Gene Expression Meta-Analysis of Potential Metastatic Breast Cancer Markers

On discovery of novel hub genes for ER+ and TN breast cancer types through RNA seq data analyses and classification models

Breast cancer (BC) is a malignant neoplasm which is classified into various types defined by underlying molecular factors such as estrogen receptor positive (ER+), progesterone receptor positive (PR+), human epidermal growth factor positive (HER2+) and triple negative (TNBC). Early detection of ER+ and TNBC is crucial in the choice of diagnosis and appropriate treatment strategy. Here we report the key genes associated to ER+ and TNBC using RNA-Seq analysis and machine learning models. Three ER+ and TNBC RNA seq datasets comprising 164 patients in-toto were selected for standard NGS hierarchical data processing and data analyses protocols. Enrichment pathway analysis and network analysis was done and finally top hub genes were identified. To come with a reliable classifier which could distinguish the distinct transcriptome patterns associated to ER+ and TNBC, ML models were built employing Naïve Bayes, SVM and kNN. 1730 common DEG's exhibiting significant logFC values with 0.05 p-value threshold were identified. A list of top ten hub genes were screened on the basis of maximal clique centrality (MCC) which included CDC20, CDK1, BUB1, AURKA, CDCA8, RRM2, TTK, CENPF, CEP55 and NDC80.These genes were found to be involved in crucial cell cycle pathways. k-Nearest Neighbor (kNN) model was observed to be best classifier with accuracy 84%, specificity 66% and sensitivity 95% to differentiate between ER+ and TNBC RNA-Seq transcriptomes. Our screened list of 10 hub genes can thus help unearth novel molecular signatures implicated in ER+ and TNBC onset, prognosis and design of novel protocols for breast cancer diagnostics and therapeutics.

The Overexpression of NUSAP1 and GTSE1 Could Predict An Unfavourable Prognosis and Shorter Disease Free Survival in ccRenal Cell Carcinoma

BACKGROUND

Although it has been reported that NUSAP1 and GTSE1 are highly expressed in different types of tumors and associated with malignant progression and poor clinical prognosis, their significances with clinicopathological data and correlations with patients' survival in ccRCC are still poorly understood. Therefore, in our study we attempted to evaluate the link between NUSAP1 and GTSE1 in ccRCC and to correlate their immunoexpression with clinico-pathological parameters and the patients' survival to identify their significance as potential therapeutic targets, indicators for tumor progression, and patients' prognosis.

METHOD

NUSAP1 and GTSE1 were examined in 100 ccRCC patients by immunohistochemistry. The association between NUSAP1 and GTSE1 immunoreactivity and clinicopathological variables were evaluated. The disease free survival (DFS) was examined by the Kaplan-Meier method. The multivariate Cox regressions was estimated to detect the prognostic role of both proteins.

RESULTS

We detected high NUSAP1 and GTSE1 expression in 60% and 62% of the cases, respectively. A significant association was detected between NUSAP1 and GTSE1 immunoexpression and size (p=0.007 and p=0.026, respectively), Fuhrman grade (p=0.022 and p=0.004, respectively), tumor stage (p=0.003 and p=0.019, respectively), TILs (p=0.026 and p=0.04 respectively), capsular invasion (p=0.002 and p=0.009, respectively), Distant metastasis (p=0.007 and p=0.009, respectively), and DFS (p=0.007 and 0.009, respectively). Multivariate Cox regression showed that high NUSAP1 and GTSE1 expression levels were independently associated with an unfavourable poor prognosis of ccRCC cases.

CONCLUSION

We demonstrated that NUSAP1 and GTSE1 overexpression was closely related to the poor prognostic clinicopathological features of ccRCC and predicted an unfavorable prognosis. Therefore, NUSAP1 and GTSE1 might act together as potential futuristic prognostic indicators and therapeutic targets for ccRCC patients. However, further analysis in molecular studies on larger scale are mandatory to highlight the interactive crosstalk regulatory mechanisms between both markers and their combined effect on ccRCC.

