Selection of suitable reference genes for accurate normalization of gene expression profile studies in non-small cell lung cancer

Differential cytokine expression in gastric tissues highlights helicobacter pylori's role in gastritis

Helicobacter pylori (H. pylori), known for causing gastric inflammation, gastritis and gastric cancer, prompted our study to investigate the differential expression of cytokines in gastric tissues, which is crucial for understanding H. pylori infection and its potential progression to gastric cancer. Focusing on Il-1β, IL-6, IL-8, IL-12, IL-18, and TNF-α, we analysed gene and protein levels to differentiate between H. pylori-infected and non-infected gastritis. We utilised real-time quantitative polymerase chain reaction (RT-qPCR) for gene quantification, immunohistochemical staining, and ELISA for protein measurement. Gastric samples from patients with gastritis were divided into three groups: (1) non-gastritis (N-group) group, (2) gastritis without H. pylori infection (G-group), and (3) gastritis with H. pylori infection (GH-group), each consisting of 8 samples. Our findings revealed a statistically significant variation in cytokine expression. Generally, cytokine levels were higher in gastritis, but in H. pylori-infected gastritis, IL-1β, IL-6, and IL-8 levels were lower compared to H. pylori-independent gastritis, while IL-12, IL-18, and TNF-α levels were higher. This distinct cytokine expression pattern in H. pylori-infected gastritis underscores a unique inflammatory response, providing deeper insights into its pathogenesis.

Construction and validation of a prognostic model for stemness-related genes in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with poor overall prognosis. Early identification of high-risk patients and individualized treatment can help extend the survival time of patients. This study aimed to construct and validate a prognostic prediction least absolute shrinkage and selection operator (LASSO) model for stemness-related genes in LUAD.

Methods

Firstly, LUAD RNA-sequencing data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor stemness index based on mRNA expression (mRNAsi) was calculated, and the relationship between mRNAsi and the survival prognosis as well as clinical features of LUAD patients was analyzed. Then, the weighted gene co-expression network analysis (WGCNA) method was used to screen for gene modules highly correlated with mRNAsi, and functional annotation [Gene Ontology (GO) analysis] and pathway enrichment analysis [Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis] were performed for the selected stemness-related gene module. Furthermore, prognosis-associated genes were determined from the stemness-related genes through univariate Cox analysis, and a prognostic model was constructed using LASSO analysis. Finally, a series of validations including survival curve analysis, receiver operating characteristic (ROC) curve analysis, and risk analysis were conducted for the prognostic model, and nomogram based on the risk model and various clinicopathological features were constructed.

Results

LUAD patients with high mRNAsi had a higher mortality rate than those with low mRNAsi. GO analysis showed that stemness-related genes were mainly involved in mRNA processing and extracellular matrix organization, while KEGG analysis revealed their involvement in cell cycle and PI3K-Akt signaling pathways. A prognostic model based on 12 stemness-related genes was constructed using LASSO regression. Validation of the prognostic model demonstrated its good accuracy in predicting the prognosis of LUAD patients.

Conclusions

mRNAsi plays an important role in the occurrence and development of LUAD. This study successfully constructed a prognostic prediction LASSO model for stemness-related genes in LUAD, which can serve as a novel prognostic indicator for LUAD and may be an effective complement to the current Tumor Node Metastasis (TNM) clinical staging of LUAD.

Experimental assessment of robust reference genes for qRT-PCR in lung cancer studies

Stable internal reference genes are crucial for quantitative real-time PCR (qRT-PCR) analyses in lung cancer studies. Widely used reference genes are mostly chosen by intuition or from pan-cancer transcriptome data and lack experimental validation by qRT-PCR in the context of lung cancer. This study evaluated the stability of candidate reference genes in lung cancer cell lines under normal homeostasis, hypoxia, and serum deprivation to screen for robust reference genes for qRT-PCR in lung cancer studies. The stability of reference gene combinations was also assessed. We found that most of the stably expressed genes from pan-cancer transcriptome analyses were not sufficiently stable under some of the tested conditions. CIAO1, CNOT4, and SNW1 were found to be the most stable reference genes under various conditions. Greater stability was achieved by combining more reference genes. We further used the hypoxia biomarker hypoxia-inducible factor (HIF)-2α to demonstrate that choosing inappropriate reference genes can lead to incorrect qRT-PCR results. We also found that the stable reference genes were irrelevant to malignancy, which may explain their stability under various conditions that cancer cells often encounter. This study provides a list of validated and stable qRT-PCR reference genes and reference gene combinations for lung cancer that may standardize qRT-PCR experiments in future lung cancer studies.

Inferencing Bulk Tumor and Single-Cell Multi-Omics Regulatory Networks for Discovery of Biomarkers and Therapeutic Targets

There are insufficient accurate biomarkers and effective therapeutic targets in current cancer treatment. Multi-omics regulatory networks in patient bulk tumors and single cells can shed light on molecular disease mechanisms. Integration of multi-omics data with large-scale patient electronic medical records (EMRs) can lead to the discovery of biomarkers and therapeutic targets. In this review, multi-omics data harmonization methods were introduced, and common approaches to molecular network inference were summarized. Our Prediction Logic Boolean Implication Networks (PLBINs) have advantages over other methods in constructing genome-scale multi-omics networks in bulk tumors and single cells in terms of computational efficiency, scalability, and accuracy. Based on the constructed multi-modal regulatory networks, graph theory network centrality metrics can be used in the prioritization of candidates for discovering biomarkers and therapeutic targets. Our approach to integrating multi-omics profiles in a patient cohort with large-scale patient EMRs such as the SEER-Medicare cancer registry combined with extensive external validation can identify potential biomarkers applicable in large patient populations. These methodologies form a conceptually innovative framework to analyze various available information from research laboratories and healthcare systems, accelerating the discovery of biomarkers and therapeutic targets to ultimately improve cancer patient survival outcomes.

Multi-Omics Immune Interaction Networks in Lung Cancer Tumorigenesis, Proliferation, and Survival

There are currently no effective biomarkers for prognosis and optimal treatment selection to improve non-small cell lung cancer (NSCLC) survival outcomes. This study further validated a seven-gene panel for diagnosis and prognosis of NSCLC using RNA sequencing and proteomic profiles of patient tumors. Within the seven-gene panel, ZNF71 expression combined with dendritic cell activities defined NSCLC patient subgroups (n = 966) with distinct survival outcomes (p = 0.04, Kaplan-Meier analysis). ZNF71 expression was significantly associated with the activities of natural killer cells (p = 0.014) and natural killer T cells (p = 0.003) in NSCLC patient tumors (n = 1016) using Chi-squared tests. Overexpression of ZNF71 resulted in decreased expression of multiple components of the intracellular intrinsic and innate immune systems, including dsRNA and dsDNA sensors. Multi-omics networks of ZNF71 and the intracellular intrinsic and innate immune systems were computed as relevant to NSCLC tumorigenesis, proliferation, and survival using patient clinical information and in-vitro CRISPR-Cas9/RNAi screening data. From these networks, pan-sensitive and pan-resistant genes to 21 NCCN-recommended drugs for treating NSCLC were selected. Based on the gene associations with patient survival and in-vitro CRISPR-Cas9, RNAi, and drug screening data, MEK1/2 inhibitors PD-198306 and U-0126, VEGFR inhibitor ZM-306416, and IGF-1R inhibitor PQ-401 were discovered as potential targeted therapy that may also induce an immune response for treating NSCLC.

Hub Genes in Non-Small Cell Lung Cancer Regulatory Networks

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson's correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes.

