Networking of differentially expressed genes in human cancer cells resistant to methotrexate

Citrus flavonoids for overcoming breast cancer resistance to methotrexate: identification of potential targets of nobiletin and sinensetin

Breast cancer is a potentially fatal illness that affects millions of women worldwide. Methotrexate (MTX) may be beneficial for treating breast cancer; however, high doses and prolonged use can cause drug resistance. Although certain citrus flavonoids-nobiletin, sinensetin, tangeretin, hesperidin, hesperetin, and naringenin-may overcome resistance to chemotherapy, no study has investigated MTX resistance. This study investigated the potential of natural chemicals, specifically nobiletin and sinensetin, to overcome MTX resistance in breast cancer cells using MTX-resistant MCF-7 (MCF-7/MTX) and MCF-7 cells. Protein targets of citrus flavonoids were identified from multiple databases and were collected using Venny 2.1. Microarray data of MCF-7 and MCF-7/MTX cells were acquired from the Gene Expression Omnibus. Subsequently, we constructed a protein-protein interaction network and selected the hub proteins. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, drug- and disease-gene enrichment analyses, genetic alteration examination, receiver operating characteristic curve analysis, mRNA levels analysis, prognostic value analysis, and molecular docking analysis were performed along with in vitro experiments. Cytotoxicity of citrus flavonoids (individually and combined) was assessed in MCF-7/MTX cells. Nobiletin and sinensetin significantly enhanced the cytotoxicity of MTX in MCF-7/MTX cells. BCL2L1, CDK1, EGFR, PTGS2, PLK1, MMP2, ACHE, ABCG2, and KIT genes were enriched in cholinesterase activity, cell cycle regulation, and the PI3K/Akt signaling pathway. Nobiletin and sinensetin impeded PLK1, CDK1, and ACHE activities based on molecular docking. Nobiletin and sinensetin in combination with MTX may overcome breast cancer cell resistance to MTX.

The eEF1A protein in cancer: Clinical significance, oncogenic mechanisms, and targeted therapeutic strategies

Eukaryotic elongation factor 1A (eEF1A) is among the most abundant proteins in eukaryotic cells. Evolutionarily conserved across species, eEF1A is in charge of translation elongation for protein biosynthesis as well as a plethora of non-translational moonlighting functions for cellular homeostasis. In malignant cells, however, eEF1A becomes a pleiotropic driver of cancer progression via a broad diversity of pathways, which are not limited to hyperactive translational output. In the past decades, mounting studies have demonstrated the causal link between eEF1A and carcinogenesis, gaining deeper insights into its multifaceted mechanisms and corroborating its value as a prognostic marker in various cancers. On the other hand, an increasing number of natural and synthetic compounds were discovered as anticancer eEF1A-targeting inhibitors. Among them, plitidepsin was approved for the treatment of multiple myeloma whereas metarrestin was currently under clinical development. Despite significant achievements in these two interrelated fields, hitherto there lacks a systematic examination of the eEF1A protein in the context of cancer research. Therefore, the present work aims to delineate its clinical implications, molecular oncogenic mechanisms, and targeted therapeutic strategies as reflected in the ever expanding body of literature, so as to deepen mechanistic understanding of eEF1A-involved tumorigenesis and inspire the development of eEF1A-targeted chemotherapeutics and biologics.

Identifying squalene epoxidase as a metabolic vulnerability in high-risk osteosarcoma using an artificial intelligence-derived prognostic index

BACKGROUND

Osteosarcoma (OSA) presents a clinical challenge and has a low 5-year survival rate. Currently, the lack of advanced stratification models makes personalized therapy difficult. This study aims to identify novel biomarkers to stratify high-risk OSA patients and guide treatment.

METHODS

We combined 10 machine-learning algorithms into 101 combinations, from which the optimal model was established for predicting overall survival based on transcriptomic profiles for 254 samples. Alterations in transcriptomic, genomic and epigenomic landscapes were assessed to elucidate mechanisms driving poor prognosis. Single-cell RNA sequencing (scRNA-seq) unveiled genes overexpressed in OSA cells as potential therapeutic targets, one of which was validated via tissue staining, knockdown and pharmacological inhibition. We characterized changes in multiple phenotypes, including proliferation, colony formation, migration, invasion, apoptosis, chemosensitivity and in vivo tumourigenicity. RNA-seq and Western blotting elucidated the impact of squalene epoxidase (SQLE) suppression on signalling pathways.

RESULTS

The artificial intelligence-derived prognostic index (AIDPI), generated by our model, was an independent prognostic biomarker, outperforming clinicopathological factors and previously published signatures. Incorporating the AIDPI with clinical factors into a nomogram improved predictive accuracy. For user convenience, both the model and nomogram are accessible online. Patients in the high-AIDPI group exhibited chemoresistance, coupled with overexpression of MYC and SQLE, increased mTORC1 signalling, disrupted PI3K-Akt signalling, and diminished immune infiltration. ScRNA-seq revealed high expression of MYC and SQLE in OSA cells. Elevated SQLE expression correlated with chemoresistance and worse outcomes in OSA patients. Therapeutically, silencing SQLE suppressed OSA malignancy and enhanced chemosensitivity, mediated by cholesterol depletion and suppression of the FAK/PI3K/Akt/mTOR pathway. Furthermore, the SQLE-specific inhibitor FR194738 demonstrated anti-OSA effects in vivo and exhibited synergistic effects with chemotherapeutic agents.

CONCLUSIONS

AIDPI is a robust biomarker for identifying the high-risk subset of OSA patients. The SQLE protein emerges as a metabolic vulnerability in these patients, providing a target with translational potential.

Identification of Prognostic Markers and Potential Therapeutic Targets using Gene Expression Profiling and Simulation Studies in Pancreatic Cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a 5-year relative survival rate of less than 10% making it one of the most fatal cancers. A lack of early measures of prognosis, challenges in molecular targeted therapy, ineffective adjuvant chemotherapy, and strong resistance to chemotherapy cumulatively make pancreatic cancer challenging to manage.

OBJECTIVE

The present study aims to enhance understanding of the disease mechanism and its progression by identifying prognostic biomarkers, potential drug targets, and candidate drugs that can be used for therapy in pancreatic cancer.

METHODS

Gene expression profiles from the GEO database were analyzed to identify reliable prognostic markers and potential drug targets. The disease's molecular mechanism and biological pathways were studied by investigating gene ontologies, KEGG pathways, and survival analysis to understand the strong prognostic power of key DEGs. FDA-approved anti-cancer drugs were screened through cell line databases, and docking studies were performed to identify drugs with high affinity for ARNTL2 and PIK3C2A. Molecular dynamic simulations of drug targets ARNTL2 and PIK3C2A in their native state and complex with nilotinib were carried out for 100 ns to validate their therapeutic potential in PDAC.

RESULTS

Differentially expressed genes that are crucial regulators, including SUN1, PSMG3, PIK3C2A, SCRN1, and TRIAP1, were identified. Nilotinib as a candidate drug was screened using sensitivity analysis on CCLE and GDSC pancreatic cancer cell lines. Molecular dynamics simulations revealed the underlying mechanism of the binding of nilotinib with ARNTL2 and PIK3C2A and the dynamic perturbations. It validated nilotinib as a promising drug for pancreatic cancer.

