spinal cord.

Glycerophospholipids, the structural components of cell membranes, have not been considered to be spatial cues for intercellular signaling because of their ubiquitous distribution. We identified lyso-phosphatidyl-ß-D-glucoside (LysoPtdGlc), a hydrophilic glycerophospholipid, and demonstrated its role in modality-specific repulsive guidance of spinal cord sensory axons. LysoPtdGlc is locally synthesized and released by radial glia in a patterned spatial distribution to regulate the targeting of nociceptive but not proprioceptive central axon projections. Library screening identified the G protein-coupled receptor GPR55 as a high-affinity receptor for LysoPtdGlc, and GPR55 deletion or LysoPtdGlc loss of function in vivo caused the misallocation of nociceptive axons into proprioceptive zones. These findings show that LysoPtdGlc/GPR55 is a lipid-based signaling system in glia-neuron communication for neural development.

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.

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.

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. Pearson's 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 Pearson's 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 (Pearson's, Spearman's and Kendall's correlations; distance correlation; Hoeffding's 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.

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.

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.

Domain-domain interaction of P-Rex1 is essential for the activation and inhibition by G protein betagamma subunits and PKA.

PtdIns(3, 4, 5)P(3)-dependent Rac exchanger (P-Rex) 1 is a guanine nucleotide exchange factor (GEF) for the small GTPase Rac. P-Rex1 is activated by G protein betagamma subunits (Gbetagamma), and the Gbetagamma-induced activation is inhibited by cAMP-dependent protein kinase A (PKA). However, the details of regulatory mechanism of P-Rex1 remain to be clarified. In the present study, we investigated the mechanism of activation and inhibition of P-Rex1 using various truncated and alanine-substituted mutants and found that the domain-domain interaction of P-Rex1 is important for Gbetagamma-induced activation and PKA-induced inhibition. Immunoprecipitation analysis showed that the second Disheveled/EGL-10/Pleckstrin (DEP) and first PSD-95/Dlg/ZO-1 (PDZ) domains of P-Rex1 associate with the inositol polyphosphate-4-phosphatase (IP4P) domain. Carboxyl-terminal truncation on the IP4P domain or mutations in the protein-binding pocket of the first PDZ domain abolished the association. Analysis of in vitro guanine nucleotide exchange assay, PAK1/2 phosphorylation, and Rac-specific actin reorganization revealed that Gbetagamma could activate a complex of the P-Rex1 mutant lacking the IP4P domain and the isolated IP4P domain as well as full-length P-Rex1. Moreover, PKA phosphorylation prevented the domain-domain interaction and Gbetagamma-binding. These results provide a new insight into the regulation of other Rho-family GEFs and cell responses induced by the heterotrimeric G protein.