A Novel Strategy for Identifying NSCLC MicroRNA Biomarkers and Their Mechanism Analysis Based on a Brand-New CeRNA-Hub-FFL Network

Finding reliable miRNA markers and revealing their potential mechanisms will play an important role in the diagnosis and treatment of NSCLC. Most existing computational methods for identifying miRNA biomarkers only consider the expression variation of miRNAs or rely heavily on training sets. These deficiencies lead to high false-positive rates. The independent regulatory model is an important complement to traditional models of co-regulation and is more impervious to the dataset. In addition, previous studies of miRNA mechanisms in the development of non-small cell lung cancer (NSCLC) have mostly focused on the post-transcriptional level and did not distinguish between NSCLC subtypes. For the above problems, we improved mainly in two areas: miRNA identification based on both the NOG network and biological functions of miRNA target genes; and the construction of a 4-node directed competitive regulatory network to illustrate the mechanisms. NSCLC was classified as lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) in this work. One miRNA biomarker of LUAD (miR-708-5p) and four of LUSC (miR-183-5p, miR-140-5p, miR-766-5p, and miR-766-3p) were obtained. They were validated using literature and external datasets. The ceRNA-hub-FFL involving transcription factors (TFs), microRNAs (miRNAs), mRNAs, and long non-coding RNAs (lncRNAs) was constructed. There were multiple interactions among these components within the net at the transcriptional, post-transcriptional, and protein levels. New regulations were revealed by the network. Meanwhile, the network revealed the reasons for the previous conflicting conclusions on the roles of CD44, ACTB, and ITGB1 in NSCLC, and demonstrated the necessity of typing studies on NSCLC. The novel miRNA markers screening method and the 4-node directed competitive ceRNA-hub-FFL network constructed in this work can provide new ideas for screening tumor markers and understanding tumor development mechanisms in depth.

RNA Sequencing of Tumor-Educated Platelets Reveals a Three-Gene Diagnostic Signature in Esophageal Squamous Cell Carcinoma

There is no cost-effective, accurate, and non-invasive method for the detection of esophageal squamous cell carcinoma (ESCC) in clinical practice. We aimed to investigate the diagnostic potential of tumor-educated platelets in ESCC. In this study, seventy-one ESCC patients and eighty healthy individuals were enrolled and divided into a training cohort (23 patients and 27 healthy individuals) and a validation cohort (48 patients and 53 healthy individuals). Next-generation RNA sequencing was performed on platelets isolated from peripheral blood of all participants, and a support vector machine/leave-one-out cross validation (SVM/LOOCV) approach was used for binary classification. A diagnostic signature composed of ARID1A, GTF2H2, and PRKRIR discriminated ESCC patients from healthy individuals with 91.3% sensitivity and 85.2% specificity in the training cohort and 87.5% sensitivity and 81.1% specificity in the validation cohort. The AUC was 0.924 (95% CI, 0.845–0.956) and 0.893 (95% CI, 0.821–0.966), respectively, in the training cohort and validation cohort. This 3-gene platelet RNA signature could effectively discriminate ESCC from healthy control. Our data highlighted the potential of tumor-educated platelets for the noninvasive diagnosis of ESCC. Moreover, we found that keratin and collagen protein families and ECM-related pathways might be involved in tumor progression and metastasis of ESCC, which might provide insights to understand ESCC pathobiology and advance novel therapeutics.

A Multi-Omics Network of a Seven-Gene Prognostic Signature for Non-Small Cell Lung Cancer

There is an unmet clinical need to identify patients with early-stage non-small cell lung cancer (NSCLC) who are likely to develop recurrence and to predict their therapeutic responses. Our previous study developed a qRT-PCR-based seven-gene microfluidic assay to predict the recurrence risk and the clinical benefits of chemotherapy. This study showed it was feasible to apply this seven-gene panel in RNA sequencing profiles of The Cancer Genome Atlas (TCGA) NSCLC patients (n = 923) in randomly partitioned feasibility-training and validation sets (p < 0.05, Kaplan-Meier analysis). Using Boolean implication networks, DNA copy number variation-mediated transcriptional regulatory network of the seven-gene signature was identified in multiple NSCLC cohorts (n = 371). The multi-omics network genes, including PD-L1, were significantly correlated with immune infiltration and drug response to 10 commonly used drugs for treating NSCLC. ZNF71 protein expression was positively correlated with epithelial markers and was negatively correlated with mesenchymal markers in NSCLC cell lines in Western blots. PI3K was identified as a relevant pathway of proliferation networks involving ZNF71 and its isoforms formulated with CRISPR-Cas9 and RNA interference (RNAi) profiles. Based on the gene expression of the multi-omics network, repositioning drugs were identified for NSCLC treatment.

A pan-cancer analysis of the prognostic and immunological role of β-actin (ACTB) in human cancers

Beta-actin (ACTB), a highly conserved cytoskeleton structural protein, has been regarded as a common housekeep gene and used as a reference gene for years. However, accumulating evidence indicates that ACTB is abnormally expressed in multiple cancers and hence changes the cytoskeleton to affect the invasiveness and metastasis of tumors. This study aimed to investigate the function and clinical significance of ACTB in pan-cancer. The role of ACTB for prognosis and immune regulation across 33 tumors was explored based on the datasets of gene expression omnibus and the cancer genome atlas. Differential expression of ACTB was found between cancer and adjacent normal tissues, and significant associations was found between ACTB expression and prognosis of tumor patients. In most cancers, ACTB expression was associated with immune cells infiltration, immune checkpoints and other immune modulators. Relevance between ACTB and metastasis and invasion was identified in various types of cancers by CancerSEA. Moreover, focal adhesion and actin regulation-associated pathways were included in the functional mechanisms of ACTB. The expression of ACTB was verified by quantitative real-time polymerase chain reaction. Knockdown of ACTB inhibited head and neck squamous carcinoma cell migration and invasion by NF-κB and Wnt/β-catenin pathways. Our first pan-cancer study of ACTB offers insight into the prognostic and immunological roles of ACTB across different tumors, indicating ACTB may be a potential biomarker for poor prognosis and immune infiltration in cancers, and the role of ACTB as a reference gene in cancers was challenged.

Dynamin 3 Inhibits the Proliferation of Non-small-Cell Lung Cancer Cells by Suppressing c-MET-GBR2-STAT3 Complex Formation

Dynamin 3 (DNM3) has gained increased attention ever since its potential as a tumor suppressor was reported. However, its action in lung cancer (LC) is undefined. In this study, the role of DNM3 in LC development was investigated. DNM3 expression was found to be downregulated in tumors of patients with LC, especially those with metastasis. The DNM3 downregulation enhanced the proliferative and metastatic ability of LC cells, whereas its upregulation had the opposite effects. In vivo xenograft experiments confirmed that lung tumors with lower DNM3 expression had higher growth and metastatic abilities. Mechanistic studies revealed that DNM3 interacts with growth factor receptor-bound protein 2 (GBR2), thereby interrupting tyrosine-protein kinase Met (c-MET)-GBR2-signal transducer and activator of transcription 3 (STAT3) complex formation, which suppressed STAT3 activation. Therefore, the absence of DNM3 frees GBR2 to activate STAT3, which regulates the expression of genes related to LC proliferation and metastasis (e.g., cyclin D1 and Snail family transcriptional repressor 1). Additionally, the c-MET inhibitor crizotinib effectively suppressed LC cell proliferation and migration in vitro and in vivo, even with DNM3 depleted. Therefore, our study has demonstrated the antitumor effect of DNM3 in LC and suggests that the inhibition of c-MET might be a promising strategy for treating those LC patients with low DNM3 expression.

Immune-Omics Networks of CD27, PD1, and PDL1 in Non-Small Cell Lung Cancer

To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. Major immune-checkpoint inhibitors (ICIs) have more DNA copy number variations (CNV) than mutations in The Cancer Genome Atlas (TCGA) NSCLC tumors. Nevertheless, CNV-mediated dysregulated gene expression in NSCLC is not well understood. Integrated CNV and transcriptional profiles in NSCLC tumors (n = 371) were analyzed using Boolean implication networks for the identification of a multi-omics CD27, PD1, and PDL1 network, containing novel prognostic genes and proliferation genes. A 5-gene (EIF2AK3, F2RL3, FOSL1, SLC25A26, and SPP1) prognostic model was developed and validated for patient stratification (p < 0.02, Kaplan-Meier analyses) in NSCLC tumors (n = 1163). A total of 13 genes (COPA, CSE1L, EIF2B3, LSM3, MCM5, PMPCB, POLR1B, POLR2F, PSMC3, PSMD11, RPL32, RPS18, and SNRPE) had a significant impact on proliferation in 100% of the NSCLC cell lines in both CRISPR-Cas9 (n = 78) and RNA interference (RNAi) assays (n = 92). Multiple identified genes were associated with chemoresponse and radiotherapy response in NSCLC cell lines (n = 117) and patient tumors (n = 966). Repurposing drugs were discovered based on this immune-omics network to improve NSCLC treatment.