CONCLUSION

This study accounts for prognostic markers, drug targets, and repurposed anti-cancer drugs to highlight their usefulness for translational research on developing novel therapies. Our results revealed potential and prospective clinical applications in drug targets ARNTL2, EGFR, and PI3KC2A for pancreatic cancer therapy.

A targetable pathway to eliminate TRA-1-60+/TRA-1-81+ chemoresistant cancer cells

Chemoresistance is a primary cause of treatment failure in pancreatic cancer. Identifying cell surface markers specifically expressed in chemoresistant cancer cells (CCCs) could facilitate targeted therapies to overcome chemoresistance. We performed an antibody-based screen and found that TRA-1-60 and TRA-1-81, two 'stemness' cell surface markers, are highly enriched in CCCs. Furthermore, TRA-1-60+/TRA-1-81+ cells are chemoresistant compared to TRA-1-60-/TRA-1-81- cells. Transcriptome profiling identified UGT1A10, shown to be both necessary and sufficient to maintain TRA-1-60/TRA-1-81 expression and chemoresistance. From a high-content chemical screen, we identified Cymarin, which downregulates UGT1A10, eliminates TRA-1-60/TRA-1-81 expression, and increases chemosensitivity both in vitro and in vivo. Finally, TRA-1-60/TRA-1-81 expression is highly specific in primary cancer tissue and positively correlated with chemoresistance and short survival, which highlights their potentiality for targeted therapy. Therefore, we discovered a novel CCC surface marker regulated by a pathway that promotes chemoresistance, as well as a leading drug candidate to target this pathway.

Identification of the methotrexate resistance-related diagnostic markers in osteosarcoma via adaptive total variation netNMF and multi-omics datasets

Osteosarcoma is one of the most common malignant bone tumors with high chemoresistance and poor prognosis, exhibiting abnormal gene regulation and epigenetic events. Methotrexate (MTX) is often used as a primary agent in neoadjuvant chemotherapy for osteosarcoma; However, the high dosage of methotrexate and strong drug resistance limit its therapeutic efficacy and application prospects. Studies have shown that abnormal expression and dysfunction of some coding or non-coding RNAs (e.g., DNA methylation and microRNA) affect key features of osteosarcoma progression, such as proliferation, migration, invasion, and drug resistance. Comprehensive multi-omics analysis is critical to understand its chemoresistant and pathogenic mechanisms. Currently, the network analysis-based non-negative matrix factorization (netNMF) method is widely used for multi-omics data fusion analysis. However, the effects of data noise and inflexible settings of regularization parameters affect its performance, while integrating and processing different types of genetic data is also a challenge. In this study, we introduced a novel adaptive total variation netNMF (ATV-netNMF) method to identify feature modules and characteristic genes by integrating methylation and gene expression data, which can adaptively choose an anisotropic smoothing scheme to denoise or preserve feature details based on the gradient information of the data by introducing an adaptive total variation constraint in netNMF. By comparing with other similar methods, the results showed that the proposed method could extract multi-omics fusion features more effectively. Furthermore, by combining the mRNA and miRNA data of methotrexate (MTX) resistance with the extracted feature genes, four genes, Carboxypeptidase E (CPE), LIM, SH3 protein 1 (LASP1), Pyruvate Dehydrogenase Kinase 1 (PDK1) and Serine beta-lactamase-like protein (LACTB) were finally identified. The results showed that the gene signature could reliably predict the prognostic status and immune status of osteosarcoma patients.

Cluster of resistance-inducing genes in MCF-7 cells by estrogen, insulin, methotrexate and tamoxifen extracted via NMF

Breast cancer has become a leading cause of death for women as the economy has grown and the number of women in the labor force has increased. Several biomarkers with diagnostic, prognostic, and therapeutic implications for breast cancer have been identified in studies, leading to therapeutic advances. Resistance, on the other hand, is one of clinical practice's limitations. In this paper, we use Nonnegative Matrix Factorization to automatically extract two gene signatures from gene expression profiles of wild-type and resistance MCF-7 cells, which were then investigated further using pathways analysis and proved useful in relating resistance pathways to breast cancer regardless of the stimulus that caused it. A few extracted genes (including MAOA, IL4I1, RRM2, DUT, NME4, and SUMO3) represent new elements in the functional network for resistance in MCF-7 ER+ breast cancer. As a result of this research, a better understanding of how resistance occurs or the pathways that contribute to it may allow more effective therapies to be developed.

Chemotherapy induces ACE2 expression in breast cancer via the ROS-AKT-HIF-1α signaling pathway: a potential prognostic marker for breast cancer patients receiving chemotherapy

Background

Angiotensin-converting enzyme 2 (ACE2) is a key enzyme of the renin-angiotensin system and a well-known functional receptor for the entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into host cells. The COVID-19 pandemic has brought ACE2 into the spotlight, and ACE2 expression in tumors and its relationship with SARS-COV-2 infection and prognosis of cancer patients have received extensive attention. However, the association between ACE2 expression and tumor therapy and prognosis, especially in breast cancer, remains ambiguous and requires further investigation. We have previously reported that ACE2 is elevated in drug-resistant breast cancer cells, but the exact function of ACE2 in drug resistance and progression of this malignant disease has not been explored.

Methods

The expression of ACE2 and HIF-1α in parental and drug-resistant breast cancer cells under normoxic and hypoxic conditions was analyzed by Western blot and qRT-PCR methods. The protein levels of ACE2 in plasma samples from breast cancer patients were examined by ELISA. The relationship between ACE2 expression and breast cancer treatment and prognosis was analyzed using clinical specimens and public databases. The reactive oxygen species (ROS) levels in breast cancer cells were measured by using a fluorescent probe. Small interfering RNAs (siRNAs) or lentivirus-mediated shRNA was used to silence ACE2 and HIF-1α expression in cellular models. The effect of ACE2 knockdown on drug resistance in breast cancer was determined by Cell Counting Kit 8 (CCK-8)-based assay, colony formation assay, apoptosis and EdU assay.

Results

ACE2 expression is relatively low in breast cancer cells, but increases rapidly and specifically after exposure to anticancer drugs, and remains high after resistance is acquired. Mechanistically, chemotherapeutic agents increase ACE2 expression in breast cancer cells by inducing intracellular ROS production, and increased ROS levels enhance AKT phosphorylation and subsequently increase HIF-1α expression, which in turn upregulates ACE2 expression. Although ACE2 levels in plasma and cancer tissues are lower in breast cancer patients compared with healthy controls, elevated ACE2 in patients after chemotherapy is a predictor of poor treatment response and an unfavorable prognostic factor for survival in breast cancer patients.

Conclusion

ACE2 is a gene in breast cancer cells that responds rapidly to chemotherapeutic agents through the ROS-AKT-HIF-1α axis. Elevated ACE2 modulates the sensitivity of breast cancer cells to anticancer drugs by optimizing the balance of intracellular ROS. Moreover, increased ACE2 is not only a predictor of poor response to chemotherapy, but is also associated with a worse prognosis in breast cancer patients. Thus, our findings provide novel insights into the spatiotemporal differences in the function of ACE2 in the initiation and progression of breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03716-w.

