Meta-analysis of multiple microarray datasets reveals a common gene signature of metastasis in solid tumors

Genetic Changes in Mastocytes and Their Significance in Mast Cell Tumor Prognosis and Treatment

Mast cell tumors are a large group of diseases occurring in dogs, cats, mice, as well as in humans. Systemic mastocytosis (SM) is a disease involving the accumulation of mast cells in organs. KIT gene mutations are very often seen in abnormal mast cells. In SM, high KIT/CD117 expression is observed; however, there are usually no KIT gene mutations present. Mastocytoma (MCT)-a form of cutaneous neoplasm-is common in animals but quite rare in humans. KIT/CD117 receptor mutations were studied as the typical changes for human mastocytosis. In 80% of human cases, the KIT gene substitution p.D816H was present. In about 25% of MCTs, metastasis was observed. Changes in the gene expression of certain genes, such as overexpression of the DNAJ3A3 gene, promote metastasis. In contrast, the SNORD93 gene blocks the expression of metastasis genes. The panel of miR-21-5p, miR-379, and miR-885 has a good efficiency in discriminating healthy and MCT-affected dogs, as well as MCT-affected dogs with and without nodal metastasis. Further studies on the pathobiology of mast cells can lead to clinical improvements, such as better MCT diagnosis and treatment. Our paper reviews studies on the topic of mast cells, which have been carried out over the past few years.

A novel method to identify gene interaction patterns

BACKGROUND

Gene interaction patterns, including modules and motifs, can be used to identify cancer specific biomarkers and to reveal the mechanism of tumorigenesis. Most of the existing module network inferencing methods focus on gene independent functional patterns, while the studies of overlapping characteristics between modules are lacking. The objective of this study was to reveal the functional overlapping patterns in gene modules, helping elucidate the regulatory relationship between overlapping genes and communities, as well as to explore cancer formation and progression.

RESULTS

We analyzed six cancer datasets from The Cancer Genome Atlas and obtained three kinds of gene functional modules for each cancer, including Independent-Community, Dependent-Community and Merged-Community. In the six cancers, 59(3.5%) Independent-Communities were identified, while 1631(96.5%) Dependent-Communities were acquired. Compared with Lemon-Tree and K-Means, the gene communities identified by our method were enriched in more known GO categories with lower p-values. Meanwhile, those identified distinguishing communities can significantly distinguish the survival prognostic of patients by Kaplan-Meier analysis. Furthermore, identified driver genes in the gene communities can be considered as biomarkers which can accurately distinguish the tumour or normal samples for each cancer type.

CONCLUSIONS

In all identified communities, Dependent-Communities are the majority. Our method is more effective than the other two methods which do not consider the overlapping characteristics of modules. This indicates that overlapping genes are located in different specific functional groups, and a communication bridge is established between the communities to construct a comprehensive carcinogenesis.

Metastasis is altered through multiple processes regulated by the E2F1 transcription factor

The E2F family of transcription factors is important for many cellular processes, from their canonical role in cell cycle regulation to other roles in angiogenesis and metastasis. Alteration of the Rb/E2F pathway occurs in various forms of cancer, including breast cancer. E2F1 ablation has been shown to decrease metastasis in MMTV-Neu and MMTV-PyMT transgenic mouse models of breast cancer. Here we take a bioinformatic approach to determine the E2F1 regulated genomic alterations involved in the metastatic cascade, in both Neu and PyMT models. Through gene expression analysis, we reveal few transcriptome changes in non-metastatic E2F1^-/- tumors relative to transgenic tumor controls. However investigation of these models through whole genome sequencing found numerous differences between the models, including differences in the proposed tumor etiology between E2F1^-/- and E2F1^+/+ tumors induced by Neu or PyMT. For example, loss of E2F1 within the Neu model led to an increased contribution of the inefficient double stranded break repair signature to the proposed etiology of the tumors. While the SNV mutation burden was higher in PyMT mouse tumors than Neu mouse tumors, there was no statistically significant differences between E2F WT and E2F1 KO mice. Investigating mutated genes through gene set analysis also found a significant number of genes mutated in the cell adhesion pathway in E2F1^-/- tumors, indicating this may be a route for disruption of metastasis in E2F1^-/- tumors. Overall, these findings illustrate the complicated nature of uncovering drivers of the metastatic process.

Multi-omics characterization and validation of invasiveness-related molecular features across multiple cancer types

Background

Tumor invasiveness reflects many biological changes associated with tumorigenesis, progression, metastasis, and drug resistance. Therefore, we performed a systematic assessment of invasiveness-related molecular features across multiple human cancers.

Materials and methods

Multi-omics data, including gene expression, miRNA, DNA methylation, and somatic mutation, in approximately 10,000 patients across 30 cancer types from The Cancer Genome Atlas, Gene Expression Omnibus, PRECOG, and our institution were enrolled in this study.

Results

Based on a robust gene signature, we established an invasiveness score and found that the score was significantly associated with worse prognosis in almost all cancers. Then, we identified common invasiveness-associated dysregulated molecular features between high- and low-invasiveness score group across multiple cancers, as well as investigated their mutual interfering relationships thus determining whether the dysregulation of invasiveness-related genes was caused by abnormal promoter methylation or miRNA expression. We also analyzed the correlations between the drug sensitivity data from cancer cell lines and the expression level of 685 invasiveness-related genes differentially expressed in at least ten cancer types. An integrated analysis of the correlations among invasiveness-related genetic features and drug response were conducted in esophageal carcinoma patients to outline the complicated regulatory mechanism of tumor invasiveness status in multiple dimensions. Moreover, functional enrichment suggests the invasiveness score might serve as a predictive biomarker for cancer patients receiving immunotherapy.

