Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation

Transcriptome profiling and analysis of patients with esophageal squamous cell carcinoma from Kazakhstan

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal cancer in Central Asia, often diagnosed at advanced stages. Understanding population-specific patterns of ESCC is crucial for tailored treatments. This study aimed to unravel ESCC's genetic basis in Kazakhstani patients and identify potential biomarkers for early diagnosis and targeted therapies. ESCC patients from Kazakhstan were studied. We analyzed histological subtypes and conducted in-depth transcriptome sequencing. Differential gene expression analysis was performed, and significantly dysregulated pathways were identified using KEGG pathway analysis (p-value < 0.05). Protein-protein interaction networks were constructed to elucidate key modules and their functions. Among Kazakhstani patients, ESCC with moderate dysplasia was the most prevalent subtype. We identified 42 significantly upregulated and two significantly downregulated KEGG pathways, highlighting molecular mechanisms driving ESCC pathogenesis. Immune-related pathways, such as viral protein interaction with cytokines, rheumatoid arthritis, and oxidative phosphorylation, were elevated, suggesting immune system involvement. Conversely, downregulated pathways were associated with extracellular matrix degradation, crucial in cancer invasion and metastasis. Protein-protein interaction network analysis revealed four distinct modules with specific functions, implicating pathways in esophageal cancer development. High-throughput transcriptome sequencing elucidated critical molecular pathways underlying esophageal carcinogenesis in Kazakhstani patients. Insights into dysregulated pathways offer potential for early diagnosis and precision treatment strategies for ESCC. Understanding population-specific patterns is essential for personalized approaches to ESCC management.

Transcriptomic analysis of eyelid pigmentation in Hereford cattle

The study of skin color in cattle holds both economic and scientific interest. Several ocular diseases of cattle have been associated with low pigmentation of the eyelids, including ocular squamous cell carcinoma and infectious keratoconjunctivitis, the two most common ocular diseases affecting cattle production. Although low eyelid pigmentation is a well-known risk factor for various ocular diseases, the genetic and biological basis of this relationship is largely unknown. We investigated the transcriptome of eyelid skin in Hereford cattle using RNA-sequencing technology. Two contrasting groups were evaluated: steers that were completely pigmented and steers with no pigmentation in both eyelids. Most of the up-regulated genes in pigmented samples are directly implicated in melanogenesis and melanosome development, whereas up-regulated genes in non-pigmented samples are implicated in cancer development and the immune system, among other functions. Interestingly, network analysis comparing pigmented vs. non-pigmented samples revealed significant differences in the co-expression patterns of genes related to melanosome, pigmentation and defense response to bacteria, showing higher gene activity, greater co-expression patterns and tighter co-regulation mechanisms in pigmented samples. Overall, our findings indicate that bovine eyelid pigmentation depends on the expression of many genes involved not only in pigmentation and melanosome function but also related to inflammatory response, infection and tumoral pathways.

Replication-dependent histone isoforms: a new source of complexity in chromatin structure and function

Replication-dependent histones are expressed in a cell cycle regulated manner and supply the histones necessary to support DNA replication. In mammals, the replication-dependent histones are encoded by a family of genes that are located in several clusters. In humans, these include 16 genes for histone H2A, 22 genes for histone H2B, 14 genes for histone H3, 14 genes for histone H4 and 6 genes for histone H1. While the proteins encoded by these genes are highly similar, they are not identical. For many years, these genes were thought to encode functionally equivalent histone proteins. However, several lines of evidence have emerged that suggest that the replication-dependent histone genes can have specific functions and may constitute a novel layer of chromatin regulation. This Survey and Summary reviews the literature on replication-dependent histone isoforms and discusses potential mechanisms by which the small variations in primary sequence between the isoforms can alter chromatin function. In addition, we summarize the wealth of data implicating altered regulation of histone isoform expression in cancer.

Knockdown of ribosomal protein S15A inhibits proliferation of breast cancer cells through induction of apoptosis in vitro

To explore the role of ribosomal protein S15A (RPS15A) in breast cancer. The Oncomine database was used to compare the expression of RPS15A in human breast cancer tissues and normal tissues. RPS15A in breast cancer cell line ZR-75-30 and BT474 was specifically knocked down using lentivirus-mediated short hairpin RNAs (shRNAs). RPS15A knockdown efficiency was validated by quantitative polymerase chain reaction and western blot analysis. Subsequently, the functional effects of RPS15A on proliferation of breast cancer cells were investigated by MTT, colony formation and flow cytometry assays. Functional analysis indicated that RPS15A knockdown could inhibit cell proliferation, induced cell cycle arrest and apoptosis. Mechanism analysis revealed RPS15A mediated apoptosis via activating of caspase-3 and PARP cleavage, upregulating of Bad and BAX and downregulating of Bcl-2. Our preliminary study highlighted the importance of RPS15A in breast cancer growth. The inhibition of RPS15A may be a promising therapeutic target for breast cancer treatment.

