CERS6 required for cell migration and metastasis in lung cancer.

Sphingolipids constitute a class of bio-reactive molecules that transmit signals and exhibit a variety of physical properties in various cell types, though their functions in cancer pathogenesis have yet to be elucidated. Analyses of gene expression profiles of clinical specimens and a panel of cell lines revealed that the ceramide synthase gene CERS6 was overexpressed in non-small-cell lung cancer (NSCLC) tissues, while elevated expression was shown to be associated with poor prognosis and lymph node metastasis. NSCLC profile and in vitro luciferase analysis results suggested that CERS6 overexpression is promoted, at least in part, by reduced miR-101 expression. Under a reduced CERS6 expression condition, the ceramide profile became altered, which was determined to be associated with decreased cell migration and invasion activities in vitro. Furthermore, CERS6 knockdown suppressed RAC1-positive lamellipodia/ruffling formation and attenuated lung metastasis efficiency in mice, while forced expression of CERS6 resulted in an opposite phenotype in examined cell lines. Based on these findings, we consider that ceramide synthesis by CERS6 has important roles in lung cancer migration and metastasis.

Targeting ceramide synthase 6-dependent metastasis-prone phenotype in lung cancer cells.

Sphingolipids make up a family of molecules associated with an array of biological functions, including cell death and migration. Sphingolipids are often altered in cancer, though how these alterations lead to tumor formation and progression is largely unknown. Here, we analyzed non-small-cell lung cancer (NSCLC) specimens and cell lines and determined that ceramide synthase 6 (CERS6) is markedly overexpressed compared with controls. Elevated CERS6 expression was due in part to reduction of microRNA-101 (miR-101) and was associated with increased invasion and poor prognosis. CERS6 knockdown in NSCLC cells altered the ceramide profile, resulting in decreased cell migration and invasion in vitro, and decreased the frequency of RAC1-positive lamellipodia formation while CERS6 overexpression promoted it. In murine models, CERS6 knockdown in transplanted NSCLC cells attenuated lung metastasis. Furthermore, combined treatment with l-α-dimyristoylphosphatidylcholine liposome and the glucosylceramide synthase inhibitor D-PDMP induced cell death in association with ceramide accumulation and promoted cancer cell apoptosis and tumor regression in murine models. Together, these results indicate that CERS6-dependent ceramide synthesis and maintenance of ceramide in the cellular membrane are essential for lamellipodia formation and metastasis. Moreover, these results suggest that targeting this homeostasis has potential as a therapeutic strategy for CERS6-overexpressing NSCLC.

miR-342-3p regulates MYC transcriptional activity via direct repression of E2F1 in human lung cancer.

Accumulating evidence indicates that altered miRNA expression is crucially involved in lung cancer development, though scant information is available regarding how MYC, an archetypical oncogene, is regulated by miRNAs, especially via a mechanism involving MYC cofactors. In this study, we attempted to identify miRNAs involved in regulation of MYC transcriptional activity in lung cancer. To this end, we utilized an integrative approach with combinatorial usage of miRNA and mRNA expression profile datasets of patient tumor tissues, as well as those of MYC-inducible cell lines in vitro. In addition to miRNAs previously reported to be directly regulated by MYC, including let-7 and miR-17-92, our strategy also helped to identify miR-342-3p as capable of indirectly regulating MYC activity via direct repression of E2F1, a MYC-cooperating molecule. Furthermore, miR-342-3p module activity, which we defined as a gene set reflecting the experimentally substantiated influence of miR-342-3p on mRNA expression, was found to be inversely correlated with MYC activity reflected by MYC module activity in three independent datasets of lung adenocarcinoma patients obtained from the Director's Challenge Consortium of the United States (P = 1.94 × 10(-73)), the National Cancer Center of Japan (P = 9.05 × 10(-34)) and the present study (P = 1.17 × 10(-19)). Our integrative approach appears to be useful to elucidate inter-regulatory relationships between miRNAs and protein coding genes of interest, even those present in patient tumor tissues, which remains a challenge to better understand the pathogenesis of this devastating disease.

