The reconstruction of transcriptional networks reveals critical genes with implications for clinical outcome of multiple myeloma

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival.

Correlation of changes in subclonal architecture with progression in the MMRF CoMMpass study

Multiple myeloma (MM) is a heterogeneous plasma cell proliferative disorder that arises from its premalignant precursor stages through a complex cascade of interactions between clonal mutations and co-evolving microenvironment. The temporo-spatial evolutionary trajectories of MM are established early during myelomatogenesis in precursor stages and retained in MM. Such molecular events impact subsequent disease progression and clinical outcomes. Identification of clonal sweeps of actionable gene targets in MM could reveal potential vulnerabilities that may exist in early stages and thus potentiate prognostication and customization of early therapeutic interventions. We have evaluated clonal evolution at multiple time points in 76 MM patients enrolled in the MMRF CoMMpass study. The major findings of this study are (a) MM progresses predominantly through branching evolution, (b) there is a heterogeneous spectrum of mutational landscapes that include unique actionable gene targets at diagnosis compared to progression, (c) unique clonal gains/ losses of mutant driver genes can be identified in patients with different cytogenetic aberrations, (d) there is a significant correlation between co-occurring oncogenic mutations/ co-occurring subclones e.g., with mutated TP53+SYNE1, NRAS+MAGI3, and anticorrelative dependencies between FAT3+FCGBP gene pairs. Such co-trajectories may synchronize molecular events of drug response, myelomatogenesis and warrant future studies to explore their potential for early prognostication and development of risk stratified personalized therapies in MM.

Glycogenes in Oncofetal Chondroitin Sulfate Biosynthesis are Differently Expressed and Correlated With Immune Response in Placenta and Colorectal Cancer

Oncofetal chondroitin sulfate expression plays an important role in the development of tumors and the pathogenesis of malaria in pregnancy. However, the biosynthesis and functions of these chondroitin sulfates, particularly the tissue-specific regulation either in tumors or placenta, have not been fully elucidated. Here, by examining the glycogenes availability in chondroitin sulfate biosynthesis such as xylosytransferase, chondroitin synthase, sulfotransferase, and epimerase, the conserved or differential CS glycosylation in normal, colorectal cancer (CRC), and placenta tissue were predicted. We found that the expression of seven chondroitin sulfate biosynthetic enzymes, namely B4GALT7, B3GALT6, B3GAT3, CHSY3, CHSY1, CHPF, and CHPF2, were significantly increased, while four other enzymes (XYLT1, CHST7, CHST15, and UST) were decreased in the colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) patients. In the human placenta, where the distinct chondroitin sulfate is specifically bound with VAR2CSA on Plasmodium parasite-infected RBC, eight chondroitin sulfate biosynthesis enzymes (CSGALNACT1, CSGALNACT2, CHSY3, CHSY1, CHPF, DSE, CHST11, and CHST3) were significantly higher than the normal colon tissue. The similarly up-regulated chondroitin synthases (CHSY1, CHSY3, and CHPF) in both cancer tissue and human placenta indicate an important role of the proteoglycan CS chains length for Plasmodium falciparum VAR2CSA protein binding. Interestingly, twelve highly expressed chondroitin sulfate enzymes were significantly correlated to worse outcomes (prognosis) in both COAD and READ. Furthermore, we showed that the levels of chondroitin sulfate enzymes are significantly correlated with the expression of immuno-regulators and immune infiltration levels in CRCs and placenta, and involved in multiple essential pathways, such as extracellular matrix organization, epithelial-mesenchymal transition, and cell adhesion. Our study provides novel insights into the oncofetal chondroitin sulfate biosynthesis regulation and identifies promising targets and biomarkers of immunotherapy for CRC and malaria in pregnancy.

Analysis of Genetic Alterations Related to DNA Methylation in Testicular Germ Cell Tumors Based on Data Mining

Embryonal carcinoma (EC) and seminoma (SE) are both derived from germ cell neoplasia in situ but show big differences in growth patterns and clinical prognosis. Epigenetic regulation may play an important role in the development of EC and SE. This study investigated the DNA methylation-based genetic alterations between EC and SE by analyzing the datasets of mRNA expression and DNA methylation profiling. The datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified between EC and SE by limma package in R environment. Gene function enrichment analysis of the DEGs was performed on the DAVID tool, the results of which suggested differences in capability of pluripotency and genomic stability between EC and SE. The minfi package and wANNOVAR tool were used to identify differentially methylated genes. A total of 37 genes were discovered with both mRNA expression and the accordant DNA methylation changes. The findings were verified by the sequencing data from The Cancer Genome Atlas database, and Kaplan-Meier survival analysis was performed. Finally, 5 genes (PRDM1, LMO2, FAM53B, HCN4, and FAM124B) were found that showed both low expression and high methylation in EC, and were significantly associated with relapse-free survival. The findings of methylation-based genetic features between EC and SE might be helpful in studying the role of DNA methylation in cancer development.

Mechanism-Centric Approaches for Biomarker Detection and Precision Therapeutics in Cancer

Biomarker discovery is at the heart of personalized treatment planning and cancer precision therapeutics, encompassing disease classification and prognosis, prediction of treatment response, and therapeutic targeting. However, many biomarkers represent passenger rather than driver alterations, limiting their utilization as functional units for therapeutic targeting. We suggest that identification of driver biomarkers through mechanism-centric approaches, which take into account upstream and downstream regulatory mechanisms, is fundamental to the discovery of functionally meaningful markers. Here, we examine computational approaches that identify mechanism-centric biomarkers elucidated from gene co-expression networks, regulatory networks (e.g., transcriptional regulation), protein-protein interaction (PPI) networks, and molecular pathways. We discuss their objectives, advantages over gene-centric approaches, and known limitations. Future directions highlight the importance of input and model interpretability, method and data integration, and the role of recently introduced technological advantages, such as single-cell sequencing, which are central for effective biomarker discovery and time-cautious precision therapeutics.

Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes. We identified 141 genetic programs whose activity profiles stratify patients into 25 distinct transcriptional states and proved to be more predictive of outcomes than did mutations. The coherence of these programs and accuracy of our network-based risk prediction was validated in two independent datasets. We observed subtype-specific vulnerabilities to interventions with existing drugs and revealed plausible mechanisms for relapse, including the establishment of an immunosuppressive microenvironment. Investigation of the t(4;14) clinical subtype using the TRN revealed that 16% of these patients exhibit an extreme-risk combination of genetic programs (median progression-free survival of 5 months) that create a distinct phenotype with targetable genes and pathways.

SLC7A7 is a prognostic biomarker correlated with immune infiltrates in non-small cell lung cancer

Background

SLC7A7 (solute carrier family 7, amino acid transporter light chain, y + L system, member 7) is a critical gene in the regulation of cationic amino acid transport. However, the relationships between SLC7A7 and prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear.

Methods

SLC7A7 expression was analyzed using the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. The enrichment of the GO (Gene Oncology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was conducted by DAVID. We evaluated the influence of SLC7A7 on clinical prognosis using the PrognoScan database. The functional state of SLC7A7 in various types of cancers was analyzed by CancerSEA. The relationships between SLC7A7 and cancer immune infiltrates was investigated by TIMER. Furthermore, correlations between SLC7A7 expression and gene marker sets of immune infiltrates were analyzed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). The expression of SLC7A7 was verified by GEO database and immunohistochemistry.