Analysis of Interleukin-6 Gene Variants (rs1800795, rs1800796, rs1554606, rs1800797, rs2069840, rs12700386, and rs2069861) as Prognostic Markers in Breast Cancer: A Systematic Review, Meta-Analysis, and Network Analysis

Interleukin-6 (IL-6) has obviously tumor-promoting and tumor-inhibitory effects and can induce an epithelial-mesenchymal transition phenotype in human breast cancer (BC) cells and implicate its potential to promote BC metastasis. Herein, we aimed to evaluate the association of IL-6 variants (rs1800795, rs1800796, rs1554606, rs1800797, rs2069840, rs12700386, and rs2069861) with the susceptibility to BC. The databases of PubMed/Medline, Web of Science, Scopus, and Cochrane Library were searched until December 19, 2022, without any restrictions. The quality assessment of each study was performed based on the Newcastle-Ottawa Scale tool. The Review Manager 5.3 software presented the effect sizes including odds ratio (OR) along with a 95% confidence interval (CI). Both publication bias and sensitivity analyses were carried out by the Comprehensive Meta-Analysis version 2.0 software. A total of 2,508 records were identified among databases and at last, 27 articles were entered into the meta-analysis. Seven polymorphisms of IL-6 were entered into the analyses. Just rs1800797 polymorphism in the dominant model (OR = 1.51; 95% CI = 1.15-2.00; P = 0.003) and rs2069840 polymorphism in heterozygous (OR = 0.89; 95% CI = 0.81-0.97; P = 0.008) and dominant (OR = 0.91; 95% CI = 0.84-0.99; P = 0.02) models had a significant association with the BC risk. In conclusion, among 7 polymorphisms and despite a few included cases, the present meta-analysis recommended that the AA+GA genotype of rs1800797 polymorphism had a significantly elevated risk and the GC and the CC+GC genotypes of rs2069840 polymorphism had a protective role in the BC patients.

Organ-Specificity of Breast Cancer Metastasis

Breast cancer (BC) remains one of the most common malignancies among women worldwide. Breast cancer shows metastatic heterogeneity with priority to different organs, which leads to differences in prognosis and response to therapy among patients. The main targets for metastasis in BC are the bone, lung, liver and brain. The molecular mechanism of BC organ-specificity is still under investigation. In recent years, the appearance of new genomic approaches has led to unprecedented changes in the understanding of breast cancer metastasis organ-specificity and has provided a new platform for the development of more effective therapeutic agents. This review summarises recent data on molecular organ-specific markers of metastasis as the basis of a possible therapeutic approach in order to improve the diagnosis and prognosis of patients with metastatically heterogeneous breast cancer.

Copy number variations in male breast cancer

Common copy number variations often contain cancer-related genes and are likely to play a role in carcinogenesis. Different mechanisms of tumorigenesis are suggested in female and male breast cancer because of different molecular profiles. The cytogenetic analysis of GTG-banded chromosomes was performed in six male patients with infiltrating ductal carcinoma and six healthy male controls matched for age. Single-nucleotide polymorphism (SNP) array analysis was performed in male breast cancer (MBC) patients. Cytogenetic analysis found aberrations previously implicated in cancer. SNP array analysis in patients revealed a gain of Xp11.23, 8p23.2, Yq11.221, Yq11.3 (AZF region), 12p11.21, 18q12.1, and 17q21.3; a loss of Yq11.222 and 7q11.21; and a loss of heterozygosity of 4p16.3, 6p12.3, 6p22.2-p21.31, 7p14.2-14.1, 18q11.2-q12.1, 20p11.23-11.1, 20q11.21-11.23, 1q25.2-q25.3, 2q11.1-q11.2, 5q23.1-23.2, 11p15.4-15.3, and 22q13.1-13.31. Some of these variations, especially those of the Y-chromosome, have not been reported earlier. Chromosomal loci identified by SNP array harbor genes were reported to be associated with cancer progression and metastasis, indicating their involvement in MBC also.

Transcriptome Profiling Analysis of Breast Cancer Cell MCF-7 Treated by Sesamol

Background

Breast cancer is a highly malignant tumor that affects a large number of women worldwide. Sesamol, a natural compound, has been shown to exhibit inhibitory effects on various tumors, including breast cancer. However, the underlying mechanism of its action has not been fully explored. In this study, we aimed to investigate the effect of sesamol on the transcriptome of MCF-7 breast cancer cells, in order to better understand its potential as an anti-cancer agent.

Methods

The transcriptome profiles of MCF-7 breast cancer cells treated with sesamol were analyzed using Illumina deep-sequencing. The differentially expressed genes (DEGs) between the control and sesamol-treated groups were identified, and GO and KEGG pathway analyses of these DEGs were conducted using ClueGO. Protein-protein interaction (PPI) network of DEGs was mapped on STRING database and visualized by Cytoscape software. Hub genes in the network were screened by Cytohubba plugin of Cytoscape. Prognostic values of hub genes were analyses by the online Kaplan-Meier plotter and validated by qRT-PCR in MCF-7 cells.