Lung adenocarcinoma subtypes definable by lung development-related miRNA expression profiles in association with clinicopathologic features.

Accumulation of genetic and epigenetic changes alters regulation of a web of interconnected genes including microRNAs (miRNAs), which confer hallmark capabilities and characteristic cancer features. In this study, the miRNA and messenger RNA expression profiles of 126 non-small cell lung cancer specimens were analyzed, with special attention given to the diversity of lung adenocarcinomas. Of those, 76 adenocarcinomas were classified into two major subtypes, developing lung-like and adult lung-like, based on their distinctive miRNA expression profiles resembling those of either developing or adult lungs, respectively. A systems biology-based approach using a Bayesian network and non-parametric regression was employed to estimate the gene regulatory circuitry functioning in patient tumors in order to identify subnetworks enriched for genes with differential expression between the two major subtypes. miR-30d and miR-195, identified as hub genes in such subnetworks, had lower levels of expression in the developing lung-like subtype, whereas introduction of miR-30d or miR-195 into the lung cancer cell lines evoked shifts of messenger RNA expression profiles toward the adult lung-like subtype. Conversely, the influence of miR-30d and miR-195 was significantly different between the developing lung-like and adult lung-like subtypes in our analysis of the patient data set. In addition, RRM2, a child gene of the miR-30d-centered subnetwork, was found to be a direct target of miR-30d. Together, our findings reveal the existence of two miRNA expression profile-defined lung adenocarcinoma subtypes with distinctive clinicopathologic features and also suggest the usefulness of a systems biology-based approach to gain insight into the altered regulatory circuitry involved in cancer development.

Seven-signal proteomic signature for detection of operable pancreatic ductal adenocarcinoma and their discrimination from autoimmune pancreatitis.

There is urgent need for biomarkers that provide early detection of pancreatic ductal adenocarcinoma (PDAC) as well as discrimination of autoimmune pancreatitis, as current clinical approaches are not suitably accurate for precise diagnosis. We used mass spectrometry to analyze protein profiles of more than 300 plasma specimens obtained from PDAC, noncancerous pancreatic diseases including autoimmune pancreatitis patients and healthy subjects. We obtained 1063 proteomic signals from 160 plasma samples in the training cohort. A proteomic signature consisting of 7 mass spectrometry signals was used for construction of a proteomic model for detection of PDAC patients. Using the test cohort, we confirmed that this proteomic model had discrimination power equal to that observed with the training cohort. The overall sensitivity and specificity for detection of cancer patients were 82.6% and 90.9%, respectively. Notably, 62.5% of the stage I and II cases were detected by our proteomic model. We also found that 100% of autoimmune pancreatitis patients were correctly assigned as noncancerous individuals. In the present paper, we developed a proteomic model that was shown able to detect early-stage PDAC patients. In addition, our model appeared capable of discriminating patients with autoimmune pancreatitis from those with PDAC.

NKX2-1/TITF1/TTF-1-Induced ROR1 is required to sustain EGFR survival signaling in lung adenocarcinoma.

We and others previously identified NKX2-1, also known as TITF1 and TTF-1, as a lineage-survival oncogene in lung adenocarcinomas. Here we show that NKX2-1 induces the expression of the receptor tyrosine kinase-like orphan receptor 1 (ROR1), which in turn sustains a favorable balance between prosurvival PI3K-AKT and pro-apoptotic p38 signaling, in part through ROR1 kinase-dependent c-Src activation, as well as kinase activity-independent sustainment of the EGFR-ERBB3 association, ERBB3 phosphorylation, and consequential PI3K activation. Notably, ROR1 knockdown effectively inhibited lung adenocarcinoma cell lines, irrespective of their EGFR status, including those with resistance to the EGFR tyrosine kinase inhibitor gefitinib. Our findings thus identify ROR1 as an "Achilles' heel" in lung adenocarcinoma, warranting future development of therapeutic strategies for this devastating cancer.

MYBPH, a transcriptional target of TTF-1, inhibits ROCK1, and reduces cell motility and metastasis.