The role of lncRNA H19 in tumorigenesis and drug resistance of human Cancers

Systemic therapy is one of the most significant cancer treatments. However, drug resistance often appears and has become the primary cause of cancer therapy failure. Regulation of drug target, drug metabolism and drug efflux, cell death escape (apoptosis, autophagy, et al.), epigenetic changes, and many other variables are complicatedly involved in the mechanisms of drug resistance. In various types of cancers, long non-coding RNA H19 (lncRNA H19) has been shown to play critical roles in tumor development, proliferation, metastasis, and multiple drug resistance as well. The efficacy of chemotherapy, endocrine therapy, and targeted therapy are all influenced by the expression of H19, especially in breast cancer, liver cancer, lung cancer and colorectal cancer. Here, we summarize the relationship between lncRNA H19 and tumorigenesis, and illustrate the drug resistance mechanisms caused by lncRNA H19 as well. This review may provide more therapeutic potential targets for future cancer treatments.

Arylamine N-acetyltransferase 1 deficiency inhibits drug-induced cell death in breast cancer cells: switch from cytochrome C-dependent apoptosis to necroptosis

Purpose

Arylamine N-acetyltransferase 1 (NAT1) deficiency has been associated with drug resistance and poor outcomes in breast cancer patients. The current study aimed to investigate drug resistance in vitro using normal breast cancer cell lines and NAT1-deficient cell lines to understand the changes induced by the lack of NAT1 that resulted in poor drug response.

Methods

The response to seven chemotherapeutic agents was quantified following NAT1 deletion using CRISPR-Cas 9 in MDA-MB-231 and T-47D cells. Apoptosis was monitored by annexin V staining and caspase 3/7 activity. Cytochrome C release and caspase 8 and 9 activities were measured by Western blots. Caspase 8 was inhibited using Z-IETD-FMK and necroptosis was inhibited using necrostatin and necrosulfonamide.

Results

Compared to parental cells, NAT1 depleted cells were resistant to drug treatment. This could be reversed following NAT1 rescue of the NAT1 deleted cells. Release of cytochrome C in response to treatment was decreased in the NAT1 depleted cells, suggesting suppression of the intrinsic apoptotic pathway. In addition, NAT1 knockout resulted in a decrease in caspase 8 activation. Treatment with necrosulfonamide showed that NAT1 deficient cells switched from intrinsic apoptosis to necroptosis when treated with the anti-cancer drug cisplatin.

Conclusions

NAT1 deficiency can switch cell death from apoptosis to necroptosis resulting in decreased response to cytotoxic drugs. The absence of NAT1 in patient tumours may be a useful biomarker for selecting alternative treatments in a subset of breast cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-022-06668-3.

BOSO: A novel feature selection algorithm for linear regression with high-dimensional data

With the frenetic growth of high-dimensional datasets in different biomedical domains, there is an urgent need to develop predictive methods able to deal with this complexity. Feature selection is a relevant strategy in machine learning to address this challenge. We introduce a novel feature selection algorithm for linear regression called BOSO (Bilevel Optimization Selector Operator). We conducted a benchmark of BOSO with key algorithms in the literature, finding a superior accuracy for feature selection in high-dimensional datasets. Proof-of-concept of BOSO for predicting drug sensitivity in cancer is presented. A detailed analysis is carried out for methotrexate, a well-studied drug targeting cancer metabolism.

We present BOSO (Bilevel Optimization Selector Operator), a novel method to conduct feature selection in linear regression models. In machine learning, feature selection consists of identifying the subset of input variables (features) that are correctly associated with the response variable that is aimed to be predicted. An adequate feature selection is particularly relevant for high-dimensional datasets, commonly encountered in biomedical research questions that rely on -omics data, e.g. predictive models of drug sensitivity, resistance or toxicity, construction of gene regulatory networks, biomarker selection or association studies. The need of feature selection is emphasized in many of these complex problems, since the number of features is greater than the number of samples, which makes it harder to obtain accurate and general predictive models. In this context, we show that the models derived by BOSO make a better combination of accuracy and simplicity than competing approaches in the literature. The relevance of BOSO is illustrated in the prediction of drug sensitivity of cancer cell lines, using RNA-seq data and drug screenings from GDSC (Genomics of Drug Sensitivity in Cancer) database. BOSO obtains linear regression models with a similar level of accuracy but involving a substantially lower number of features, which simplifies the interpretation and validation of predictive models.

Tribbles Gene Expression Profiles in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of death due to cancer in the world. Therefore, the identification of novel druggable targets is urgently needed. Tribbles proteins belong to a pseudokinase family, previously recognized in CRC as oncogenes and potential therapeutic targets. Here, we analyzed the expression of TRIB1, TRIB2, and TRIB3 simultaneously in 33 data sets from CRC based on available GEO profiles. We show that all three Tribbles genes are overrepresented in CRC cell lines and primary tumors, though depending on specific features of the CRC samples. Higher expression of TRIB2 in the tumor microenvironment and TRIB3 overexpression in an early stage of CRC development, unveil a potential and unexplored role for these proteins in the context of CRC. Differential Tribbles expression was also explored in diverse cellular experimental conditions where either genetic or pharmacological approaches were used, providing novel hints for future research. This comprehensive bioinformatic analysis provides new insights into Tribbles gene expression and transcript regulation in CRC.

Tribbles Gene Expression Profiles in Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of death due to cancer in the world. Therefore, the identification of novel druggable targets is urgently needed. Tribbles proteins belong to a pseudokinase family, previously recognized in CRC as oncogenes and potential therapeutic targets. Here, we analyzed the expression of TRIB1, TRIB2, and TRIB3 simultaneously in 33 data sets from CRC based on available GEO profiles. We show that all three Tribbles genes are overrepresented in CRC cell lines and primary tumors, though depending on specific features of the CRC samples. Higher expression of TRIB2 in the tumor microenvironment and TRIB3 overexpression in an early stage of CRC development, unveil a potential and unexplored role for these proteins in the context of CRC. Differential Tribbles expression was also explored in diverse cellular experimental conditions where either genetic or pharmacological approaches were used, providing novel hints for future research. This comprehensive bioinformatic analysis provides new insights into Tribbles gene expression and transcript regulation in CRC.

Single-cell sequencing reveals the potential oncogenic expression atlas of human iPSC-derived cardiomyocytes

Human induced pluripotent stem cells (iPSCs) are important source for regenerative medicine. However, the links between pluripotency and oncogenic transformation raise safety issues. To understand the characteristics of iPSC-derived cells at single-cell resolution, we directly reprogrammed two human iPSC lines into cardiomyocytes and collected cells from four time points during cardiac differentiation for single-cell sequencing. We captured 32,365 cells and identified five molecularly distinct clusters that aligned well with our reconstructed differentiation trajectory. We discovered a set of dynamic expression events related to the upregulation of oncogenes and the decreasing expression of tumor suppressor genes during cardiac differentiation, which were similar to the gain-of-function and loss-of-function patterns during oncogenesis. In practice, we characterized the dynamic expression of the TP53 and Yamanaka factor genes (OCT4, SOX2, KLF4 and MYC), which were widely used for human iPSCs lines generation; and revealed the co-occurrence of MYC overexpression and TP53 silencing in some of human iPSC-derived TNNT2+ cardiomyocytes. In summary, our oncogenic expression atlas is valuable for human iPSCs application and the single-cell resolution highlights the clues potentially associated with the carcinogenic risk of human iPSC-derived cells.