Results

A lung cancer cohort study (GSE31210) showed that high SLC7A7 expression was associated with poor overall survival (OS) and relapse-free survival (RFS). In addition, SLC7A7 had a significant impact on the prognosis of diverse cancers. SLC7A7 expression was positively correlated with infiltrating levels of CD4 + and CD8 + T cells, macrophages, neutrophils and dendritic cells (DCs) in non-small cell lung cancer (NSCLC). SLC7A7 expression was also strongly correlated with various immune marker sets in NSCLC.

Conclusions

These results indicated a role for SLC7A7 in infiltration of CD8 + T cells, CD4 + T cells, tumor-associated macrophages (TAMs), neutrophils and DCs in multiple cancers, and regulation of T cell exhaustion and Tregs in NSCLC. These findings suggest that SLC7A7 could be served as a biomarker for prognosis and immune infiltration in NSCLC.

Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients

Multiple myeloma (MM) is a malignant plasma cell tumor with high heterogeneity, characterized by anemia, hypercalcemia, renal failure, and lytic bone lesions. Although various powerful prognostic factors and models have been exploited, the development of more accurate prognosis and treatment for MM patients is still facing many challenges. Given the essential roles of super-enhancer (SE) associated genes in the tumorigenesis of MM, we tried to initially screen and identify the significant prognostic factors from SE associated genes in MM by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis using GSE24080 and GSE9782 datasets. Risk score model of five genes including CSGALNACT1, FAM53B, TAPBPL, REPIN1, and DDX11, was further constructed and the Kaplan-Meier (K-M) curves showed that the low-risk group seems to have better clinical outcome of survival compared to the high-risk group. Time-dependent receiver operating characteristic (ROC) curves presented the favorable performance of the model. An interactive nomogram consisting of the five-gene risk group and eleven clinical traits was established and identified by calibration curves. Therefore, the risk score model of SE associated five genes developed here could be used to predict the prognosis of MM patients, which may assist the clinical treatment of MM patients in the future.

Prognostic value of Kinesin-4 family genes mRNA expression in early-stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy

BACKGROUND

The aim of this study was to investigate the potential prognostic value of Kinesin-4 family genes mRNA expression in early-stage pancreatic ductal adenocarcinoma (PDAC) patients after pancreaticoduodenectomy.

METHODS

Kaplan-Meier survival analysis method with log-rank test and Cox proportional hazards regression analysis were performed to figure out the association between Kinesin-4 family genes expression and PDAC patients overall survival time. Joint-effect survival analysis and stratified survival analysis were carried out to assess the prognosis prediction value of prognosis-related gene. Nomogram was constructed for the individualized prognosis prediction. In addition, we had used the gene set enrichment analysis and genome-wide co-expression analysis to further explore the potential mechanism.

RESULTS

KIF21A expression level was significantly associated with PDAC patient clinical prognosis outcome and patient with a high expression of KIF21A would have a shorter overall survival time. The prognosis prediction significance of KIF21A was well validated by the joint-effect survival analysis, stratified survival analysis, and nomogram. Meanwhile, the gene set enrichment analysis and genome-wide co-expression analysis revealed that KIF21A might involve in DNA damage and repair, transcription and translation process, post-translation protein modification, cell cycle, carcinogensis genes and pathways.

CONCLUSIONS

Our current research demonstrated that KIF21A could serve as a potential prognostic biomarker for patient with early-stage PDAC after pancreaticoduodenectomy.

Clinicopathologic and Prognostic Significance of Thymopoietin-α Overexpression in Gastric Cancer

As one of the deadliest and most common malignancies in the world, gastric cancer (GC) represents a serious health threat. Despite recent advances in the field, the prognosis of patients with metastatic GC remains poor. In this study, we aimed to investigate the clinical impact of the alpha subunit of the nuclear structural protein thymopoietin (TMPO-α) in GC. The expression of TMPO-α in seven gastric cell lines was detected by immunoblotting. The expression level of TMPO-α levels in gastric tissues collected from 145 GC patients was examined by immunohistochemistry. The correlations between TMPO-α expression level and clinicopathologic parameters, as well as the association of TMPO-α expression with overall survival, were assessed. Immunohistochemistry showed that the expression of TMPO-α was significantly higher in GC tissues and cells in comparison with non-tumor tissues and cells. Furthermore, the overexpression of TMPO-α in gastric tissues (56%) was positively associated with Lauren classification (P = 0.0159), nodal status (P = 0.0265), distant metastasis (P < 0.0001), stage (P = 0.0367), and degree of differentiation (P = 0.0009). Patients with high TMPO-α levels had a significantly poorer overall survival than those with low levels (P = 0.001). Multivariate Cox regression analysis also indicated that TMPO-α was an independent prognostic marker for GC (P = 0.045). In addition, studies conducted in GC cells indicated that knockdown of TMPO-α suppressed cell proliferation and invasion. These findings indicate that TMPO-α overexpression can predict clinicopathologic features and the outcome of patients with GC.

Long Noncoding RNA MIR17HG Promotes Colorectal Cancer Progression via miR-17-5p

Immune dysregulation plays a vital role in colorectal cancer initiation and progression. Long noncoding RNAs (lncRNA) exhibit multiple functions including regulation of gene expression. Here, we identified an immune-related lncRNA, MIR17HG, whose expression was gradually upregulated in adjacent, adenoma, and colorectal cancer tissue. MIR17HG promoted tumorigenesis and metastasis in colorectal cancer cells both in vitro and in vivo. Mechanistically, MIR17HG increased the expression of NF-κB/RELA by competitively sponging the microRNA miR-375. In addition, RELA transcriptionally activated MIR17HG in a positive feedback loop by directly binding to its promoter region. Moreover, miR-17-5p, one of the transcribed miRNAs from MIR17HG, reduced the expression of the tumor suppressor B-cell linker (BLNK), resulting in increased migration and invasion of colorectal cancer cells. MIR17HG also upregulated PD-L1, indicating its potential role in immunotherapy. Overall, these findings demonstrate that MIR17HG plays an oncogenic role in colorectal cancer and may serve as a promising therapeutic target. SIGNIFICANCE: These findings provide mechanistic insight into the role of the lncRNA MIR17HG and its miRNA members in regulating colorectal cancer carcinogenesis and progression.

Silencing RRM2 inhibits multiple myeloma by targeting the Wnt/β‑catenin signaling pathway

Ribonucleotide reductase M2 (RRM2) is one of the two subunits that comprise ribonucleotide reductase (RR), the enzyme that catalyzes the conversion of ribonucleotide 5'‑diphosphates into 2'‑deoxyribonucleotides, which are required for DNA synthesis. RRM2 is a stress response factor important for the development of several tumors. However, its role in multiple myeloma (MM) remains to be fully elucidated. The present study aimed to investigate the role of RRM2 in MM. The expression of RRM2 in patients with MM was analyzed using the Oncomine database. The results demonstrated that RRM2 expression was higher in MM compared with healthy subjects. Reverse transcription‑quantitative polymerase chain reaction and western blot results revealed that RRM2 expression was decreased following transfection with a small interfering RNA targeting RRM2 into NCI‑H929 cells. RR activity and Cell Counting Kit‑8 assays demonstrated that RRM2 silencing reduced RR activity and inhibited cell proliferation. Annexin V‑propidium iodide staining indicated that the percentage of apoptotic NCI‑H929 cells was increased following RRM2 silencing compared with that in the control group. Increased phosphorylation of H2AX indicated that RRM2 silencing may activate the DNA‑damage response pathway in NCI‑H929 cells. Western blot analysis revealed that protein levels of the apoptosis‑associated factor Bcl‑2 were reduced, whereas Bax, cleaved caspase‑3 and cleaved poly(ADP‑ribose) polymerase 1 were upregulated following RRM2 silencing compared with the control group. In addition, the results demonstrated that RRM2 silencing may inhibit target gene expression in the Wnt/β‑catenin signaling pathway by increasing the phosphorylation of glucose synthase kinase 3β. These findings indicated that RRM2 may be involved in the proliferation and apoptosis of MM cells via the Wnt/β‑catenin signaling pathway, suggesting that RRM2 may represent a novel therapeutic target for MM.

