CCAAT/enhancer binding protein α predicts poorer prognosis and prevents energy starvation-induced cell death in hepatocellular carcinoma

CCAAT enhancer binding protein α (C/EBPα) plays an essential role in cellular differentiation, growth, and energy metabolism. Here, we investigate the correlation between C/EBPα and hepatocellular carcinoma (HCC) patient outcomes and how C/EBPα protects cells against energy starvation. Expression of C/EBPα protein was increased in the majority of HCCs examined (191 pairs) compared with adjacent nontumor liver tissues in HCC tissue microarrays. Its upregulation was correlated significantly with poorer overall patient survival in both Kaplan-Meier survival (P = 0.017) and multivariate Cox regression (P = 0.028) analyses. Stable C/EBPα-silenced cells failed to establish xenograft tumors in nude mice due to extensive necrosis, consistent with increased necrosis in human C/EBPα-deficient HCC nodules. Expression of C/EBPα protected HCC cells in vitro from glucose and glutamine starvation-induced cell death through autophagy-involved lipid catabolism. Firstly, C/EBPα promoted lipid catabolism during starvation, while inhibition of fatty acid beta-oxidation significantly sensitized cell death. Secondly, autophagy was activated in C/EBPα-expressing cells, and the inhibition of autophagy by ATG7 knockdown or chloroquine treatment attenuated lipid catabolism and subsequently sensitized cell death. Finally, we identified TMEM166 as a key player in C/EBPα-mediated autophagy induction and protection against starvation.

CONCLUSION: The C/EBPα gene is important in that it links HCC carcinogenesis to autophagy-mediated lipid metabolism and resistance to energy starvation; its expression in HCC predicts poorer patient prognosis.

FKBPL: a marker of good prognosis in breast cancer

FK506-binding protein-like (FKBPL) has established roles as an anti-tumor protein, with a therapeutic peptide based on this protein, ALM201, shortly entering phase I/II clinical trials. Here, we evaluated FKBPL's prognostic ability in primary breast cancer tissue, represented on tissue microarrays (TMA) from 3277 women recruited into five independent retrospective studies, using immunohistochemistry (IHC). In a meta-analysis, FKBPL levels were a significant predictor of BCSS; low FKBPL levels indicated poorer breast cancer specific survival (BCSS) (hazard ratio (HR) = 1.30, 95% confidence interval (CI) 1.14-1.49, p < 0.001). The prognostic impact of FKBPL remained significant after adjusting for other known prognostic factors (HR = 1.25, 95% CI 1.07-1.45, p = 0.004). For the sub-groups of 2365 estrogen receptor (ER) positive patients and 1649 tamoxifen treated patients, FKBPL was significantly associated with BCSS (HR = 1.34, 95% CI 1.13-1.58, p < 0.001, and HR = 1.25, 95% CI 1.04-1.49, p = 0.02, respectively). A univariate analysis revealed that FKBPL was also a significant predictor of relapse free interval (RFI) within the ER positive patient group, but it was only borderline significant within the smaller tamoxifen treated patient group (HR = 1.32 95% CI 1.05-1.65, p = 0.02 and HR = 1.23 95% CI 0.99-1.54, p = 0.06, respectively). The data suggests a role for FKBPL as a prognostic factor for BCSS, with the potential to be routinely evaluated within the clinic.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

The prognostic value of the stem-like group in colorectal cancer using a panel of immunohistochemistry markers

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the Western world. It is becoming increasingly clear that CRC is a diverse disease, as exemplified by the identification of subgroups of CRC tumours that are driven by distinct biology. Recently, a number of studies have begun to define panels of diagnostically relevant markers to align patients into individual subgroups in an attempt to give information on prognosis and treatment response. We examined the immunohistochemical expression profile of 18 markers, each representing a putative role in cancer development, in 493 primary colorectal carcinomas using tissue microarrays. Through unsupervised clustering in stage II cancers, we identified two cluster groups that are broadly defined by inflammatory or immune-related factors (CD3, CD8, COX-2 and FOXP3) and stem-like factors (CD44, LGR5, SOX2, OCT4). The expression of the stem-like group markers was associated with a significantly worse prognosis compared to cases with lower expression. In addition, patients classified in the stem-like subgroup displayed a trend towards a benefit from adjuvant treatment. The biologically relevant and poor prognostic stem-like group could also be identified in early stage I cancers, suggesting a potential opportunity for the identification of aggressive tumors at a very early stage of the disease.