Summary: The single-cell expression atlas in the cardiomyocytes generated from human iPSCs provide potential carcinogenic information for the clinical application of human iPSC-derived cells.

In-Vitro and In-Vivo Establishment and Characterization of Bioluminescent Orthotopic Chemotherapy-Resistant Human Osteosarcoma Models in NSG Mice

Osteosarcoma, the most common bone malignancy with a peak incidence at adolescence, had no survival improvement since decades. Persistent problems are chemo-resistance and metastatic spread. We developed in-vitro osteosarcoma models resistant to chemotherapy and in-vivo bioluminescent orthotopic cell-derived-xenografts (CDX). Continuous increasing drug concentration cultures in-vitro resulted in five methotrexate (MTX)-resistant and one doxorubicin (DOXO)-resistant cell lines. Resistance persisted after drug removal except for MG-63. Different resistance mechanisms were identified, affecting drug transport and action mechanisms specific to methotrexate (RFC/SCL19A1 decrease, DHFR up-regulation) for MTX-resistant lines, or a multi-drug phenomenon (PgP up-regulation) for HOS-R/DOXO. Differential analysis of copy number abnormalities (aCGH) and gene expression (RNAseq) revealed changes of several chromosomic regions translated at transcriptomic level depending on drug and cell line, as well as different pathways implicated in invasive and metastatic potential (e.g., Fas, Metalloproteinases) and immunity (enrichment in HLA cluster genes in 6p21.3) in HOS-R/DOXO. Resistant-CDX models (HOS-R/MTX, HOS-R/DOXO and Saos-2-B-R/MTX) injected intratibially into NSG mice behaved as their parental counterpart at primary tumor site; however, they exhibited a slower growth rate and lower metastatic spread, although they retained resistance and CGH main characteristics without drug pressure. These models represent valuable tools to explore resistance mechanisms and new therapies in osteosarcoma.

Trimodal distribution of arylamine N-acetyltransferase 1 mRNA in breast cancer tumors: association with overall survival and drug resistance

BACKGROUND

Arylamine N-acetyltransferase 1 (NAT1) is a drug metabolizing enzyme that has been associated with cancer cell proliferation in vitro and with survival in vivo. NAT1 expression has been associated with the estrogen receptor and it has been proposed as a prognostic marker for estrogen receptor positive cancers. However, little is known about the distribution of NAT1 mRNA across an entire patient population or its effects on outcomes. To address this, gene expression data from breast cancer patient cohorts were investigated to identify sub-populations based on the level of NAT1 expression. Patient survival and drug response was examined to determine whether NAT1 mRNA levels influenced any of these parameters.

RESULTS

NAT1 expression showed a trimodal distribution in breast cancer samples (n = 1980) but not in tumor tissue from ovarian, prostate, cervical or colorectal cancers. In breast cancer, NAT1 mRNA in each sub-population correlated with a separate set of genes suggesting different mechanisms of NAT1 gene regulation. Kaplan-Meier plots showed significantly better survival in patients with highest NAT1 mRNA compared to those with intermediate or low expression. While NAT1 expression was elevated in estrogen receptor-positive patients, it did not appear to be dependent on estrogen receptor expression. Overall survival was analyzed in patients receiving no treatment, hormone therapy or chemotherapy. NAT1 expression correlated strongly with survival in the first 5 years in those patients receiving chemotherapy but did not influence survival in the other two groups. This suggests that low NAT1 expression is associated with chemo-resistance. The sensitivity of NAT1 mRNA levels as a single parameter to identify non-responders to chemotherapy was 0.58 at a log(2) < 6.5.

CONCLUSIONS

NAT1 mRNA can be used to segregate breast cancer patients into sub-populations that demonstrate different overall survival. Moreover, low NAT1 expression shows a distinct poor response to chemotherapy. Analysis of NAT1 expression may be useful for identifying specific individuals who would benefit from alternative therapy or drug combinations. However, additional information is required to increase the sensitivity of identifying non-responders.

Exploring the key genes and pathways of side population cells in human osteosarcoma using gene expression array analysis

BACKGROUND

Human osteosarcoma (OS) is one of the most common primary bone sarcoma, because of early metastasis and few treatment strategies. It has been reported that the tumorigenicity and self-renewal capacity of side population (SP) cells play roles in human OS via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) that regulated between the SP cells and the non-SP cells from primary human OS and identify their functions and molecular pathways associated with OS.

METHODS

The gene expression profile GSE63390 was downloaded, and bioinformatics analysis was made.

RESULTS

One hundred forty-one DEGs totally were identified. Among them, 72 DEGs (51.06%) were overexpressed, and the remaining 69 DEGs (48.94%) were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene-gene interaction network analysis such as EIF4E, FAU, HSPD1, IL-6, and KISS1, which may have a relationship with the development process of OS. We also discovered that EIF4E/mTOR signaling pathway could be a potential research target for therapy and tumorigenesis of OS.

CONCLUSION

This analysis provides a comprehensive understanding of the roles of DEGs coming from SP cells in the development of OS. However, these predictions need further experimental validation in future studies.

Curcumin may serve an anticancer role in human osteosarcoma cell line U-2 OS by targeting ITPR1

The present study aimed to determine the mechanisms of action of curcumin in osteosarcoma. Human osteosarcoma U-2 OS cells was purchased from the Cell Bank of the Chinese Academy of Sciences. RNA sequencing analysis was performed for 2 curcumin-treated samples and 2 control samples using Illumina deep sequencing technology. The differentially expressed genes were identified using Cufflink software. Enrichment and protein-protein interaction network analyses were performed separately using cluster Profiler package and Cytoscape software to identify key genes. Then, the mRNA levels of key genes were detected by quantitative reverse transcription polymerase chain reaction (RT-qPCR) in U-2 OS cells. Finally, cell apoptosis, proliferation, migration and invasion arrays were performed. In total, 201 DEGs were identified in the curcumin-treated group. EEF1A1 (degree=88), ATF7IP, HIF1A, SMAD7, CLTC, MCM10, ITPR1, ADAM15, WWP2 and ATP5C1, which were enriched in 'biological process', exhibited higher degrees than other genes in the PPI network. RT-qPCR demonstrated that treatment with curcumin was able to significantly increase the levels of CLTC and ITPR1 mRNA in curcumin-treated cells compared with control. In addition, targeting ITPR1 with curcumin significantly promoted apoptosis and suppressed proliferation, migration and invasion. Targeting ITPR1 via curcumin may serve an anticancer role by mediating apoptosis, proliferation, migration and invasion in U-2 OS cells.