The remodelling of actin composition as a hallmark of cancer

Actin is a key structural protein that makes up the cytoskeleton of cells, and plays a role in functions such as division, migration, and vesicle trafficking. It comprises six different cell-type specific isoforms: ACTA1, ACTA2, ACTB, ACTC1, ACTG1, and ACTG2. Abnormal actin isoform expression has been reported in many cancers, which led us to hypothesize that it may serve as an early biomarker of cancer. We show an overview of the different actin isoforms and highlight mechanisms by which they may contribute to tumorigenicity. Furthermore, we suggest how the aberrant expression of actin subunits can confer cells with greater proliferation ability, increased migratory capability, and chemoresistance through incorporation into the normal cellular F-actin network and altered actin binding protein interaction. Studying this fundamental change that takes place within cancer cells can further our understanding of neoplastic transformation in multiple tissue types, which can ultimately aid in the early-detection, diagnosis and treatment of cancer.

Network mapping of primary CD34+ cells by Ampliseq based whole transcriptome targeted resequencing identifies unexplored differentiation regulatory relationships

With the exception of a few master transcription factors, regulators of neutrophil maturation are poorly annotated in the intermediate phenotypes between the granulocyte-macrophage progenitor (GMP) and the mature neutrophil phenotype. Additional challenges in identifying gene expression regulators in differentiation pathways relate to challenges wherein starting cell populations are heterogeneous in lineage potential and development, are spread across various states of quiescence, as well as sample quality and input limitations. These factors contribute to data variability make it difficult to draw simple regulatory inferences. In response we have applied a multi-omics approach using primary blood progenitor cells primed for homogeneous proliferation and granulocyte differentiation states which combines whole transcriptome resequencing (Ampliseq RNA) supported by droplet digital PCR (ddPCR) validation and mass spectrometry-based proteomics in a hypothesis-generation study of neutrophil differentiation pathways. Primary CD34+ cells isolated from human cord blood were first precultured in non-lineage driving medium to achieve an active, proliferating phenotype from which a neutrophil primed progenitor was isolated and cultured in neutrophil lineage supportive medium. Samples were then taken at 24-hour intervals over 9 days and analysed by Ampliseq RNA and mass spectrometry. The Ampliseq dataset depth, breadth and quality allowed for several unexplored transcriptional regulators and ncRNAs to be identified using a combinatorial approach of hierarchical clustering, enriched transcription factor binding motifs, and network mapping. Network mapping in particular increased comprehension of neutrophil differentiation regulatory relationships by implicating ARNT, NHLH1, PLAG1, and 6 non-coding RNAs associated with PU.1 regulation as cell-engineering targets with the potential to increase total neutrophil culture output. Overall, this study develops and demonstrates an effective new hypothesis generation methodology for transcriptome profiling during differentiation, thereby enabling identification of novel gene targets for editing interventions.

Identification of suitable reference genes in blood samples of carcinoma lung patients using quantitative real-time polymerase chain reaction

INTRODUCTION:

Lung cancer (LC), among all other cancers, is the leading cause of death worldwide, while the third most common cancer-causing mortality in India. Several techniques of the assay for early detection of cancer that improve survival rates have been employed in tissues and cell lines. Reverse transcriptase quantitative polymerase chain reaction (RTqPCR) is one of the most common techniques employed for gene expression studies for the normalization of a target gene using a reference gene (RG). The present study used the three most common RGs: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), β-Actin, and 18s ribosomal ribonucleic acid (18s rRNA), which were assessed by qPCR to validate, as of which is a more effective RG in blood samples of LC patients.

MATERIALS AND METHODS:

A total of thirty participants with LC of non-small cell and small cell type were included along with twenty healthy controls. Ribonucleic acid (RNA) isolated from peripheral blood mononuclear cells was quantified, prepared for complementary deoxyribose nucleic acid synthesis, and analyzed for expression of three RG on RTqPCR.

RESULTS:

Expression levels as Ct values of studied RG were reported as mean ± standard deviation for GAPDH (26.97 ± 5.107), β-actin (20.5 ± 2.3), and 18s rRNA (25.10 ± 4.075). GAPDH showed the lowest expression, whereas β-actin showed the highest expression among the studied RG in subjects of LC. The expression of GAPDH and 18s rRNA were statistically significantly lower than β-actin (p < 0.0001), whereas expression levels of GAPDH and 18s rRNA were comparable. However, the expression level of only β-actin in LC patients was comparable with healthy controls with P < 0.1611 at 95% confidence interval.

CONCLUSION:

It is concluded that β -actin may be considered the most suitable RG isolated and studied from peripheral blood mononuclear cells using RT qPCR in LC.

Selection of endogenous control genes for normalising gene expression data derived from formalin-fixed paraffin-embedded tumour tissue

Quantitative real time polymerase chain reaction (qPCR) data are normalised using endogenous control genes. We aimed to: (1) demonstrate a pathway to identify endogenous control genes for qPCR analysis of formalin-fixed paraffin-embedded (FFPE) tissue using bladder cancer as an exemplar; and (2) examine the influence of probe length and sample age on PCR amplification and co-expression of candidate genes on apparent expression stability. RNA was extracted from prospective and retrospective samples and subject to qPCR using TaqMan human endogenous control arrays or single tube assays. Gene stability ranking was assessed using coefficient of variation (CoV), GeNorm and NormFinder. Co-expressed genes were identified from The Cancer Genome Atlas (TCGA) using the on-line gene regression analysis tool GRACE. Cycle threshold (Ct) values were lower for prospective (19.49 ± 2.53) vs retrospective (23.8 ± 3.32) tissues (p < 0.001) and shorter vs longer probes. Co-expressed genes ranked as the most stable genes in the TCGA cohort by GeNorm when analysed together but ranked lower when analysed individually omitting co-expressed genes indicating bias. Stability values were < 1.5 for the 20 candidate genes in the prospective cohort. As they consistently ranked in the top ten by CoV, GeNorm and Normfinder, UBC, RPLP0, HMBS, GUSB, and TBP are the most suitable endogenous control genes for bladder cancer qPCR.

Validation of Reference Genes for Normalization of Relative qRT-PCR Studies in Papillary Thyroid Carcinoma

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) in thyroid tumors require accurate data normalization, however, there are no sufficient studies addressing the suitable reference genes for gene expression analysis in malignant and normal thyroid tissue specimens. The purpose of this study was to identify valid internal control genes for normalization of relative qRT-PCR studies in human papillary thyroid carcinoma tissue samples. The expression characteristics of 12 candidate reference genes (GAPDH, ACTB, HPRT1, TBP, B2M, PPIA, 18SrRNA, HMBS, GUSB, PGK1, RPLP0, and PGM1) were assessed by qRT-PCR in 45 thyroid tissue samples (15 papillary thyroid carcinoma, 15 paired normal tissues and 15 multinodular goiters). These twelve candidate reference genes were selected by a systematic literature search. GeNorm, NormFinder, and BestKeeper statistical algorithms were applied to determine the most stable reference genes. The three algorithms were in agreement in identifying GUSB and HPRT1 as the most stably expressed genes in all thyroid tumors investigated. According to the NormFinder software, the pair of genes including ‘GUSB and HPRT1’ or ‘GUSB and HMBS’ or ‘GUSB and PGM1’ were the best combinations for selection of pair reference genes. The optimal number of genes required for reliable normalization of qPCR data in thyroid tissues would be three according to calculations made by GeNorm algorithm. These results suggest that GUSB and HPRT1 are promising reference genes for normalization of relative qRT-PCR studies in papillary thyroid carcinoma.