Conclusion

Our pan-cancer study provides a comprehensive atlas of tumor invasiveness and may guide more precise therapeutic strategies for tumor patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02773-x

Vitamin C Inhibits Triple-Negative Breast Cancer Metastasis by Affecting the Expression of YAP1 and Synaptopodin 2

Vitamin C supplementation has been shown to decrease triple-negative breast cancer (TNBC) metastasis. However, the molecular mechanism whereby vitamin C inhibits metastasis remains elusive. It has been postulated that vitamin C reduces the levels of HIF-1α, the master regulator of metastasis, by promoting its hydroxylation and degradation. Here, we show that vitamin C at 100 µM, a concentration achievable in the plasma in vivo by oral administration, blocks TNBC cell migration and invasion in vitro. The protein level of HIF-1α remains largely unchanged in cultured TNBC cells and xenografts, partially due to its upregulated transcription by vitamin C, suggesting that HIF-1α unlikely mediates the action of vitamin C on metastasis. Vitamin C treatment upregulates the expression of synaptopodin 2 and downregulates the expression of the transcription coactivator YAP1, both genes in the Hippo pathway. The changes in SYNPO2 and YAP1 expression were subsequently validated at mRNA and protein levels in cultured TNBC cells and xenografts. Further experiments showed that vitamin C treatment inhibits F-actin assembly and lamellipodia formation, which correlates with the changes in SYNPO2 and YAP1 expression. Overall, these results suggest that vitamin C inhibits TNBC metastasis by affecting the expression of SYNPO2 and YAP1. Vitamin C may thus have a potential role in the prevention and treatment of TNBC metastasis.

Preoperative AFU Is a Useful Serological Prognostic Predictor for Colorectal Liver Oligometastasis Patients Undergoing Hepatic Resection

Background: Preoperative alpha-l-fucosidase (AFU) has been used as a diagnostic biomarker for several cancers, but its role as a prognostic predictor in colorectal cancer liver oligometastasis (CLOM) patients after radical surgery has not been well defined. This study aimed to investigate the prognostic significance of preoperative serum AFU for CLOM patients after hepatic resection.

Methods: A retrospective data set was collected to evaluate the prognostic value of preoperative AFU in CLOM patients after radical hepatic resection. A total of 269 patients with histopathologically confirmed CLOM were enrolled. The optimal cut-off value of preoperative AFU was determined using X-tile software. Univariate and multivariate analyses were used to identify the prognostic significance of preoperative serum AFU.

Results: The X-tile software showed that the optimal cut-off value of preoperative AFU was set at 30.8 U/L. Patients with preoperative AFU≤30.8 and >30.8 were classified into high and low AFU groups, respectively. Female patients and those with a single liver metastasis had a higher tendency to have a preoperative AFU≤30.8 U/L; patients with lower clinical risk score (CRS) were more likely to have AFU >30.8 U/L than patients with higher CRS. The results showed that preoperative AFU was an independent prognostic factor for overall survival (OS) (P=0.041). Patients with a preoperative AFU≤30.8 U/L had a lower OS rate than those with AFU>30.8 U/L. Furthermore, for patients with lower CRS scores (0-2), the tendency clearly showed that patients with higher preoperative AFU had a better prognosis (P=0.029).

Conclusions: Higher preoperative serum AFU can predict better survival in CLOM patients after hepatic resection, especially for CLOM patients with lower CRS scores.

Genome-wide analysis of canine oral malignant melanoma metastasis-associated gene expression

Oral malignant melanoma (OMM) is the most common canine melanocytic neoplasm. Overlap between the somatic mutation profiles of canine OMM and human mucosal melanomas suggest a shared UV-independent molecular aetiology. In common with human mucosal melanomas, most canine OMM metastasise. There is no reliable means of predicting canine OMM metastasis, and systemic therapies for metastatic disease are largely palliative. Herein, we employed exon microarrays for comparative expression profiling of FFPE biopsies of 18 primary canine OMM that metastasised and 10 primary OMM that did not metastasise. Genes displaying metastasis-associated expression may be targets for anti-metastasis treatments, and biomarkers of OMM metastasis. Reduced expression of CXCL12 in the metastasising OMMs implies that the CXCR4/CXCL12 axis may be involved in OMM metastasis. Increased expression of APOBEC3A in the metastasising OMMs may indicate APOBEC3A-induced double-strand DNA breaks and pro-metastatic hypermutation. DNA double strand breakage triggers the DNA damage response network and two Fanconi anaemia DNA repair pathway members showed elevated expression in the metastasising OMMs. Cross-validation was employed to test a Linear Discriminant Analysis classifier based upon the RT-qPCR-measured expression levels of CXCL12, APOBEC3A and RPL29. Classification accuracies of 94% (metastasising OMMs) and 86% (non-metastasising OMMs) were estimated.