[Effect of 1q21 amplification on bortezomib therapeutic response and prognosis of newly diagnosed multiple myeloma patients]

Objective: To investigate the effect of 1q21 amplification (1q) on the therapeutic response and prognosis of bortezomib(Btz) in the treatment of newly diagnosed multiple myeloma (MM) patients. Methods: A total of 180 newly diagnosed MM were included for analyses of clinical characteristics, cytogenetics, objective response rate (ORR), progression-free survival (PFS) and overall survival (OS), retrospectively. Gene expression profiling (GEP) was analyzed using publicly available R2 platform. Results: ① In 180 patients, 1q was found in 51.1% cases. Of them, 174 patients had complete follow-up data, including 88 cases with 1q and 86 without 1q (non-1q). ②Incidence of 1q was positively associated with percentage of IGH rearrangement (72.2%, P=0.017) and 1p deletion (1p) (27.8%, P=0.040). ③ The median PFS was 15.0 and 20.3 months for the 1q group and non-1q group, and the median OS was 29.4 and 44.0 months, respectively. Both PFS and OS of 1q group was significantly shorter than those of the non-1q group (P=0.029 and 0.038, respectively). Multivariate analysis further revealed that 1q was an independent prognostic factor for both PFS (HR=1.910, 95% CI 1.105-3.303, P=0.020) and OS (HR=2.353, 95% CI 1.090-5.078, P=0.029). ④ In 91 evaluable cases with 1q, very good partial remission (VGPR) rate was higher after treatment with Btz than those without Btz (62.1% vs 40.0%, P=0.032). Of note, the patients with 1q who received auto-HSCT after induction with Btz had significantly longer PFS than those without auto-HSCT (19 months vs 13 months, P=0.048). ⑤GEP analysis revealed that 1q21 amplification predominantly up-regulated expression of >50% genes within 1q21 region, and also altered expression of 28% genes in chromosome 1 and 10% genes in whole genome, particularly related to DNA repair and cell cycle. Conclusions: 1q is an independent adverse prognostic factor in patients with newly diagnosed MM. It is often associated with 1p deletion and IGH rearrangement. Patients with 1q respond well to Btz-based regimen, but they fail to gain long-term benefit from this treatment itself. However, auto-HSCT following Btz induction might improve survival of patients with 1q, suggesting a potential strategy to treat this high-risk subset of MM. GEP analysis warrants further attention in understanding the mechanisms underlying the high-risk of 1q.

Multiple myeloma-derived exosomes are enriched of amphiregulin (AREG) and activate the epidermal growth factor pathway in the bone microenvironment leading to osteoclastogenesis

Background

Multiple myeloma (MM) is a clonal plasma cell malignancy associated with osteolytic bone disease. Recently, the role of MM-derived exosomes in the osteoclastogenesis has been demonstrated although the underlying mechanism is still unknown. Since exosomes-derived epidermal growth factor receptor ligands (EGFR) are involved in tumor-associated osteolysis, we hypothesize that the EGFR ligand amphiregulin (AREG) can be delivered by MM-derived exosomes and participate in MM-induced osteoclastogenesis.

Methods

Exosomes were isolated from the conditioned medium of MM1.S cell line and from bone marrow (BM) plasma samples of MM patients. The murine cell line RAW264.7 and primary human CD14⁺ cells were used as osteoclast (OC) sources.

Results

We found that AREG was specifically enriched in exosomes from MM samples and that exosomes-derived AREG led to the activation of EGFR in pre-OC, as showed by the increase of mRNA expression of its downstream SNAIL in both RAW264.7 and CD14⁺ cells. The presence of neutralizing anti-AREG monoclonal antibody (mAb) reverted this effect. Consequently, we showed that the effect of MM-derived exosomes on osteoclast differentiation was inhibited by the pre-treatment of exosomes with anti-AREG mAb. In addition, we demonstrated the ability of MM-derived AREG-enriched exosomes to be internalized into human mesenchymal stromal cells (MSCs) blocking osteoblast (OB) differentiation, increasing MM cell adhesion and the release of the pro-osteoclastogenic cytokine interleukin-8 (IL8). Accordingly, anti-AREG mAb inhibited the release of IL8 by MSCs suggesting that both direct and indirect effects are responsible for AREG-enriched exosomes involvement on MM-induced osteoclastogenesis.

Conclusions

In conclusion, our data indicate that AREG is packed into MM-derived exosomes and implicated in OC differentiation through an indirect mechanism mediated by OBs.

Electronic supplementary material

The online version of this article (10.1186/s13045-018-0689-y) contains supplementary material, which is available to authorized users.

Noncanonical SQSTM1/p62-Nrf2 pathway activation mediates proteasome inhibitor resistance in multiple myeloma cells via redox, metabolic and translational reprogramming

Multiple Myeloma (MM) is a B-cell malignancy characterized by the accumulation of clonal plasma cells in the bone marrow, with drug resistance being a major cause of therapeutic failure. We established a carfilzomib-resistant derivative of the LP-1 MM cell line (LP-1/Cfz) and found that the transcription factor NF-E2 p45-related factor 2 (Nrf2; gene symbol NFE2L2) contributes to carfilzomib resistance. The mechanism of Nrf2 activation involved enhanced translation of Nrf2 as well as its positive regulator, the autophagy receptor sequestosome 1 (SQSTM1)/p62. The eukaryotic translation initiation factor gene EIF4E3 was among the Nrf2 target genes upregulated in LP-1/Cfz cells, suggesting existence of a positive feedback loop. In line with this, we found that siRNA knockdown of eIF4E3 decreased Nrf2 protein levels. On the other hand, elevated SQSTM1/p62 levels were due at least in part to activation of the PERK-eIF2α pathway. LP-1/Cfz cells had decreased levels of reactive oxygen species as well as elevated levels of fatty acid oxidation and prosurvival autophagy. Genetic and pharmacologic inhibition of the Nrf2-EIF4E3 axis or the PERK-eIF2α pathway, disruption of redox homeostasis or inhibition of fatty acid oxidation or autophagy conferred sensitivity to carfilzomib. Our findings were supported by clinical data where increased EIF4E3 expression was predictive of Nrf2 target gene upregulation in a subgroup of patients with chemoresistant minimal residual disease and relapsed/refractory MM. Thus, our data offer a preclinical rationale for including inhibitors of the SQSTM1/p62-Nrf2 pathway to the treatment regimens for certain advanced stage MM patients.

TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer

TP53 overexpression is indicative of somatic TP53 mutations and associates with aggressive tumors and poor prognosis in breast cancer. We utilized a two-stage SNP association study to detect variants associated with breast cancer survival in a TP53-dependent manner. Initially, a genome-wide study (n = 575 cases) was conducted to discover candidate SNPs for genotyping and validation in the Breast Cancer Association Consortium (BCAC). The SNPs were then tested for interaction with tumor TP53 status (n = 4,610) and anthracycline treatment (n = 17,828). For SNPs interacting with anthracycline treatment, siRNA knockdown experiments were carried out to validate candidate genes.In the test for interaction between SNP genotype and TP53 status, we identified one locus, represented by rs10916264 (p(interaction) = 3.44 × 10-5; FDR-adjusted p = 0.0011) in estrogen receptor (ER) positive cases. The rs10916264 AA genotype associated with worse survival among cases with ER-positive, TP53-positive tumors (hazard ratio [HR] 2.36, 95% confidence interval [C.I] 1.45 - 3.82). This is a cis-eQTL locus for FBXO28 and TP53BP2; expression levels of these genes were associated with patient survival specifically in ER-positive, TP53-mutated tumors. Additionally, the SNP rs798755 was associated with survival in interaction with anthracycline treatment (p(interaction) = 9.57 × 10-5, FDR-adjusted p = 0.0130). RNAi-based depletion of a predicted regulatory target gene, FAM53A, indicated that this gene can modulate doxorubicin sensitivity in breast cancer cell lines.If confirmed in independent data sets, these results may be of clinical relevance in the development of prognostic and predictive marker panels for breast cancer.

The genetic and genomic background of multiple myeloma patients achieving complete response after induction therapy with bortezomib, thalidomide and dexamethasone (VTD)

The prime focus of the current therapeutic strategy for Multiple Myeloma (MM) is to obtain an early and deep tumour burden reduction, up to the level of complete response (CR). To date, no description of the characteristics of the plasma cells (PC) prone to achieve CR has been reported. This study aimed at the molecular characterization of PC obtained at baseline from MM patients in CR after bortezomib-thalidomide-dexamethasone (VTD) first line therapy.

One hundred and eighteen MM primary tumours obtained from homogeneously treated patients were profiled both for gene expression and for single nucleotide polymorphism genotype. Genomic results were used to obtain a predictor of sensitivity to VTD induction therapy, as well as to describe both the transcription and the genomic profile of PC derived from MM with subsequent optimal response to primary induction therapy.

By analysing the gene profiles of CR patients, we identified a 5-gene signature predicting CR with an overall median accuracy of 75% (range: 72%–85%). In addition, we highlighted the differential expression of a series of genes, whose deregulation might explain patients' sensitivity to VTD therapy. We also showed that a small copy number loss, covering 606Kb on chromosome 1p22.1 was the most significantly associated with CR patients.

Dependence on glutamine uptake and glutamine addiction characterize myeloma cells: a new attractive target

The importance of glutamine (Gln) metabolism in multiple myeloma (MM) cells and its potential role as a therapeutic target are still unknown, although it has been reported that human myeloma cell lines (HMCLs) are highly sensitive to Gln depletion. In this study, we found that both HMCLs and primary bone marrow (BM) CD138(+) cells produced large amounts of ammonium in the presence of Gln. MM patients have lower BM plasma Gln with higher ammonium and glutamate than patients with indolent monoclonal gammopathies. Interestingly, HMCLs expressed glutaminase (GLS1) and were sensitive to its inhibition, whereas they exhibited negligible expression of glutamine synthetase (GS). High GLS1 and low GS expression were also observed in primary CD138(+) cells. Gln-free incubation or treatment with the glutaminolytic enzyme l-asparaginase depleted the cell contents of Gln, glutamate, and the anaplerotic substrate 2-oxoglutarate, inhibiting MM cell growth. Consistent with the dependence of MM cells on extracellular Gln, a gene expression profile analysis, on both proprietary and published datasets, showed an increased expression of the Gln transporters SNAT1, ASCT2, and LAT1 by CD138(+) cells across the progression of monoclonal gammopathies. Among these transporters, only ASCT2 inhibition in HMCLs caused a marked decrease in Gln uptake and a significant fall in cell growth. Consistently, stable ASCT2 downregulation by a lentiviral approach inhibited HMCL growth in vitro and in a murine model. In conclusion, MM cells strictly depend on extracellular Gln and show features of Gln addiction. Therefore, the inhibition of Gln uptake is a new attractive therapeutic strategy for MM.

Galectin-1 suppression delineates a new strategy to inhibit myeloma-induced angiogenesis and tumoral growth in vivo

Galectin-1 (Gal-1) is involved in tumoral angiogenesis, hypoxia and metastases. Actually the Gal-1 expression profile in multiple myeloma (MM) patients and its pathophysiological role in MM-induced angiogenesis and tumoral growth are unknown. In this study, we found that Gal-1 expression by MM cells was upregulated in hypoxic conditions and that stable knockdown of hypoxia inducible factor-1α significantly downregulated its expression. Therefore, we performed Gal-1 inhibition using lentivirus transfection of shRNA anti-Gal-1 in human myeloma cell lines (HMCLs), and showed that its suppression modified transcriptional profiles in both hypoxic and normoxic conditions. Interestingly, Gal-1 inhibition in MM cells downregulated proangiogenic genes, including MMP9 and CCL2, and upregulated the antiangiogenic ones SEMA3A and CXCL10. Consistently, Gal-1 suppression in MM cells significantly decreased their proangiogenic properties in vitro. This was confirmed in vivo, in two different mouse models injected with HMCLs transfected with anti-Gal-1 shRNA or the control vector. Gal-1 suppression in both models significantly reduced tumor burden and microvascular density as compared with the control mice. Moreover, Gal-1 suppression induced smaller lytic lesions on X-ray in the intratibial model. Overall, our data indicate that Gal-1 is a new potential therapeutic target in MM blocking angiogenesis.

Drug metabolism and clearance system in tumor cells of patients with multiple myeloma

Resistance to chemotherapy is a major limitation of cancer treatments with several molecular mechanisms involved, in particular altered local drug metabolism and detoxification process. The role of drug metabolism and clearance system has not been satisfactorily investigated in Multiple Myeloma (MM), a malignant plasma cell cancer for which a majority of patients escapes treatment. The expression of 350 genes encoding for uptake carriers, xenobiotic receptors, phase I and II Drug Metabolizing Enzymes (DMEs) and efflux transporters was interrogated in MM cells (MMCs) of newly-diagnosed patients in relation to their event free survival. MMCs of patients with a favourable outcome have an increased expression of genes coding for xenobiotic receptors (RXRα, LXR, CAR and FXR) and accordingly of their gene targets, influx transporters and phase I/II DMEs. On the contrary, MMCs of patients with unfavourable outcome displayed a global down regulation of genes coding for xenobiotic receptors and the downstream detoxification genes but had a high expression of genes coding for ARNT and Nrf2 pathways and ABC transporters. Altogether, these data suggests ARNT and Nrf2 pathways could be involved in MM primary resistance and that targeting RXRα, PXR, LXR and FXR through agonists could open new perspectives to alleviate or reverse MM drug resistance.

Detection of Critical Genes Associated with Overall Survival (OS) and Progression-Free Survival (PFS) in Reconstructed Canine B-Cell Lymphoma Gene Regulatory Network (GRN)

Canine B-cell lymphoma GRN was reconstructed from gene expression data in the STRING and MiMI databases. Critical genes of networks were identified and correlations of critical genes with overall survival (OS) and progression-free survival (PFS) were evaluated. Significant changes were detected in the expressions of GLUL, CD44, CD79A, ARF3, FOS, BLOC1S1, FYN, GZMB, GALNT3, IFI44, CD3G, GNG2, ESRP1, and CCND1 in the STRING network and of PECAM1, GLUL, CD44, GDI1, E2F4, TLE1, CD79A, UCP2, CCND1, FYN, RHOQ, BIN1, and A2M in the MiMI network. Final survival analysis highlighted CCND1 and FOS as genes with significant correlations with OS and PFS.