Cell migration driven by actomyosin filament assembly is a critical step in tumour invasion and metastasis. Herein, we report identification of myosin binding protein H (MYBPH) as a transcriptional target of TTF-1 (also known as NKX2-1 and TITF1), a master regulator of lung development that also plays a role as a lineage-survival oncogene in lung adenocarcinoma development. MYBPH inhibited assembly competence-conferring phosphorylation of the myosin regulatory light chain (RLC) as well as activating phosphorylation of LIM domain kinase (LIMK), unexpectedly through its direct physical interaction with Rho kinase 1 (ROCK1) rather than with RLC. Consequently, MYBPH inhibited ROCK1 and negatively regulated actomyosin organization, which in turn reduced single cell motility and increased collective cell migration, resulting in decreased cancer invasion and metastasis. Finally, we also show that MYBPH is epigenetically inactivated by promoter DNA methylation in a fraction of TTF-1-positive lung adenocarcinomas, which appears to be in accordance with its deleterious functions in lung adenocarcinoma invasion and metastasis, as well as with the paradoxical association of TTF-1 expression with favourable prognosis in lung adenocarcinoma patients.

miR-375 is activated by ASH1 and inhibits YAP1 in a lineage-dependent manner in lung cancer.

Lung cancers with neuroendocrine (NE) features are often very aggressive but the underlying molecular mechanisms remain elusive. The transcription factor ASH1/ASCL1 is a master regulator of pulmonary NE cell development that is involved in the pathogenesis of lung cancers with NE features (NE-lung cancers). Here we report the definition of the microRNA miR-375 as a key downstream effector of ASH1 function in NE-lung cancer cells. miR-375 was markedly induced by ASH1 in lung cancer cells where it was sufficient to induce NE differentiation. miR-375 upregulation was a prerequisite for ASH1-mediated induction of NE features. The transcriptional coactivator YAP1 was determined to be a direct target of miR-375. YAP1 showed a negative correlation with miR-375 in a panel of lung cancer cell lines and growth inhibitory activities in NE-lung cancer cells. Our results elucidate an ASH1 effector axis in NE-lung cancers that is functionally pivotal in controlling NE features and the alleviation from YAP1-mediated growth inhibition.

Proteasomal non-catalytic subunit PSMD2 as a potential therapeutic target in association with various clinicopathologic features in lung adenocarcinomas.

We previously identified PSMD2, a subunit of the 19S regulatory complex of proteasomes, as a constituent of a signature associated with the acquisition of metastatic phenotype and poor prognosis in lung cancers. In the present study, we found that knockdown of PSMD2 decreased proteasome activity, and induced growth inhibition and apoptosis in lung cancer cell lines. These effects of siRNA-mediated PSMD2 inhibition were associated with changes in the balance between phosphorylated AKT and p38, as well as with induction of p21. In addition, patients with higher PSMD2 expression had poorer prognosis and a small fraction of lung cancer specimens carried increased copies of PSMD2. Notably, our findings clearly illustrate that lung adenocarcinomas can be divided into two groups; those with and without general upregulation of proteasome pathway genes including PSMD2. This general upregulation was significantly more prevalent in the non-terminal respiratory unit (non-TRU)-type, a recently proposed genetically and clinicopathologically relevant expression profile-defined classification of adenocarcinomas (P < 0.001 by Fisher's exact test). Patients with adenocarcinomas with general upregulation had significantly shorter survival after potentially curative resection (P = 0.0001 by log-rank test) independent of disease stage, as shown by multivariate Cox regression analysis. Our results suggest that PSMD2 may be a good molecular target candidate and that other co-regulated proteasome pathway genes and/or their common regulator(s) might also be potential targets, warranting future study including elucidation of the underlying common regulatory mechanism.

Novel metastasis-related gene CIM functions in the regulation of multiple cellular stress-response pathways.

