Confirmation of gene expression-based prediction of survival in non-small cell lung cancer

Functionalized graphene oxide NPs as a nanocarrier for drug delivery system in quercetin/ lurbinectedin as dual sensitive therapeutics for A549 lung cancer treatment

Functionalized graphene oxide nanoparticles (NPs) have emerged as promising nanocarriers for drug delivery in lung cancer therapy. Quercetin and lurbinectedin encapsulated in graphene oxide (GO) NPs are tested for treating A549 lung cancer cells. Spectroscopic analyses show that graphene oxide functionalization creates a transparent, smooth surface for drug loading. Treatment with quercetin/lurbinectedin-loaded GO NPs induces notable cytotoxic effects in lung cancer cells, as evidenced by distinct morphological alterations and confirmed apoptotic cellular death observed through fluorescence microscopy. Additionally, our study highlights the impact of this approach on lung cancer metastasis, supported by qRT-PCR analysis of relative gene expression levels, including p53, Bax, Caspase-3, and Bcl 2, revealing robust molecular mechanisms underlying therapeutic efficacy against A549 and PC9 cell lines. Flow cytometric analyses further confirm the induction of cellular death in lung cancer cells following administration of the nanoformulation. Our findings show that quercetin/lurbinectedin-loaded GO NPs may be a promising lung cancer treatment, opening new avenues for targeted and effective therapies.

PSMD3-ILF3 signaling cascade drives lung cancer cell proliferation and migration

BACKGROUND

Proteasome 26S subunit, non-ATPase 3 (PSMD3) has been reported to participate in various human cancers. Nevertheless, the function of PSMD3 in lung cancer (LC) remains unclear.

METHODS

RT-qPCR and western blot were used to detect the expression of PSMD3 in LC tissues form TCGA database and clinical samples, and LC cell lines. To study the effect of PSMD3 on LC cell proliferation, migration, invasion, and apoptosis, siRNAs targeting PSMD3 were synthesized and overexpressed plasmids were constructed. CCK-8 assay, Transwell assay, and etc. were used to evaluate the results. Tumor xenograft model was used to evaluate the function of PSMD3 on tumor growth. CO-IP and MS were used to scan the proteins that bind with PSMD3. The interaction between PSMD3 and ILF3 in lung cancer cells were studied using IF staining, CHX protein stability, and ubiquitination assay. Additionally, the effect of ILF3 on cell progression and LC tumor growth was demonstrated by conducting a recovery assay using siILF3 and an ILF3 inhibitor YM155.

RESULTS

We observed that PSMD3 was significantly overexpressed in LC tissues and cells, which indicated a poor prognosis. Meanwhile, we found that PSMD3 promoted cell proliferation, migration, and invasion of LC cells. We also determined that PSMD3 stabilized the protein expression of ILF3 and the deubiquitination of ILF3 in lung cancer cells. Furthermore, animal experiments showed that the ILF3 inhibitor YM155 could suppress tumor growth with the presence of PSMD3.

CONCLUSIONS

PSMD3 collectively regulated the stability of ILF3 protein and facilitated the ubiquitination of endogenous ILF3 in LC, which ultimately promoted the progression of LC cells. The PSMD3/ ILF3 axis could potentially be used as a novel strategy for both diagnosis and treatment of LC.

Prognostic and immunotherapeutic predictive value of interleukin enhancer-binding factor 3 in hepatocellular carcinoma: Integrated bioinformatics and experimental analysis

Interleukin enhancer-binding factor 3 (ILF3) as an RNA-binding protein that plays a critical role in the process of cancer and antiviral responses. However, no researcher has focused on the pan-cancer analysis of ILF3, and the effect of ILF3 on tumor immunity is still largely unclear. This study synthetically analyzed the relationship between the expression of ILF3 across various cancers and prognosis, microsatellite instability (MSI), tumor mutational burden (TMB), tumor immune cell infiltration, and common immune checkpoint molecules by multiple bioinformatics databases. Experimentally, we detected the mRNA abundance of ILF3 and immune checkpoint molecules in liver hepatocellular carcinoma (LIHC) tissues. The functions of ILF3 on hepatocellular carcinoma (HCC) cells were verified by western blot assay and cytotoxicity assay. We found that ILF3 was aberrantly expressed and associated with the prognosis in several types of tumors. The ILF3 expression was significantly correlated with infiltrating levels of immune cells and immune molecules in certain cancers, particularly in LIHC. Detection of clinical liver cancer tissues confirmed the positive correlation between ILF3 and immune checkpoint molecules, including programmed cell death 1 (PD-1), programmed cell death ligand 1 (PD-L1), cytotoxic T lymphocyte-associated antigen 4 (CTLA4), lymphocyte-activation gene 3 (LAG3), and T cell immunoglobulin domain and mucin domain-3 (TIM3). Furthermore, reduced PD-L1 and increased sensitivity of HCC cells to T cells cytotoxicity were found in ILF3-knockdown cells. This work suggested ILF3 may be used as a prognostic marker for various tumors to predict the response to immunotherapy.

LncRNA LINC00649 promotes the growth and metastasis of triple-negative breast cancer by maintaining the stability of HIF-1α through the NF90/NF45 complex

There is no clear treatment guideline or individualized treatment plan for triple-negative breast cancer (TNBC). The aim of this study was to investigate more effective targets for TNBC-targeted therapy. MDA-MB-231 and BT549 cell lines were used to explore the function of LINC00649 on the proliferation, invasion, and migration of TNBC cells. A mice subcutaneous tumor model and a pulmonary metastasis model was established to identify the role of LINC00649 on the growth and metastasis of TNBC in vivo. LINC00649 was found to be a key molecule involved in the occurrence and development of TNBC by screening of public databases and detection of TNBC clinical samples. LINC00649 increased hypoxia-inducible factor 1α (HIF-1α) mRNA stability and protein expression by interacting with the nuclear factor 90 (NF90)/NF45 complex. In vitro, interference with LINC00649 inhibits MDA-MB-231 and BT549 cell proliferation, migration, and invasion, and the addition of HIF-1α revised this effect. In vivo experiments showed that LINC00649 promoted the growth and metastasis of TNBC. We demonstrated that LINC00649 interacts with the NF90/NF45 complex to increase the mRNA stability of HIF-1α and up-regulate HIF-1α expression, thereby inducing the proliferation, invasion, and migration of TNBC cells as well as tumor growth and metastasis.

Molecular Radiobiology in Non-Small Cell Lung Cancer: Prognostic and Predictive Response Factors

Simple Summary

The identification of prognostic and predictive gene signatures of response to cancer treatment (radiotherapy) could help in making therapeutic decisions in patients affected by NSCLC. There are multiple proposals for gene signatures that attempt to predict survival or predict response to treatment (not radiotherapy), but they mainly focus on early stages or metastasis at diagnosis. In contrast, there have been few studies that raise these predictive and/or prognostic elements in nonmetastatic locally advanced stages, where treatment with ionizing radiation plays an important role. In this work, we review in depth previous works discovering the prognostic and predictive response factors in non-small cell lung cancer, specially focused on non-deeply studied radiation-based therapy.