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10-4) alone remained predictive after adjusting for clinical predictors.

Histone isoform H2A1H promotes attainment of distinct physiological states by altering chromatin dynamics

Background

The distinct functional effects of the replication-dependent histone H2A isoforms have been demonstrated; however, the mechanistic basis of the non-redundancy remains unclear. Here, we have investigated the specific functional contribution of the histone H2A isoform H2A1H, which differs from another isoform H2A2A3 in the identity of only three amino acids.

Results

H2A1H exhibits varied expression levels in different normal tissues and human cancer cell lines (H2A1C in humans). It also promotes cell proliferation in a context-dependent manner when exogenously overexpressed. To uncover the molecular basis of the non-redundancy, equilibrium unfolding of recombinant H2A1H-H2B dimer was performed. We found that the M51L alteration at the H2A–H2B dimer interface decreases the temperature of melting of H2A1H-H2B by ~ 3 °C as compared to the H2A2A3-H2B dimer. This difference in the dimer stability is also reflected in the chromatin dynamics as H2A1H-containing nucleosomes are more stable owing to M51L and K99R substitutions. Molecular dynamic simulations suggest that these substitutions increase the number of hydrogen bonds and hydrophobic interactions of H2A1H, enabling it to form more stable nucleosomes.

Conclusion

We show that the M51L and K99R substitutions, besides altering the stability of histone–histone and histone–DNA complexes, have the most prominent effect on cell proliferation, suggesting that the nucleosome stability is intimately linked with the physiological effects observed. Our work provides insights into the molecular basis of the non-redundancy of the histone H2A isoforms that are being increasingly reported to be functionally important in varied physiological contexts.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-017-0155-z) contains supplementary material, which is available to authorized users.

RNA-seq in kinetoplastids: A powerful tool for the understanding of the biology and host-pathogen interactions

The kinetoplastids include a large number of parasites responsible for serious diseases in humans and animals (Leishmania and Trypanosoma brucei) considered endemic in several regions of the world. These parasites are characterized by digenetic life cycles that undergo morphological and genetic changes that allow them to adapt to different microenvironments on their vertebrates and invertebrates hosts. Recent advances in ´omics´ technology, specifically transcriptomics have allowed to reveal aspects associated with such molecular changes. So far, different techniques have been used to evaluate the gene expression profile during the various stages of the life cycle of these parasites and during the host-parasite interactions. However, some of them have serious drawbacks that limit the precise study and full understanding of their transcriptomes. Therefore, recently has been implemented the latest technology (RNA-seq), which overcomes the drawbacks of traditional methods. In this review, studies that so far have used RNA-seq are presented and allowed to expand our knowledge regarding the biology of these parasites and their interactions with their hosts.

Ribosomal protein S15A augments human osteosarcoma cell proliferation in vitro

As a highly conserved housekeeping gene, the biological implications of ribosomal protein S15A (RPS15A) during various processes, including carcinogenesis, remain elusive. Herein, the authors reported that knockdown of RPS15A expression significantly inhibited human osteosarcoma U2OS cell proliferation and colony formation in vitro by using a lentivirus-mediated RNA interference (RNAi) system. Moreover, an excess accumulation of cells in the G0/G1 phase was observed in U2OS cells transduced with lentivirus targeting RPS15A, suggesting that the growth inhibition mediated by RPS15A knockdown in osteosarcoma cells was probably due to the induction of cell cycle arrest. Taken together, this study highlights the crucial role of RPS15A in promoting osteosarcoma cell proliferation, and provides a foundation for further study into the clinical potential of inhibition of RPS15A for the treatment of osteosarcoma.

Insights into RNA transcriptome profiling of cardiac tissue in obesity and hypertension conditions

Several epidemiologic studies suggest that obesity and hypertension are associated with cardiac transcriptome modifications that could be further associated with inflammatory processes and cardiac hypertrophy. In this field, transcriptome studies have demonstrated their importance to elucidate physiologic mechanisms, pathways or genes involved in many biologic processes. Over the past decade, RNA microarray and RNA-seq analysis has become an essential component to examine metabolic pathways in terms of mRNA expression in cardiology. In this review, cardiac muscle gene expression in response to effects of obesity and hypertension will be focused, providing a broad view on cardiac transcriptome and physiologic and biochemical mechanisms involved in gene expression changes produced by these events, emphasizing the use of new technologies for gene expression analyses.