Various stresses of the tumor microenvironment produced by insufficient nutrients, pH, and oxygen can contribute to the generation of altered metabolic and proliferative states that promote the survival of metastatic cells. Among many cellular stress-response pathways activated under such conditions are the hypoxia-inducible factor (HIF) pathway and the unfolded protein response (UPR), which is elicited as a response to endoplasmic reticulum (ER) stress. In this study, we report the identification of a novel cancer invasion and metastasis-related gene (hereafter referred to as CIM, also called ERLEC1), which influences both of these stress-response pathways to promote metastasis. CIM was identified by comparing the gene expression profile of a highly metastatic human lung cancer cell line with its weakly metastatic parental clone. We showed that CIM is critical for metastatic properties in this system. Proteomic approaches combined with bioinformatic analyses revealed that CIM has multifaceted roles in controlling the response to hypoxia and ER stress. Specifically, CIM sequestered OS-9 from the HIF-1α complex and PHD2, permitting HIF-1α accumulation by preventing its degradation. Ectopic expression of CIM in lung cancer cells increased their tolerance to hypoxia. CIM also modulated UPR through interaction with the key ER stress protein BiP, influencing cell proliferation under ER stress conditions. Our findings shed light on how tolerance to multiple cellular stresses at a metastatic site can be evoked by an integrated mechanism involving CIM, which can function to coordinate those responses in a manner that promotes metastatic cell survival.

Regulation of DNA polymerase POLD4 influences genomic instability in lung cancer.

Genomic instability is an important factor in cancer susceptibility, but a mechanistic understanding of how it arises remains unclear. We examined hypothesized contributions of the replicative DNA polymerase δ (pol δ) subunit POLD4 to the generation of genomic instability in lung cancer. In examinations of 158 lung cancers and 5 mixtures of 10 normal lungs, cell cycle- and checkpoint-related genes generally showed mRNA expression increases in cancer, whereas POLD4 showed reduced mRNA in small cell lung cancer (SCLC). A fraction of non-small cell lung cancer patients also showed low expression comparable with that in SCLC, which was associated with poor prognosis. The lung cancer cell line ACC-LC-48 was found to have low POLD4 expression, with higher histone H3K9 methylation and lower acetylation in the POLD4 promoter, as compared with the A549 cell line with high POLD4 expression. In the absence of POLD4, pol δ exhibited impaired in vitro DNA synthesis activity. Augmenting POLD4 expression in cells where it was attenuated altered the sensitivity to the chemical carcinogen 4-nitroquinoline-1-oxide. Conversely, siRNA-mediated reduction of POLD4 in cells with abundant expression resulted in a cell cycle delay, checkpoint activation, and an elevated frequency of chromosomal gap/break formation. Overexpression of an engineered POLD4 carrying silent mutations at the siRNA target site rescued these phenotypes, firmly establishing the role of POLD4 in these effects. Furthermore, POLD4 overexpression reduced intrinsically high induction of γ-H2AX, a well-accepted marker of double-stranded DNA breaks. Together, our findings suggest that reduced expression of POLD4 plays a role in genomic instability in lung cancer.

Clinically relevant characterization of lung adenocarcinoma subtypes based on cellular pathways: an international validation study.

Lung adenocarcinoma (AD) represents a predominant type of lung cancer demonstrating significant morphologic and molecular heterogeneity. We sought to understand this heterogeneity by utilizing gene expression analyses of 432 AD samples and examining associations between 27 known cancer-related pathways and the AD subtype, clinical characteristics and patient survival. Unsupervised clustering of AD and gene expression enrichment analysis reveals that cell proliferation is the most important pathway separating tumors into subgroups. Further, AD with increased cell proliferation demonstrate significantly poorer outcome and an increased solid AD subtype component. Additionally, we find that tumors with any solid component have decreased survival as compared to tumors without a solid component. These results lead to the potential to use a relatively simple pathological examination of a tumor in order to determine its aggressiveness and the patient's prognosis. Additional results suggest the ability to use a similar approach to determine a patient's sensitivity to targeted treatment. We then demonstrated the consistency of these findings using two independent AD cohorts from Asia (N = 87) and Europe (N = 89) using the identical analytic procedures.