Abstract

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide, generating huge economic and social impacts that have not slowed in recent years. Oncological treatment for this neoplasm usually includes surgery, chemotherapy, treatments on molecular targets and ionizing radiation. The prognosis in terms of overall survival (OS) and the different therapeutic responses between patients can be explained, to a large extent, by the existence of widely heterogeneous molecular profiles. The identification of prognostic and predictive gene signatures of response to cancer treatment, could help in making therapeutic decisions in patients affected by NSCLC. Given the published scientific evidence, we believe that the search for prognostic and/or predictive gene signatures of response to radiotherapy treatment can significantly help clinical decision-making. These signatures may condition the fractions, the total dose to be administered and/or the combination of systemic treatments in conjunction with radiation. The ultimate goal is to achieve better clinical results, minimizing the adverse effects associated with current cancer therapies.

A Six-Gene Prognostic and Predictive Radiotherapy-Based Signature for Early and Locally Advanced Stages in Non-Small-Cell Lung Cancer

Simple Summary

The search for prognostic and/or predictive gene signatures of the response to radiotherapy treatment can significantly aid clinical decision making. These signatures can condition the fractionation, the total dose to be administered, and/or the combination of systemic treatments and radiation. The ultimate goal is to achieve better clinical results, as well as to minimize the adverse effects associated with current cancer therapies. To this end, we analyzed the intrinsic radiosensitivity of 15 NSCLC lines and found the differences in gene expression levels between radiosensitive and radioresistant lines, resulting in a potentially applicable six-gene signature in NSCLC patients. The six-gene signature had the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received.

Abstract

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death worldwide, generating an enormous economic and social impact that has not stopped growing in recent years. Cancer treatment for this neoplasm usually includes surgery, chemotherapy, molecular targeted treatments, and ionizing radiation. The prognosis in terms of overall survival (OS) and the disparate therapeutic responses among patients can be explained, to a great extent, by the existence of widely heterogeneous molecular profiles. The main objective of this study was to identify prognostic and predictive gene signatures of response to cancer treatment involving radiotherapy, which could help in making therapeutic decisions in patients with NSCLC. To achieve this, we took as a reference the differential gene expression pattern among commercial cell lines, differentiated by their response profile to ionizing radiation (radiosensitive versus radioresistant lines), and extrapolated these results to a cohort of 107 patients with NSCLC who had received radiotherapy (among other therapies). We obtained a six-gene signature (APOBEC3B, GOLM1, FAM117A, KCNQ1OT1, PCDHB2, and USP43) with the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received. Patients who had an unfavorable prognostic signature had a median OS of 24.13 months versus 71.47 months for those with a favorable signature, and the median PFS was 12.65 months versus 47.11 months, respectively. We also carried out a univariate analysis of multiple clinical and pathological variables and a bivariate analysis by Cox regression without any factors that substantially modified the HR value of the proposed gene signature.

TRIM29 regulates the SETBP1/SET/PP2A axis via transcription factor VEZF1 to promote progression of ovarian cancer

Ovarian cancer (OC) is a common gynecological malignant tumor that seriously endangers the health of women worldwide. Tripartite motif containing 29 (TRIM29) is a TRIM family member that is frequently overexpressed in OC. However, the specific role of TRIM29 in OC remains obscure. To investigate the underlying molecular mechanism, a global proteomics analysis identified SET binding protein 1 (SETBP1) as a crucial target of TRIM29. Subsequently, the SETBP1/SET/Protein phosphatase 2 (PP2A) axis was confirmed to be required for the recovery of cancer stem cell (CSC)-like phenotype suppressed by TRIM29 knockdown. Mechanistically, TRIM29 facilitated SETBP1 transcriptional activation via the VEZF1 transcription factor. More importantly, TRIM29 promoted VEZF1 mRNA translation by recruiting RNA binding protein BICC1 to its 3'UTR. The clinical significance was established by the association of TRIM29 and SETBP1 expression with clinicopathological features in OC samples. The SETBP1/SET/PP2A axis driven by TRIM29 via transcription factor VEZF1 is at least one of the primary mechanisms underlying TRIM29 maintenance of the CSC-like characteristics in OC.

Long non-coding RNA SNHG1 suppresses cell migration and invasion and upregulates SOCS2 in human gastric carcinoma

Gastric carcinoma (GC) is one of the most common malignancies and the third leading cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) may be an important class of functional regulators involved in human gastric cancers development. In this study, we investigated the clinical significance and function of lncRNA SNHG1 in GC. SNHG1 was significantly downregulated in GC tumor tissues compared with adjacent noncancerous tissues. Overexpression of SNHG1 in BGC-823 cells remarkably inhibited not only cell proliferation, migration, invasion in vitro, but also tumorigenesis and lung metastasis in the chick embryo chorioallantoic membrane (CAM) assay in vivo. Conversely, inhibition of SNHG1 by transfection of siRNA in AGS cells resulted in opposite phenotype changes. Mechanically, SNHG1 was found interacted with ILF3, NONO and SFPQ. RNA-seq combined with bioinformatic analysis identified a serial of downstream genes of SNHG1, including SOCS2, LOXL2, LTBP3, LTBP4. Overexpression of SNHG1 induced SOCS2 expression whereas knockdown of SNHG1 decreased SOCS2 expression. In addition, knockdown of SNHG1 promoted the activation of JAK2/STAT signaling pathway. Taken together, our data suggested that SNHG1 suppressed aggressive phenotype of GC cells and regulated SOCS2/JAK2/STAT pathway.

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SNHG1 was significantly downregulated in GC tumor tissues.

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SNHG1 suppressed proliferation and migration of GC cells.

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SNHG1 localized in nucleus of GC cells and interacted with ILF3, NONO and SFPQ.

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SNHG1 regulate SOCS2 expression in GC cell lines and JAK2/STAT signaling pathway in AGS cells.

Combining gene expression signature with clinical features for survival stratification of gastric cancer

The AJCC staging system is considered as the golden standard in clinical practice. However, it remains some pitfalls in assessing the prognosis of gastric cancer (GC) patients with similar clinicopathological characteristics. We aim to develop a new clinic and genetic risk score (CGRS) to improve the prognosis prediction of GC patients. We established genetic risk score (GRS) based on nine-gene signature including APOD, CCDC92, CYS1, GSDME, ST8SIA5, STARD3NL, TIMEM245, TSPYL5, and VAT1 based on the gene expression profiles of the training set from the Asian Cancer Research Group (ACRG) cohort by LASSO-Cox regression algorithms. CGRS was established by integrating GRS with clinical risk score (CRS) derived from Surveillance, Epidemiology, and End Results (SEER) database. GRS and CGRS dichotomized GC patients into high and low risk groups with significantly different prognosis in four independent cohorts with different data types, such as microarray, RNA sequencing and qRT-PCR (all HR > 1, all P < 0.001). Both GRS and CGRS were prognostic signatures independent of the AJCC staging system. Receiver operating characteristic (ROC) analysis showed that area under ROC curve of CGRS was larger than that of the AJCC staging system in most cohorts we studied. Nomogram and web tool (http://39.100.117.92/CGRS/) based on CGRS were developed for clinicians to conveniently assess GC prognosis in clinical practice. CGRS integrating genetic signature with clinical features shows strong robustness in predicting GC prognosis, and can be easily applied in clinical practice through the web application.

Identification of gene signatures and potential therapeutic targets for acquired chemotherapy resistance in gastric cancer patients

BACKGROUND

Gastric cancer (GC) is the most common type of gastrointestinal cancer, and has been studied extensively. However, resistance to chemotherapeutic agents has become a major problem, leading to treatment failure. This study aimed to investigate the molecular mechanisms mediating acquired resistance to cisplatin and fluorouracil (CF) combination-based chemotherapy in GC patients.