Homeobox C8 is a transcriptional repressor of E-cadherin gene expression in non-small cell lung cancer

Loss of E-cadherin expression is a hallmark of epithelial-mesenchymal transition (EMT) in tumor progression. Because previous findings suggested that homeobox C8 (HOXC8) promotes EMT in non-small-cell lung cancer (NSCLC), we investigated whether E-cadherin is a target of HOXC8 protein. In this study, we report that HOXC8 binds to the E-cadherin promoter and acts as a transcriptional repressor to regulate E-cadherin transcription in NSCLC. We further show that loss of E-cadherin leads to an increase in anchorage-independent growth and migration of NSCLC cells, and the inhibitory effects mediated by HOXC8 knockdown can be largely rescued by reduction of E-cadherin expression, suggesting that the HOXC8-E-cadherin pathway is involved in lung cancer progression. Moreover, analysis of E-cadherin and HOXC8 expression indicates that expression of HOXC8 is strongly correlated with loss of E-cadherin expression, and high HOXC8 / low E-cadherin expression is significantly correlated with poor survival for lung cancer patients. Taken together, these data indicate that E-cadherin is a target gene of HOXC8 and that the loss of E-cadherin promotes the growth and migration of NSCLC.

Conventionally used reference genes are not outstanding for normalization of gene expression in human cancer research

BACKGROUND

The selection of reference genes is essential for quantifying gene expression. Theoretically they should be expressed stably and not regulated by experimental or pathological conditions. However, identification and validation of reference genes for human cancer research are still being regarded as a critical point, because cancerous tissues often represent genetic instability and heterogeneity. Recent pan-cancer studies have demonstrated the importance of the appropriate selection of reference genes for use as internal controls for the normalization of gene expression; however, no stably expressed, consensus reference genes valid for a range of different human cancers have yet been identified.

RESULTS

In the present study, we used large-scale cancer gene expression datasets from The Cancer Genome Atlas (TCGA) database, which contains 10,028 (9,364 cancerous and 664 normal) samples from 32 different cancer types, to confirm that the expression of the most commonly used reference genes is not consistent across a range of cancer types. Furthermore, we identified 38 novel candidate reference genes for the normalization of gene expression, independent of cancer type. These genes were found to be highly expressed and highly connected to relevant gene networks, and to be enriched in transcription-translation regulation processes. The expression stability of the newly identified reference genes across 29 cancerous and matched normal tissues were validated via quantitative reverse transcription PCR (RT-qPCR).

CONCLUSIONS

We reveal that most commonly used reference genes in current cancer studies cannot be appropriate to serve as representative control genes for quantifying cancer-related gene expression levels, and propose in this study three potential reference genes (HNRNPL, PCBP1, and RER1) to be the most stably expressed across various cancerous and normal human tissues.

Prognostic significance of nuclear Yes-associated protein 1 in patients with nonsmall cell lung cancer: A systematic review and meta-analysis

BACKGROUND

Nuclear Yes-associated protein 1 (YAP1) has often been regarded as an adverse prognostic indicator in various tumors. Recent studies have associated YAP1 with unfavorable prognosis in nonsmall cell lung cancer (NSCLC). However, due to small sample sizes, the prognostic value of nuclear YAP1 in NSCLC patients is not well understood. In the present study, we evaluated the prognostic role of nuclear YAP1 in NSCLC patients via a systematic review and meta-analysis.

METHODS

We searched the PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang Databases for papers investigating the prognostic significance of nuclear YAP1 expression in NSCLC patients. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were calculated with reference to overall survival (OS) and progression-free survival (PFS) of NSCLC patients to provide synthesized estimates of the effects of nuclear YAP1 expression.

RESULTS

Among 414 cases, higher nuclear YAP1 expression presented as a predictive factor of poorer OS (HR = 1.52; 95% CI: 1.11-2.08; P = .01; I = 0.0%) and decreased PFS (HR = 2.11; 95% CI: 1.52-2.93; P < .001; I = 44.2%) in NSCLC patients. Subgroup analysis revealed shortened OS (HR = 1.63; 95% CI: 1.14-2.34; P = .007; I = 0.0%) and worse PFS (HR = 2.25; 95% CI: 1.53-3.30; P < .001; I = 0.0%) in patients from Asia with higher nuclear YAP1 expression. Prognosis was also worse in patients with III-IV stage cancer (PFSHR = 2.09; 95% CI: 1.45-3.01; P < .001; I = 58.1%) and in patients treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) (OS HR = 1.59; 95% CI: 1.00-2.51; P = .048; I = 15.5%, and PFS HR = 2.35, 95% CI: 1.62-3.42; P < .001; I = 0.0%).

CONCLUSION

High expression of nuclear YAP1 was associated with shorter survival outcome in patients with NSCLC.

Anti-tumoral activity of the human-specific duplicated form of α7-nicotinic receptor subunit in tobacco-induced lung cancer progression

OBJECTIVES

Tobacco smoking is strongly correlated with the onset and progression of non-small cell lung cancer (NSCLC). By activating α7 nicotinic acetylcholine receptors (α7-nAChRs) in these tumors nicotine and its tobacco-derived nitrosamine, NNK, contribute to these oncogenic processes. Here, we investigated whether the human-specific duplicated form of the α7-nAChR subunit (dupα7) behaves as an endogenous negative regulator of α7-nAChR-mediated tumorigenic activity induced by tobacco in NSCLC cells, similarly to its influence on other α7-nAChR-controlled functions in non-tumor cells.

METHODS

Two human NSCLC cell lines, lung adenocarcinoma (A549) and squamous cell carcinoma of the lung (SK-MES-1), both wild-type or with stable overexpression of dupα7 (A549^dupα7 or SK-MES-1^dupα7), were used to investigate in vitro anti-tumor activity of dupα7 on nicotine- or NNK-induced tumor progression. For this purpose, migration, proliferation or epithelial-mesenchymal transition (EMT) were examined. The anti-tumor effect of dupα7 on nicotine-promoted tumor growth, proliferation or angiogenesis was also assessed in vivo in an athymic mouse model implanted with A549^dupα7 or A549 xenografts.

RESULTS

Overexpression of dupα7 in both cell lines almost completely suppresses the in vitro tumor-promoting effects induced by nicotine (1 μM) or NNK (100 nM) in wild-type cells. Furthermore, in mice receiving nicotine, A549^dupα7 xenografts show: (i) a significant reduction of tumor growth, and (ii) decreased expression of cell markers for proliferation (Ki67) or angiogenesis (VEGF) compared to A549 xenografts.

CONCLUSION

Our study demonstrates, for the first time, the in vitro and in vivo anti-tumor capacity of dupα7 to block the α7-nAChR-mediated tumorigenic effects of tobacco in NSCLC, suggesting that up-regulation of dupα7 expression in these tumors could offer a potential new therapeutic target in smoking-related cancers.

Remodeling of the Candida glabrata cell wall in the gastrointestinal tract affects the gut microbiota and the immune response

The gastrointestinal (GI) microbiota acts a natural barrier to the proliferation of opportunistic pathogens. Candida glabrata is an opportunistic yeast pathogen that has adapted to colonize all segments of the human GI tract. We observed an increase in Escherichia coli, Enterococcus faecalis, and Bacteroides vulgatus populations, and a decrease in Lactobacillus johnsonii, Bacteroides thetaiotaomicron, and Bifidobacterium animalis in mice with DSS-induced colitis. This reduction was more pronounced for L. johnsonii during C. glabrata overgrowth. In addition, C. glabrata overgrowth increased mouse mortality and inflammatory parameters, and modulated the expression of intestinal receptors and signaling pathways. The C. glabrata cell wall underwent various changes during the course of C. glabrata colonization, and showed a significant increase in chitin. C. glabrata deficient in chitin synthase-3 induced fewer inflammatory parameters than the parental strain during intestinal inflammation. Oral administration of chitin attenuated the impact of colitis, and reduced the number of aerobic bacteria and C. glabrata overgrowth, while chitinase-3-like protein-1 increased. This study provides evidence that inflammation of the gut alters the microbial balance and leads to C. glabrata cell wall remodeling through an increase in chitin, which is involved in promoting persistence of C. glabrata in the gut.