Relapse-related molecular signature in lung adenocarcinomas identifies patients with dismal prognosis.

PURPOSE: In order to aid the development of patient-tailored therapeutics, we attempted to identify a relapse-related signature that allows selection of a group of adenocarcinoma patients with a high probability of relapse. PATIENTS AND METHODS: Whole-genome expression profiles were analyzed in 117 lung adenocarcinoma samples using microarrays consisting of 41,000 probes. A weighted voting classifier for identifying patients with a relapse-related signature was constructed with an approach that allowed no information leakage during each training step, using 10-fold cross-validation and 100 random partitioning procedures. RESULTS: We identified a relapse-related molecular signature represented by 82 probes (RRS-82) through genome-wide expression profiling analysis of a training set of 60 patients. The robustness of RRS-82 in the selection of patients with a high probability of relapse was then validated with a completely blinded test set of 27 adenocarcinoma patients, showing a clear association of high risk RRS-82 with very poor patient prognosis regardless of disease stage. The discriminatory power of RRS-82 was further validated using an additional independent cohort of 30 stage I patients who underwent surgery at a distinct period of time as well as with the Duke data set on a different platform. Furthermore, completely separate training and validation procedures using another data set recently reported by the Director's Challenge Consortium also successfully confirmed the predictive power of the genes comprising RRS-82. CONCLUSION: RRS-82 may be useful for identifying adenocarcinoma patients at very high risk for relapse, even those with cancer in the early stage.

Relationship of deregulated signaling converging onto mTOR with prognosis and classification of lung adenocarcinoma shown by two independent in silico analyses.

There is marked disparity with a slight overlap among prognosis-predictive signatures reported thus far for lung cancers. In this study, we aimed at linking poor prognosis with particular pathways and/or functions of the gene sets involved to better understand the underlying molecular characteristics associated with the prognosis of lung adenocarcinomas. Gene set enrichment analysis identified a gene set down-regulated by rapamycin as the most significant, whereas several others responsive to withdrawal of glucose or amino acids, which are related to signaling converging onto mammalian target of rapamycin (mTOR), were also shown to be significantly associated, in addition to those related to DNA damage response and cell cycle progression. We also used connectivity map (C-MAP) analysis, an independent bioinformatics approach, to search for Food and Drug Administration-approved drugs that potentially transform an unfavorable signature to a favorable one. Those results identified inhibitors of phosphatidylinositol 3-kinase (PI3K) and mTOR, as well as unexpected drugs such as phenothiazine antipsychotics and resveratrol as potential candidates. Experimental validation revealed that the latter unexpected agents also inhibited signaling converging onto mTOR and exhibited antitumor activities. In addition, deregulation of multiple signaling converging onto mTOR was shown to be significantly associated with sensitivity to PI-103, a dual specificity PI3K/mTOR inhibitor that is not contained in the C-MAP database, lending further support for the connection. Our results clearly show the existence of gene set-definable, intrinsic heterogeneities in lung adenocarcinomas, which seem to be related to both clinical behavior and sensitivity to agents affecting the identified pathways.

Modified fuzzy gap statistic for estimating preferable number of clusters in fuzzy k-means clustering.

In clustering methods, the estimation of the optimal number of clusters is significant for subsequent analysis. Without detailed biological information on the genes involved, the evaluation of the number of clusters becomes difficult, and we have to rely on an internal measure that is based on the distribution of the data of the clustering result. The Gap statistic has been proposed as a superior method for estimating the number of clusters in crisp clustering. In this study, we proposed a modified Fuzzy Gap statistic (MFGS) and applied it to fuzzy k-means clustering. For estimating the number of clusters, fuzzy k-means clustering with the MFGS was applied to two artificial data sets with noise and to two experimentally observed gene expression data sets. For the artificial data sets, compared with other internal measures, the MFGS showed a higher performance in terms of robustness against noise for estimating the optimal number of clusters. Moreover, it could be used to estimate the optimal number of clusters in experimental data sets. It was confirmed that the proposed MFGS is a useful method for estimating the number of clusters for microarray data sets.