METHODS

The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor. Possible targets of the DEMs were predicted using miRWalk, and the putative miRNA-mRNA regulatory network was constructed using Cytoscape software. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses were then conducted and visualized using the Search Tool for Retrieval of Interacting Genes (STRING) and Cytoscape. The prognostic value of hub genes was revealed by Kaplan-Meier Plotter. The causal relationships and interactions between proteins were displayed using DisNor. Finally, similarity analysis was conducted using the Connectivity Map (CMap) profiles to predict a group of small molecules in GC treatment.

RESULTS

A total of 394 DEGs and 31 DEMs were identified after analysis of pre- and post-treatment samples of clinical responders to CF therapy. TM9SF4, hsa-miR-185-5p, and hsa-miR-145-5p were found to be critical in the miRNA-mRNA regulatory network. The DEGs were found to be mainly enriched in the processes of ribonucleoprotein complex assembly, catalytic activity acting on RNA, mitochondrial matrix, and thermogenesis. The DEMs were predominantly found to be involved in single-stranded RNA binding and endoplasmic reticulum lumen. HDAC5, DDX17, ILF3, and SDHC were identified as hub genes in the PPI network. Of these, HDAC5, DDX17, and ILF3 were found to be closely related to the overall survival of GC patients. DisNor identified the first neighbors of the key genes. Furthermore, CMap profiles predicted a group of small molecules, including several histone deacetylase inhibitors (HDACIs), menadione, and mibefradil, which could serve as promising therapeutic agents to reverse acquired resistance to CF therapy.

CONCLUSIONS

Our findings reveal new targets and alternative therapies to overcome the acquired resistance of GC patients to CF treatment.

TRIM29 mediates lung squamous cell carcinoma cell metastasis by regulating autophagic degradation of E-cadherin

Lung squamous cell carcinoma (LSCC) is the most common histological type of primary lung cancer. In this study, we had tested the biological role of TRIM29 in LSCC cells. TRIM29 abundance, the relationships between TRIM29 and E-cadherin and autophagy degradation related proteins in clinical tissues and six cell lines were studied with quantitative real-time PCR test (qRT-PCR) and western blot. TRIM29 overexpression treated HTB-182 cells and knockdown treated NCL-H1915 cells was used for studying cell proliferation, colony formation, migration, invasion, and the expression of epithelial mesenchymal transformation (EMT) associated biomarkers. The relationships between TRIM29 and BECN1 were investigated with western blot. TRIM29 was profoundly overexpressed in LSCC tissues and cells compared with human normal bronchial epithelial cells (HNBE). High TRIM29 expression was closely related to overall survival (OS). TRIM29 overexpression and knockdown affected LSCC activity and the expression of EMT associated biomarkers. TRIM29 can regulate the degradation of E-cadherin and autophagy of LSCC through BECN1 gene, and promote autophagy in HTB-182 and NCL-H1915 cells. Our results revealed that TRIM29 could promote the proliferation, migration, and invasion of LSCC via E-cadherin autophagy degradation. The results are useful for further study in LSCC.

A Shallow Convolutional Neural Network Predicts Prognosis of Lung Cancer Patients in Multi-Institutional CT-Image Data

Lung cancer is the most common fatal malignancy in adults worldwide, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography (CT) is routinely used in clinical practice to determine lung cancer treatment and assess prognosis. Here, we developed LungNet, a shallow convolutional neural network for predicting outcomes of NSCLC patients. We trained and evaluated LungNet on four independent cohorts of NSCLC patients from four medical centers: Stanford Hospital (n = 129), H. Lee Moffitt Cancer Center and Research Institute (n = 185), MAASTRO Clinic (n = 311) and Charité - Universitätsmedizin (n=84). We show that outcomes from LungNet are predictive of overall survival in all four independent survival cohorts as measured by concordance indices of 0.62, 0.62, 0.62 and 0.58 on cohorts 1, 2, 3, and 4, respectively. Further, the survival model can be used, via transfer learning, for classifying benign vs malignant nodules on the Lung Image Database Consortium (n = 1010), with improved performance (AUC=0.85) versus training from scratch (AUC=0.82). LungNet can be used as a noninvasive predictor for prognosis in NSCLC patients and can facilitate interpretation of CT images for lung cancer stratification and prognostication.

High expression of interleukin-enhancer binding factor 3 predicts poor prognosis in patients with lung adenocarcinoma

Interleukin-enhancer binding factor 3 (ILF3) is a double-stranded RNA-binding protein that has been reported to contribute to the occurrence and progression of various malignant tumors. The aim of the present study was to evaluate the prognostic value of ILF3 and to apply this knowledge to avoid excessive medical treatment in patients with lung adenocarcinoma (LUAD). ILF3 expression in a discovery set consisting of tumor and peri-tumor tissue microarrays was analyzed using immunohistochemical methods. The mRNA level of ILF3 was subsequently analyzed in a validation set downloaded from The Cancer Genome Atlas. The Kaplan-Meier method, univariate and multivariate Cox analyses, decision curve analysis and nomogram models were used to evaluate the prognostic value of ILF3. ILF3 expression was upregulated in tumor tissues compared with peri-tumor tissues and was negatively associated with the overall survival time of patients with LUAD in the discovery and validation sets. Moreover, ILF3 expression was used for risk stratification in patients with tumor-node-metastasis stages II-IV and poor-to-moderate tumor differentiation. ILF3 expression was identified as an independent predictor of adverse prognosis for patients with LUAD in the discovery and validation sets. Finally, nomogram models for the 3- and 5 year survival time of patients with LUAD revealed that ILF3 expression may be used to improve the predictive accuracy of the prognosis and to avoid excessive medical treatment for certain patients with the disease. Overall, the data obtained in the current study revealed that high ILF3 expression was associated with poor prognosis, and demonstrated that ILF3, as a potential independent risk factor, may improve the hierarchical postoperative management of patients with LUAD.

CaPSSA: visual evaluation of cancer biomarker genes for patient stratification and survival analysis using mutation and expression data

Summary

Predictive biomarkers for patient stratification play critical roles in realizing the paradigm of precision medicine. Molecular characteristics such as somatic mutations and expression signatures represent the primary source of putative biomarker genes for patient stratification. However, evaluation of such candidate biomarkers is still cumbersome and requires multistep procedures especially when using massive public omics data. Here, we present an interactive web application that divides patients from large cohorts (e.g. The Cancer Genome Atlas, TCGA) dynamically into two groups according to the mutation, copy number variation or gene expression of query genes. It further supports users to examine the prognostic value of resulting patient groups based on survival analysis and their association with the clinical features as well as the previously annotated molecular subtypes, facilitated with a rich and interactive visualization. Importantly, we also support custom omics data with clinical information.

Availability and implementation

CaPSSA (Cancer Patient Stratification and Survival Analysis) runs on a web-browser and is freely available without restrictions at http://www.kobic.re.kr/capssa/. The source code is available on https://github.com/yjjang/capssa.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Blockwise Consistency Method for Parameter Estimation of Complex Models

The drastic improvement in data collection and acquisition technologies has enabled scientists to collect a great amount of data. With the growing dataset size, typically comes a growing complexity of data structures and of complex models to account for the data structures. How to estimate the parameters of complex models has put a great challenge on current statistical methods. This paper proposes a blockwise consistency approach as a potential solution to the problem, which works by iteratively finding consistent estimates for each block of parameters conditional on the current estimates of the parameters in other blocks. The blockwise consistency approach decomposes the high-dimensional parameter estimation problem into a series of lower-dimensional parameter estimation problems, which often have much simpler structures than the original problem and thus can be easily solved. Moreover, under the framework provided by the blockwise consistency approach, a variety of methods, such as Bayesian and frequentist methods, can be jointly used to achieve a consistent estimator for the original high-dimensional complex model. The blockwise consistency approach is illustrated using two high-dimensional problems, variable selection and multivariate regression. The results of both problems show that the blockwise consistency approach can provide drastic improvements over the existing methods. Extension of the blockwise consistency approach to many other complex models is straightforward.