NPY1R is a novel peripheral blood marker predictive of metastasis and prognosis in breast cancer patients

The aim of the current study was to evaluate a novel tumor marker, neuropeptide Y receptor Y1 (NPY1R), for the detection of circulating cancer cells and to investigate its clinical significance in breast cancer patients. The Digital Gene Expression Displayer tool of the Cancer Genome Anatomy Project was used to identify the marker gene NPY1R, which is able to detect circulating cancer cells. Nested quantitative polymerase chain reaction was performed to correlate the NPY1R expression levels with the clinicopathological features of 142 breast cancer patients. A follow-up study of 131 of the breast cancer patients was conducted for 38 months. Compared with the 60 normal control individuals, NPY1R was highly expressed in the cancer patients (P<0.01). These high levels of NPY1R expression were positively correlated with the clinical stage and lymph node metastasis status of the disease, as well as with the status of the estrogen and progesterone receptors (P<0.05). Breast cancer patients with circulating cancer cells that expressed NPY1R exhibited shorter tumor-specific survival when compared with those with no NPY1R expression (P<0.01). Additionally, the mortality rate was associated with HER2 expression in the NPY1R positive and negative groups. These results indicate that NPY1R may serve as a useful marker to predict breast cancer metastasis and to evaluate the prognosis of breast cancer patients.

Co-development of diagnostic vectors to support targeted therapies and theranostics: essential tools in personalized cancer therapy

Novel technologies are being developed to improve patient therapy through the identification of targets and surrogate molecular signatures that can help direct appropriate treatment regimens for efficacy and drug safety. This is particularly the case in oncology whereby patient tumor and biofluids are routinely isolated and analyzed for genetic, immunohistochemical, and/or soluble markers to determine if a predictive biomarker signature (i.e., mutated gene product, differentially expressed protein, altered cell surface antigen, etc.) exists as a means for selecting optimal treatment. These biomarkers may be drug-specific targets and/or differentially expressed nucleic acids, proteins, or cell lineage profiles that can directly affect the patient’s disease tissue or immune response to a therapeutic regimen. Improvements in diagnostics that can prescreen predictive response biomarker profiles will continue to optimize the ability to enhance patient therapy via molecularly defined disease-specific treatment. Conversely, patients lacking predictive response biomarkers will no longer needlessly be exposed to drugs that are unlikely to provide clinical benefit, thereby enabling patients to pursue other therapeutic options and lowering overall healthcare costs by avoiding futile treatment. While patient molecular profiling offers a powerful tool to direct treatment options, the difficulty in identifying disease-specific targets or predictive biomarker signatures that stratify a significant fraction within a disease indication remains challenging. A goal for drug developers is to identify and implement new strategies that can rapidly enable the development of beneficial disease-specific therapies for broad patient-specific targeting without the need of tedious predictive biomarker discovery and validation efforts, currently a bottleneck for development timelines. Successful strategies may gain an advantage by employing repurposed, less-expensive existing agents while potentially improving the therapeutic activity of novel, target-specific therapies that may otherwise have off-target toxicities or less efficacy in cells exhibiting certain pathways. Here, we discuss the use of co-developing diagnostic-targeting vectors to identify patients whose malignant tissue can specifically uptake a targeted anti-cancer drug vector prior to treatment. Using this system, a patient can be predetermined in real-time as to whether or not their tumor(s) can specifically uptake a drug-linked diagnostic vector, thus inferring the uptake of a similar vector linked to an anti-cancer agent. If tumor-specific uptake is observed, then the patient may be suitable for drug-linked vector therapy and have a higher likelihood of clinical benefit while patients with no tumor uptake should consider other therapeutic options. This approach offers complementary opportunities to rapidly develop broad tumor-specific agents for use in personalized medicine.

Hypoxia and the extracellular matrix: drivers of tumour metastasis

Of the deaths attributed to cancer, 90% are due to metastasis, and treatments that prevent or cure metastasis remain elusive. Emerging data indicate that hypoxia and the extracellular matrix (ECM) might have crucial roles in metastasis. During tumour evolution, changes in the composition and the overall content of the ECM reflect both its biophysical and biological properties and these strongly influence tumour and stromal cell properties, such as proliferation and motility. Originally thought of as independent contributors to metastatic spread, recent studies have established a direct link between hypoxia and the composition and the organization of the ECM, which suggests a new model in which multiple microenvironmental signals might converge to synergistically influence metastatic outcome.