Results

The results of the study showed that sesamol treatment had a significant effect on the transcriptome of MCF-7 cells, with a total of 351 DEGs identified. Functional enrichment analyses of DEGs revealed their involvement in extracellular matrix (ECM) remodeling, fatty acid metabolism and monocyte chemotaxis. The protein-protein interaction (PPI) network analysis of DEGs resulted in the identification of 10 hub genes, namely IGF2, MMP1, MSLN, CXCL10, WT1, ITGAL, PLD1, MME, TWIST1, and FOXA2. Survival analysis showed that MMP1 and ITGAL were significantly associated with overall survival (OS) and recovery-free survival (RFS) in breast cancer patients.

Conclusion

Sesamol may play important roles in extracellular matrix (ECM) remodeling, fatty acid metabolism and cell cycle of MCF-7.

RABC: Rheumatoid Arthritis Bioinformatics Center

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.

An Integrated Study on the Differential Expression of the FOX Gene Family in Cancer and Their Response to Chemotherapy Drugs

The Forkhead-box (FOX) transcription factors, as one of the largest gene families in humans, play key roles in cancer. Although studies have suggested that several FOX transcription factors have a significant impact on cancer, the functions of most of the FOX genes in cancer remain elusive. In the study, the expression of 43 FOX genes in 63 kinds of cancer diseases (including many subtypes of same cancer) and in response to 60 chemical substances was obtained from the Gene Expression Atlas database of the European Bioinformatics Institute. Based on the high degree of overlap in FOXO family members differentially expressed in various cancers and their particular responses to chemotherapeutic drugs, our data disclosed the FOX genes that played an important role in the development and progression of cancer. More importantly, we predicted the role of one or several combinatorial FOX genes in the diagnosis and prognostic assessment of a specific cancer and evaluated the potential of a certain anticancer drug therapy for this type of cancer by integrating patterns of FOX genes expression with anticancer drugs sensitivity.

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.

Aurora Kinase A and Bcl-xL Inhibition Suppresses Metastasis in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a heterogeneous disease that accounts for 10–15% of all breast cancer cases. Within TNBC, the treatment of basal B is the most challenging due to its highly invasive potential, and thus treatments to suppress metastasis formation in this subgroup are urgently needed. However, the mechanisms underlying the metastatic ability of TNBC remain unclear. In the present study, we investigated the role of Aurora A and Bcl-xL in regulating basal B cell invasion. We found gene amplification and elevated protein expression in the basal B cells, which also showed increased invasiveness in vitro, compared to basal A cells. Chemical inhibition of Aurora A with alisertib and siRNA-mediated knockdown of BCL2L1 decreased the number of invading cells compared to non-treated cells in basal B cell lines. The analysis of the correlation between AURKA and BCL2L1 expression in TNBC and patient survival revealed significantly decreased relapse-free survival (n = 534, p = 0.012) and distant metastasis-free survival (n = 424, p = 0.017) in patients with primary tumors exhibiting a high combined expression of AURKA and BCL2L1. Together, our findings suggest that high levels of Aurora A and Bcl-xL promote metastasis, and inhibition of these proteins may suppress metastasis and improve patient survival in basal B TNBC.

Matrix Metalloproteinase-1 (MMP1) Upregulation through Promoter Hypomethylation Enhances Tamoxifen Resistance in Breast Cancer

Simple Summary

Cancer recurrence caused by tamoxifen resistance hampers chemotherapy in breast cancer patients. The reasons behind the resistance were investigated by screening epigenetically regulated genes through analysis of methylation data from tamoxifen-resistant MCF-7 cells. MMP1 locus was found to be hypomethylated at a promoter CpG site and its expression was upregulated in the cell line, which was verified by the drug-resistant tumor tissues from breast cancer patients (n = 28). Downregulating MMP1 using a short hairpin RNA inhibited the growth of resistant cells and increased sensitivity to tamoxifen in vitro as well as in a xenografted mouse model in vivo. This study suggests that MMP1 is potentially a target gene to control tamoxifen resistance in breast cancer.