Enhanced and Selective Antiproliferative Activity of Methotrexate-Functionalized-Nanocapsules to Human Breast Cancer Cells (MCF-7)

Methotrexate is a folic acid antagonist and its incorporation into nanoformulations is a promising strategy to increase the drug antiproliferative effect on human breast cancer cells by overexpressing folate receptors. To evaluate the efficiency and selectivity of nanoformulations containing methotrexate and its diethyl ester derivative, using two mechanisms of drug incorporation (encapsulation and surface functionalization) in the in vitro cellular uptake and antiproliferative activity in non-tumoral immortalized human keratinocytes (HaCaT) and in human breast carcinoma cells (MCF-7). Methotrexate and its diethyl ester derivative were incorporated into multiwall lipid-core nanocapsules with hydrodynamic diameters lower than 160 nm and higher drug incorporation efficiency. The nanoformulations were applied to semiconfluent HaCaT or MCF-7 cells. After 24 h, the nanocapsules were internalized into HaCaT and MCF-7 cells; however, no significant difference was observed between the nanoformulations in HaCaT (low expression of folate receptors), while they showed significantly higher cellular uptakes than the blank-nanoformulation in MCF-7, which was the highest uptakes observed for the drug functionalized-nanocapsules. No antiproliferative activity was observed in HaCaT culture, whereas drug-containing nanoformulations showed antiproliferative activity against MCF-7 cells. The effect was higher for drug-surface functionalized nanocapsules. In conclusion, methotrexate-functionalized-nanocapsules showed enhanced and selective antiproliferative activity to human breast cancer cells (MCF-7) being promising products for further in vivo pre-clinical evaluations.

Characterizing biomarkers in osteosarcoma metastasis based on an ego-network

OBJECTIVES

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network.

RESULTS

From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway.

CONCLUSIONS

These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.

Comparative proteomics analysis of human osteosarcoma by 2D DIGE with MALDI-TOF/TOF MS

Osteosarcoma (OS) is the most common primary malignant tumor of bone and the third most common cancer in childhood and adolescence. However, controversy concerning the ideal combination of chemotherapy agents ensued throughout the last quarter of the 20th century because of conflicting and often nonrandomized data. Collaborative efforts to increase understanding of the biology of osteosarcoma and the use of preclinical models to test novel protein targets will be critical to identify the path toward improving outcomes for patients. We attempted to identify potential protein markers or therapy targets of osteosarcoma and give a glance at tumorigenesis of osteosarcoma. A sensitive and accurate method was employed in comparative proteomic analysis between benign tumor and osteosarcoma. Tumor tissues obtained by open biopsy before induction chemotherapy were investigated With 2D DIGE and MALDI-TOF/TOF MS, 22 differentially expressed proteins were identified after database searching, including 8 up-regulated and 14 down-regulated proteins. We also validated the expression levels of interesting proteins(have higher Ratios(tumor/normal)) by Western blotting assay. Annotating by bioinformatic tools, we found structural and signal transduction associated proteins were in large percentage among altered level proteins. In particular, some low abundant proteins involving translation and transcription, such as EEF2(Elongation Factor 2), LUM Lumican 23 kDa Protein) and GTF2A2(Transcription Initiation Factor Iia Gamma Chain.), were firstly reported by our study comparing to previous observations. Our findings suggest that these differential proteins may be potential biomarkers for diagnosis or molecules for understanding of osteosarcoma tumorigenesis, coming with biologic, preclinical, and clinical trial efforts being described to improve outcomes for patients.

Vascular endothelial growth factor A as predictive marker for mTOR inhibition in relapsing high-grade serous ovarian cancer

Background

Development of resistance against first line drug therapy including cisplatin and paclitaxel in high-grade serous ovarian cancer (HGSOC) presents a major challenge. Identifying drug candidates breaking resistance, ideally combined with predictive biomarkers allowing precision use are needed for prolonging progression free survival of ovarian cancer patients.

Modeling of molecular processes driving drug resistance in tumor tissue further combined with mechanism of action of drugs provides a strategy for identification of candidate drugs and associated predictive biomarkers.

Results

Consolidation of transcriptomics profiles and biomedical literature mining results provides 1242 proteins linked with ovarian cancer drug resistance. Integrating this set on a protein interaction network followed by graph segmentation results in a molecular process model representation of drug resistant HGSOC embedding 409 proteins in 24 molecular processes. Utilizing independent transcriptomics profiles with follow-up data on progression free survival allows deriving molecular biomarker-based classifiers for predicting recurrence under first line therapy. Biomarkers of specific relevance are identified in a molecular process encapsulating TGF-beta, mTOR, Jak-STAT and Neurotrophin signaling. Mechanism of action molecular model representations of cisplatin and paclitaxel embed the very same signaling components, and specifically proteins afflicted with the activation status of the mTOR pathway become evident, including VEGFA. Analyzing mechanism of action interference of the mTOR inhibitor sirolimus shows specific impact on the drug resistance signature imposed by cisplatin and paclitaxel, further holding evidence for a synthetic lethal interaction to paclitaxel mechanism of action involving cyclin D1.

Conclusions

Stratifying drug resistant high grade serous ovarian cancer via VEGFA, and specifically treating with mTOR inhibitors in case of activation of the pathway may allow adding precision for overcoming resistance to first line therapy.

Identification of genes associated with methotrexate resistance in methotrexate-resistant osteosarcoma cell lines

BACKGROUND

This study aimed to better understand the mechanisms underlying methotrexate (MTX)-resistance in osteosarcoma.

METHODS

The raw transcription microarray data GSE16089 collected from three MTX-sensitive osteosarcoma (Saos-2) cell samples and three MTX-resistant osteosarcoma (Saos-2) cell samples were downloaded from Gene Expression Omnibus. After data processing, the differentially expressed genes (DEGs) were identified. Next, DEGs were submitted to DAVID for functional annotation based on the GO (Gene Ontology) database, as well as pathway enrichment analysis based on the KEGG (Kyoto Encyclopedia of Genes and Genomes) database. Transcription factors (TFs) and tumor-associated genes (TAGs) were identified with reference to TRANSFAC and TAG, and TSGene databases, respectively. The protein-protein interaction (PPI) network of the gene-encoded products was constructed, and the subnetwork with the highest score was also detected using Search Tool for the Retrieval of Interacting Genes and BioNet package.

RESULTS

A total of 690 up-regulated genes and down-regulated 626 genes were identified. Up-regulated DEGs (including AARS and PARS2) were associated to transfer RNA (tRNA) aminoacylation while down-regulated DEGs (including AURKA, CCNB1, CCNE2, CDK1, and CENPA) were correlated with mitotic cell cycle. Totally, 13 TFs (including HMGB2), 13 oncogenes (including CCNA2 and AURKA), and 19 tumor suppressor genes (TSGs) (including CDKN2C) were identified from the down-regulated DEGs. Ten DEGs, including nine down-regulated genes (such as AURKA, CDK1, CCNE2, and CENPA) and one up-regulated gene (GADD45A), were involved in the highest score subnetwork.

CONCLUSION

AARS, AURKA, AURKB, CENPA, CCNB1, CCNE2, and CDK may contribute to MTX resistance via aminoacyl-tRNA biosynthesis pathway, cell cycle pathway, or p53 signaling pathway.

Urolithin A causes p21 up-regulation in prostate cancer cells

PURPOSE

Walnuts contain several bioactive compounds, including pedunculagin, a polyphenol metabolized by microbiota to form urolithins, namely urolithin A (UA). The aim of this study was to determine gene expression changes in prostate cancer cells after incubation with UA.

METHODS

We performed a genomic analysis to study the effect of UA on LNCaP prostate cells. Cells were incubated with 40 µM UA for 24 h, and RNA was extracted and hybridized to Affymetrix Human Genome U219 array. Microarray results were analyzed using GeneSpring v13 software. Differentially expressed genes (p < 0.05, fold change > 2) were used to perform biological association networks. Cell cycle was analyzed by flow cytometry and apoptosis measured by the rhodamine method and by caspases 3 and 7 activation. Cell viability was determined by MTT assay.