Identification of molecular genetic contributants to canine cutaneous mast cell tumour metastasis by global gene expression analysis

Cutaneous mast cell tumours are one of the most common canine cancers. Approximately 25% of the tumours metastasise. Activating c-kit mutations are present in about 20% of tumours, but metastases occur in the absence of mutations. Tumour metastasis is associated with significantly diminished survival in spite of adjuvant chemotherapy. Available prognostic tests do not reliably predict whether a tumour will metastasise. In this study we compared the global expression profiles of 20 primary cutaneous mast cell tumours that metastasised with those of 20 primary tumours that did not metastasise. The objective was to identify genes associated with mast cell tumour metastatic progression that may represent targets for therapeutic intervention and biomarkers for prediction of tumour metastasis. Canine Gene 1.1 ST Arrays were employed for genome-wide expression analysis of formalin-fixed, paraffin-embedded biopsies of mast cell tumours borne by dogs that either died due to confirmed mast cell tumour metastasis, or were still alive more than 1000 days post-surgery. Decreased gene expression in the metastasising tumours appears to be associated with a loss of cell polarity, reduced cell-cell and cell-ECM adhesion, and increased cell deformability and motility. Dysregulated gene expression may also promote extracellular matrix and base membrane degradation, suppression of cell cycle arrest and apoptosis, and angiogenesis. Down-regulation of gene expression in the metastasising tumours may be achieved at least in part by small nucleolar RNA-derived RNA and microRNA-effected gene silencing. Employing cross-validation, a linear discriminant analysis-based classifier featuring 19 genes that displayed two-fold differences in expression between metastasising and non-metastasising tumours was estimated to classify metastasising and non-metastasising tumours with accuracies of 90-100% and 70-100%, respectively. The differential expression of 9 of the discriminator genes was confirmed by quantitative reverse transcription-PCR.

Gene set enrichment analysis and meta-analysis to identify six key genes regulating and controlling the prognosis of esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a common malignancy with high mortality. Because of the lack of clarity in the relevant genes and mechanisms involved, and the current difficulty for oncotherapy in providing therapeutic solutions, there is an urgent need to study this matter. While gene probe studies have been used to select the most virulent genes and pathways, paucity of case controls during gene screening and lack of conclusive results to expound the etiology and pathogenesis of the disease, have reduced study reliability.

Methods

We chose six datasets from independent studies in the Gene Expression Omnibus (GEO) database and used gene set enrichment analysis and meta-analysis to select key genes and pathways.

Results

We found four down-regulated and four up-regulated pathways through gene set enrichment analysis, and 406 differential genes through meta-analysis. Based on The Cancer Genome Atlas (TCGA), 995 differentially expressed genes were screened out. Comparing the 406 gene set with the 995 gene set, we found 19 common genes, of which 6 had a common pathway and were screened out as key genes regulating and controlling the prognosis of ESCC.

Conclusions

Among the 19 genes, we found three genes that affect the chemotherapy of ESCC: BUB1B, BUB1, and TTK. Another three genes NDC1, NUP107, and NUP155 on the RNA transport pathway were also found. Altogether, these six genes are not only crucial in the development of ESCC, but also determine the prognosis of patients. The key genes and pathways identified in the present study will be used for the next stage in our study, which will involve gene elimination and other experimentation methods.

Human a-L-fucosidase-1 attenuates the invasive properties of thyroid cancer

Glycans containing α-L-fucose participate in diverse interactions between cells and extracellular matrix. High glycan expression on cell surface is often associated with neoplastic progression. The lysosomal exoenzyme, α-L-fucosidase-1 (FUCA-1) removes fucose residues from glycans. The FUCA-1 gene is down-regulated in highly aggressive and metastatic human tumors. However, the role of FUCA-1 in tumor progression remains unclear. It is speculated that its inactivation perturbs glycosylation of proteins involved in cell adhesion and promotes cancer. FUCA-1 expression of various thyroid normal and cancer tissues assayed by immunohistochemical (IHC) staining was high in normal thyroids and papillary thyroid carcinomas (PTC), whereas it progressively decreased in poorly differentiated, metastatic and anaplastic thyroid carcinomas (ATC). FUCA-1 mRNA expression from tissue samples and cell lines and protein expression levels and enzyme activity in thyroid cancer cell lines paralleled those of IHC staining. Furthermore, ATC-derived 8505C cells adhesion to human E-selectin and HUVEC cells was inhibited by bovine α-L-fucosidase or Lewis antigens, thus pointing to an essential role of fucose residues in the adhesive phenotype of this cancer cell line. Finally, 8505C cells transfected with a FUCA-1 containing plasmid displayed a less invasive phenotype versus the parental 8505C. These results demonstrate that FUCA-1 is down-regulated in ATC compared to PTC and normal thyroid tissues and cell lines. As shown for other human cancers, the down-regulation of FUCA-1 correlates with increased aggressiveness of the cancer type. This is the first report indicating that the down-regulation of FUCA-1 is related to the increased aggressiveness of thyroid cancer.

MicroRNA-mRNA expression profiles associated with medulloblastoma subgroup 4

Purpose

Medulloblastoma (MB), the most common malignant brain tumor in children, is divided into four tumor subgroups: wingless-type (WNT), sonic hedgehog (SHH), Group 3, and Group 4. Ideally, clinical practice and treatment design should be subgroup specific. While WNT and SHH subgroups have well-defined biomarkers, distinguishing Group 3 from Group 4 is not straightforward. MicroRNAs (miRNAs), which regulate posttranscriptional gene expression, are involved in MB tumorigenesis. However, the miRNA–messenger RNA (mRNA) regulatory network in MB is far from being fully understood. Our aims were to investigate miRNA expression regulation in MB subgroups, to assess miRNA target relationships, and to identify miRNAs that can distinguish Group 3 from Group 4.

Patients and methods

With these aims, integrated transcriptome mRNA and miRNA expression analysis was performed on primary tumor samples collected from 18 children with MB, using miRNA sequencing (miRNA-seq), RNA sequencing (RNA-seq), and quantitative PCR.