A negative feedback loop between nuclear factor 90 (NF90) and an anti-oncogenic microRNA, miR-7

Alterations in microRNAs (miRNAs) levels deeply correlate with tumorigenesis. However, the molecular mechanism for the regulation of the miRNA production in tumors is not fully understood. We previously reported that downregulation of miR-7, which is an anti-oncogenic miRNA, was caused by overexpression of the nuclear factor 90 (NF90)-nuclear factor 45 (NF45) complex through the binding of double-stranded (ds) RNA-binding proteins to primary miR-7, resulting in promotion of tumorigenesis (Higuchi et al 2016). During this study, we found that the level of NF90 protein was dramatically decreased by overexpression of miR-7. Interestingly, the miR-7-mediated reduction in NF90 family proteins was only observed in NF90 protein, but not in NF110 protein, which is a longer form of the NF90 gene. Luciferase reporter analysis indicated that the overexpression of miR-7 significantly repressed the luciferase activity in the coding region of NF90 mRNA harboring a predicted target sequence of miR-7. The luciferase activity of the reporter vector, which has a mutated miR-7 target site in the coding region, was the same in the control and miR-7 overexpressed cells. Furthermore, the translation of TARGET-tagged NF90 mRNA without the 3'UTR of the NF90 mRNA was inhibited by the overexpression of miR-7. These results imply that miR-7 suppresses NF90 at the protein level through the binding of miR-7 to the complementary site of the seed sequence in the coding region of the NF90 mRNA. We further confirmed increased endogenous NF90 protein levels in SK-N-SH cells transfected with antisense oligonucleotides targeting miR-7, indicating that miR-7-mediated translational repression of NF90 is a physiological event. Taken together with our previous findings (Higuchi et al 2016), it suggests that the level of NF90 is increased by a negative feedback loop between NF90 and miR-7 in tumor tissues under physiological conditions.

A Predictive 7-Gene Assay and Prognostic Protein Biomarkers for Non-small Cell Lung Cancer

PURPOSE

This study aims to develop a multi-gene assay predictive of the clinical benefits of chemotherapy in non-small cell lung cancer (NSCLC) patients, and substantiate their protein expression as potential therapeutic targets.

PATIENTS AND METHODS

The mRNA expression of 160 genes identified from microarray was analyzed in qRT-PCR assays of independent 337 snap-frozen NSCLC tumors to develop a predictive signature. A clinical trial JBR.10 was included in the validation. Hazard ratio was used to select genes, and decision-trees were used to construct the predictive model. Protein expression was quantified with AQUA in 500 FFPE NSCLC samples.

RESULTS

A 7-gene signature was identified from training cohort (n = 83) with accurate patient stratification (P = 0.0043) and was validated in independent patient cohorts (n = 248, P < 0.0001) in Kaplan-Meier analyses. In the predicted benefit group, there was a significantly better disease-specific survival in patients receiving adjuvant chemotherapy in both training (P = 0.035) and validation (P = 0.0049) sets. In the predicted non-benefit group, there was no survival benefit in patients receiving chemotherapy in either set. The protein expression of ZNF71 quantified with AQUA scores produced robust patient stratification in separate training (P = 0.021) and validation (P = 0.047) NSCLC cohorts. The protein expression of CD27 quantified with ELISA had a strong correlation with its mRNA expression in NSCLC tumors (Spearman coefficient = 0.494, P < 0.0088). Multiple signature genes had concordant DNA copy number variation, mRNA and protein expression in NSCLC progression.

CONCLUSIONS

This study presents a predictive multi-gene assay and prognostic protein biomarkers clinically applicable for improving NSCLC treatment, with important implications in lung cancer chemotherapy and immunotherapy.

Nuclear factor 90 promotes angiogenesis by regulating HIF-1α/VEGF-A expression through the PI3K/Akt signaling pathway in human cervical cancer

Vascular endothelial growth factor A (VEGF-A), a fundamental component of angiogenesis, provides nutrients and oxygen to solid tumors, and enhances tumor cell survival, invasion, and migration. Nuclear factor 90 (NF90), a double-stranded RNA-binding protein, is strongly expressed in several human cancers, promotes tumor growth by reducing apoptosis, and increasing cell cycle process. The mechanisms by which cervical cancer cells inducing VEGF-A expression and angiogenesis upon NF90 upregulation remain to be fully established. We demonstrated that NF90 is upregulated in human cervical cancer specimens and the expression of NF90 is paralleled with that of VEGF-A under hypoxia. The expressions of hypoxia inducible factor-1α (HIF-1α) and VEGF-A are downregulated upon NF90 knockdown, which can be rescued by ectopic expression of NF90. Suppression of NF90 decreases the tube formation and cell migration of HUVECs. Moreover, the PI3K/Akt signaling pathway participates in the regulation. Knockdown of NF90 also reduces the tumor growth and angiogenesis of cervical cancer cell line in the mouse xenograft model. Taken together, suppression of NF90 in cervical cancer cell lines can decrease VEGF-A expression, inhibit angiogenesis, and reduce tumorigenic capacity in vivo.

Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non-Small Cell Lung Cancer

Importance

The prevalence of early-stage non-small cell lung cancer (NSCLC) is expected to increase with recent implementation of annual screening programs. Reliable prognostic biomarkers are needed to identify patients at a high risk for recurrence to guide adjuvant therapy.

Objective

To develop a robust, individualized immune signature that can estimate prognosis in patients with early-stage nonsquamous NSCLC.

Design, Setting, and Participants

This retrospective study analyzed the gene expression profiles of frozen tumor tissue samples from 19 public NSCLC cohorts, including 18 microarray data sets and 1 RNA-Seq data set for The Cancer Genome Atlas (TCGA) lung adenocarcinoma cohort. Only patients with nonsquamous NSCLC with clinical annotation were included. Samples were from 2414 patients with nonsquamous NSCLC, divided into a meta-training cohort (729 patients), meta-testing cohort (716 patients), and 3 independent validation cohorts (439, 323, and 207 patients). All patients underwent surgery with a negative surgical margin, received no adjuvant or neoadjuvant therapy, and had publicly available gene expression data and survival information. Data were collected from July 22 through September 8, 2016.

Main Outcomes and Measures

Overall survival.

Results

Of 2414 patients (1205 men [50%], 1111 women [46%], and 98 of unknown sex [4%]; median age [range], 64 [15-90] years), a prognostic immune signature of 25 gene pairs consisting of 40 unique genes was constructed using the meta-training data set. In the meta-testing and validation cohorts, the immune signature significantly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I, IA, IB, or II disease and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.72 [95% CI, 1.26-2.33; P < .001] to 2.36 [95% CI, 1.47-3.79; P < .001]) after adjusting for clinical and pathologic factors. Several biological processes, including chemotaxis, were enriched among genes in the immune signature. The percentage of neutrophil infiltration (5.6% vs 1.8%) and necrosis (4.6% vs 1.5%) was significantly higher in the high-risk immune group compared with the low-risk groups in TCGA data set (P < .003). The immune signature achieved a higher accuracy (mean concordance index [C-index], 0.64) than 2 commercialized multigene signatures (mean C-index, 0.53 and 0.61) for estimation of survival in comparable validation cohorts. When integrated with clinical characteristics such as age and stage, the composite clinical and immune signature showed improved prognostic accuracy in all validation data sets relative to molecular signatures alone (mean C-index, 0.70 vs 0.63) and another commercialized clinical-molecular signature (mean C-index, 0.68 vs 0.65).