Diverse gene expression patterns in response to anticancer drugs between human and mouse cell lines revealed by a comparative transcriptomic analysis

The aim of the present study was to perform comparative genomics using gene expression profile datasets of mice and humans who had been treated with anticancer drugs, to determine the similarities and differences in the antitumor mechanisms in the two mammals. This involved data mining of antitumor gene expression regulation, and screening of genetic loci from experimental mouse models of antitumor targets, to provide a theoretical basis of drug design. Subsequently, 9 overlapping genes with opposite expression patterns were identified across mouse and human cell lines that were treated with a specific cyclin-dependent kinase 4/6 inhibitor, PD0332991. These genes included LIM homeobox 2, adenomedullin, bone marrow stromal cell antigen 1, caveolin 1, histone cluster 1 (HIST1) H2B family member C, HIST1 H3 family member F, low density lipoprotein-receptor related protein 11, prolyl 4-hydroxylase subunit α1 and torsin family 3 member A. In addition, the janus kinase-signal transducer and activator of transcription signaling pathway, Toll-like receptor signaling pathway, T cell receptor signaling pathway and the nucleotide-binding oligomerization domain-like receptor signaling pathway were identified as candidate pathways for explaining antitumor mechanisms.

Expression patterns for nicotinic acetylcholine receptor subunit genes in smoking-related lung cancers

Cigarette smoking is associated with increased risk for all histologic types of lung cancer, but why the strength of this association is stronger for squamous cell carcinoma than adenocarcinoma of the lung (SQC-L, ADC-L) is not fully understood. Because nicotine and tobacco-specific nitrosamines contribute to carcinogenesis by activating nicotinic acetylcholine receptors (nAChRs) on lung tumors and epithelial cells, we investigated whether differential expression of nAChR subtypes in these tumors could explain their different association with smoking. Expression of nAChR subunit genes in paired tumor and non-tumor lung specimens from 40 SQC-L and 38 ADC-L patients was analyzed by quantitative PCR. Compared to normal lung, both tumors share: i) transcriptional dysregulation of CHRNA3/CHRNA5/CHRNB4 (α3, α5, β4 subunits) at the chromosomal locus that predisposes to lung cancer; and ii) decreased expression of CHRFAM7A (dupα7 subunit); this last subunit negatively modulates α7-nAChR activity in oocytes. In contrast, CHRNA7 (α7 subunit) expression was increased in SQC-L, particularly in smokers and non-survivors, while CHRNA4 (α4 subunit) expression was decreased in ADC-L. Thus, over-representation of cancer-stimulating α7-nAChR in SQC-L, also potentiated by smoking, and under-representation of cancer-inhibiting α4β2-nAChR in ADC-L could explain the different tobacco influences on the tumorigenic process in each cancer type.

Role of TLR1, TLR2 and TLR6 in the modulation of intestinal inflammation and Candida albicans elimination

Background

Toll-like receptors (TLRs) are the major pattern recognition receptors that mediate sensing of a wide range of microorganisms. TLR2 forms heterodimers with either TLR1 or TLR6, broadening its ligand diversity against pathogens. TLR1, TLR2 and TLR6 have been implicated in the recognition of Candida albicans, an opportunistic fungal pathogen that colonizes the gastrointestinal tract. In this study, we explored whether the deficiency in TLR1, TLR2 or TLR6 impacts C. albicans colonization and inflammation-associated colonic injury in the dextran sulfate sodium (DSS)-induced colitis in mice.

Results

DSS treatment and C. albicans challenge induced greater weight loss, worse clinical signs of inflammation, higher histopathologic scores, and increased mortality rates in TLR1^−/− and TLR2^−/− mice when compared to TLR6^−/− and wild-type mice. The number of C. albicans colonies in the stomach, colon and feces was decreased in TLR6^−/− mice as compared to TLR2^−/−, TLR1^−/− and wild-type mice. Interestingly, the population of E. coli in colonic luminal contents, intestinal permeability to FITC-dextran and cytokine expression were significantly increased in TLR1^−/− and TLR2^−/− mice, while they were decreased in TLR6^−/− mice.

Conclusion

In contrast to TLR6, both TLR1 and TLR2 deficiencies increased intestinal inflammation, and the overgrowth of C. albicans and E. coli populations in the colitis model, suggesting the involvement of TLR1 and TLR2 in epithelial homeostasis, and a role of TLR6 in increasing intestinal inflammation in response to pathogen-sensing.

Electronic supplementary material

The online version of this article (doi:10.1186/s13099-017-0158-0) contains supplementary material, which is available to authorized users.

Human basonuclin 2 up-regulates a cascade set of interferon-stimulated genes with anti-cancerous properties in a lung cancer model

BACKGROUND

Human basonuclin 2 (BNC2) acts as a tumor suppressor in multiple cancers in an as yet unidentified manner. The role and expression of the BNC2 gene in lung cancer has not yet been investigated.

METHODS

BNC2 expression was studied in the A549 and BEAS-2B cell lines, as well as in lung cancer tissue. Illumina array analysis and a viability assay were used to study the effects of transient transfection of BNC2 in A549 cells. Ingenuity pathway analysis and g:Profiler were applied to identify affected pathways and networks. RT-qPCR was used to validate the array results.

RESULTS

We showed the reduced mRNA expression of BNC2 in non-small cell lung cancer tissue and lung cancer cell line A549 compared to non-cancerous lung tissue and BEAS-2B cells, respectively. Further array analysis demonstrated that the transfection of BNC2 into A549 cells resulted in the increased expression of 139 genes and the down-regulation of 13 genes. Pathway analysis revealed that half of the up-regulated genes were from the interferon/signal transducer and activator of transcription signaling pathways. The differential expression of selected sets of genes, including interferon-stimulated and tumor suppressor genes of the XAF1 and OAS families, was confirmed by RT-qPCR. In addition, we showed that the over-expression of BNC2 inhibited the proliferation of A549 cells.

CONCLUSION

Our data suggest that human BNC2 is an activator of a subset of IFN-regulated genes and might thereby act as a tumor suppressor.

Identification of reliable reference genes for quantitative gene expression studies in oral squamous cell carcinomas compared to adjacent normal tissues in the F344 rat model

Oral squamous cell carcinomas (OSCCs) induced in F344 rats by 4-nitroquinoline-1-oxide (4-NQO) demonstrate considerable phenotypic similarity to human oral cancers and the model has been widely used for carcinogenesis and chemoprevention studies. Molecular characterization of this model needs reliable reference genes (RGs) to avoid false- positive and -negative results for proper interpretation of gene expression data between tumor and adjacent normal tissues. Microarray analysis of 11 pairs of OSCC and site-matched phenotypically normal oral tissues from 4-NQO-treated rats identified 10 stably expressed genes in OSCC compared to adjacent normal tissues (p>0.5, CV<15%) that could serve as potential RGs in this model. The commonly used 27 RGs in the rat were also analyzed based on microarray data and most of them were found unsuitable for RGs in this model. Traditional RGs such as ACTB and GAPDH were significantly altered in OSCC compared to adjacent normal tissues (p<0.01, n=11); however, the Hsp90ab1 was ranked as the best RG candidate and the combination of Hsp90ab1 and HPRT1 was identified by NormFinder to be a superior reference for gene normalization among the commonly used RGs. This result was also validated by RT-PCR based on the selected top RG candidate pool. These data suggest that there are no common RGs suitable for different models and RG(s) should be identified before gene expression analysis. We successfully identified Hsp90ab1 as a stable RG in 4-NQO-induced OSCC compared to adjacent normal tissues in F344 rats. The combination of two stably expressed genes may be a better option for gene normalization in tissue samples.