Results

Of all the expressed miRNAs, 19 appeared to be significantly differentially expressed (DE) between Group 4 and non-Group 4 subgroups (false discovery rate [FDR] <0.05), including 10 miRNAs, which, for the first time, are reported to be in conjunction with MB. RNA-seq analysis identified 165 genes that were DE between Group 4 and the other subgroups (FDR <0.05), among which seven are predicted targets of five DE miRNAs and exhibit inverse expression pattern.

Conclusion

This study identified miRNA molecules that may be involved in Group 4 etiology, in general, and can distinguish between Group 3 and Group 4, in particular. In addition, understanding the involvement of miRNAs and their targets in MB may improve diagnosis and advance the development of targeted treatment for MB.

Reduced expression of α-L-Fucosidase-1 (FUCA-1) predicts recurrence and shorter cancer specific survival in luminal B LN+ breast cancer patients

Background

The lysosomal enzyme α-L-Fucosidase-1 (FUCA-1) catalyzes the hydrolytic cleavage of terminal fucose residues. FUCA-1 gene is down-regulated in highly aggressive and metastatic human tumors as its inactivation perturbs the fucosylation of proteins involved in cell adhesion, migration and metastases.

Results

Negativity to FUCA-1 was significantly related to the development of later recurrences in breast cancer patients with lymph node involvement at diagnosis. Cancer specific survival of luminal B LN+ patients was influenced by FUCA-1 expression as luminal B LN+ patients with positive expression had a longer cancer specific survival. FUCA-1 mRNA expression was inversely related to cancer stage and lymph node involvement. WB and qPCR analysis of FUCA-1 expression in breast cancer-derived cell lines confirmed an inverse relationship with tumor aggressiveness.

Conclusions

This study shows that, within LN+ breast cancer patients, FUCA-1 is able to identify a sub-set of non recurrent patients characterized by the positive expression of FUCA-1 and that, within luminal B LN+ patients, the expression of FUCA-1 predicts longer cancer specific survival.

Methods

We have analyzed FUCA-1 in 305 breast cancer patients by Immunohistochemistry (IHC), and by qPCR in breast cancer patients and in breast cancer cell lines.

A core program of gene expression characterizes cancer metastases

While aberrant expression or splicing of metastasis genes conveys to cancers the ability to break through tissue barriers and disseminate, the genetic basis for organ preference in metastasis formation has remained incompletely understood. Utilizing the gene expression profiles from 653 GEO datasets, we investigate whether the signatures by diverse cancers in various metastatic sites display common features. We corroborate the meta-analysis in a murine model. Metastases are generally characterized by a core program of gene expression that induces the oxidative metabolism, activates vascularization/tissue remodeling, silences extracellular matrix interactions, and alters ion homeostasis. This program distinguishes metastases from their originating primary tumors as well as from their target host tissues. Site-selectivity is accomplished through specific components that adjust to the target micro-environment. The same functional groups of gene expression programs are activated in the metastases of B16-F10 cells to various target organs. It remains to be investigated whether these genetic signatures precede implantation and thus determine organ preference or are shaped by the target site and are thus a consequence of implantation. Conceivably, chemotherapy of disseminated cancer might be more efficacious if selected to match the genetic makeup of the metastases rather than the organ of origin by the primary tumor.

Investigation of a common gene expression signature in gastrointestinal cancers using systems biology approaches

According to GLOBOCAN 2012, the incidence and the mortality rate of colorectal, stomach and liver cancers are the highest among the total gastrointestinal (GI) cancers.

Heme oxygenase-1 in the forefront of a multi-molecular network that governs cell-cell contacts and filopodia-induced zippering in prostate cancer

Prostate cancer (PCa) cells display abnormal expression of cytoskeletal proteins resulting in an augmented capacity to resist chemotherapy and colonize distant organs. We have previously shown that heme oxygenase 1 (HO-1) is implicated in cell morphology regulation in PCa. Here, through a multi 'omics' approach we define the HO-1 interactome in PCa, identifying HO-1 molecular partners associated with the integrity of the cellular cytoskeleton. The bioinformatics screening for these cytoskeletal-related partners reveal that they are highly misregulated in prostate adenocarcinoma compared with normal prostate tissue. Under HO-1 induction, PCa cells present reduced frequency in migration events, trajectory and cell velocity and, a significant higher proportion of filopodia-like protrusions favoring zippering among neighboring cells. Moreover forced expression of HO-1 was also capable of altering cell protrusions in transwell co-culture systems of PCa cells with MC3T3 cells (pre-osteoblastic cell line). Accordingly, these effects were reversed under siHO. Transcriptomics profiling evidenced significant modulation of key markers related to cell adhesion and cell–cell communication under HO-1 induction. The integration from our omics-based research provides a four molecular pathway foundation (ANXA2/HMGA1/POU3F1; NFRSF13/GSN; TMOD3/RAI14/VWF; and PLAT/PLAU) behind HO-1 regulation of tumor cytoskeletal cell compartments. The complementary proteomics and transcriptomics approaches presented here promise to move us closer to unravel the molecular framework underpinning HO-1 involvement in the modulation of cytoskeleton pathways, pushing toward a less aggressive phenotype in PCa.