Abstract

Background: Tamoxifen (tam) is widely used to treat estrogen-positive breast cancer. However, cancer recurrence after chemotherapy remains a major obstacle to achieve good patient prognoses. In this study, we aimed to identify genes responsible for epigenetic regulation of tam resistance in breast cancer. Methods: Methylation microarray data were analyzed to screen highly hypomethylated genes in tam resistant (tamR) breast cancer cells. Quantitative RT-PCR, Western blot analysis, and immunohistochemical staining were used to quantify expression levels of genes in cultured cells and cancer tissues. Effects of matrix metalloproteinase-1 (MMP1) expression on cancer cell growth and drug resistance were examined through colony formation assays and flow cytometry. Xenografted mice were generated to investigate the effects of MMP1 on drug resistance in vivo. Results: MMP1 was found to be hypomethylated and overexpressed in tamR MCF-7 (MCF-7/tamR) cells and in tamR breast cancer tissues. Methylation was found to be inversely associated with MMP1 expression level in breast cancer tissues, and patients with lower MMP1 expression exhibited a better prognosis for survival. Downregulating MMP1 using shRNA induced tam sensitivity in MCF-7/tamR cells along with increased apoptosis. The xenografted MCF-7/tamR cells that stably expressed short hairpin RNA (shRNA) against MMP1 exhibited retarded tumor growth compared to that in cells expressing the control shRNA, which was further suppressed by tam. Conclusions: MMP1 can be upregulated through promoter hypomethylation in tamR breast cancer, functioning as a resistance driver gene. MMP1 can be a potential target to suppress tamR to achieve better prognoses of breast cancer patients.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology’s potential, a set of transcriptomic datasets are meta-analyzed as an example.

Unveiling a Hidden Biomarker of Inflammation and Tumor Progression: The 65 kDa Isoform of MMP-9 New Horizons for Therapy

Cancer metastasis is a stage of the disease where therapy is mostly ineffective; hence, the need to find reliable markers of its onset. The metalloproteinase-9 (MMP-9, gelatinase B) in its 82 kDa active form, is a good candidate, but here we show that the correspondent little known 65 kDa active MMP-9 isoform, often misrepresented with the other gelatinase MMP-2, is a more suitable marker. Sera from patients with lung and breast cancer were analyzed by bidimensional zymography to detect the activity of MMP-9 and MMP-2. Enzyme identity was confirmed by comparison with MMP-9 standards and by western blotting. The 65 kDa isoform of MMP-9 is a suitable biomarker to monitor tumor progression from tissue neoplasms to metastatic stage, as its activity begins to appear when disease severity increases and becomes very high in metastasis. Moreover, the 65 kDa MMP-9, which derives from the 82 kDa MMP-9, no longer responds to natural MMP-9 inhibitors. As its activity cannot be controlled, its appearance may warn that the pathological process is becoming irreversible. Identification and inhibition of the enzymes converting the inhibitor-sensitive 82 kDa MMP-9 into the corresponding “wild” 65 kDa MMP-9 may allow to develop therapies capable of blocking metastases.

Contribution of Stemness-linked Transcription Regulators to the Progression of Breast Cancer

Although there are currently several factors that allow measuring the risk of having breast cancer or predicting its progression, the underlying causes of this malignancy have remained unknown. Several molecular studies have described some mechanisms involved in the progress of breast cancer. These have helped in identifying new targets with therapeutic potential. However, despite the therapeutic strategies implemented from the advances achieved in breast cancer research, a large percentage of patients with breast cancer die due to the spread of malignant cells to other tissues or organs, such as bones and lungs. Therefore, determining the processes that promote the migration of malignant cells remains one of the greatest challenges for oncological research. Several research groups have reported evidence on how the dedifferentiation of tumor cells leads to the acquisition of stemness characteristics, such as invasion, metastasis, the capability to evade the immunological response, and resistance to several cytotoxic drugs. These phenotypic changes have been associated with a complex reprogramming of gene expression in tumor cells during the Epithelial-Mesenchymal Transition (EMT). Considering the determining role that the transcriptional regulation plays in the expression of the specific characteristics and attributes of breast cancer during ETM, in the present work, we reviewed and analyzed several transcriptional mechanisms that support the mesenchymal phenotype. In the same way, we established the importance of transcription factors with a therapeutic perspective in the progress of breast cancer.