Identification of Valid Housekeeping Genes for Real-Time Quantitative PCR Analysis of Collapsed Lung Tissues of Neonatal Somatic Cell Nuclear Transfer-Derived Cattle

Cloned calves produced by somatic cell nuclear transfer frequently suffer alveolar collapse as newborns. To study the underlying pathophysiological mechanisms responsible for this phenomenon, the expression profiles of numerous genes involved in lung development need to be investigated. Quantitative real-time PCR is commonly adopted in gene expression analysis. However, selection of an appropriate reference gene for normalization is critical for obtaining reliable and accurate results. Seven housekeeping genes-β-glucuronidase (GUSB), phosphoglycerate kinase 1 (PGK1), β-2-microglobolin (B2M), peptidylprolyl isomerase A (PPIA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), TATA-box binding protein (TBP), and 5.8S ribosomal RNA (5.8S rRNA)-were selected and evaluated as candidates. Their gene expression levels in the collapsed lungs of deceased neonate cloned calves and normal lung derived from normal calves were assessed. The ranking of gene expression stability was estimated by the geNorm, NormFinder, and BestKeeper programs. 5.8S rRNA and PPIA were determined to be the most stable reference genes by geNorm and BestKeeper, whereas the combination of GAPDH and TBP was suggested as reference genes by NormFinder. Taking these results into account, we conclude that 5.8S rRNA and PPIA could be the most reliable reference genes for studying the genes involved in alveolar collapse. Moreover, 5.8S rRNA could be represented as a uniform reference gene in similar cases.

Role of mannose-binding lectin in intestinal homeostasis and fungal elimination

Mannose-binding lectin (MBL) is a soluble lectin of the innate immune system that is produced by the liver and secreted into the circulation where it activates the lectin complement pathway, enhances phagocytosis of microorganisms by leukocytes, and modulates inflammation. MBL can recognize patterns on the surface of different pathogens, including Candida albicans. Our aims were to investigate whether MBL is expressed in the gut epithelium and to examine its effect on the modulation of intestinal inflammation and C. albicans elimination. Using reverse transcriptase-PCR, MBL transcripts were highly expressed in different parts of the mouse gut. MBL expression was also detected by immunoblotting and immunolocalization in response to C. albicans colonization of the gut; the highest expression of MBL was detected in the stomach. Blocking MBL by administering mannans to mice increased C. albicans colonization. MBL-deficient mice had a higher level of colonization than wild-type mice. Dextran sodium sulfate-induced colitis promoted C. albicans dissemination to the kidneys and lungs of MBL-deficient mice. MBL-deficient mice exhibited elevated expression of interleukin (IL)-17, IL-23, dectin-1, and Toll-like receptor-4. This study shows that MBL expression is induced in the gut in response to C. albicans sensing and is required for intestinal homeostasis and host defense against C. albicans.

Consensus reference gene(s) for gene expression studies in human cancers: end of the tunnel visible?

BACKGROUND

Gene expression studies are increasingly used to provide valuable information on the diagnosis and prognosis of human cancers. Also, for in vitro and in vivo experimental cancer models gene expression studies are widely used. The complex algorithms of differential gene expression analyses require normalization of data against a reference or normalizer gene, or a set of such genes. For this purpose, mostly invariant housekeeping genes are used. Unfortunately, however, there are no consensus (housekeeping) genes that serve as reference or normalizer for different human cancers. In fact, scientists have employed a wide range of reference genes across different types of cancer for normalization of gene expression data. As a consequence, comparisons of these data and/or data harmonizations are difficult to perform and challenging. In addition, an inadequate choice for a reference gene may obscure genuine changes and/or result in erroneous gene expression data comparisons.

METHODS

In our effort to highlight the importance of selecting the most appropriate reference gene(s), we have screened the literature for gene expression studies published since the turn of the century on thirteen of the most prevalent human cancers worldwide.

CONCLUSIONS

Based on the analysis of the data at hand, we firstly recommend that in each study the suitability of candidate reference gene(s) should carefully be evaluated in order to yield reliable differential gene expression data. Secondly, we recommend that a combination of PPIA and either GAPDH, ACTB, HPRT and TBP, or appropriate combinations of two or three of these genes, should be employed in future studies, to ensure that results from different studies on different human cancers can be harmonized. This approach will ultimately increase the depth of our understanding of gene expression signatures across human cancers.

Reference genes for real-time qPCR in leukocytes from asthmatic patients before and after anti-asthma treatment

The aim of this study was to develop a set of reference genes whose expression is stable and suitable for normalization of target gene expression measured in asthma patients during anti-asthmatic treatment. Real-time qPCR was used to determine expression of 7 candidate reference genes (18S rRNA, ACTB, B2M, GAPDH, POLR2A, RPL13A and RPL32) and 7 target genes in leukocytes from asthma patients before and after treatment with inhaled corticosteroids and leukotriene receptor antagonist. Variance of Cq values was analyzed and stability ranking was determined with geNorm. We further investigated how the different normalization strategies affected the consistency of conclusions if the specific investigated target gene is down-regulated or up-regulated after anti-asthmatic therapy. The top-ranking reference genes determined by geNorm, when samples before and after therapy were analyzed (ACTB, B2M and GAPDH) were different from those (POLR2A and B2M) when only samples before treatment were analyzed. Using only a single reference gene for normalization of 7 target gene expression compared to our strategy, there would be as low as 19% of consistency in conclusions. We suggest the use of the geometric mean of ACTB, B2M and GAPDH for normalization of qPCR data of target genes in pharmacogenomics studies in asthma patients before and after anti-asthmatic therapy, however if gene expression is measured only before anti-asthmatic treatment, we recommend the use of the geometric mean of POLR2A and B2M.

Identification of suitable reference genes for gene expression studies using quantitative polymerase chain reaction in lung cancer in vitro

The present study aimed to examine 10 housekeeping genes (HKGs), including 18s ribosomal RNA (18S), glyceraldehyde‑3‑phosphate dehydrogenase (GAPDH), ribosomal protein large P0 (RPLP0), β‑actin (ACTB), peptidylprolyl isomerase A (PPIA), phosphoglycerate kinase‑1 (PGK1), β‑2‑microglobulin (B2M), ribosomal protein LI3a (RPL13A), hypoxanthine phosphoribosyl transferase‑1 (HPRT1) and TATA box binding protein (TBP) in order to identify the most stable and suitable reference genes for use in expression studies in non‑small cell lung cancer. The mRNA expression encoding the panel of the 10 HKGs was determined using reverse transcription‑quantitative PCR (RT‑qPCR) in human lung cancer cell lines. Three software programs, BestKeeper, NormFinder and geNorm, were used to ascertain the most suitable reference genes to normalize the RNA input. The present study examined three lung cancer cell lines (A549, NCI‑H446 and NCI‑H460). The analysis of the experimental data using BestKeeper software revealed that all 10 HKGs were stable, with GADPH, followed by 18S being the most stable genes and PPIA and HPRT1 being the least stable genes. The NormFinder software results demonstrated that PPIA followed by ACTB were the most stable and B2M and RPLP0 were the least stable. The geNorm software results revealed that ACTB and PGK1, followed by PPIA were the most stable genes and B2M and RPLP0 were identified as the least stable genes. Due to discrepancies in the ranking orders of the reference genes obtained by different analyzing software programs, it was not possible to determine a single universal reference gene. The suitability of selected reference genes requires unconditional validation prior to each study. Based on the three analyzing programs, ACTB, PPIA and PGK1 were the most stable reference genes in lung cancer cell lines.