Molecular markers for predicting recurrence, progression and outcomes of bladder cancer (do the poster boys need new posters

Purpose of review
Molecular markers for bladder cancer recurrence and
progression continue to drive many research programmes.
Translating the laboratory findings into the clinical environment
where these markers are used in clinical decision making has
proved problematic. In the clinical arena, stage and grade are
still the main focus for decisions about patient management.
There is however an evolution in bladder cancer research from
single-marker/single-pathway research to a more global
assessment of the tumour cell with DNA microarrays and
proteomics.
Recent findings
In the last year, DNA microarray assessment has revealed
several interesting molecular markers such as p33ING1 and
DEK. Parallel ‘conventional’ single-pathway research has
focused on new novel markers such as HER2/neu, survivin and
matrix metalloproteinase 2 (MMP-2). Molecular markers that
have a long-standing association with bladder cancer
progression such as p53, E-cadherin and Ki-67 have been
reviewed by both single-marker studies and by microarray
studies and their status remains important.
Summary
It is an exciting time in the molecular biology research of bladder
cancer as the focus changes to assess the global genetic and
protein expression within tumour cells. From such a wealth of
information it is likely that molecular markers will make the
translation from benchside to bedside.

Genomics and the impact of new technologies on the management of colorectal cancer

High-throughput genomic technologies have the potential to have a major impact on preclinical and clinical drug development and the selection and stratification of patients in clinical trials. These technologies, which are at varying stages of commercialization, include array-based comparative genomic hybridization, single-nucleotide polymorphism arrays, and (the most mature example) expression-based arrays. One of the rate-limiting steps in the routine clinical application of expression array-based technology is the need for suitable clinical samples. One of the major challenges moving forward, therefore, relates to the ability to use formalin-fixed, paraffin-embedded--derived tissue in expression profiling-based approaches.

Uncovering BRCA1-regulated signalling pathways by microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has dramatically changed the way in which we now address basic biomedical questions. Expression profiling using microarrays facilitates an experimental approach where alterations in the transcript level of entire transcriptomes can be simultaneously assayed in response to defined stimuli. We have used microarray analysis to identify downstream transcriptional targets of the BRCA1 (Breast Cancer 1) tumour-suppressor gene as a means of defining its function. BRCA1 has been implicated in the predisposition to early onset breast and ovarian cancer and while its exact function remains to be defined, roles in DNA repair, cell-cycle control and transcriptional regulation have been implied. In the current study we have generated cell lines with tetracycline-regulated, inducible expression of BRCA1 as a tool to identify genes, which might represent important effectors of BRCA1 function. Oligonucleotide array-based expression profiling identified a number of genes that were upregulated at various times following inducible expression of BRCA1 including the DNA damage-responsive gene GADD45 (Growth Arrest after DNA Damage). Identified targets were confirmed by Northern blot analysis and their functional significance as BRCA1 targets examined.

Uncovering functionally relevant signaling pathways using microarray-based expression profiling

The introduction of microarray technology to the scientific and medical communities has fundamentally altered the way in which we now address basic biomedical questions. Microarrays technology facilitates a more complete and inclusive experimental approach where alterations in the transcript level of entire genomes can be simultaneously assayed in response to a variety of stimuli. Conceptually different approaches to the development of microarray technology have resulted in the generation of two different array formats: oligonucleotide arrays and cDNA arrays. The application of microarray and related technologies to identify specific targets of defined genes that have clearly been implicated in cancer progression requires a specific experimental approach. The objective of tiffs approach is to define changes in transcriptional profile that occur in response to modulating the expression level of the gene to be studied. The resulting altered expression profile can then be viewed as a blueprint by which that gene effects its cellular function. We have used oligonucleotide array-based expression profiling in collaboration with Affymetrix to identify downstream transcriptional targets of the BRCA1 tumor-suppressor gene as a means of defining its function. BRCA1 has been implicated in at least three functional pathways, namely, mediating the cellular response to DNA damage, as a cell cycle checkpoint protein and in the regulation of transcription. The physiological significance of these properties and their implications for the function of BRCA1 as a tumor-suppressor gene remain to be defined.

The role of secreted frizzled-related protein 2 expression in prostate cancer

AIMS: Improved prostate cancer (PCa)-specific biomarkers are urgently required to distinguish between indolent and aggressive disease, in order to avoid overtreatment. In this study, we investigated the prostatic tissue expression of secreted frizzled-related protein (SFRP)-2.