Regulatory network reconstruction reveals genes with prognostic value for chronic lymphocytic leukemia

Background

The clinical course of chronic lymphocytic leukemia (CLL) is highly variable; some patients follow an indolent course, but others progress to a more advanced stage. The mutational status of rearranged immunoglobulin heavy chain variable (IGVH) genes in CLL is a feature that is widely recognized for dividing patients into groups that are related to their prognoses. However, the regulatory programs associated with the IGVH statuses are poorly understood, and markers that can precisely predict survival outcomes have yet to be identified.

Methods

In this study, (i) we reconstructed gene regulatory networks in CLL by applying an information-theoretic approach to the expression profiles of 5 cohorts. (ii) We applied master regulator analysis (MRA) to these networks to identify transcription factors (TFs) that regulate an IGVH mutational status signature. The IGVH mutational status signature was developed by searching for differentially expressed genes between the IGVH mutational statuses in numerous CLL cohorts. (iii) To evaluate the biological implication of the inferred regulators, prognostic values were determined using time to treatment (TTT) and overall survival (OS) in two different cohorts.

Results

A robust IGVH expression signature was obtained, and various TFs emerged as regulators of the signature in most of the reconstructed networks. The TF targets expression profiles exhibited significant differences with respect to survival, which allowed the definition of a reduced profile with a high value for OS. TCF7 and its targets stood out for their roles in progression.

Conclusion

TFs and their targets, which were obtained merely from inferred regulatory associations, have prognostic implications and reflect a regulatory context for prognosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2189-6) contains supplementary material, which is available to authorized users.

Identification of the key genes connected with plasma cells of multiple myeloma using expression profiles

Objective

To uncover the potential regulatory mechanisms of the relevant genes that contribute to the prognosis and prevention of multiple myeloma (MM).

Methods

Microarray data (GSE13591) were downloaded, including five plasma cell samples from normal donors and 133 plasma cell samples from MM patients. Differentially expressed genes (DEGs) were identified by Student’s t-test. Functional enrichment analysis was performed for DEGs using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Transcription factors and tumor-associated genes were also explored by mapping genes in the TRANSFAC, the tumor suppressor gene (TSGene), and tumor-associated gene (TAG) databases. A protein–protein interaction (PPI) network and PPI subnetworks were constructed by Cytoscape software using the Search Tool for the Retrieval of Interacting Genes (STRING) database.

Results

A total of 63 DEGs (42 downregulated, 21 upregulated) were identified. Functional enrichment analysis showed that HLA-DRB1 and VCAM1 might be involved in the positive regulation of immune system processes, and HLA-DRB1 might be related to the intestinal immune network for IgA production pathway. The genes CEBPD, JUND, and ATF3 were identified as transcription factors. The top ten nodal genes in the PPI network were revealed including HLA-DRB1, VCAM1, and TFRC. In addition, genes in the PPI subnetwork, such as HLA-DRB1 and VCAM1, were enriched in the cell adhesion molecules pathway, whereas CD4 and TFRC were both enriched in the hematopoietic cell pathway.

Conclusion

Several crucial genes correlated to MM were identified, including CD4, HLA-DRB1, TFRC, and VCAM1, which might exert their roles in MM progression via immune-mediated pathways. There might be certain regulatory correlations between HLA-DRB1, CD4, and TFRC.

Reconstruction of canine diffuse large B-cell lymphoma gene regulatory network: detection of functional modules and hub genes

Lymphoma is one of the most common malignancies in dogs. Canine lymphoma is similar to human non-Hodgkin's lymphoma (NHL) with shared clinical presentation and histopathological features. This study reports the construction of a comprehensive gene regulatory network (GRN) for canine diffuse large B-cell lymphoma (DLBCL), the most common type of canine lymphoma, and performs analysis for detection of major functional modules and hub genes (the most important genes in a GRN). The canine DLBCL GRN was reconstructed from gene expression data (NCBI GEO dataset: GSE30881) using the STRING and MiMI interaction databases. Reconstructed GRNs were then assessed, using various bioinformatics programmes, in order to analyze network topology and identify major pathways and hub genes. The resultant network from both interaction databases had a logically scale-free pattern. Gene ontology (GO) analysis revealed cell activation, cell cycle phase, immune effector process, immune system development, immune system process, integrin-mediated signalling pathway, intracellular protein kinase cascade, intracellular signal transduction, leucocyte activation and differentiation, lymphocyte activation and differentiation as major GO terms in the biological processes of the networks. Moreover, bioinformatics analysis showed E2F1, E2F4, PTEN, CDKN1A, PCNA, DKC1, MNAT1, NDUFB4, ATP5J, PRKDC, BRCA1, MYCN, RFC4 and POLA1 as the most important hub genes. The phosphatidyl inositol signalling system, P53 signalling pathway, Rac CycD pathway, G1/S checkpoint, chemokine signalling pathway and telomere maintenance were the main signalling pathways in which the protein products of the hub genes are involved.

Comparison of microarray expression profiles between follicular variant of papillary thyroid carcinomas and follicular adenomas of the thyroid

Background

Follicular variant of papillary thyroid carcinoma (FVPTC) and follicular adenoma (FA) are histologically closely related tumors and differential diagnosis remains challenging. RNA expression profiling is an established method to unravel molecular mechanisms underlying the histopathology of diseases.

Methods

BRAF mutational status was established by direct sequencing the hotspot region of exon 15 in six FVPTCs and seven FAs. Whole-transcript arrays were employed to generate expression profiles in six FVPTCs, seven FAs and seven normal thyroid tissue samples. The threshold of significance for differential expression on the gene and exon level was a p-value with a false discovery rate (FDR) < 0.05 and a fold change cutoff > 2. Two dimensional average linkage hierarchical clustering was generated using differentially expressed genes. Network, pathway, and alternative splicing utilities were employed to interpret significance of expression data on the gene and exon level.

Results

Expression profiling in FVPTCs and FAs, all of which were negative for a BRAF mutation, revealed 55 transcripts that were significantly differentially expressed, 40 of which were upregulated and 15 downregulated in FVPTCs vs. FAs. Amongst the most significantly upregulated genes in FVPTCs were GABA B receptor, 2 (GABBR2), neuronal cell adhesion molecule (NRCAM), extracellular matrix protein 1 (ECM1), heparan sulfate 6-O-sulfotransferase 2 (HS6ST2), and retinoid X receptor, gamma (RXRG). The most significantly downregulated genes in FVPTCs included interaction protein for cytohesin exchange factors 1 (IPCEF1), G protein-coupled receptor 155 (GPR155), Purkinje cell protein 4 (PCP4), chondroitin sulfate N-acetylgalactosaminyltransferase 1 (CSGALNACT1), and glutamate receptor interacting protein 1 (GRIP1). Alternative splicing analysis detected 87 genes, 52 of which were also included in the list of 55 differentially expressed genes. Network analysis demonstrated multiple interactions for a number of differentially expressed molecules including vitamin D (1,25- dihydroxyvitamin D3) receptor (VDR), SMAD family member 9 (SMAD9), v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT), and RXRG.

Conclusions

This is one of the first studies using whole-transcript expression arrays to compare expression profiles between FVPTCs and FAs. A set of differentially expressed genes has been identified that contains valuable candidate genes to differentiate both histopathologically related tumor types on the molecular level.