Quantifying mRNA and microRNA with qPCR in cervical carcinogenesis: a validation of reference genes to ensure accurate data

A number of recent studies have catalogued global gene expression patterns in a panel of normal, tumoral cervical tissues so that potential biomarkers can be identified. The qPCR has been one of the most widely used technologies for detecting these potential biomarkers. However, few studies have investigated a correct strategy for the normalization of data in qPCR assays for cervical tissues. The aim of this study was to validate reference genes in cervical tissues to ensure accurate quantification of mRNA and miRNA levels in cervical carcinogenesis. For this purpose, some issues for obtaining reliable qPCR data were evaluated such as the following: geNorm analysis with a set of samples which meet all of the cervical tissue conditions (Normal + CIN1 + CIN2 + CIN3 + Cancer); the use of individual Ct values versus pooled Ct values; and the use of a single (or multiple) reference genes to quantify mRNA and miRNA expression levels. Two different data sets were put on the geNorm to assess the expression stability of the candidate reference genes: the first dataset comprised the quantities of the individual Ct values; and the second dataset comprised the quantities of the pooled Ct values. Moreover, in this study, all the candidate reference genes were analyzed as a single “normalizer”. The normalization strategies were assessed by measuring p16^INK4a and miR-203 transcripts in qPCR assays. We found that the use of pooled Ct values, can lead to a misinterpretation of the results, which suggests that the maintenance of inter-individual variability is a key factor in ensuring the reliability of the qPCR data. In addition, it should be stressed that a proper validation of the suitability of the reference genes is required for each experimental setting, since the indiscriminate use of a reference gene can also lead to discrepant results.

Gene expression profiling in human lung development: an abundant resource for lung adenocarcinoma prognosis

A tumor can be viewed as a special “organ” that undergoes aberrant and poorly regulated organogenesis. Progress in cancer prognosis and therapy might be facilitated by re-examining distinctive processes that operate during normal development, to elucidate the intrinsic features of cancer that are significantly obscured by its heterogeneity. The global gene expression signatures of 44 human lung tissues at four development stages from Asian descent and 69 lung adenocarcinoma (ADC) tissue samples from ethnic Chinese patients were profiled using microarrays. All of the genes were classified into 27 distinct groups based on their expression patterns (named as PTN1 to PTN27) during the developmental process. In lung ADC, genes whose expression levels decreased steadily during lung development (genes in PTN1) generally had their expression reactivated, while those with uniformly increasing expression levels (genes in PTN27) had their expression suppressed. The genes in PTN1 contain many n-gene signatures that are of prognostic value for lung ADC. The prognostic relevance of a 12-gene demonstrator for patient survival was characterized in five cohorts of healthy and ADC patients [ADC_CICAMS (n = 69, p = 0.007), ADC_PNAS (n = 125, p = 0.0063), ADC_GSE13213 (n = 117, p = 0.0027), ADC_GSE8894 (n = 62, p = 0.01), and ADC_NCI (n = 282, p = 0.045)] and in four groups of stage I patients [ADC_CICAMS (n = 22, p = 0.017), ADC_PNAS (n = 76, p = 0.018), ADC_GSE13213 (n = 79, p = 0.02), and ADC_qPCR (n = 62, p = 0.006)]. In conclusion, by comparison of gene expression profiles during human lung developmental process and lung ADC progression, we revealed that the genes with a uniformly decreasing expression pattern during lung development are of enormous prognostic value for lung ADC.

Far from resolved: stromal cell-based iTRAQ research of muscle-invasive bladder cancer regarding heterogeneity

The aim of the present study was to globally characterize the cancer stroma expression profile of muscle-invasive bladder cancer in different metastatic risk groups and to discuss the decisive role of biological pathway change in cancer heterogeneity. Laser capture microdissection was employed to harvest purified muscle-invasive bladder cancer stromal cells derived from 30 clinical samples deriving from 3 different metastatic risk groups. Isobaric tags for relative and absolute quantitation (iTRAQ) and two-dimensional liquid chromatography tandem mass spectrometry (2D LC-MS/MS) were used to identify the differentially expressed proteins. Subsequently, the differentially expressed proteins were further analyzed by bioinformatics tools. After completing the above tasks, the proteins of interest were further compared with the published litterature. We identified 1,049 differentially expressed proteins by paired comparison (high risk vs. median, low risk and normal groups; median risk vs. low risk and normal groups, low risk vs. normal group; a total of 6 comparisons). A total of 510,549,548 proteins as significantly altered (ratio fold-change≥1.5 or ≤0.667 between the metastatic potential risk group and the normal group) were presented in the low/median/high metastatic risk group, respectively. Pathway analysis revealed that the differentially expressed proteins were mainly located in the Kyoto Encyclopedia of Genes and Genomes pathways, including focal adhesion pathway, systemic lupus erythematosus pathway and ECM-receptor interaction pathway. In addition, several proteins such as EXOC4, MYH10 and MMP-9 may serve as candidate biomarkers of muscle-invasive bladder cancer. Our study confirmed that stromal cells, an important part of the cancer tissue, are pivotal for regulating the heterogeneity of cancer. Common changes in biological pathways determined the malignant phenotype of muscle-invasive bladder cancer, and biomarker discovery should take into account both neoplastic cells and their corresponding stromata.

Reduced NF1 expression confers resistance to EGFR inhibition in lung cancer

Activating mutations in the EGF receptor (EGFR) are associated with clinical responsiveness to EGFR tyrosine kinase inhibitors (TKI), such as erlotinib and gefitinib. However, resistance eventually arises, often due to a second EGFR mutation, most commonly T790M. Through a genome-wide siRNA screen in a human lung cancer cell line and analyses of murine mutant EGFR-driven lung adenocarcinomas, we found that erlotinib resistance was associated with reduced expression of neurofibromin, the RAS GTPase-activating protein encoded by the NF1 gene. Erlotinib failed to fully inhibit RAS-ERK signaling when neurofibromin levels were reduced. Treatment of neurofibromin-deficient lung cancers with a MAP-ERK kinase (MEK) inhibitor restored sensitivity to erlotinib. Low levels of NF1 expression were associated with primary and acquired resistance of lung adenocarcinomas to EGFR TKIs in patients. These findings identify a subgroup of patients with EGFR-mutant lung adenocarcinoma who might benefit from combination therapy with EGFR and MEK inhibitors.

A novel panel of biomarkers predicts radioresistance in patients with squamous cell carcinoma of the head and neck

PURPOSE

Global gene expression analysis was performed on pre-treatment biopsies from patients with squamous cell carcinoma of the head and neck (SCCHN) to discover biomarkers that can predict outcome of radiation based therapy.

METHODS

We initially evaluated RNA expression using cDNA microarray analysis of 38 patients that received radiotherapy (RT). The five strongest candidates (VEGF, BCL-2, CLAUDIN-4, YAP-1 and c-MET) were then analysed in pre-treatment biopsies in a second group of 86 patients who received radiation based treatment using immunohistochemical staining (IHC), prepared by tissue microarray.

RESULTS

In the first population, 13 of 38 (34%) had no (NR) or partial response (PR) to RT. cDNA microarrays revealed 60 genes that were linked to response to therapy. In the second series, 12 of 86 patients (14%) experienced NR or PR to CRT. Cause specific survival (CSS) and recurrence free survival (RFS) at 2 years was 85% and 90% and at 3 years 81% and 84%, respectively. Biomarkers predictive for NR/PR were increased expression of vascular endothelial growth factor (VEGF) (p=0.02), Yes-associated protein (YAP-1) (p<0.01), CLAUDIN-4 (p<0.01), c-MET (p<0.01) and BCL-2 (p=0.02). Biomarkers predictive of poor RFS were YAP-1 (p=0.01) and BCL-2 (p<0.01). Biomarkers predictive of poor CSS were YAP-1 (p=0.04), VEGF (p=0.03) and CLAUDIN-4 (p=0.03). Furthermore, when YAP-1 and c-MET expression levels were combined the prediction of radio-resistance was increased.

CONCLUSION

All five biomarkers were predictive of poor response to radiation based therapy. In particular, YAP-1 and c-MET have synergistic power and could be used to make treatment decisions.

ACTB in cancer

Beta-actin (ACTB) has traditionally been regarded as an endogenous housekeeping gene and has been widely used as a reference gene/protein in quantifying expression levels in tumors. However, ACTB is closely associated with a variety of cancers and accumulating evidence indicates that ACTB is de-regulated in liver, melanoma, renal, colorectal, gastric, pancreatic, esophageal, lung, breast, prostate, ovarian cancers, leukemia and lymphoma. ACTB is generally found to be up-regulated in the majority of tumor cells and tissues. The abnormal expression and polymerization of ACTB and the resulting changes to the cytoskeleton are revealed to be associated with the invasiveness and metastasis of cancers. The current review explores relevant mechanisms, integrates current understandings, and provides suggestions for future studies of the roles of ACTB in tumors.