METHODS AND RESULTS: Following immunohistochemical analysis on PCa tissue microarrays with samples from 216 patients, strong/moderate SFRP-2 expression was observed in epithelial cells of benign prostatic hyperplasia, and negative/weak SFRP-2 expression was observed in the majority of tumour epithelia. However, among Gleason grade 5 carcinomas, 40% showed strong/moderate SFRP-2 expression and 60% showed negative SFRP-2 expression in epithelial cells. Further microscopic evaluation of Gleason grade 5 tumours revealed different morphological patterns, corresponding with differential SFRP-2 expression. The first subgroup (referred to as Type A) appeared to have a morphologically solid growth pattern, whereas the second subgroup (referred to as Type B) appeared to have a more diffuse pattern. Furthermore, 100% (4/4) of Type A patients experienced biochemical recurrence, as compared with 0% (0/6) of Type B patients.

CONCLUSIONS: These results imply: (i) that there is a loss of SFRP-2 expression from benign to malignant prostate glands; and (ii) differential SFRP-2 expression among two possible subgroups of Gleason grade 5 tumours.

The TGF-β-inducible miR-23a cluster attenuates IFN-γ levels and antigen-specific cytotoxicity in human CD8+ T cells

Cytokine secretion and degranulation represent key components of CD8(+) T-cell cytotoxicity. While transcriptional blockade of IFN-γ and inhibition of degranulation by TGF-β are well established, we wondered whether TGF-β could also induce immune-regulatory miRNAs in human CD8(+) T cells. We used miRNA microarrays and high-throughput sequencing in combination with qRT-PCR and found that TGF-β promotes expression of the miR-23a cluster in human CD8(+) T cells. Likewise, TGF-β up-regulated expression of the cluster in CD8(+) T cells from wild-type mice, but not in cells from mice with tissue-specific expression of a dominant-negative TGF-β type II receptor. Reporter gene assays including site mutations confirmed that miR-23a specifically targets the 3'UTR of CD107a/LAMP1 mRNA, whereas the further miRNAs expressed in this cluster-namely, miR-27a and -24-target the 3'UTR of IFN-γ mRNA. Upon modulation of the miR-23a cluster by the respective miRNA antagomirs and mimics, we observed significant changes in IFN-γ expression, but only slight effects on CD107a/LAMP1 expression. Still, overexpression of the cluster attenuated the cytotoxic activity of antigen-specific CD8(+) T cells. These functional data thus reveal that the miR-23a cluster not only is induced by TGF-β, but also exerts a suppressive effect on CD8(+) T-cell effector functions, even in the absence of TGF-β signaling.

RMA with quantile normalization mixes biological signals between different sample groups in microarray data analysis

Quantile normalization (QN) is a technique for microarray data processing and is the default normalization method in the Robust Multi-array Average (RMA) procedure, which was primarily designed for analysing gene expression data from Affymetrix arrays. Given the abundance of Affymetrix microarrays and the popularity of the RMA method, it is crucially important that the normalization procedure is applied appropriately. In this study we carried out simulation experiments and also analysed real microarray data to investigate the suitability of RMA when it is applied to dataset with different groups of biological samples. From our experiments, we showed that RMA with QN does not preserve the biological signal included in each group, but rather it would mix the signals between the groups. We also showed that the Median Polish method in the summarization step of RMA has similar mixing effect. RMA is one of the most widely used methods in microarray data processing and has been applied to a vast volume of data in biomedical research. The problematic behaviour of this method suggests that previous studies employing RMA could have been misadvised or adversely affected. Therefore we think it is crucially important that the research community recognizes the issue and starts to address it. The two core elements of the RMA method, quantile normalization and Median Polish, both have the undesirable effects of mixing biological signals between different sample groups, which can be detrimental to drawing valid biological conclusions and to any subsequent analyses. Based on the evidence presented here and that in the literature, we recommend exercising caution when using RMA as a method of processing microarray gene expression data, particularly in situations where there are likely to be unknown subgroups of samples.

Molecular subtyping of primary prostate cancer reveals specific and shared target genes of different ETS rearrangements

This work aimed to evaluate whether ETS transcription factors frequently involved in rearrangements in prostate carcinomas (PCa), namely ERG and ETV1, regulate specific or shared target genes. We performed differential expression analysis on nine normal prostate tissues and 50 PCa enriched for different ETS rearrangements using exon-level expression microarrays, followed by in vitro validation using cell line models. We found specific deregulation of 57 genes in ERG-positive PCa and 15 genes in ETV1-positive PCa, whereas deregulation of 27 genes was shared in both tumor subtypes. We further showed that the expression of seven tumor-associated ERG target genes (PLA1A, CACNA1D, ATP8A2, HLA-DMB, PDE3B, TDRD1, and TMBIM1) and two tumor-associated ETV1 target genes (FKBP10 and GLYATL2) was significantly affected by specific ETS silencing in VCaP and LNCaP cell line models, respectively, whereas the expression of three candidate ERG and ETV1 shared targets (GRPR, KCNH8, and TMEM45B) was significantly affected by silencing of either ETS. Interestingly, we demonstrate that the expression of TDRD1, the topmost overexpressed gene of our list of ERG-specific candidate targets, is inversely correlated with the methylation levels of a CpG island found at -66 bp of the transcription start site in PCa and that TDRD1 expression is regulated by direct binding of ERG to the CpG island in VCaP cells. We conclude that ETS transcription factors regulate specific and shared target genes and that TDRD1, FKBP10, and GRPR are promising therapeutic targets and can serve as diagnostic markers for molecular subtypes of PCa harboring specific fusion gene rearrangements.