Identification of phenotype-relevant differentially expressed genes in breast cancer demonstrates enhanced quantile discretization protocol's utility in multi-platform microarray data integration

Microarray for transcriptomics experiments often suffer from limited statistical power due to small sample size. Quantile discretization (QD) maps expression values for a sample into a series of equivalently sized 'bins' that represent a discrete numerical range, e.g. [Formula: see text]4 to [Formula: see text]4, which enables normalized data from multiple experiments and/or expression platforms to be combined for re-analysis. We found, however, that informal selection of bin numbers often resulted in loss of the underlying correlation structure in the data through assigning of the same numerical value to genes that are in reality expressed at significantly different levels within a sample. Here we report a procedure for determining an optimal bin number for dataset. Applying this to integrated public breast cancer datasets enabled statistical identification of several differentially expressed tumorigenesis-related genes that were not found when analyzing the individual datasets, and also several cancer biomarkers not previously indicated as having utility in the disease. Notably, differential modulation of translational control and protein synthesis via multiple pathways were found to potentially have central roles in breast cancer development and progression. These findings suggest that our protocol has significant utility in making meaningful novel biomedical discoveries by leveraging the large public expression data repositories.

Targeting Serglycin Prevents Metastasis in Murine Mammary Carcinoma

In hematopoietic cells, serglycin proteoglycans mainly contribute to proper storage and secretion of inflammatory mediators via their negatively charged glycosaminoglycans. Serglycin proteoglycans are also expressed in cancer cells where increased expression has been linked to poor prognosis. However, the serglycin-dependent mediators promoting cancer progression remain to be determined. In the present study we report that genetic ablation of serglycin proteoglycan completely blocks lung metastasis in the MMTV-PyMT-driven mouse breast cancer model, while serglycin-deficiency did not affect primary tumour growth or number of mammary tumours. Although E-cadherin expression was higher in the serglycin-deficient primary tumour tissue, indicating reduced invasiveness, serglycin-deficient tumour cells were still detected in the circulation. These data suggest that serglycin proteoglycans play a role in extravasation as well as colonization and growth of metastatic cells. A microarray expression analysis and functional annotation of differentially expressed genes identified several biological pathways where serglycin may be important. Our results suggest that serglycin and serglycin-dependent mediators are potential drug targets to prevent metastatic disease/dissemination of cancer.

Combined analysis of primary lymphoid tissues' transcriptomic response to extra-intestinal Escherichia coli (ExPEC) infection

Avian pathogenic Escherichia coli (APEC), an extraintestinal pathogenic E. coli (ExPEC), constitutes an animal health and a potential zoonotic risk. Most studies focus on the response of a single tissue to APEC infection. Understanding interactions among lymphoid tissues is of importance in controlling APEC infection. Therefore, we studied bone marrow, bursa, and thymus transcriptomes because of these tissues' crucial roles in development of pre-lymphocytes, B cells, and T cells, respectively. Using lesion scores of liver, pericardium, and air sacs, infected birds were classified as either resistant or susceptible. Little difference in gene expression was detected in resistant birds in bone marrow versus bursa or thymus, while there were large differences between tissues in susceptible birds. Phagosome, lysosome and cytokine interactions were strongly enhanced in thymus versus bone marrow in susceptible birds, and T cell receptor (TCR), cell cycle, and p53 signaling were significantly decreased. B cell receptor (BCR) was also significantly suppressed in bursa versus bone marrow in susceptible birds. This research provides novel insights into the complex developmental changes in gene expression occurring across the primary lymphoid organs and, therefore, serves as a foundation to understanding the cellular and molecular basis of host resistance to APEC infection.

Cripto-1 as a novel therapeutic target for triple negative breast cancer

Triple-negative breast cancer (TNBC) presents the poorest prognosis among the breast cancer subtypes and no current standard therapy. Here, we performed an in-depth molecular analysis of a mouse model that establishes spontaneous lung metastasis from JygMC(A) cells. These primary tumors resembled the triple-negative breast cancer (TNBC) both phenotypically and molecularly. Morphologically, primary tumors presented both epithelial and spindle-like cells but displayed only adenocarcinoma-like features in lung parenchyma. The use of laser-capture microdissection combined with Nanostring mRNA and microRNA analysis revealed overexpression of either epithelial and miRNA-200 family or mesenchymal markers in adenocarcinoma and mesenchymal regions, respectively. Cripto-1, an embryonic stem cell marker, was present in spindle-like areas and its promoter showed activity in primary tumors. Cripto-1 knockout by the CRISPR-Cas9 system inhibited tumor growth and pulmonary metastasis. Our findings show characterization of a novel mouse model that mimics the TNBC and reveal Cripto-1 as a TNBC target hence may offer alternative treatment strategies for TNBC.

Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

BACKGROUND

A high caloric diet, in conjunction with low levels of physical activity, promotes obesity. Many studies are available regarding the relation between dietary saturated fats and the etiology of obesity, but most focus on liver, muscle and white adipose tissue. Furthermore, the majority of transcriptomic studies seek to identify linear effects of an external stimulus on gene expression, although such an assumption does not necessarily hold. Our work assesses the dose-dependent effects of dietary fat intake on differential gene expression in the proximal, middle and distal sections of the small intestine in C57BL/6J mice. Gene expression is analyzed in terms of either linear or nonlinear responses to fat intake.

RESULTS

The highest number of differentially expressed genes was observed in the middle section. In all intestine sections, most of the identified processes exhibited a linear response to increasing fat intake. The relative importance of logarithmic and exponential responses was higher in the proximal and distal sections, respectively. Functional enrichment analysis highlighted a constantly linear regulation of acute-phase response along the whole small intestine, with up-regulation of Serpina1b. The study of gene expression showed that exponential down-regulation of cholesterol transport in the middle section is coupled with logarithmic up-regulation of cholesterol homeostasis. A shift from linear to exponential response was observed in genes involved in the negative regulation of caspase activity, from middle to distal section (e.g., Birc5, up-regulated).