Utilization of translational bioinformatics to identify novel biomarkers of bortezomib resistance in multiple myeloma

Multiple myeloma (MM) is an incurable malignant neoplasm hallmarked by a clonal expansion of plasma cells, the presence of a monoclonal protein in the serum and/or urine (M-spike), lytic bone lesions, and end organ damage. Clinical outcomes for patients with MM have improved greatly over the last decade as a result of the re-purposing of compounds such as thalidomide derivatives, as well as the development of novel chemotherapeutic agents including first and second generation proteasome inhibitors, bortezomib (Bz) and carfilzomib. Unfortunately, despite these improvements, the majority of patients relapse following treatment. While Bz, one of the most commonly used proteasome inhibitors, has been successfully incorporated into clinical practice, some MM patients have de novo resistance to Bz, and the majority of the remainder subsequently develop drug resistance following treatment. A significant gap in clinical care is the lack of a reliable clinical test that would predict which MM patients have or will subsequently develop Bz resistance. Thus, as Bz resistance remains a significant challenge, research efforts are needed to identify novel biomarkers of early Bz resistance, particularly when an early therapeutic intervention can be initiated. Recent advances in MM research indicate that genomic data can be extracted to identify novel biomarkers that can be utilized to select more effective, personalized treatment protocols for individual patients. Computationally integrating large patient databases with data from whole transcriptome profiling and laboratory-based models can potentially revolutionize our understanding of MM disease mechanisms. This systems-wide approach can provide rational therapeutic targets and novel biomarkers of risk and treatment response. In this review, we discuss the use of high-content datasets (predominantly gene expression profiling) to identify novel biomarkers of treatment response and resistance to Bz in MM.

Simplet/Fam53b is required for Wnt signal transduction by regulating β-catenin nuclear localization

Canonical β-catenin-dependent Wnt signal transduction is important for several biological phenomena, such as cell fate determination, cell proliferation, stem cell maintenance and anterior-posterior axis formation. The hallmark of canonical Wnt signaling is the translocation of β-catenin into the nucleus where it activates gene transcription. However, the mechanisms regulating β-catenin nuclear localization are poorly understood. We show that Simplet/Fam53B (Smp) is required for Wnt signaling by positively regulating β-catenin nuclear localization. In the zebrafish embryo, the loss of smp blocks the activity of two β-catenin-dependent reporters and the expression of Wnt target genes, and prevents nuclear accumulation of β-catenin. Conversely, overexpression of smp increases β-catenin nuclear localization and transcriptional activity in vitro and in vivo. Expression of mutant Smp proteins lacking either the nuclear localization signal or the β-catenin interaction domain reveal that the translocation of Smp into the nucleus is essential for β-catenin nuclear localization and Wnt signaling in vivo. We also provide evidence that mammalian Smp is involved in regulating β-catenin nuclear localization: the protein colocalizes with β-catenin-dependent gene expression in mouse intestinal crypts; siRNA knockdown of Smp reduces β-catenin nuclear localization and transcriptional activity; human SMP mediates β-catenin transcriptional activity in a dose-dependent manner; and the human SMP protein interacts with human β-catenin primarily in the nucleus. Thus, our findings identify the evolutionary conserved SMP protein as a regulator of β-catenin-dependent Wnt signal transduction.

Expression profiling of genes modulated by minocycline in a rat model of neuropathic pain

Background

The molecular mechanisms underlying neuropathic pain are constantly being studied to create new opportunities to prevent or alleviate neuropathic pain. The aim of our study was to determine the gene expression changes induced by sciatic nerve chronic constriction injury (CCI) that are modulated by minocycline, which can effectively diminish neuropathic pain in animal studies. The genes associated with minocycline efficacy in neuropathic pain should provide insight into the etiology of neuropathic pain and identify novel therapeutic targets.

Results

We screened the ipsilateral dorsal part of the lumbar spinal cord of the rat CCI model for differentially expressed genes. Out of 22,500 studied transcripts, the abundance levels of 93 transcripts were altered following sciatic nerve ligation. Percentage analysis revealed that 54 transcripts were not affected by the repeated administration of minocycline (30 mg/kg, i.p.), but the levels of 39 transcripts were modulated following minocycline treatment. We then selected two gene expression patterns, B1 and B2. The first transcription pattern, B1, consisted of 10 mRNA transcripts that increased in abundance after injury, and minocycline treatment reversed or inhibited the effect of the injury; the B2 transcription pattern consisted of 7 mRNA transcripts whose abundance decreased following sciatic nerve ligation, and minocycline treatment reversed the effect of the injury. Based on the literature, we selected seven genes for further analysis: Cd40, Clec7a, Apobec3b, Slc7a7, and Fam22f from pattern B1 and Rwdd3 and Gimap5 from pattern B2. Additionally, these genes were analyzed using quantitative PCR to determine the transcriptional changes strongly related to the development of neuropathic pain; the ipsilateral DRGs (L4-L6) were also collected and analyzed in these rats using qPCR.

Conclusion

In this work, we confirmed gene expression alterations previously identified by microarray analysis in the spinal cord and analyzed the expression of selected genes in the DRG. Moreover, we reviewed the literature to illustrate the relevance of these findings for neuropathic pain development and therapy. Further studies are needed to elucidate the roles of the individual genes in neuropathic pain and to determine the therapeutic role of minocycline in the rat neuropathic pain model.

Identifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis

For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs) generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

BACKGROUND

Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures.

RESULTS

In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process.

CONCLUSIONS

This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally.

RNA sequencing identifies multiple fusion transcripts, differentially expressed genes, and reduced expression of immune function genes in BRAF (V600E) mutant vs BRAF wild-type papillary thyroid carcinoma

CONTEXT

The BRAF V600E mutation (BRAF-MUT) confers an aggressive phenotype in papillary thyroid carcinoma, but unidentified additional genomic abnormalities may be required for full phenotypic expression.

OBJECTIVE

RNA sequencing (RNA-Seq) was performed to identify genes differentially expressed between BRAF-MUT and BRAF wild-type (BRAF-WT) tumors and to correlate changes to patient clinical status.

DESIGN

BRAF-MUT and BRAF-WT tumors were identified in patients with T1N0 and T2-3N1 tumors evaluated in a referral medical center. Gene expression levels were determined (RNA-Seq) and fusion transcripts were detected. Multiplexed capture/detection and digital counting of mRNA transcripts (nCounter, NanoString Technologies) validated RNA-Seq data for immune system-related genes.

PATIENTS

BRAF-MUT patients included nine women, three men; nine were TNM stage I and three were stage III. Three (25%) had tumor infiltrating lymphocytes. BRAF-WT included five women, three men; all were stage I, and five (62.5%) had tumor infiltrating lymphocytes.

RESULTS

RNA-Seq identified 560 of 13 085 genes differentially expressed between BRAF-MUT and BRAF-WT tumors. Approximately 10% of these genes were related to MetaCore immune function pathways; 51 were underexpressed in BRAF-MUT tumors, whereas 4 (HLAG, CXCL14, TIMP1, IL1RAP) were overexpressed. The four most differentially overexpressed immune genes in BRAF-WT tumors (IL1B; CCL19; CCL21; CXCR4) correlated with lymphocyte infiltration. nCounter confirmed the RNA-Seq expression level data. Eleven different high-confidence fusion transcripts were detected (four interchromosomal; seven intrachromosomal) in 13 of 20 tumors. All in-frame fusions were validated by RT-PCR.