RESULTS

We identified two nodes, FN-1 and CDKN1A, among the differentially expressed genes upon UA treatment. CDKN1A was validated, its mRNA and protein levels were significantly up-regulated, and the promoter activation measured by luciferase. Cell cycle analysis showed an increase in G1-phase, and we also observed an induction of apoptosis and caspases 3 and 7 activation upon UA treatment.

CONCLUSION

Our results indicate a potential role of UA as a chemopreventive agent for prostate cancer.

Methotrexate diethyl ester-loaded lipid-core nanocapsules in aqueous solution increased antineoplastic effects in resistant breast cancer cell line

Breast cancer is the most frequent cancer affecting women. Methotrexate (MTX) is an antimetabolic drug that remains important in the treatment of breast cancer. Its efficacy is compromised by resistance in cancer cells that occurs through a variety of mechanisms. This study evaluated apoptotic cell death and cell cycle arrest induced by an MTX derivative (MTX diethyl ester [MTX(OEt)₂]) and MTX(OEt)₂-loaded lipid-core nanocapsules in two MTX-resistant breast adenocarcinoma cell lines, MCF-7 and MDA-MB-231. The formulations prepared presented adequate granulometric profile. The treatment responses were evaluated through flow cytometry. Relying on the mechanism of resistance, we observed different responses between cell lines. For MCF-7 cells, MTX(OEt)₂ solution and MTX(OEt)₂-loaded lipid-core nanocapsules presented significantly higher apoptotic rates than untreated cells and cells incubated with unloaded lipid-core nanocapsules. For MDA-MB-231 cells, MTX(OEt)₂-loaded lipid-core nanocapsules were significantly more efficient in inducing apoptosis than the solution of the free drug. S-phase cell cycle arrest was induced only by MTX(OEt)₂ solution. The drug nanoencapsulation improved apoptosis induction for the cell line that presents MTX resistance by lack of transport receptors.

Aven is dynamically regulated during Xenopus oocyte maturation and is required for oocyte survival

We have analyzed the expression and function of the cell death and cell cycle regulator Aven in Xenopus. Analysis of Xenopus Aven expression in oocytes and embryos revealed a band close to the predicted molecular weight of the protein (36 kDa) in addition to two bands of higher molecular weight (46 and 49 kDa), one of which was determined to be due to phosphorylation of the protein. The protein is primarily detected in the cytoplasm of oocytes and is tightly regulated during meiotic and mitotic cell cycles. Progesterone stimulation of oocytes resulted in a rapid loss of Aven expression with the protein levels recovering before germinal vesicle breakdown (GVBD). This loss of Aven is required for the G2–M1 cell cycle transition. Aven morpholino knockdown experiments revealed that early depletion of the protein increases progesterone sensitivity and facilitates GVBD, but prolonged depletion of Aven results in caspase-3 activation and oocyte death by apoptosis. Phosphorylated Aven (46 kDa) was found to bind Bcl-x_L in oocytes, but this interaction was lost in apoptotic oocytes. Thus, Aven alters progesterone sensitivity in oocytes and is critical for oocyte survival.

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

This study defines a network of synthetic sick/lethal interactions with a set of query genes in a series of isogenic cancer cell lines. Analysis of differential essentiality reveals general properties in genetic interaction networks derived from studies on model organisms.

This study defined about 200 negative genetic interactions in the isogenic cancer cell line background.

Mapping of negative genetic interactions in a systematic fashion in isogenic cancer cell lines has revealed novel functions for several uncharacterized genes.

This study demonstrates that differential essentiality profiles derived from isogenic cancer cell lines can be used to classify genetic dependencies in non-isogenic cancer cell lines.

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN^−/− DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

Eukaryotic translation elongation factor 1-alpha 1 inhibits p53 and p73 dependent apoptosis and chemotherapy sensitivity

The p53 family of transcription factors is a key regulator of cell proliferation and death. In this report we identify the eukaryotic translation elongation factor 1-alpha 1 (eEF1A1) to be a novel p53 and p73 interacting protein. Previous studies have demonstrated that eEF1A1 has translation-independent roles in cancer. We report that overexpression of eEF1A1 specifically inhibits p53-, p73- and chemotherapy-induced apoptosis resulting in chemoresistance. Short-interfering RNA-mediated silencing of eEF1A1 increases chemosensitivity in cell lines bearing wild type p53, but not in p53 null cells. Furthermore, silencing of eEF1A1 partially rescues the chemoresistance observed in response to p53 or p73 knockdown, suggesting that eEF1A1 is a negative regulator of the pro-apoptotic function of p53 and p73. Thus, in the context of p53-family signaling, eEF1A1 has anti-apoptotic properties. These findings identify a novel mechanism of regulation of the p53 family of proteins by eEF1A1 providing additional insight into potential targets to sensitize tumors to chemotherapy.

The redox state of cytochrome c modulates resistance to methotrexate in human MCF7 breast cancer cells

Background

Methotrexate is a chemotherapeutic agent used to treat a variety of cancers. However, the occurrence of resistance limits its effectiveness. Cytochrome c in its reduced state is less capable of triggering the apoptotic cascade. Thus, we set up to study the relationship among redox state of cytochrome c, apoptosis and the development of resistance to methotrexate in MCF7 human breast cancer cells.

Results

Cell incubation with cytochrome c-reducing agents, such as tetramethylphenylenediamine, ascorbate or reduced glutathione, decreased the mortality and apoptosis triggered by methotrexate. Conversely, depletion of glutathione increased the apoptotic action of methotrexate, showing an involvement of cytochrome c redox state in methotrexate-induced apoptosis. Methotrexate-resistant MCF7 cells showed increased levels of endogenous reduced glutathione and a higher capability to reduce exogenous cytochrome c. Using functional genomics we detected the overexpression of GSTM1 and GSTM4 in methotrexate-resistant MCF7 breast cancer cells, and determined that methotrexate was susceptible of glutathionylation by GSTs. The inhibition of these GSTM isoforms caused an increase in methotrexate cytotoxicity in sensitive and resistant cells.

Conclusions

We conclude that overexpression of specific GSTMs, GSTM1 and GSTM4, together with increased endogenous reduced glutathione levels help to maintain a more reduced state of cytochrome c which, in turn, would decrease apoptosis, thus contributing to methotrexate resistance in human MCF7 breast cancer cells.

Regulation of Phosphatidylethanolamine Homeostasis&#8212;The Critical Role of CTP:Phosphoethanolamine Cytidylyltransferase (Pcyt2)

Phosphatidylethanolamine (PE) is the most abundant lipid on the protoplasmatic leaflet of cellular membranes. It has a pivotal role in cellular processes such as membrane fusion, cell cycle regulation, autophagy, and apoptosis. CTP:phosphoethanolamine cytidylyltransferase (Pcyt2) is the main regulatory enzyme in de novo biosynthesis of PE from ethanolamine and diacylglycerol by the CDP-ethanolamine Kennedy pathway. The following is a summary of the current state of knowledge on Pcyt2 and how splicing and isoform specific differences could lead to variations in functional properties in this family of enzymes. Results from the most recent studies on Pcyt2 transcriptional regulation, promoter function, autophagy, and cell growth regulation are highlighted. Recent data obtained from Pcyt2 knockout mouse models is also presented, demonstrating the essentiality of this gene in embryonic development as well as the major physiological consequences of deletion of one Pcyt2 allele. Those include development of symptoms of the metabolic syndrome such as elevated lipogenesis and lipoprotein secretion, hypertriglyceridemia, liver steatosis, obesity, and insulin resistance. The objective of this review is to elucidate the nature of Pcyt2 regulation by linking its catalytic function with the regulation of lipid and energy homeostasis.