CONCLUSIONS

The transcriptomic signature associated with inflammatory processes preserved a linear response in the whole small intestine (e.g., up-regulation of Serpina1b). Processes related to cholesterol homeostasis were particularly active in the middle small intestine and only the highest fat intake down-regulated cholesterol transport and efflux (with a key role played by the down-regulation of ATP binding cassette transporters). Characterization of nonlinear patterns of gene expression triggered by different levels of dietary fat is an absolute novelty in intestinal studies. This approach helps identifying which processes are overloaded (i.e., positive, logarithmic regulation) or arrested (i.e., negative, exponential regulation) in response to excessive fat intake, and can shed light on the relationships linking lipid intake to obesity and its associated molecular disturbances.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications.

Gene set enrichment ensemble using fold change data only

In a number of biological studies, the raw gene expression data are not usually published due to different causes, such as data privacy and patent rights. Instead, significant gene lists with fold change values are usually provided in most studies. However, due to variations in data sources and profiling conditions, only a small number of common significant genes could be found among similar studies. Moreover, traditional gene set based analyses that consider these genes have not taken into account the fold change values, which may be important to distinguish between the different levels of significance of the genes. Human embryonic stem cell derived cardiomyocytes (hESC-CM) is a good representative of this category. hESC-CMs, with its role as a potentially unlimited source of human heart cells for regenerative medicine, have attracted the attentions of biological and medical researchers. Because of the difficulty of acquiring data and the resulting expenses, there are only a few related hESC-CM studies and few hESC-CM gene expression data are provided. In view of these challenges, we propose a new Gene Set Enrichment Ensemble (GSEE) approach to perform gene set based analysis on individual studies based on significant up-regulated gene lists with fold change data only. Our approach provides both explicit and implicit ways to utilize the fold change data, in order to make full use of scarce data. We validate our approach with hESC-CM data and fetal heart data, respectively. Experimental results on significant gene lists from different studies illustrate the effectiveness of our proposed approach.

Genetic instability in the tumor microenvironment: a new look at an old neighbor

The recent exponential increase in our knowledge of cellular and molecular mechanisms involved in carcinogenesis has largely failed to translate into new therapies and clinical practices. This lack of success may result in part from the fact that most studies focus on tumor cells as potential therapeutic targets and neglect the complex microenvironment that undergoes profound changes during tumor development. Furthermore, an unfortunate association of factors such as tumor genetic complexity, overestimation of biomarker and drug potentials, as well as a poor understanding of tumor microenvironment in diagnosis and prognosis leads to the current levels of treatment failure regarding a vast majority of cancer types. A growing body of evidence points to the importance of the functional diversity of immune and structural cells during tumor development. In this sense, the lack of technologies that would allow for molecular screening of individual stromal cell types poses a major challenge for the development of therapies targeting the tumor microenvironment. Progress in microenvironment genetic studies represents a formidable opportunity for the development of new selective drugs because stromal cells have lower mutation rates than malignant cells, and should prove to be good targets for therapy.

Identification of a multi-cancer gene expression biomarker for cancer clinical outcomes using a network-based algorithm

Cancer types are commonly classified by histopathology and more recently through molecular characteristics such as gene expression, mutations, copy number variations, and epigenetic alterations. These molecular characterizations have led to the proposal of prognostic biomarkers for many cancer types. Nevertheless, most of these biomarkers have been proposed for a specific cancer type or even specific subtypes. Although more challenging, it is useful to identify biomarkers that can be applied for multiple types of cancer. Here, we have used a network-based exploration approach to identify a multi-cancer gene expression biomarker highly connected by ESR1, PRKACA, LRP1, JUN and SMAD2 that can be predictive of clinical outcome in 12 types of cancer from The Cancer Genome Atlas (TCGA) repository. The gene signature of this biomarker is highly supported by cancer literature, biological terms, and prognostic power in other cancer types. Additionally, the signature does not seem to be highly associated with specific mutations or copy number alterations. Comparisons with cancer-type specific and other multi-cancer biomarkers in TCGA and other datasets showed that the performance of the proposed multi-cancer biomarker is superior, making the proposed approach and multi-cancer biomarker potentially useful in research and clinical settings.

MYLK and MYL9 expression in non-small cell lung cancer identified by bioinformatics analysis of public expression data

Gene expression microarrays are widely used to investigate molecular targets in cancers, including lung cancer. In this study, we analyzed online non-small cell lung cancer (NSCLC) microarray databases, to screen the key genes and pathways related to NSCLC by bioinformatics analyses. And then, the expression levels of two selected genes in the down-regulated co-pathways, myosin light chain kinase (MYLK) and myosin regulatory light chain 9 (MYL9), were determined in tumor, paired paraneoplastic, and normal lung tissues. First, gene set enrichment analysis and meta-analysis were conducted to identify key genes and pathways that contribute to NSCLC carcinogenesis. Second, using the total RNA and protein extracted from lung cancer tissues (n = 240), adjacent non-cancer tissues (n = 240), and normal lung tissues (n = 300), we examined the MYLK and MYL9 expression levels by quantitative real-time PCR and Western blot. Finally, we explored the correlations between mRNA and protein expressions of these two genes and the clinicopathological parameters of NSCLC. Fifteen up-regulated and nine down-regulated co-pathways were observed. A number of differentially expressed genes (CALM1, THBS1, CSF3, BMP2, IL6ST, MYLK, ROCK2, IL3RA, MYL9, PPP2CA, CSF2RB, CNAQ, GRIA2, IL10RA, IL10RB, IL11RA, LIFR, PLCB4, and RAC3) were identified (P < 0.01) in the down-regulated co-pathways. The expression levels of MYLK and MYL9, which act downstream of the vascular smooth muscle contraction signal pathway and focal adhesion pathway, were significantly lower in cancer tissue than those in the paraneoplastic and normal tissues (P < 0.05). Moreover, the expression levels of these two genes in stages III and IV NSCLC were significantly increased, when compared to stages I and II, and expressions levels in NSCLC with lymphatic metastasis were higher than that without lymphatic metastasis (P < 0.05). Additionally, significant lower expression levels of the two genes were found in smokers than in nonsmokers (P < 0.05). In contrast, gender, differentiated degrees, and pathohistological type appeared to have no impact on these gene expressions (P > 0.05). These findings suggested that low MYLK and MYL9 expressions might be associated with the development of NSCLC. These genes may be also relevant to NSCLC metastasis. Future investigations with large sample sizes needed to verify these findings.