CONCLUSION

BRAF-MUT papillary thyroid cancers have reduced expression of immune/inflammatory response genes compared with BRAF-WT tumors and correlate with lymphocyte infiltration. In contrast, HLA-G and CXCL14 are overexpressed in BRAF-MUT tumors. Sixty-five percent of tumors had between one and three fusion transcripts. Functional studies will be required to determine the potential role of these newly identified genomic abnormalities in contributing to the aggressiveness of BRAF-MUT and BRAF-WT tumors.

Upregulation of E2F transcription factor 3 is associated with poor prognosis in hepatocellular carcinoma

E2F transcription factor 3 (E2F3), a member of the E2F transcription factor family and a member of the genes involved in the regulation of cell cycle, is an oncogene with strong proliferative potential. E2F3 is involved in many processes and plays important roles in the development of several types of cancer, while its relationship with prognosis in hepatocellular carcinoma (HCC) has yet to be reported. In the present study, based on 4 independent microarray data sets which covered 385 cases of HCC and 327 cases of normal livers retrieved from the Oncomine database, we demonstrated that E2F3 was upregulated at least 1.5-fold and on average 2.3-fold in HCC when compared with normal controls. Comprehensive bioinformatics analysis consisting of protein-protein interaction, gene co-occurrence, microRNA-mRNA interaction and biological process annotation indicated that E2F3 interacted with a large number of genes, proteins and microRNAs which were all associated with poor prognosis in patients with HCC and other types of cancer, suggesting that E2F3 may also serve as a biomarker for poor prognosis. Taken together, for the first time, we show that the overexpression of E2F3 may be associated with unfavorable prognosis in HCC.

Lamina-associated polypeptide (LAP)2α and other LEM proteins in cancer biology

The LEM proteins comprise a heterogeneous family of chromatin-associated proteins that share the LEM domain, a structural motif mediating interaction with the DNA associated protein, Barrier-to-Autointegration Factor (BAF). Most of the LEM proteins are integral proteins of the inner nuclear membrane and associate with the nuclear lamina, a structural scaffold of lamin intermediate filament proteins at the nuclear periphery, which is involved in nuclear mechanical functions and (hetero-)chromatin organization. A few LEM proteins, such as Lamina-associated polypeptide (LAP)2α and Ankyrin and LEM domain-containing protein (Ankle)1 lack transmembrane domains and localize throughout the nucleoplasm and cytoplasm, respectively. LAP2α has been reported to regulate cell proliferation by affecting the activity of retinoblastoma protein in tissue progenitor cells and numerous studies showed upregulation of LAP2α in cancer. Ankle1 is a nuclease likely involved in DNA damage repair pathways and single nucleotide polymorphisms in the Ankle1 gene have been linked to increased breast and ovarian cancer risk. In this review we describe potential mechanisms of the involvement of LEM proteins, particularly of LAP2α and Ankle1 in tumorigenesis and we provide evidence that LAP2α expression may be a valuable diagnostic and prognostic marker for tumor analyses.

Proof of the concept to use a malignant B cell line drug screen strategy for identification and weight of melphalan resistance genes in multiple myeloma

In a conceptual study of drug resistance we have used a preclinical model of malignant B-cell lines by combining drug induced growth inhibition and gene expression profiling. In the current report a melphalan resistance profile of 19 genes were weighted by microarray data from the MRC Myeloma IX trial and time to progression following high dose melphalan, to generate an individual melphalan resistance index. The resistance index was subsequently validated in the HOVON65/GMMG-HD4 trial data set to prove the concept. Biologically, the assigned resistance indices were differentially distributed among translocations and cyclin D expression classes. Clinically, the 25% most melphalan resistant, the intermediate 50% and the 25% most sensitive patients had a median progression free survival of 18, 32 and 28 months, respectively (log-rank P-value  = 0.05). Furthermore, the median overall survival was 45 months for the resistant group and not reached for the intermediate and sensitive groups (log-rank P-value  = 0.003) following 38 months median observation. In a multivariate analysis, correcting for age, sex and ISS-staging, we found a high resistance index to be an independent variable associated with inferior progression free survival and overall survival. This study provides clinical proof of concept to use in vitro drug screen for identification of melphalan resistance gene signatures for future functional analysis.

Genetic variants in SLC7A7 are associated with risk of glioma in a Chinese population

Dysregulation of the amino acid transporter SLC7A7 is involved in multiple types of cancer including gliobastoma (GBM), the most malignant form of glioma. We hypothesized that SLC7A7 genetic variants may influence glioma risk. To test this hypothesis, we conducted a case-control study in 736 incident glioma cases and 793 cancer-free controls in a Chinese population by genotyping 22 common single nucleotide polymorphisms in SLC7A7. In single-locus analysis, we found an increased risk was associated with the variant genotypes of rs12888930 (adjusted odds ratio [OR] = 1.25, 95% confidence interval [CI] 1.02-1.54, P = 0.034), rs12433985 (adjusted OR = 1.38, 95%CI = 1.13-1.70), rs2065134 (adjusted OR = 1.43, 95% CI 1.05-1.95) in a dominant genetic model and rs12436190 (adjusted OR = 1.37, 95%CI 1.06-1.77) in a recessive model. Multivariate analysis confirmed that rs12433985 and rs2065134 were significant and independent risk factor for glioma as well as GBM subtype (for rs12433985, OR = 1.21, 95%CI 1.04-1.42, P = 0.016 for all types of gliomas and P = 0.013, OR = 1.30, 95%CI 1.06-1.60 for GBM. For rs2065134, OR = 1.39, 95%CI 1.02-1.89, P = 0.039 for all types of gliomas and OR = 1.66, 95%CI 1.12-2.24, P = 0.011). These results, for the first time, provide suggestive evidence of polymorphisms in SLC7A7 is involved in the aetiology of glioma.

Evaluating gene expression profiling by quantitative polymerase chain reaction to develop a clinically feasible test for outcome prediction in multiple myeloma

The gene expression profiles (GEPs) of 96 selected genes were analysed by real-time quantitative polymerase chain reaction (qPCR) with a TaqMan low-density array card in isolated tumour plasma cells (PCs) from 157 newly diagnosed multiple myeloma (MM) patients. This qPCR-based GEP correctly classified cases following the Translocation-cyclin D classification. Classic prognostic parameters and qPCR-based GEP predicted MM patient outcome and, although multivariate analyses revealed that cytogenetic risk (standard vs. high risk) was the variable that most strongly predicted prognosis, GEP added significant information for risk stratification. Considering only the standard risk cytogenetic patients, multivariate analyses revealed that high β2-microglobulin, low CDKN1A and high SLC19A1 gene expression levels independently predicted a short time-to-progression (TTP), while high International Staging System stage, low CDKN2B and high TBRG4 gene expression predicted poor overall survival (OS). A gene expression risk score enabled the division of standard risk patients into two groups with different TTPs (83% vs. 38% at 3 years, P < 0·0001) and OS rates (88% vs. 61% at 5 years; P = 0·003). This study demonstrates that quantitative PCR is a robust, accurate and feasible technique for implementing in the daily routine as a surrogate for GEP-arrays.

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing

INTRODUCTION

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity.

AREAS COVERED

Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed.