Conclusions and Relevance

The proposed clinical-immune signature is a promising biomarker for estimating overall survival in nonsquamous NSCLC, including early-stage disease. Prospective studies are needed to test the clinical utility of the biomarker in individualized management of nonsquamous NSCLC.

Interleukin enhancer-binding factor 3 and HOXC8 co-activate cadherin 11 transcription to promote breast cancer cells proliferation and migration

Cadherin 11 (CDH11) expression is detected only in invasive breast cancer cells and aggressive breast cancer specimens. However, little is known about the molecular mechanisms of CDH11 transcriptional regulation. Here, we report that interleukin enhancer binding factor 3 (ILF3) interacts with Homeobox C8 (HOXC8) to activate CDH11 transcription in breast cancer cells. Using co-immunoprecipitation and mass spectrometry analyses, ILF3 is shown to interact with HOXC8 in breast cancer cells. We demonstrate that ILF3 binds to the CDH11 promoter on nucleotides –2982 ~ –2978 and –2602 ~ 2598 and interacts with HOXC8 to co-activate CDH11 transcription. We further show that ILF3 promotes proliferation and migration, at least partially, by facilitating CDH11 expression in breast cancer cells. Moreover, immunohistochemistry (IHC) shows that expression of CDH11, ILF3 and HOXC8 are all upregulated in breast cancer specimens compared to normal breast tissues. Importantly, the expression levels of CDH11, ILF3 and HOXC8 are elevated in the advanced stages of breast cancer, and high expression of CDH11, ILF3 and HOXC8 is associated with poor distant metastasis-free survival (DMFS) for breast cancer patients.

Identification of early-stage lung adenocarcinoma prognostic signatures based on statistical modeling

BACKGROUND

Current staging methods are lack of precision in predicting prognosis of early-stage lung adenocarcinomas.

OBJECTIVE

We aimed to develop a gene expression signature to identify high- and low-risk groups of patients.

METHODS

We used the Bayesian Model Averaging algorithm to analyze the DNA microarray data from 442 lung adenocarcinoma patients from three independent cohorts, one of which was used for training.

RESULTS

The patients were assigned to either high- or low-risk groups based on the calculated risk scores based on the identified 25-gene signature. The prognostic power was evaluated using Kaplan-Meier analysis and the log-rank test. The testing sets were divided into two distinct groups with log-rank test p-values of 0.00601 and 0.0274 respectively.

CONCLUSIONS

Our results show that the prognostic models could successfully predict patients' outcome and serve as biomarkers for early-stage lung adenocarcinoma overall survival analysis.

Nanoscale hybrid systems based on carbon nanotubes for biological sensing and control

This paper provides a concise review on the recent development of nanoscale hybrid systems based on carbon nanotubes (CNTs) for biological sensing and control. CNT-based hybrid systems have been intensively studied for versatile applications of biological interfaces such as sensing, cell therapy and tissue regeneration. Recent advances in nanobiotechnology not only enable the fabrication of highly sensitive biosensors at nanoscale but also allow the applications in the controls of cell growth and differentiation. This review describes the fabrication methods of such CNT-based hybrid systems and their applications in biosensing and cell controls.

High Energy Particle Radiation-associated Oncogenic Transformation in Normal Mice: Insight into the Connection between Activation of Oncotargets and Oncogene Addiction

Concerns on high-energy particle radiation-induced tumorigenic transformation of normal tissue in astronauts, and in cancer patients undergoing radiotherapy, emphasizes the significance of elucidating the mechanisms involved in radiogenic transformation processes. Mostly used genetically modified or tumor-prone models are less reliable in determining human health risk in space or protracted post-treatment normal tissue toxicity. Here, in wild type C57BL/6 mice, we related the deregulation of distinctive set of tissue-specific oncotargets in major organs upon ⁵⁶Fe (600 MeV/amu; 0.5 Gy/min; 0.8 Gy) particle radiation and compared the response with low LET γ-radiation (¹³⁷Cs; 0.5 Gy/min; 2 Gy). One of the novel findings is the ‘tissue-independent’ activation of TAL2 upon high-energy radiation, and thus qualifies TAL2 as a potential biomarker for particle and other qualities of radiation. Heightened expression of TAL2 gene transcript, which sustained over four weeks post-irradiation foster the concept of oncogene addiction signaling in radiogenic transformation. The positive/negative expression of other selected oncotargets that expresses tissue-dependent manner indicated their role as a secondary driving force that addresses the diversity of tissue-dependent characteristics of tumorigenesis. This study, while reporting novel findings on radiogenic transformation of normal tissue when exposed to particle radiation, it also provides a platform for further investigation into different radiation quality, LET and dose/dose rate effect in healthy organs.

From Proteomic Analysis to Potential Therapeutic Targets: Functional Profile of Two Lung Cancer Cell Lines, A549 and SW900, Widely Studied in Pre-Clinical Research

Lung cancer is a serious health problem and the leading cause of cancer death worldwide. The standard use of cell lines as in vitro pre-clinical models to study the molecular mechanisms that drive tumorigenesis and access drug sensitivity/effectiveness is of undisputable importance. Label-free mass spectrometry and bioinformatics were employed to study the proteomic profiles of two representative lung cancer cell lines and to unravel the specific biological processes. Adenocarcinoma A549 cells were enriched in proteins related to cellular respiration, ubiquitination, apoptosis and response to drug/hypoxia/oxidative stress. In turn, squamous carcinoma SW900 cells were enriched in proteins related to translation, apoptosis, response to inorganic/organic substances and cytoskeleton organization. Several proteins with differential expression were related to cancer transformation, tumor resistance, proliferation, migration, invasion and metastasis. Combined analysis of proteome and interactome data highlighted key proteins and suggested that adenocarcinoma might be more prone to PI3K/Akt/mTOR and topoisomerase IIα inhibitors, and squamous carcinoma to Ck2 inhibitors. Moreover, ILF3 overexpression in adenocarcinoma, and PCNA and NEDD8 in squamous carcinoma shows them as promising candidates for therapeutic purposes. This study highlights the functional proteomic differences of two main subtypes of lung cancer models and hints several targeted therapies that might assist in this type of cancer.

MiR-590-5p inhibits colorectal cancer angiogenesis and metastasis by regulating nuclear factor 90/vascular endothelial growth factor A axis

Altered expression of microRNA-590-5p (miR-590-5p) is involved in tumorigenesis, however, its role in colorectal cancer (CRC) remains to be determined. In this study, we focused on examining the effects of different expression levels of miR-590-5p in cancer cells and normal cells. Results showed that there are lower expression levels of miR-590-5p in human CRC cells and tissues than in normal control cells and tissues. Similarly, in our xenograft mouse model, knockdown of miR-590-5p promoted the progression of CRC. However, an overexpression of miR-590-5p in the mice inhibited angiogenesis, tumor growth, and lung metastasis. Nuclear factor 90 (NF90), a positive regulator of vascular endothelial growth factor (VEGF) mRNA stability and protein synthesis, was shown to be a direct target of miR-590-5p. The overexpression of NF90 restored VEGFA expression and rescued the loss of tumor angiogenesis caused by miR-590-5p. Conversely, the NF90-shRNA attenuated the increased tumor progression caused by the miR-590-5p inhibitor. Clinically, the levels of miR-590-5p were inversely correlated with those of NF90 and VEGFA in CRC tissues. Furthermore, knockdown of NF90 lead to a reduction of pri-miR-590 and an increase of mature miR-590-5p, suggesting a negative feedback loop between miR-590-5p and NF90. Collectively, these data establish miR-590-5p as an anti-onco-miR that inhibits CRC angiogenesis and metastasis through a new mechanism involving NF90/VEGFA signaling axis, highlighting the potential of miR-590-5p as a target for human CRC therapy.