The genomic architecture of metastasis in breast cancer: focus on mechanistic aspects, signalling pathways and therapeutic strategies

Breast cancer is a multifactorial, heterogeneous disease and the second most frequent cancer amongst women worldwide. Metastasis is one of the most leading causes of death in these patients. Early-stage or locally advanced breast cancer is limited to the breast or nearby lymph nodes. When breast cancer spreads to farther tissues/organs from its original site, it is referred to as metastatic or stage IV breast cancer. Normal breast development is regulated by specific genes and signalling pathways controlling cell proliferation, cell death, cell differentiation and cell motility. Dysregulation of genes involved in various signalling pathways not only leads to the formation of primary tumour but also to the metastasis as well. The metastatic cascade is represented by a multi-step process including invasion of the local tumour cell followed by its entry into the vasculature, exit of malignant cells from the circulation and ultimately their colonization at the distant sites. These stages are referred to as formation of primary tumour, angiogenesis, invasion, intravasation and extravasation, respectively. The major sites of metastasis of breast cancer are the lymph nodes, bone, brain and lung. Only about 28% five-year survival rate has been reported for stage IV breast cancer. Metastasis is a serious concern for breast cancer and therefore, various therapeutic strategies such as tyrosine kinase inhibitors have been developed to target specific dysregulated genes and various signalling pathways involved in different steps of metastasis. In addition, other therapies like hyperbaric oxygen therapy, RNA interference and CRISPR/Cas9 are also being explored as novel strategies to cure the stage IV/metastatic breast cancer. Therefore, the current review has been compiled with an aim to evaluate the genetic basis of stage IV breast cancer with a focus on the molecular mechanisms. In addition, the therapeutic strategies targeting these dysregulated genes involved in various signalling pathways have also been discussed. Genome editing technologies that can target specific genes in the affected areas by making knock-in and knock-out alternations and thereby bring significant treatment outcomes in breast cancer have also been summarized.

Meta-Analysis of Microdissected Breast Tumors Reveals Genes Regulated in the Stroma but Hidden in Bulk Analysis

Transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, sample heterogeneity, and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicates the interpretation of bulk transcriptomic profiles. To address these issues, we collected 48 microarray datasets derived from laser capture microdissected stroma or epithelium in breast tumors and performed a meta-analysis identifying robust lists of differentially expressed genes. This was used to create a database with carefully harmonized metadata that we make freely available to the research community. As predicted, combining the results of multiple datasets improved statistical power. Moreover, the separate analysis of stroma and epithelium allowed the identification of genes with different contributions in each compartment, which would not be detected by bulk analysis due to their distinct regulation in the two compartments. Our method can be profitably used to help in the discovery of biomarkers and the identification of functionally relevant genes in both the stroma and the epithelium. This database was made to be readily accessible through a user-friendly web interface.

A predictive biomarker panel for bone metastases: Liquid biopsy approach

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Data mining of published microarray datasets directed us to the identification of a multi gene panel involving of 15 genes that are particular to bone metastases.

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Serum exosomal markers HSP90AA1, SPP1, IL3, and PTK2 found in the present study might be useful in detecting the early spread of bone metastases leading to better clinical outcomes.

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This multi-gene panel and their related pathways may assist as promising conclusion predictors using novel approaches of exosome as liquid biopsy and their application in therapeutic targets in breast and lung cancer patients with bone metastases.

Bone metastases is one of the common metastatic site and leading cause of cancer-related mortality in progressive cancer patients. The purpose of the present study is to establish a liquid biopsy based multi-gene classifier and associated signalling pathways for early diagnosis of bone metastases. We used publically available microarray datasets and analysed them in a platform/chip-specific manner using GeneSpring software. Analyses of gene expression datasets identified 15 consistently over-expressed genes with statistical significance. Further, expression profile of same set of 15 genes were compared in breast and lung cancer exosome derived mRNA with (n = 10) and without (n = 10) bone metastases against healthy controls. ROC curve analysis performed individually for all the 15 genes shortlisted the 5 most relevant genes with significant sensitivity and specificity in both cancers. This liquid biopsy-based bone metastases predictor using multi-gene panel is a unique approach with potential clinical applications for effective management of aggressive cancers.