High expression of GEM and EDNRA is associated with metastasis and poor outcome in patients with advanced bladder cancer

Background

The standard treatment for non-metastatic muscle-invasive bladder cancer (stages T2–T4a) is radical cystectomy with lymphadenectomy. However, patients undergoing cystectomy show metastatic spread in 25% of cases and these patients will have limited benefit from surgery. Identification of patients with high risk of lymph node metastasis will help select patients that may benefit from neoadjuvant and/or adjuvant chemotherapy.

Methods

RNA was procured by laser micro dissection of primary bladder tumors and corresponding lymph node metastases for Affymetrix U133 Plus 2.0 Gene Chip expression profiling. A publically available dataset was used for identification of the best candidate markers, and these were validated using immunohistochemistry in an independent patient cohort of 368 patients.

Results

Gene Set Enrichment Analysis showed significant enrichment for e.g. metastatic signatures in the metastasizing tumors, and a set of 12 genes significantly associated with lymph node metastasis was identified. Tumors did not cluster according to their metastatic ability when analyzing gene expression profiles using hierarchical cluster analysis. However, half (6/12) of the primary tumor clustered together with matching lymph node metastases, indicating a large degree of intra-patient similarity in these patients. Immunohistochemical analysis of 368 tumors from cystectomized patients showed high expression of GEM (P = 0.033; HR = 1.46) and EDNRA (P = 0.046; HR = 1.60) was significantly associated with decreased cancer-specific survival.

Conclusions

GEM and EDNRA were identified as promising prognostic markers for patients with advanced bladder cancer. The clinical relevance of GEM and EDNRA should be evaluated in independent prospective studies.

Expression of integrin β1 and its significance in squamous cell carcinoma of the cervix

The aim of the present study was to examine the expression of integrin β1 in squamous cell carcinoma (SCC) of the cervix and its association with the clinicopathological features of patients. The expression of integrin β1 in 87 SCC cervical tissues and 32 normal cervical tissues was detected using an enzyme-linked immunosorbent assay, western blot analysis and the immunohistochemical streptavidin-peroxidase method. Integrin β1 expression was greater in SCC cervical tissues compared with that in normal cervical tissues (P<0.05), and its mean expression level in the SCC cervical tissues was also markedly higher compared with that in the normal cervical tissues (P<0.05). In terms of the association between the expression of integrin β1 with clinicopathological features, patients with stage IIA SCC had higher integrin β1 positive rates compared with patients with stage I SCC (P<0.05). The integrin β1 positive rates in SCC tissues with histological grade 3 were also significantly higher than that in the SCC tissues with histological grade 1 (P<0.05). Furthermore, patients with cervical SCC with lymph node metastasis showed increased integrin β1 positive expression compared with those without lymph node metastasis (P<0.05). In conclusion, the expression of integrin β1 protein in cervical SCC tissues was significantly higher than that in the normal cervical tissues, and it increased with the clinical stage and the degree of malignancy.

Using a systems biology approach to understand and study the mechanisms of metastasis

Metastasis remains the main cause for cancer-related deaths due to the lack of effective therapy. The clonal selection model has long been thought to be the primary mechanism of metastatic progression but many different mechanisms have been hypothesized for the progression from tumorigenesis to the successful dissemination and expansion of tumor cells at the secondary site. MicroRNAs, germline polymorphisms in combination with the tumor microenvironment are few of the different pathways to explain the metastatic cascade. Technological advances for high-throughput screening of cells such as expression profiling, next generation sequencing, as well as global network analyses have advanced the studies of these mechanisms. Combined with new insights into the various mechanisms of metastasis a systems biology approach has also been shown to be useful in identifying metastasis-specific gene signatures as well as predicting disease outcome. Furthermore, the results of these studies have been relevant for identifying biomarkers for metastatic disease.

Seed and soil: A conceptual framework of metastasis for clinicians

Most mortality from cancer is secondary to metastasis. Metastasis refers both to the process by which tumor cells establish themselves at organs distinct from where they originated and to the life-threatening lesions themselves. Metastases are often resistant to conventional therapies, highlighting a key distinction between these progeny lesions and the primary tumor from which they arose. Here, we summarize recent advances in understanding and targeting primary tumors and the mechanisms and therapeutic challenges of metastasis.

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.

Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs.

Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

[Bioinformatic screening of key genes controlling the development and progression of lung cancer]

BACKGROUND AND OBJECTIVE

Lung cancer is the most common cancer in the world. The gene expression profiling of lung cancer has been extensively investigated. However, only a few studies have identified the possible pathways and significant genes related to lung cancer. The aim of this study is to explore the large number of lung cancer-related microarray datasets and identify the crucial genes that can benefit the understanding of the progression and development of this disease.