EXPERT OPINION

High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Identification of an ABCB1 (P-glycoprotein)-positive carfilzomib-resistant myeloma subpopulation by the pluripotent stem cell fluorescent dye CDy1

Multiple myeloma (MM) is characterized by the malignant expansion of differentiated plasma cells. Although many chemotherapeutic agents display cytotoxic activity toward MM cells, patients inevitably succumb to their disease because the tumor cells become resistant to the anticancer drugs. The cancer stem cell hypothesis postulates that a small subpopulation of chemotherapy-resistant cancer cells is responsible for propagation of the tumor. Herein we report that efflux of the pluripotent stem cell dye CDy1 identifies a subpopulation in MM cell lines characterized by increased expression of P-glycoprotein, a member of the ABC (ATP-binding cassette) superfamily of transporters encoded by ABCB1. We also demonstrate that ABCB1-overexpressing MM cells are resistant to the second-generation proteasome inhibitor carfilzomib that recently received accelerated approval for the treatment of therapy-refractive MM by the U.S. Food and Drug Administration. Moreover, increased resistance to carfilzomib in sensitive MM cells following drug selection was associated with upregulation of ABCB1 cell-surface expression which correlated with increased transporter activity as measured by CDy1 efflux. We further show that chemosensitization of MM cells to carfilzomib could be achieved in vitro by cotreatment with vismodegib, a hedgehog pathway antagonist which is currently in MM clinical trials. CDy1 efflux may therefore be a useful assay to determine whether high expression of ABCB1 is predictive of poor clinical responses in MM patients treated with carfilzomib. Our data also suggest that inclusion of vismodegib might be a potential strategy to reverse ABCB1-mediated drug resistance should it occur.

Overexpression of SLC7A7 predicts poor progression-free and overall survival in patients with glioblastoma

The clinical significance of SLC7A7 expression remains unclear. In this study, we aimed to explore whether SLC7A7 expression in tumor tissues could be used to assess subsequent prognosis in patients with glioblastoma (GBM). A total of 119 patients with pathologically confirmed GBM and 16 normal controls were recruited for this study. The expression of SLC7A7 in GBM and normal tissues was evaluated by immunohistochemistry in tissue microarrays and quantitative real-time PCR. Kaplan-Meier method and Cox's proportional hazards model were used in survival analysis. Compared with normal tissues, GBM specimens had significantly increased expression of SLC7A7 at both mRNA and protein levels (both P < 0.05). Moreover, multivariate analysis confirmed that overexpression of SLC7A7 was a significant and independent indicator for predicting poor prognosis. Our results suggest, for the first time, that overexpression of SLC7A7 is correlated with worse outcomes in patients with GBM. SLC7A7 plays a critical role in GBM carcinogenesis and may be a potential prognosis predictor of GBM.

Genome-scale technology driven advances to research into normal and malignant haematopoiesis

Haematopoiesis or blood development has long served as a model system for adult stem cell biology. Moreover, when combined, the various cancers of the blood represent one of the commonest human malignancies. Large numbers of researchers have therefore dedicated their scientific careers to studying haematopoiesis for more than a century. Throughout this period, many new technologies have first been applied towards the study of blood cells, and the research fields of normal and malignant haematopoiesis have also been some of the earliest adopters of genome-scale technologies. This has resulted in significant new insights with implications ranging from basic biological mechanisms to patient diagnosis and prognosis and also produced lessons likely to be relevant for many other areas of biomedical research. This paper discusses the current state of play for a range of genome-scale applications within haemopoiesis research, including gene expression profiling, ChIP-sequencing, genomewide association analysis, and cancer genome sequencing. A concluding outlook section explores likely future areas of progress as well as potential technological and educational bottlenecks.

Immunomodulatory drugs lenalidomide and pomalidomide inhibit multiple myeloma-induced osteoclast formation and the RANKL/OPG ratio in the myeloma microenvironment targeting the expression of adhesion molecules

Multiple myeloma (MM)-induced osteoclast (OC) formation is mainly due to an imbalance of the receptor activator NF-κB ligand (RANKL)-osteoprotegerin (OPG) ratio in favor of RANKL in the bone microenvironment and to the CCL3 production by MM cells. The purpose of the study was to investigate the effect of the immunomodulatory drugs on RANKL/OPG ratio, the production of pro-osteoclastogenic cytokines, and MM-induced OC formation. We found that in vivo concentrations of both lenalidomide (LEN) and pomalidomide (POM) significantly blunted RANKL upregulation normalizing the RANKL/OPG ratio in human osteoprogenitor cells (PreOBs) when co-cultured with MM cells and also inhibited CCL3 production by MM cells. A reduction in CD49d expression, a molecule critically involved in RANKL upregulation in the MM microenvironment, accompanied this effect. Consistently, the pro-osteoclastogenic property of MM cells co-cultured with PreOBs was reduced by both LEN and POM. We further investigated the effect of these drugs on the transcriptional profile of both MM cells and PreOBs by microarray analysis, which showed that adhesion molecules, such as ITGA8 and ICAM2, are significantly downregulated in MM cells. Our data suggest that LEN and POM inhibit MM-induced OC formation through normalization of the RANKL/OPG ratio targeting the expression of adhesion molecules by MM cells.

Development of gene expression-based score to predict sensitivity of multiple myeloma cells to DNA methylation inhibitors

Multiple myeloma is a plasma cell cancer with poor survival, characterized by the clonal expansion of multiple myeloma cells (MMC), primarily in the bone marrow. Novel compounds are currently tested in this disease, but partial or minor patients' responses are observed for most compounds used as a single agent. The design of predictors for drug efficacy could be most useful to better understand basic mechanisms targeted by these drugs and design clinical trials. In the current study, we report the building of a DNA methylation score (DM score) predicting the efficacy of decitabine, an inhibitor of DNA methyltransferase (DNMT), targeting methylation-regulated gene expression. DM score was built by identifying 47 genes regulated by decitabine in human myeloma cell lines and the expression of which in primary MMCs of previously untreated patients is predictive for overall survival. A high DM score predicts patients' poor survival, and, of major interest, high sensitivity of primary MMCs or human myeloma cell lines to decitabine in vitro. Thus, DM score could be useful to design novel treatments with DMNT inhibitor in multiple myeloma and has highlighted 47 genes, the gene products of which could be important for multiple myeloma disease development.

Canonical and noncanonical Hedgehog pathway in the pathogenesis of multiple myeloma

The Hedgehog (Hh) pathway is required for cell-fate determination during the embryonic life, as well as cell growth and differentiation in the adult organism, where the inappropriate activation has been implicated in several cancers. Here we demonstrate that Hh signaling plays a significant role in growth and survival of multiple myeloma (MM) cells. We observed that CD138(+) MM cells express Hh genes and confirmed Smoothened (Smo)-dependent Hh signaling in MM using a novel synthetic Smo inhibitor, NVP-LDE225 (Novartis), which decreased MM cell viability by inducing specific down-regulation of Gli1 and Ptch1, hallmarks of Hh activity. In addition, we detected a nuclear localization of Gli1 in MM cells, which is completely abrogated by Forskolin, a Gli1-modulating compound, confirming Smo-independent mechanisms leading to Hh activation in MM. Finally, we identified that bone marrow stromal cells are a source of the Shh ligand, although they are resistant to the Hh inhibitor because of defective Smo expression and Ptch1 up-regulation. Further in vitro as well as in vivo studies showed antitumor efficacy of NVP-LDE225 in combination with bortezomib. Altogether, our data demonstrate activation of both canonical and noncanonical Hh pathway in MM, thus providing the rationale for testing Hh inhibitors in clinical trials to improve MM patient outcome.