Global identification of androgen response elements

Chromatin immunoprecipitation (ChIP) is an invaluable tool in the study of transcriptional regulation. ChIP methods require both a priori knowledge of the transcriptional regulators which are important for a given biological system and high-quality specific antibodies for these targets. The androgen receptor (AR) is known to play essential roles in male sexual development, in prostate cancer and in the function of many other AR-expressing cell types (e.g. neurons and myocytes). As a ligand-activated transcription factor the AR also represents an endogenous, inducible system to study transcriptional biology. Therefore, ChIP studies of the AR can make use of treatment contrast experiments to define its transcriptional targets. To date several studies have mapped AR binding sites using ChIP in combination with genome tiling microarrays (ChIP-chip) or direct sequencing (ChIP-seq), mainly in prostate cancer cell lines and with varying degrees of genomic coverage. These studies have provided new insights into the DNA sequences to which the AR can bind, identified AR cooperating transcription factors, mapped thousands of potential AR regulated genes and provided insights into the biological processes regulated by the AR. However, further ChIP studies will be required to fully characterise the dynamics of the AR-regulated transcriptional programme, to map the occupancy of different AR transcriptional complexes which result in different transcriptional output and to delineate the transcriptional networks downstream of the AR.

Chromatin immunoprecipitation (ChIP) methodology and readouts

The identification of direct nuclear hormone receptor gene targets provides clues to their contribution to both development and cancer progression. Until recently, the identification of such direct target genes has relied on a combination of expression analysis and in silico searches for consensus binding motifs in gene promoters. Consensus binding motifs for transcription factors are often defined using in vitro DNA binding strategies. Such in vitro strategies fail to account for the many factors that contribute significantly to target selection by transcription factors in cells beyond the recognition of these short consensus DNA sequences. These factors include DNA methylation, chromatin structure, posttranslational modifications of transcription factors, and the cooperative recruitment of transcription factor complexes. Chromatin immunoprecipitation (ChIP) provides a means of isolating transcription factor complexes in the context of endogenous chromatin, allowing the identification of direct transcription factor targets. ChIP can be combined with site-specific PCR for candidate binding sites or alternatively with cloning, genomic microarrays or more recently direct high throughput sequencing to identify novel genomic targets. The application of ChIP-based approaches has redefined consensus binding motifs for transcription factors and provided important insights into transcription factor biology.

Alterations in beta-catenin expression and localization in prostate cancer

BACKGROUND: Wnt signaling is thought to be important in prostate cancer, in part because proteins such as beta-catenin can also affect androgen receptor signaling. beta-Catenin forms a cell adhesion complex with E-cadherin raising the possibility that loss of expression or a change in beta-catenin distribution in the cell could also alter downstream signaling, decreased inter-cellular adhesion and the promotion of metastasis. A number of studies have reported the altered expression and/or localization of beta-catenin as a biomarker in prostate cancer.

METHODS: Tissue microarrays comprised of BPH and low, moderate and high-grade prostate cancer (n=77) were assessed for beta-catenin expression and distribution using immunohistochemistry. Staining was also performed on a tissue microarray containing tissue from patients before and after hormone manipulation. The effects of fixation and different antibodies was assessed on fixed LNCaP cell pellets and small prostate tissue microarrays.

RESULTS: We have observed increased beta-catenin expression in only high Gleason score (>7) prostate cancer. A nuclear re-distribution of beta-catenin has previously been reported. We noted nuclear beta-catenin in benign prostatic hyperplasia and a gradual loss in nuclear distribution with increasing Gleason grade. We found no evidence for an alteration in beta-catenin expression or re-distribution with hormone ablation. Altered fixation, antibodies and antibody concentration did affect the intensity and specificity of staining.

CONCLUSIONS: A loss of nuclear beta-catenin is the most consistent feature in prostate cancer rather than absolute levels of expression. We also suggest that variation in immunohistochemical protocols may explain variations in the reported literature.