METHODS

To identify the genes that effected lung cancer at the mRNA level, gene set enrichment analysis was used to analyze six selected gene expression datasets.

RESULTS

Among the six gene expression datasets, 3 up-regulated and 26 down-regulated pathways were found by gene set enrichment analysis. We found 11 significant genes with P < 0.05 from the results of tight junction meta-analysis of the six data sets.

CONCLUSIONS

The tight junction pathway plays an important role in the study of the occurrence and development of lung cancer. Significant genes within the pathways will be further discussed in future studies.

Network analysis of gene lists for finding reproducible prognostic breast cancer gene signatures

Many genome-scale studies in molecular biology deliver results in the form of a ranked list of gene names, accordingly to some scoring method. There is always the question how many top-ranked genes to consider for further analysis, for example, in order creating a diagnostic or predictive gene signature for a disease. This question is usually approached from a statistical point of view, without considering any biological properties of top-ranked genes or how they are related to each other functionally. Here we suggest a new method for selecting a number of genes in a ranked gene list such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. The method allows associating a network with the gene list, providing easier interpretation of the results and classifying the genes or proteins accordingly to their position in the resulting network. We demonstrate the method on four breast cancer datasets and show that 1) the resulting gene signatures are more reproducible from one dataset to another compared to standard statistical procedures and 2) the overlap of these signatures has significant prognostic potential. The method is implemented in BiNoM Cytoscape plugin (http://binom.curie.fr).

[Screening key genes associated with the development and progression of non-small cell lung cancer based on gene-enrichment analysis and meta-analysis]

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors; however, its causes are still not completely understood. This study was designed to screen the key genes and pathways related to NSCLC occurrence and development and to establish the scientific foundation for the genetic mechanisms and targeted therapy of NSCLC.

METHODS

Both gene set-enrichment analysis (GSEA) and meta-analysis (meta) were used to screen the critical pathways and genes that might be corretacted with the development and progression of lung cancer at the transcription level.

RESULTS

Using the GSEA and meta methods, focal adhesion and regulation of actin cytoskeleton were determined to be the more prominent overlapping significant pathways. In the focal adhesion pathway, 31 genes were statistically significant (P<0.05), whereas in the regulation of actin cytoskeleton pathway, 32 genes were statistically significant (P<0.05).

CONCLUSIONS

The focal adhesion and the regulation of actin cytoskeleton pathways might play important roles in the occurrence and development of NSCLC. Further studies are needed to determine the biological function for the positive genes.

A systems biology approach reveals common metastatic pathways in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models.

RESULTS

mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a "shortest-path" algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including "Cytoskeleton remodeling/TGF/WNT", "Cytoskeleton remodeling/Cytoskeleton remodeling", and "Cell adhesion/Chemokines and adhesion". Of these, the "Cytoskeleton remodeling/TGF/WNT" was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the "Cytoskeleton remodeling/TGF/WNT" pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform.

CONCLUSIONS

In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.

Applying gene set enrichment analysis and meta-analysis to screen key genes controlling the development and progression of hepatic carcinoma

AIM: To analyze vast amounts of hepatic carcinoma-related microarray data and identify crucial genes that control the development and progression of hepatocellular carcinoma (HCC).

METHODS: Cross-species comparison could be used to explore the similarities between HCC-related gene expression profiles of human beings and other species. In order to screen genes that are involved in hepatocarcinogenesis, gene set enrichment analysis (GSEA) and meta-analysis were performed to study five gene expression data sets of independent species.

RESULTS: Among the five gene expression data sets, three up-regulated and two down-regulated pathways were found to be consistent by gene set enrichment analysis. The up-regulated pathways are amino sugar and nucleotide sugar metabolism, cell cycle, and thyroid cancer, while the down-regulated pathways are linoleic acid metabolism and arachidonic acid metabolism. A total of 1 708 genes with a P < 0.05 were found in meta-analysis for five datasets, of which 720 could be assigned to functional pathways by DAVID and KEGG. These pathways include cell cycle, oocyte meiosis, and DNA replication. Cell cycle is the overlapping significant pathway between the two methods. Twenty-five genes with a P < 0.05 were identified in meta-analysis of cell cycle pathway. Five significant genes may be involved in the occurrence and progression of HCC.

CONCLUSION: Cell cycle may be the crucial pathway to affect signal transduction in hepatocarcinogenesis.

Role of Metastasis in Hypertabastic Survival Analysis of Breast Cancer: Interaction with Clinical and Gene Expression Variables

This paper analyzes the survival of breast cancer patients, exploring the role of a metastasis variable in combination with clinical and gene expression variables. We use the hypertabastic model in a detailed analysis of 295 breast cancer patients from the Netherlands Cancer Institute given in. 1 In comparison to Cox regression the increase in accuracy is complemented by the ability to analyze the time course of the disease progression using the explicitly described hazard and survival curves. We also demonstrate the ability to compute deciles for survival and probability of survival to a given time. Our primary concern in this article is the introduction of a variable representing the existence of metastasis and the effects on the other clinical and gene expression variables. In addition to making a quantitative assessment of the impact of metastasis on the prospects for survival, we are able to look at its interactions with the other prognostic variables. The estrogen receptor status increase in importance, while the significance of the gene expression variables used in the combined model diminishes. When considering only the subgroup of patients who experienced metastasis, the covariates in the model are only the clinical variables for estrogen receptor status and tumor grade.