Identification of novel Sp1 targets involved in proliferation and cancer by functional genomics

Sp1 is a transcription factor regulating many genes through its DNA binding domain, containing three zinc fingers. We were interested in identifying target genes regulated by Sp1, particularly those involved in proliferation and cancer. Our approach was to treat HeLa cells with a siRNA directed against Sp1 mRNA to decrease the expression of Sp1 and, in turn, the genes activated by this transcription factor. Sp1-siRNA treatment led to a great number of differentially expressed genes as determined by whole genome cDNA microarray analysis. Underexpressed genes were selected since they represent putative genes activated by Sp1 and classified in six Gene Onthology categories, namely proliferation and cancer, mRNA processing, lipid metabolism, glucidic metabolism, transcription and translation. Putative Sp1 binding sites were found in the promoters of the selected genes using the Match™ software. After literature mining, 11 genes were selected for further validation. Underexpression by qRT-PCR was confirmed for the 11 genes plus Sp1 in HeLa cells after Sp1-siRNA treatment. EMSA and ChIP assays were performed to test for binding of Sp1 to the promoters of these genes. We observed binding of Sp1 to the promoters of RAB20, FGF21, IHPK2, ARHGAP18, NPM3, SRSF7, CALM3, PGD and Sp1 itself. Furthermore, the mRNA levels of RAB20, FGF21 and IHPK2 and luciferase activity for these three genes related to proliferation and cancer, were determined after overexpression of Sp1 in HeLa cells, to confirm their regulation by Sp1. Involvement of these three genes in proliferation was validated by gene silencing using polypurine reverse hoogsteen hairpins.

Coffee polyphenols change the expression of STAT5B and ATF-2 modifying cyclin D1 levels in cancer cells

Background. Epidemiological studies suggest that coffee consumption reduces the risk of cancer, but the molecular mechanisms of its chemopreventive effects remain unknown. Objective. To identify differentially expressed genes upon incubation of HT29 colon cancer cells with instant caffeinated coffee (ICC) or caffeic acid (CA) using whole-genome microarrays. Results. ICC incubation of HT29 cells caused the overexpression of 57 genes and the underexpression of 161, while CA incubation induced the overexpression of 12 genes and the underexpression of 32. Using Venn-Diagrams, we built a list of five overexpressed genes and twelve underexpressed genes in common between the two experimental conditions. This list was used to generate a biological association network in which STAT5B and ATF-2 appeared as highly interconnected nodes. STAT5B overexpression was confirmed at the mRNA and protein levels. For ATF-2, the changes in mRNA levels were confirmed for both ICC and CA, whereas the decrease in protein levels was only observed in CA-treated cells. The levels of cyclin D1, a target gene for both STAT5B and ATF-2, were downregulated by CA in colon cancer cells and by ICC and CA in breast cancer cells. Conclusions. Coffee polyphenols are able to affect cyclin D1 expression in cancer cells through the modulation of STAT5B and ATF-2.

O-miner: an integrative platform for automated analysis and mining of -omics data

High-throughput profiling has generated massive amounts of data across basic, clinical and translational research fields. However, open source comprehensive web tools for analysing data obtained from different platforms and technologies are still lacking. To fill this gap and the unmet computational needs of ongoing research projects, we developed O-miner, a rapid, comprehensive, efficient web tool that covers all the steps required for the analysis of both transcriptomic and genomic data starting from raw image files through in-depth bioinformatics analysis and annotation to biological knowledge extraction. O-miner was developed from a biologist end-user perspective. Hence, it is as simple to use as possible within the confines of the complexity of the data being analysed. It provides a strong analytical suite able to overlay and harness large, complicated, raw and heterogeneous sets of profiles with biological/clinical data. Biologists can use O-miner to analyse and integrate different types of data and annotations to build knowledge of relevant altered mechanisms and pathways in order to identify and prioritize novel targets for further biological validation. Here we describe the analytical workflows currently available using O-miner and present examples of use. O-miner is freely available at www.o-miner.org.

LC/LC-MS/MS of an innovative prostate human epithelial cancer (PHEC) in vitro model system

This work describes the proteomic characterization of a novel in vitro prostate cancer model system, the clonal prostatic human epithelial cancer (PHEC) cell lines. The model is composed of three cell lines representing the three progressive cancer states found in vivo: non-tumorigenic, tumorigenic, and metastatic. The cell lines were evaluated for differential protein expression between states using two dimensional liquid:liquid chromatographic separation followed by mass spectral identification. The proteins from cellular extracts were first separated using liquid:liquid primary separation based on their isoelectric points and hydrophobicity. The resulting peptide fractions were applied to liquid chromatography-mass spectrometry (LC-MS) separation for mass determination and protein identification based on Mascot database inquiry. Over 200 proteins that change expression over the course of progression of this in vitro prostate cancer model were discovered during the comparative analysis of the three cell lines. The importance of these proteins on prostate cancer progression remains to be elucidated with further characterizations. The combination of the two dimensional liquid:liquid separation and mass spectral identifications was used to successfully analyze differential protein expression between multiple cell lines.

Underexpression of miR-224 in methotrexate resistant human colon cancer cells

MicroRNAs (miRNAs) are small non-coding RNAs involved in RNA silencing that play a role in many biological processes. They are involved in the development of many diseases, including cancer. Extensive experimental data show that they play a role in the pathogenesis of cancer as well as the development of drug resistance during treatments. The aim of this work was to detect differentially expressed miRNAs in MTX-resistant cells. Thus, miRNA microarrays of sensitive and MTX-resistant HT29 colon cancer cells were performed. The results were analyzed using the GeneSpring GX11.5 software. Differentially expressed miRNAs in resistant cells were identified and miR-224, which was one of the most differentially expressed miRNAs and with high raw signal values, was selected for further studies. The underexpression of miR-224 was also observed in CaCo-2 and K562 cells resistant to MTX. Putative targets were predicted using TargetScan 5.1 software and integrated with the data from expression microarrays previously performed. This approach allowed us to identify miR-224 targets that were differentially expressed more than 2-fold in resistant cells. Among them CDS2, DCP2, HSPC159, MYST3 and SLC4A4 were validated at the mRNA level by qRT-PCR. Functional assays using an anti-miR against miR-224 desensitized the cells towards MTX, mimicking the resistant phenotype. On the other hand, siRNA treatment against SLC4A4 or incubation of Poly Purine Reverse Hoogsteen (PPRH) hairpins against CDS2 or HSPC159 increased sensitivity to MTX. These results revealed a role for miR-224 and its targets in MTX resistance in HT29 colon cancer cells.