Suppression of MicroRNA-7 (miR-7) Biogenesis by Nuclear Factor 90-Nuclear Factor 45 Complex (NF90-NF45) Controls Cell Proliferation in Hepatocellular Carcinoma

MicroRNA-7 (miR-7)has been characterized as an anti-oncogenic microRNA (miRNA) in several cancers, including hepatocellular carcinoma (HCC). However, the mechanism for the regulation of miR-7 production in tumors remains unclear. Here, we identified nuclear factor 90 (NF90) and NF45 complex (NF90-NF45) as negative regulators of miR-7 processing in HCC. Expression of NF90 and NF45 was significantly elevated in primary HCC tissues compared with adjacent non-tumor tissues. To examine which miRNAs are controlled by NF90-NF45, we performed an miRNA microarray and quantitative RT-PCR analyses of HCC cell lines. Depletion of NF90 resulted in elevated levels of mature miR-7, whereas the expression of primary miR-7-1 (pri-miR-7-1) was decreased in cells following knockdown of NF90. Conversely, the levels of mature miR-7 were reduced in cells overexpressing NF90 and NF45, although pri-miR-7-1 was accumulated in the same cells. Furthermore, NF90-NF45 was found to bind pri-miR-7-1 in vitro These results suggest that NF90-NF45 inhibits the pri-miR-7-1 processing step through the binding of NF90-NF45 to pri-miR-7-1. We also found that levels of the EGF receptor, an oncogenic factor that is a direct target of miR-7, and phosphorylation of AKT were significantly decreased in HCC cell lines depleted of NF90 or NF45. Of note, knockdown of NF90 or NF45 caused a reduction in the proliferation rate of HCC cells. Taken together, NF90-NF45 stimulates an elevation of EGF receptor levels via the suppression of miR-7 biogenesis, resulting in the promotion of cell proliferation in HCC.

Novel interactions between the HTLV antisense proteins HBZ and APH-2 and the NFAR protein family: Implications for the HTLV lifecycles

The human T-cell leukaemia virus type 1 and type 2 (HTLV-1/HTLV-2) antisense proteins HBZ and APH-2 play key roles in the HTLV lifecycles and persistence in the host. Nuclear Factors Associated with double-stranded RNA (NFAR) proteins NF90/110 function in the lifecycles of several viruses and participate in host innate immunity against infection and oncogenesis. Using GST pulldown and co-immunoprecipitation assays we demonstrate specific novel interactions between HBZ/APH-2 and NF90/110 and characterised the protein domains involved. Moreover we show that NF90/110 significantly enhance Tax mediated LTR activation, an effect that was abolished by HBZ but enhanced by APH-2. Additionally we found that HBZ and APH-2 modulate the promoter activity of survivin and are capable of antagonising NF110-mediated survivin activation. Thus interactions between HTLV antisense proteins and the NFAR protein family have an overall positive impact on HTLV infection. Hence NFARs may represent potential therapeutic targets in HTLV infected cells.

Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables.

METHODS

Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided.

RESULTS

The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK.

CONCLUSION

The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification.

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Overexpression of NF90-NF45 Represses Myogenic MicroRNA Biogenesis, Resulting in Development of Skeletal Muscle Atrophy and Centronuclear Muscle Fibers

MicroRNAs (miRNAs) are involved in the progression and suppression of various diseases through translational inhibition of target mRNAs. Therefore, the alteration of miRNA biogenesis induces several diseases. The nuclear factor 90 (NF90)-NF45 complex is known as a negative regulator in miRNA biogenesis. Here, we showed that NF90-NF45 double-transgenic (dbTg) mice develop skeletal muscle atrophy and centronuclear muscle fibers in adulthood. Subsequently, we found that the levels of myogenic miRNAs, including miRNA 133a (miR-133a), which promote muscle maturation, were significantly decreased in the skeletal muscle of NF90-NF45 dbTg mice compared with those in wild-type mice. However, levels of primary transcripts of the miRNAs (pri-miRNAs) were clearly elevated in NF90-NF45 dbTg mice. This result indicated that the NF90-NF45 complex suppressed miRNA production through inhibition of pri-miRNA processing. This finding was supported by the fact that processing of pri-miRNA 133a-1 (pri-miR-133a-1) was inhibited via binding of NF90-NF45 to the pri-miRNA. Finally, the level of dynamin 2, a causative gene of centronuclear myopathy and concomitantly a target of miR-133a, was elevated in the skeletal muscle of NF90-NF45 dbTg mice. Taken together, we conclude that the NF90-NF45 complex induces centronuclear myopathy through increased dynamin 2 expression by an NF90-NF45-induced reduction of miR-133a expression in vivo.

Apolipoprotein C1 (APOC1) as a novel diagnostic and prognostic biomarker for lung cancer: A marker phase I trial

BACKGROUND

Tumor cells continuously evolve over time in response to host pressures. However, explanations as to how tumor cells are influenced by the inflammatory tumor microenvironment over time are, to date, poorly defined. We hypothesized that prognostic biomarkers could be obtained by exploring the expression of inflammation-associated genes between early and late stage lung cancer tumor samples.

METHODS

Candidate inflammation-associated genes, apolipoprotein C-1 (APOC1), MMP1, KMO)1, CXCL5, CXCL)7, IL-1α, IL-1β, TNF-α and IL-6 were verified by real-time quantitative polymerase chain reaction. Gene expression profiles and immunofluorescence staining of 30 lung cancer tissues were compared.

RESULTS

Expressions of APOC1 and IL-6 mRNA on tumor tissues in late stage disease were significantly higher than in early stage lung cancer samples. Immunofluorescence staining of tumor samples showed that the expression of APOC1 gradually increased from early to late stage in lung cancer patients. The expression levels of IL-6 and APOC1 in tumor samples were positively correlated; however, no prognostic value of APOC1 can be identified in serum samples.

CONCLUSIONS

We found that the level of tumor APOC1 was highly expressed in late stage lung cancer. Further research is warranted to determine the molecular mechanisms underlying the cross talk of APOC1 and IL-6 in tumor progression. An expanded sample size marker phase II study may lead to the discovery of new lung cancer therapeutics targeting APOC1.

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis

Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

The structure, function and evolution of proteins that bind DNA and RNA

Proteins that bind both DNA and RNA typify the ability of a single gene product to perform multiple functions. Such DNA- and RNA-binding proteins (DRBPs) have unique functional characteristics that stem from their specific structural features; these developed early in evolution and are widely conserved. Proteins that bind RNA have typically been considered as functionally distinct from proteins that bind DNA and studied independently. This practice is becoming outdated, in partly owing to the discovery of long non-coding RNAs (lncRNAs) that target DNA-binding proteins. Consequently, DRBPs were found to regulate many cellular processes, including transcription, translation, gene silencing, microRNA biogenesis and telomere maintenance.