Atypical protein kinase C phosphorylates Par6 and facilitates transforming growth factor β-induced epithelial-to-mesenchymal transition

Epithelial-to-mesenchymal transition (EMT) is controlled by cellular signaling pathways that trigger the loss of cell-cell adhesion and lead to the restructuring of the cell cytoskeleton. Transforming growth factor β (TGF-β) has been shown to regulate cell plasticity through the phosphorylation of Par6 on a conserved serine residue (S345) by the type II TGF-β receptor. We show here that atypical protein kinase C (aPKC) is an essential component to this signaling pathway in non-small-cell lung cancer (NSCLC) cells. We show that the aPKC, PKCι, interacts with TGF-β receptors through Par6 and that these proteins localize to the leading edge of migrating cells. Furthermore, Par6 phosphorylation on serine 345 by TGF-β receptors is enhanced in the presence of aPKC. aPKC kinase activity, as well as an association with Par6, were found to be important for Par6 phosphorylation. In effect, small interfering RNA-targeting aPKC reduces TGF-β-induced RhoA and E-cadherin loss, cell morphology changes, stress fiber production, and the migration of NSCLC cells. Interestingly, reintroduction of a phosphomimetic Par6 (Par6-S345E) into aPKC-silenced cells rescues both RhoA and E-cadherin loss with TGF-β stimulation. In conclusion, our results suggest that aPKCs cooperate with TGF-β receptors to regulate phospho-Par6-dependent EMT and cell migration.

Xenobiotic metabolism and disposition in human lung cell models: comparison with in vivo expression profiles

Numerous lung cell lines are currently used as in vitro models for pharmacological and toxicological studies. However, no exhaustive report about the metabolic capacities of these models in comparison with those of lung tissues is available. In the present study, we used a high-throughput quantitative real-time reverse transcription-polymerase chain reaction strategy to characterize the expression profiles of 380 genes encoding proteins involved in the metabolism and disposition of xenobiotics in 10 commonly used lung cell lines (A549, H292, H358, H460, H727, Calu-1, 16HBE, 1 HAEO, BEAS-2B, and L-132) and four primary cultures of human bronchial epithelial cells. Expression results were then compared with those previously obtained in human nontumoral and tumoral lung tissues. Our results revealed disparities in gene expression between lung cell lines or when comparing lung cell lines with primary cells or lung tissues. Primary cell cultures displayed the highest similarities with bronchial mucosa in terms of transcript profiling and therefore seem to be the most relevant in vitro model for investigating the metabolism and bioactivation of toxicants and drugs in bronchial epithelium. H292 and BEAS-2B cell lines, which exhibited the highest homology in gene expression pattern with primary cells and the lowest number of dysregulated genes compared with nontumoral lung tissues, could be used as surrogates for toxicological and pharmacological studies. Overall, our study should provide references for researchers to choose the most appropriate in vitro model for analyzing the cellular effects of drugs or airborne toxicants on the airway.

Comprehensive literature review and statistical considerations for microarray meta-analysis

With the rapid advances of various high-throughput technologies, generation of ‘-omics’ data is commonplace in almost every biomedical field. Effective data management and analytical approaches are essential to fully decipher the biological knowledge contained in the tremendous amount of experimental data. Meta-analysis, a set of statistical tools for combining multiple studies of a related hypothesis, has become popular in genomic research. Here, we perform a systematic search from PubMed and manual collection to obtain 620 genomic meta-analysis papers, of which 333 microarray meta-analysis papers are summarized as the basis of this paper and the other 249 GWAS meta-analysis papers are discussed in the next companion paper. The review in the present paper focuses on various biological purposes of microarray meta-analysis, databases and software and related statistical procedures. Statistical considerations of such an analysis are further scrutinized and illustrated by a case study. Finally, several open questions are listed and discussed.

Signal Peptidase Complex Subunit 1 and Hydroxyacyl-CoA Dehydrogenase Beta Subunit Are Suitable Reference Genes in Human Lungs

Lung cancer is a common cancer, and expression profiling can provide an accurate indication to advance the medical intervention. However, this requires the availability of stably expressed genes as reference. Recent studies had shown that genes that are stably expressed in a tissue may not be stably expressed in other tissues suggesting the need to identify stably expressed genes in each tissue for use as reference genes. DNA microarray analysis has been used to identify those reference genes with low fluctuation. Fourteen datasets with different lung conditions were employed in our study. Coefficient of variance, followed by NormFinder, was used to identify stably expressed genes. Our results showed that classical reference genes such as GAPDH and HPRT1 were highly variable; thus, they are unsuitable as reference genes. Signal peptidase complex subunit 1 (SPCS1) and hydroxyacyl-CoA dehydrogenase beta subunit (HADHB), which are involved in fundamental biochemical processes, demonstrated high expression stability suggesting their suitability in human lung cell profiling.

Sec62 bridges the gap from 3q amplification to molecular cell biology in non-small cell lung cancer

The molecular carcinogenesis of lung cancer has yet to be clearly elucidated. We investigated the possible oncogenic function of SEC62 in lung cancer, which was predicted based on our previous findings that lung and thyroid cancer tissue samples exhibited increased Sec62 protein levels. The SEC62 gene locus is at 3q26.2, and 3q amplification is reportedly the most common genomic alteration in non-small cell lung cancer. We analyzed SEC62 mRNA and protein levels in tissue samples from lung cancer patients by real-time quantitative PCR, Western blot, and IHC and found significantly increased SEC62 mRNA and protein levels in tumors compared with tumor-free tissue samples from the same patients. Correlation analyses revealed significantly higher Sec62 levels in tumors with lymph node metastases compared with nonmetastatic tumors, as well as in poorly compared with moderately differentiated tumors. On the basis of these promising results, we examined the role of Sec62 in cancer cell biology in vitro. Cell migration assays with lung and thyroid cancer cells showed distinct stimulation of migration in SEC62-overexpressing cells and inhibition of migration in Sec62-depleted cells. Moreover, we found that SEC62 silencing sensitized the cells to thapsigargin-induced endoplasmic reticulum stress. Thus, our results indicate that SEC62 represents a potential candidate oncogene in the amplified 3q region in cases of non-small cell lung cancer and harbors various functions in cancer cell biology.

Mll5 is required for normal spermatogenesis

Background

Mll5 is currently a member of the Mll family of SET domain histone methyltransferase proteins but studies have also showed that it could be part of the SET3 branch of proteins. Recently, constitutive knock out animal studies have shown that Mll5 is required for proper haematopoietic stem cell differentiation, and loss of Mll5 results in synthetic lethality for genome de-methylation. Mll5 deficient male mice are infertile and here we analyse the consequences of Mll5 deficiency for spermatogenesis.

Methodology/Principal Findings

Mll5 deficient male mice, but not female mice, are infertile. Here we show using RNA in-situ hybridization that Mll5 is expressed in the germ cells of the testes of wild type mice. Consistent with the expression of Mll5, we demonstrate by electron microscopy, video microscopy and in vitro fertilisation techniques that Mll5 deficient mice have defects in terminal maturation and packaging of sperm. The defects seen include detachment of the acrosomal cap and impaired excess cytoplasm removal. Functional tests of sperm motility show a lack of progressive motility of spermatozoa from Mll5 deficient animals. None of these defects could be rescued by in vitro fertilization. Using microarray analysis we show that transcripts implicated in spermatogenesis are dysregulated.

Conclusions/Significance

Our data demonstrate a clear role of Mll5 in mammalian spermatogenesis at the level of terminal differentiation providing further support for its classification in the SET3 branch of proteins. Moreover, this study identifies Tlk2, Utx, Gpr64, Sult4a1, Rap2ip, Vstm2 and HoxA10 as possible Mll5 targets that together may account for the observed spermatozoa maturation defects.