A global insight into a cancer transcriptional space using pancreatic data: importance, findings and flaws

Despite the increasing wealth of available data, the structure of cancer transcriptional space remains largely unknown. Analysis of this space would provide novel insights into the complexity of cancer, assess relative implications in complex biological processes and responses, evaluate the effectiveness of cancer models and help uncover vital facets of cancer biology not apparent from current small-scale studies. We conducted a comprehensive analysis of pancreatic cancer-expression space by integrating data from otherwise disparate studies. We found (i) a clear separation of profiles based on experimental type, with patient tissue samples, cell lines and xenograft models forming distinct groups; (ii) three subgroups within the normal samples adjacent to cancer showing disruptions to biofunctions previously linked to cancer; and (iii) that ectopic subcutaneous xenografts and cell line models do not effectively represent changes occurring in pancreatic cancer. All findings are available from our online resource for independent interrogation. Currently, the most comprehensive analysis of pancreatic cancer to date, our study primarily serves to highlight limitations inherent with a lack of raw data availability, insufficient clinical/histopathological information and ambiguous data processing. It stresses the importance of a global-systems approach to assess and maximise findings from expression profiling of malignant and non-malignant diseases.

Genome-wide analysis reveals the active roles of keratinocytes in oral mucosal adaptive immune response

To elucidate the roles of oral keratinocytes in the adaptive immune response of oral mucosa, global gene expression analysis was performed by microarray technique and integrating computational methods, including hierarchical clustering, biological process Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, self-organizing maps (SOMs) and biological association network analysis (BAN). Raw data from microarray experiments were uploaded to the Gene Expression Omnibus Database, http://www.ncbi.nlm.nih.gov/geo/ (GEO accession GSE28035). We identified 666 differentially expressed genes in the early stage (48 h) and 993 in the late stage (96 h) of the oral mucosal adaptive immune response. The analysis revealed that oral keratinocytes exerted diverse biological functions in different stages of immune response. Specifically, in 48 h the differentially expressed genes encompassed an array of biological ontology associated with immune response, such as antigen processing and presentation, and positive regulation of T-cell-mediated cytotoxicity. Several pathways which have been reported to be critical in inflammation, including mitogen-activated protein kinase pathway, were activated. Furthermore, after BAN construction, some putative hub genes and networks such as interleukin-1α and its subnetwork were recognized. Taken together, these results give substantial evidence to support the active roles of keratinocytes in the oral mucosal adaptive immune response.

Coding polypurine hairpins cause target-induced cell death in breast cancer cells

Polypurine reverse-Hoogsteen hairpins (PPRHs) are double-stranded DNA molecules formed by two polypurine stretches linked by a pentathymidine loop, with intramolecular reverse-Hoogsteen bonds that allow a hairpin structure. PPRHs bind to polypyrimidine targets by Watson-Crick bonds maintaining simultaneously a hairpin structure due to intramolecular Hoogsteen bonds. Previously, we described the ability of Template-PPRHs to decrease mRNA levels because these PPRHs target the template DNA strand interfering with the transcription process. Now, we designed Coding-PPRHs, a new type of PPRHs that directly target the pre-mRNA. The dihydrofolate reductase (dhfr) gene was selected as a target in breast cancer therapy. These PPRHs caused a high degree of cytotoxicity and a decrease in DHFR mRNA and protein levels, but by a different mechanism of action than Template-PPRHs. Coding-PPRHs interfere with the splicing process by competing with U2 auxiliary factor 65 for binding to the polypyrimidine target sequence, leading to a lower amount of mature mRNA. These new PPRHs showed high specificity as no off-target effects were found. The application of these molecules as therapeutic tools was tested in breast cancer cells resistant to methotrexate, obtaining a noticeable cytotoxicity even though the dhfr locus was amplified. Coding-PPRHs can be considered as new molecules to decrease gene expression at the mRNA level and an alternative to other antisense molecules.

Neuroblastoma and bone metastases: clinical significance and prognostic value of Dickkopf 1 plasma levels

The critical role of the Wnt pathway inhibition in sustaining the onset of bone lesions has been demonstrated in a variety of bone diseases and tumors, and it has been associated with cancer aggressiveness. We have previously demonstrated that neuroblastoma cells express Dickkopf 1 (Dkk1), an inhibitor of the canonical Wnt pathway which prevents the differentiation of bone-forming cells. Since Dkk1 is a secreted factor, it could have potential clinical application as tumor marker for detecting bone metastasis and monitoring of disease. In this study, we investigated the diagnostic and prognostic value of Dkk1 plasma levels in 92 children affected by neuroblastoma, including 32 with bone metastases. Fifty-seven children hospitalized for minor surgical problems served as control group. Circulating levels of Dkk1 were higher in healthy children than in normal adults and were comparable to those found in adult patients with aggressive tumors. No significant differences were found between neuroblastoma patients and controls and between patients with and without bone metastases. However, when only patients with metastatic neuroblastoma were considered, the highest Dkk1 levels were detected in patients that poorly responded to induction chemotherapy and in subjects with unamplified MYCN and three or more different metastatic sites. The 'Receiver Operating Characteristic' curve enabled us to identify a threshold value to distinguish patients who were unresponsive to induction treatment. The relationship between Dkk1 and drug resistance was supported by in vitro experiments, since an increased sensitivity to doxorubicin was found in neuroblastoma cells releasing low Dkk1 levels, either constitutively or experimentally following the treatment with specific siRNA. In conclusion, Dkk1 is released by neuroblastoma cells and is able to affect the balance between osteoblastogenesis and osteoclastogenesis, thus favoring the onset of osteolytic metastases. Nevertheless, Dkk1 plasma levels do not allow the detection of bone lesions in neuroblastoma but seem to have a predictive value with regard to the severity and the prognosis of the disease in a subset of patients with metastatic tumor. New knowledge on the biological role of Dkk1 in driving the natural history of neuroblastoma has to be further investigated and could help to establish specific therapeutic strategies able to target key factors of tumor progression.

Overexpression of S100A4 in human cancer cell lines resistant to methotrexate

Background

Methotrexate is a chemotherapeutic drug that is used in therapy of a wide variety of cancers. The efficiency of treatment with this drug is compromised by the appearance of resistance. Combination treatments of MTX with other drugs that could modulate the expression of genes involved in MTX resistance would be an adequate strategy to prevent the development of this resistance.

Methods

The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. A global comparison of all the studied cell lines was performed in order to find out differentially expressed genes in the majority of the MTX-resistant cells. S100A4 mRNA and protein levels were determined by RT-Real-Time PCR and Western blot, respectively. Functional validations of S100A4 were performed either by transfection of an expression vector for S100A4 or a siRNA against S100A4. Transfection of an expression vector encoding for β-catenin was used to inquire for the possible transcriptional regulation of S100A4 through the Wnt pathway.

Results

S100A4 is overexpressed in five out of the seven MTX-resistant cell lines studied. Ectopic overexpression of this gene in HT29 sensitive cells augmented both the intracellular and extracellular S100A4 protein levels and caused desensitization toward MTX. siRNA against S100A4 decreased the levels of this protein and caused a chemosensitization in combined treatments with MTX. β-catenin overexpression experiments support a possible involvement of the Wnt signaling pathway in S100A4 transcriptional regulation in HT29 cells.

Conclusions

S100A4 is overexpressed in many MTX-resistant cells. S100A4 overexpression decreases the sensitivity of HT29 colon cancer human cells to MTX, whereas its knockdown causes chemosensitization toward MTX. Both approaches highlight a role for S100A4 in MTX resistance.