LIMK1 promotes peritoneal metastasis of gastric cancer and is a therapeutic target

Peritoneal metastasis is a common form of metastasis among advanced gastric cancer patients. In this study, we reported the identification of LIM domain kinase 1 (LIMK1) as a promoter of gastric cancer peritoneal metastasis, and its potential to be a therapeutic target of dabrafenib (DAB). Using transcriptomic sequencing of paired gastric cancer peritoneal metastasis, primary tumors, and normal gastric tissues, we first unveiled that LIMK1 is selectively up-regulated in metastatic tumors. Increased LIMK1 in gastric cancer peritoneal metastasis was validated by immunohistochemistry analysis of an independent patient cohort. In vitro functional studies demonstrated that LIMK1 knockout or knockdown significantly inhibited cell migration and invasion of gastric cancer cells. LIMK1 knockout also abrogated peritoneal and liver metastases of gastric cancer cells in nude mice in vivo. Dabrafenib, a small molecule targeting LIMK1, was found to decrease cell migration and invasion of gastric cancer cells in vitro and abolish peritoneal and liver metastasis formation in vivo. Mechanistically, either LIMK1 knockout or Dabrafenib inhibited LIMK1 expression and phosphorylation of its downstream target cofilin. Taken together, our results demonstrated that LIMK1 functions as a metastasis promoter in gastric cancer by inhibiting LIMK1-p-cofilin and that Dabrafenib has the potential to serve as a novel treatment for gastric cancer peritoneal metastasis.

Key Genes and Prognostic Analysis in HER2+ Breast Cancer

Human epidermal growth factor 2 (HER2)+ breast cancer is considered the most dangerous type of breast cancers. Herein, we used bioinformatics methods to identify potential key genes in HER2+ breast cancer to enable its diagnosis, treatment, and prognosis prediction. Datasets of HER2+ breast cancer and normal tissue samples retrieved from Gene Expression Omnibus and The Cancer Genome Atlas databases were subjected to analysis for differentially expressed genes using R software. The identified differentially expressed genes were subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses followed by construction of protein-protein interaction networks using the STRING database to identify key genes. The genes were further validated via survival and differential gene expression analyses. We identified 97 upregulated and 106 downregulated genes that were primarily associated with processes such as mitosis, protein kinase activity, cell cycle, and the p53 signaling pathway. Visualization of the protein-protein interaction network identified 10 key genes (CCNA2, CDK1, CDC20, CCNB1, DLGAP5, AURKA, BUB1B, RRM2, TPX2, and MAD2L1), all of which were upregulated. Survival analysis using PROGgeneV2 showed that CDC20, CCNA2, DLGAP5, RRM2, and TPX2 are prognosis-related key genes in HER2+ breast cancer. A nomogram showed that high expression of RRM2, DLGAP5, and TPX2 was positively associated with the risk of death. TPX2, which has not previously been reported in HER2+ breast cancer, was associated with breast cancer development, progression, and prognosis and is therefore a potential key gene. It is hoped that this study can provide a new method for the diagnosis and treatment of HER2 + breast cancer.

Regulation of Wnt Signaling Pathways at the Plasma Membrane and Their Misregulation in Cancer

Wnt signaling is one of the key signaling pathways that govern numerous physiological activities such as growth, differentiation and migration during development and homeostasis. As pathway misregulation has been extensively linked to pathological processes including malignant tumors, a thorough understanding of pathway regulation is essential for development of effective therapeutic approaches. A prominent feature of cancer cells is that they significantly differ from healthy cells with respect to their plasma membrane composition and lipid organization. Here, we review the key role of membrane composition and lipid order in activation of Wnt signaling pathway by tightly regulating formation and interactions of the Wnt-receptor complex. We also discuss in detail how plasma membrane components, in particular the ligands, (co)receptors and extracellular or membrane-bound modulators, of Wnt pathways are affected in lung, colorectal, liver and breast cancers that have been associated with abnormal activation of Wnt signaling. Wnt-receptor complex components and their modulators are frequently misexpressed in these cancers and this appears to correlate with metastasis and cancer progression. Thus, composition and organization of the plasma membrane can be exploited to develop new anticancer drugs that are targeted in a highly specific manner to the Wnt-receptor complex, rendering a more effective therapeutic outcome possible.

Gene expression comparison between primary estrogen receptor-positive and triple-negative breast cancer with paired axillary lymph node metastasis