A rapid nested polymerase chain reaction method to detect circulating cancer cells in breast cancer patients using multiple marker genes

The aim of the present study was to develop a simple and rapid method for the detection of circulating cancer cells using multiple tumor markers and to investigate the clinical significance of circulating cancer cells in breast cancer patients. A novel rapid nested polymerase chain reaction (PCR) assay, with high sensitivity and specificity, was evaluated, which was considered to be suitable for clinical application. The rapid nested PCR method was used to detect the circulating cancer cells of 142 breast cancer patients, using a panel of marker genes (FAM83A, NPY1R and KRT19), which were identified by the Digital Gene Expression Displayer Tool of the National Cancer Institute-Cancer Genome Anatomy Project. In total, 79.6% of the 142 breast cancer patient blood samples were found to express at least one tumor marker. In addition, the number of positive markers was found to significantly correlate with the disease stage and presence of distant metastasis. Furthermore, positivity for more than one tumor marker appeared to predict a reduced survival time in breast cancer patients.

Cliques for the identification of gene signatures for colorectal cancer across population

Background

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. Studies have correlated risk of CRC development with dietary habits and environmental conditions. Gene signatures for any disease can identify the key biological processes, which is especially useful in studying cancer development. Such processes can be used to evaluate potential drug targets. Though recognition of CRC gene-signatures across populations is crucial to better understanding potential novel treatment options for CRC, it remains a challenging task.

Results

We developed a topological and biological feature-based network approach for identifying the gene signatures across populations. In this work, we propose a novel approach of using cliques to understand the variability within population. Cliques are more conserved and co-expressed, therefore allowing identification and comparison of cliques across a population which can help researchers study gene variations. Our study was based on four publicly available expression datasets belonging to four different populations across the world. We identified cliques of various sizes (0 to 7) across the four population networks. Cliques of size seven were further analyzed across populations for their commonality and uniqueness. Forty-nine common cliques of size seven were identified. These cliques were further analyzed based on their connectivity profiles. We found associations between the cliques and their connectivity profiles across networks. With these clique connectivity profiles (CCPs), we were able to identify the divergence among the populations, important biological processes (cell cycle, signal transduction, and cell differentiation), and related gene pathways. Therefore the genes identified in these cliques and their connectivity profiles can be defined as the gene-signatures across populations. In this work we demonstrate the power and effectiveness of cliques to study CRC across populations.

Conclusions

We developed a new approach where cliques and their connectivity profiles helped elucidate the variation and similarity in CRC gene profiles across four populations with unique dietary habits.

Affymetrix GeneChip microarray preprocessing for multivariate analyses

Affymetrix GeneChip microarrays are the most widely used high-throughput technology to measure gene expression, and a wide variety of preprocessing methods have been developed to transform probe intensities reported by a microarray scanner into gene expression estimates. There have been numerous comparisons of these preprocessing methods, focusing on the most common analyses-detection of differential expression and gene or sample clustering. Recently, more complex multivariate analyses, such as gene co-expression, differential co-expression, gene set analysis and network modeling, are becoming more common; however, the same preprocessing methods are typically applied. In this article, we examine the effect of preprocessing methods on some of these multivariate analyses and provide guidance to the user as to which methods are most appropriate.

Meta-profiles of gene expression during aging: limited similarities between mouse and human and an unexpectedly decreased inflammatory signature

BACKGROUND

Skin aging is associated with intrinsic processes that compromise the structure of the extracellular matrix while promoting loss of functional and regenerative capacity. These processes are accompanied by a large-scale shift in gene expression, but underlying mechanisms are not understood and conservation of these mechanisms between humans and mice is uncertain.

RESULTS

We used genome-wide expression profiling to investigate the aging skin transcriptome. In humans, age-related shifts in gene expression were sex-specific. In females, aging increased expression of transcripts associated with T-cells, B-cells and dendritic cells, and decreased expression of genes in regions with elevated Zeb1, AP-2 and YY1 motif density. In males, however, these effects were contrasting or absent. When age-associated gene expression patterns in human skin were compared to those in tail skin from CB6F1 mice, overall human-mouse correspondence was weak. Moreover, inflammatory gene expression patterns were not induced with aging of mouse tail skin, and well-known aging biomarkers were in fact decreased (e.g., Clec7a, Lyz1 and Lyz2). These unexpected patterns and weak human-mouse correspondence may be due to decreased abundance of antigen presenting cells in mouse tail skin with age.

CONCLUSIONS

Aging is generally associated with a pro-inflammatory state, but we have identified an exception to this pattern with aging of CB6F1 mouse tail skin. Aging therefore does not uniformly heighten inflammatory status across all mouse tissues. Furthermore, we identified both intercellular and intracellular mechanisms of transcriptome aging, including those that are sex- and species-specific.