The expression of four genes as a prognostic classifier for stage I lung adenocarcinoma in 12 independent cohorts

BACKGROUND

We previously developed a prognostic classifier using the expression levels of BRCA1, HIF1A, DLC1, and XPO1 that identified stage I lung adenocarcinoma patients with a high risk of relapse. That study evaluated patients in five independent cohorts from various regions of the world. In an attempt to further validate the classifier, we have used a meta-analysis-based approach to study 12 cohorts consisting of 1,069 tumor-node-metastasis stage I lung adenocarcinoma patients from every suitable, publically available dataset.

METHODS

Cohorts were obtained through a systematic search of public gene expression datasets. These data were used to calculate the risk score using the previously published 4-gene risk model. A fixed effect meta-analysis model was used to generate a pooled estimate for all cohorts.

RESULTS

The classifier was associated with prognosis in 10 of the 12 cohorts (P < 0.05). This association was highly consistent regardless of the ethnic diversity or microarray platform. The pooled estimate demonstrated that patients classified as high risk had worse overall survival for all stage I [HR, 2.66; 95% confidence interval (CI), 1.93-3.67; P < 0.0001] patients and in stratified analyses of stage IA (HR, 2.69; 95% CI, 1.66-4.35; P < 0.0001) and stage IB (HR, 2.69; 95% CI, 1.74-4.16; P < 0.0001) patients.

CONCLUSIONS

The 4-gene classifier provides independent prognostic stratification of stage IA and stage IB patients beyond conventional clinical factors.

IMPACT

Our results suggest that the 4-gene classifier may assist clinicians in decisions about the postoperative management of early-stage lung adenocarcinoma patients.

Novel image markers for non-small cell lung cancer classification and survival prediction

Background

Non-small cell lung cancer (NSCLC), the most common type of lung cancer, is one of serious diseases causing death for both men and women. Computer-aided diagnosis and survival prediction of NSCLC, is of great importance in providing assistance to diagnosis and personalize therapy planning for lung cancer patients.

Results

In this paper we have proposed an integrated framework for NSCLC computer-aided diagnosis and survival analysis using novel image markers. The entire biomedical imaging informatics framework consists of cell detection, segmentation, classification, discovery of image markers, and survival analysis. A robust seed detection-guided cell segmentation algorithm is proposed to accurately segment each individual cell in digital images. Based on cell segmentation results, a set of extensive cellular morphological features are extracted using efficient feature descriptors. Next, eight different classification techniques that can handle high-dimensional data have been evaluated and then compared for computer-aided diagnosis. The results show that the random forest and adaboost offer the best classification performance for NSCLC. Finally, a Cox proportional hazards model is fitted by component-wise likelihood based boosting. Significant image markers have been discovered using the bootstrap analysis and the survival prediction performance of the model is also evaluated.

Conclusions

The proposed model have been applied to a lung cancer dataset that contains 122 cases with complete clinical information. The classification performance exhibits high correlations between the discovered image markers and the subtypes of NSCLC. The survival analysis demonstrates strong prediction power of the statistical model built from the discovered image markers.

Colorectal cancer derived organotypic spheroids maintain essential tissue characteristics but adapt their metabolism in culture

BACKGROUND

Organotypic tumor spheroids, a 3D in vitro model derived from patient tumor material, preserve tissue heterogeneity and retain structural tissue elements, thus replicating the in vivo tumor more closely than commonly used 2D and 3D cell line models. Such structures harbour tumorigenic cells, as revealed by xenograft implantation studies in animal models and maintain the genetic makeup of the original tumor material. The aim of our work was a morphological and proteomic characterization of organotypic spheroids derived from colorectal cancer tissue in order to get insight into their composition and associated biology.

RESULTS

Morphological analysis showed that spheroids were of about 250 μm in size and varied in structure, while the spheroid cells differed in shape and size and were tightly packed together by desmosomes and tight junctions. Our proteomic data revealed significant alterations in protein expression in organotypic tumor spheroids cultured as primary explants compared to primary colorectal cancer tissue. Components underlying cellular and tissue architecture were changed; nuclear DNA/ chromatin maintenance systems were up-regulated, whereas various mitochondrial components were down-regulated in spheroids. Most interestingly, the mesenchymal cells appear to be substantial component in such cellular assemblies. Thus the observed changes may partly occur in this cellular compartment. Finally, in the proteomics analysis stem cell-like characteristics were observed within the spheroid cellular assembly, reflected by accumulation of Alcam, Ctnnb1, Aldh1, Gpx2, and CD166. These findings were underlined by IHC analysis of Ctnnb1, CD24 and CD44, therefore warranting closer investigation of the tumorigenic compartment in this 3D culture model for tumor tissue.

CONCLUSIONS

Our analysis of organotypic CRC tumor spheroids has identified biological processes associated with a mixture of cell types and states, including protein markers for mesenchymal and stem-like cells. This 3D tumor model in which tumor heterogeneity is preserved may represent an advantageous model system to investigate novel therapeutic approaches.

Combining COPD with clinical, pathological and demographic information refines prognosis and treatment response prediction of non-small cell lung cancer

Background

Accurate assessment of a patient’s risk of recurrence and treatment response is an important prerequisite of personalized therapy in lung cancer. This study extends a previously described non-small cell lung cancer prognostic model by the addition of chemotherapy and co-morbidities through the use of linked SEER-Medicare data.

Methodology/Principal Findings

Data on 34,203 lung adenocarcinoma and 26,967 squamous cell lung carcinoma patients were used to determine the contribution of Chronic Obstructive Pulmonary Disease (COPD) to prognostication in 30 treatment combinations. A Cox model including COPD was estimated on 1,000 bootstrap samples, with the resulting model assessed on ROC, Brier Score, Harrell’s C, and Nagelkerke’s R² metrics in order to evaluate improvements in prognostication over a model without COPD. The addition of COPD to the model incorporating cancer stage, age, gender, race, and tumor grade was shown to improve prognostication in multiple patient groups. For lung adenocarcinoma patients, there was an improvement on the prognostication in the overall patient population and in patients without receiving chemotherapy, including those receiving surgery only. For squamous cell carcinoma, an improvement on prognostication was seen in both the overall patient population and in patients receiving multiple types of chemotherapy. COPD condition was able to stratify patients receiving the same treatments into significantly (log-rank p<0.05) different prognostic groups, independent of cancer stage.

Conclusion/Significance

Combining patient information on COPD, cancer stage, age, gender, race, and tumor grade could improve prognostication and prediction of treatment response in individual non-small cell lung cancer patients. This model enables refined prognosis and estimation of clinical outcome of comprehensive treatment regimens, providing a useful tool for personalized clinical decision-making.

Tal2 expression is induced by all-trans retinoic acid in P19 cells prior to acquisition of neural fate

TAL2 is a member of the basic helix-loop-helix family and is essential for the normal development of the mouse brain. However, the function of TAL2 during brain development is unclear. P19 cells are pluripotent mouse embryonal carcinoma cells that adopt neural fates upon exposure to all-trans retinoic acid (atRA) and culture in suspension. We found that the expression of Tal2 gene was induced in P19 cells after addition of atRA in suspension culture. Tal2 expression was detected within 3 h after the induction, and had nearly returned to basal levels by 24 h. When GFP-tagged TAL2 (GFP-TAL2) was expressed in P19 cells, we observed GFP-TAL2 in the nucleus. Moreover, we showed that atRA and retinoic acid receptor α regulated Tal2 expression. These results demonstrate for the first time that atRA induces Tal2 expression in P19 cells, and suggest that TAL2 commits to the acquisition of neural fate in brain development.