The aim of this study is to characterize and compare changes in gene expression patterns of paired axillary lymph node (ALN) metastases from estrogen receptor (ER)-positive and triple-negative (TNBC) primary breast cancer (PBC). Patients with stage 2-3 PBC with macrometastasis to an ALN were selected. Gene expression of 2567 cancer-associated genes was analyzed with the HTG EdgeSeq system coupled with the Illumina Next Generation Sequencing (NGS) platform. Changes in gene expression between ER/PR-positive, HER2-negative PBC, and their paired ALN metastases were compared with TNBC and their paired ALN metastases. Fourteen pairs of ER-positive and paired ALN metastasis were analyzed. Compared with the PBC, ALN metastasis had 673 significant differentially expressed genes, including 348 upregulated genes and 325 downregulated genes. Seventeen pairs of TNBC and paired ALN metastasis were analyzed. ALN metastasis had 257 significant differentially expressed genes, including 123 upregulated genes and 134 downregulated genes. When gene expression of the ALN for ER-positive PBC was compared to that of TNBC, 97 genes were upregulated in both, and 115 genes were similarly downregulated. Common upregulated genes were associated with cell death, necrosis, and homeostasis. Common downregulated genes were those of migration, degradation of extracellular matrix, and invasion. Although ER-positive PBC and TNBC have a distinct gene expression profiles and distinct changes from PBC to ALN metastases, a significant number of genes are similarly up- or downregulated. Understanding the role of these common genomic changes may provide clues to understanding the metastatic process itself.

Site of metastatic recurrence impacts prognosis in patients with high-grade upper tract urothelial carcinoma

PURPOSE

Metastatic recurrence occurs in over 25% of upper tract urothelial carcinoma patients treated with radical nephroureterectomy. While metastatic recurrence suggests poor prognosis, the impact of the specific site of recurrence on prognosis is not well documented.

MATERIALS AND METHODS

We retrospectively analyzed 188 patients who underwent radical nephroureterectomy for high-grade, node-negative upper tract urothelial carcinoma at our institution from 2003 to 2018 without receiving neoadjuvant or adjuvant chemotherapy. Competing-risks survival analysis was performed to evaluate the cumulative incidence and predictors of metastatic recurrence. The Kaplan-Meier method and log-rank test were used to estimate and compare recurrence site-specific survival probabilities following metastatic recurrence. Cox regression analyses were performed to assess site-specific prognoses.

RESULTS

Of the 188 patients, 47 (25%) developed metastatic recurrence over a median follow-up of 30 months (interquartile range: 10.5-58.5 months). The 1- and 2-year cumulative incidences of metastatic recurrence were 13.6% and 23.6%, respectively. On multivariable analysis, lymphovascular invasion was significantly predictive of metastatic recurrence (subhazard ratio: 2.6, P = 0.01). Of the 47 patients who developed recurrence, 38 (80.9%) died over a median follow-up of 10 months (interquartile range: 5-20 months). Metastatic recurrence was most common in the lungs (n= 13, 28%) and at multiple sites (n= 14, 30%). Median time to recurrence was shorter for recurrences at multiple sites (6.5 months) and those in the liver (13 months) and bone (18 months) compared to other sites. Patients who recurred in the liver (hazard ratio: 6.3, P = 0.007), bone (hazard ratio: 4.9, P = 0.02), and multiple sites (hazard ratio: 4.6, P = 0.01) had significantly worse prognosis compared to those who recurred in lymph nodes. Statistical significance persisted after adjusting for treatment with salvage therapy.

CONCLUSIONS

A significant proportion of high-grade upper tract urothelial carcinoma patients recur systemically after radical nephroureterectomy. Lymphovascular invasion is a predictor of metastatic recurrence and may inform decisions regarding perioperative chemotherapy. Hepatic and osseous recurrences have relatively quicker onset and less favorable prognosis compared to other sites. These findings may benefit future efforts to develop recurrence site-specific treatment plans and highlight the necessity of subsequent endeavors to explore the genetic associations of recurrence in upper tract urothelial carcinoma.

Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis

Breast cancer is one of the most common malignant tumors among women worldwide and has a high morbidity and mortality. This research aimed to identify hub genes and small molecule drugs for breast cancer by integrated bioinformatics analysis. After downloading multiple gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, 283 overlapping differentially expressed genes (DEGs) significantly enriched in different cancer-related functions and pathways were obtained using LIMMA, VennDiagram and ClusterProfiler packages of R. We then analyzed the topology of protein–protein interaction (PPI) network with overlapping DEGs and further obtained six hub genes (RRM2, CDC20, CCNB2, BUB1B, CDK1, and CCNA2) from the network via STRING and Cytoscape. Subsequently, we conducted genes expression verification, genetic alterations evaluation, immune infiltration prediction, clinicopathological parameters analysis, identification of transcriptional and post-transcriptional regulatory molecules, and survival analysis for these hub genes. Meanwhile, 29 possible drug candidates (e.g., Cladribine, Gallium nitrate, Alvocidib, 1β-hydroxyalantolactone, Berberine hydrochloride, Nitidine chloride) were identified from the DGIdb database and the GSE85871 dataset. In addition, some transcription factors and miRNAs (e.g., E2F1, PTTG1, TP53, ZBTB16, hsa-miR-130a-3p, hsa-miR-204-5p) targeting hub genes were identified as key regulators in the progression of breast cancer. In conclusion, our study identified six hub genes and 29 potential drug candidates for breast cancer. These findings may advance understanding regarding the diagnosis, prognosis and treatment of breast cancer.