Is there clinical value to prognostic signatures in early-stage NSCLC?

pAMPK and pmTOR favorably predicted outcome in early non-small cell lung cancer (NSCLC). The differences were small. Phosphoprotein lability makes routine clinical use and validation difficult. Protein immunohistochemistry is unlikely to be clinically useful, and numerous efforts to create predictive models to select resected patients for therapy have been unsuccessful.

Prognostic value of microRNA expression in operable non-small cell lung cancer patients

Background:

About 50% of non-small cell lung cancer (NSCLC) patients develop distant metastases following pulmonary resection. Currently, there are no reliable factors allowing for individual selection of high-risk patients for adjuvant systemic therapies.

Methods:

We assessed by quantitative reverse transcription PCR microRNA (miRNA) expression in 273 stage I–IIIA NSCLC samples. Expression of 677 miRNAs was evaluated in fresh-frozen tumour samples in the training cohort of 50 squamous cell carcinoma (SCC) patients who underwent curative surgery. Of those, 20 patients developed distant metastases, and 30 were free of recurrence for >4 years. In the second step, miRNAs with highest predictive value for distant relapse were re-evaluated in formalin-fixed paraffin-embedded material in an independent group of 134 stage I–IIIA SCC patients. Additionally, the same miRNAs were investigated in 89 lung adenocarcinoma (AC) patients and in normal lung parenchyma (NLP).

Results:

In the training cohort of SCC, six miRNAs were differently expressed in the non-recurrent vs recurrent groups and correlated with distant recurrence-free survival, however none reached the level of significance after correction for multiple testing. Of these six miRNAs, miR-662, -192 and -192* were confirmed as prognostic in the independent SCC cohort. Expression of miR-128, -10b, -502-3p and -192 differed between SCC and AC, and miR-128 and -192 – between NLP and NSCLC.

Conclusions:

We identified three new miRNAs predictive of distant relapse in operable SCC. Future miRNA studies should account for differences between NSCLC subtypes.

Lung Cancer Gene Signatures and Clinical Perspectives

Microarrays have been used for more than two decades in preclinical research. The tumor transcriptional profiles were analyzed to select cancer-associated genes for in-deep functional characterization, to stratify tumor subgroups according to the histopathology or diverse clinical courses, and to assess biological and cellular functions behind these gene sets. In lung cancer-the main type of cancer causing mortality worldwide-biomarker research focuses on different objectives: the early diagnosis of curable tumor diseases, the stratification of patients with prognostic unfavorable operable tumors to assess the need for further therapy regimens, or the selection of patients for the most efficient therapies at early and late stages. In non-small cell lung cancer, gene and miRNA signatures are valuable to differentiate between the two main subtypes' squamous and non-squamous tumors, a discrimination which has further implications for therapeutic schemes. Further subclassification within adenocarcinoma and squamous cell carcinoma has been done to correlate histopathological phenotype with disease outcome. Those tumor subgroups were assigned by diverse transcriptional patterns including potential biomarkers and therapy targets for future diagnostic and clinical applications. In lung cancer, none of these signatures have entered clinical routine for testing so far. In this review, the status quo of lung cancer gene signatures in preclinical and clinical research will be presented in the context of future clinical perspectives.

Forfeited hepatogenesis program and increased embryonic stem cell traits in young hepatocellular carcinoma (HCC) comparing to elderly HCC

Background

Hepatocellular carcinoma (HCC) in young subjects is rare but more devastating. We hypothesize that genes and etiological pathways are unique to young HCC (yHCC; ≤40 years old at diagnosis) patients. We therefore compared the gene expression profiles between yHCCs and HCCs from elderly patients.

Results

All 44 young HCCs (≤40 years old at the diagnosis; 23 cases in the training set while another 21 in the validation cohort) were positive for serum hepatitis B surface antigen (HBsAg), but negative for antibodies to hepatitis C virus (anti-HCV). All 48 elderly (>40 years old; 38 in the training set while another 10 in the validation cohort) HCC patients enrolled were also serum HBsAg positive and anti-HCV negative. Comparative genomics analysis was further performed for elucidating enriched or suppressed biological activities in different HCC subtypes.

The yHCC group showed more macroscopic venous invasions (60.9% vs. 10.5%, p < 0.001), fewer associated cirrhosis (17.4% vs. 63.2%, p < 0.001), and distinct profiles of expressed genes, especially those related to DNA replication and repair. yHCCs possessed increased embryonic stem cell (ESC) traits and were more dedifferentiated. A 309-gene signature was obtained from two training cohorts and validated in another independent data set. The ILF3 ESC gene, which was previously reported in poorly differentiated breast cancers and bladder carcinomas, was also present in yHCCs. Genes associated with HCC suppression, including AR and ADRA1A, were less abundant in yHCCs. ESC genes were also more enriched in advanced HCCs from elderly patients.

Conclusion

This study revealed the molecular makeup of yHCC and the link between ESC traits and HCC subtypes. Findings in elderly tumors, therefore, cannot be simply extrapolated to young patients, and yHCC should be treated differently.

The T-cell oncogene Tal2 Is a Target of PU.1 and upregulated during osteoclastogenesis

Transcription factors play a crucial role in regulating differentiation processes during human life and are important in disease. The basic helix-loop-helix transcription factors Tal1 and Lyl1 play a major role in the regulation of gene expression in the hematopoietic system and are involved in human leukemia. Tal2, which belongs to the same family of transcription factors as Tal1 and Lyl1, is also involved in human leukaemia. However, little is known regarding the expression and regulation of Tal2 in hematopoietic cells. Here we show that Tal2 is expressed in hematopoietic cells of the myeloid lineage. Interestingly, we found that usage of the Tal2 promoter is different in human and mouse cells. Two promoters, hP1 and hP2 drive Tal2 expression in human erythroleukemia K562 cells, however in mouse RAW cells only the mP1 promoter is used. Furthermore, we found that Tal2 expression is upregulated during oesteoclastogenesis. We show that Tal2 is a direct target gene of the myeloid transcription factor PU.1, which is a key transcription factor for osteoclast gene expression. Strikingly, PU.1 binding to the P1 promoter is conserved between mouse and human, but PU.1 binding to P2 was only detected in human K562 cells. Additionally, we provide evidence that Tal2 influences the expression of the osteoclastic differentiation gene TRACP. These findings provide novel insight into the expression control of Tal2 in hematopoietic cells and reveal a function of Tal2 as a regulator of gene expression during osteoclast differentiation.

NF90 in posttranscriptional gene regulation and microRNA biogenesis

Gene expression patterns are effectively regulated by turnover and translation regulatory (TTR) RNA-binding proteins (RBPs). The TTR-RBPs control gene expression at posttranscriptional levels, such as pre-mRNA splicing, mRNA cytoplasmic export, turnover, storage, and translation. Double-stranded RNA binding proteins (DSRBPs) are known to regulate many processes of cellular metabolism, including transcriptional control, translational control, mRNA processing and localization. Nuclear factor 90 (NF90), one of the DSRBPs, is abundantly expressed in vertebrate tissue and participates in many aspects of RNA metabolism. NF90 was originally purified as a component of a DNA binding complex which binds to the antigen recognition response element 2 in the interleukin 2 promoter. Recent studies have provided us with interesting insights into its possible physiological roles in RNA metabolism, including transcription, degradation, and translation. In addition, it was shown that NF90 regulates microRNA expression. In this review, we try to focus on the function of NF90 in posttranscriptional gene regulation and microRNA biogenesis.