Sensitivity to differential NRF1 gene signatures contributes to breast cancer disparities

PURPOSE

Nuclear respiratory factor 1 (NRF1) drives estrogen-dependent breast tumorigenesis. Herein we examined the impact of NRF1 activity on the aggressiveness and disparate molecular signature of breast cancer in Black, White, Asian, and Hispanic women.

METHODS

NRF1 activity by transcription factor target enrichment analysis and causal NRF1-target gene signatures by Bayesian Network Inference with Java Objects (BANJO) and Markov Chain Monte Carlo (MCMC)-based gene order were examined in The Cancer Genome Atlas (TCGA) breast cancer cohorts.

RESULTS

We are the first to report increased NRF1 activity based on its differential effects on genome-wide transcription associated with luminal A and B, HER2+ and triple-negative (TN) molecular subtypes of breast cancer in women of different race/ethnicity. We observed disparate NRF1 motif-containing causal gene signatures unique to Black, White, Asian, and Hispanic women for luminal A breast cancer. Further gene order searches showed molecular heterogeneity of each subtype of breast cancer. Six different gene order sequences involving CDK1, HMMR, CCNB2, CCNB1, E2F1, CREB3L4, GTSE1, and LMNB1 with almost equal weight predicted the probability of luminal A breast cancer in whites. Three different gene order sequences consisting of CCNB1 and GTSE1, and CCNB1, LMNB1, CDK1 or CASP3 predicted almost 100% probability of luminal B breast cancer in whites; CCNB1 and LMNB1 or GTSE predicted 100% HER2+ breast cancer in whites. GTSE1 and TUBA1C combined together predicted 100% probability of developing TNBC in whites; NRF1, TUBA1B and BAX with EFNA4, and NRF1 and BTRC predicated 100% TNBC in blacks. High expressor NRF1 TN breast tumors showed unfavorable prognosis with a high risk of breast cancer death in white women.

CONCLUSION

Our findings showed how sensitivity to high NRF1 transcriptional activity coupled with its target gene signatures contribute to racial differences in luminal A and TN breast cancer subtypes. This knowledge may be useful in personalized intervention to prevent and treat this clinically challenging problem.

Comprehensive Analysis of Candidate Diagnostic and Prognostic Biomarkers Associated with Lung Adenocarcinoma

Background

We aimed to screen and identify central genetic and molecular targets involved in advancement of lung adenocarcinoma (LUAD) and to perform an integrated analysis and clinical validation.

Material/Methods

The GEO2R technique was utilized to assess differentially expressed genes (DEGs) among the gene sets GSE75037, GSE85716, and GSE118370. Subsequently, gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytical methods were executed to determine related biofunctions and signaling pathways, which were annotated with tools from the Database for Annotation, Visualization and Integrated Discovery (DAVID) resource. Then, a protein-protein interaction (PPI) network complex consisting of all detected DEGs was built with the STRING web interface. Cytohubba and MCODE plug-ins for Cytoscape software and Gene Expression Profiling Interactive Analysis (GEPIA) were employed to identify the hub genes. Finally, the mRNA expression of the identified hub genes was quantitatively validated by The Cancer Genome Atlas (TCGA) database analysis and real-time quantitative polymerase chain reaction (RT-qPCR).

Results

We screened 146 upregulated DEGs and 431 downregulated DEGs with the criteria of |logFC| >1 and P<0.05, and the GO analysis indicated that DEGs were implicated in mitotic nuclear division (biological process, BP), the nucleus (cellular component, CC), and protein binding (molecular function, MF) and were associated with multiple KEGG pathways, such as the p53 signaling pathway in cancer. Then, the top 8 genes that predicted significantly different outcomes in LUAD patients were filtered from the DEGs and selected as hub genes. The TCGA database analysis and RT-qPCR results demonstrated that these genes were differentially expressed with the same trends in LUAD tissues compared with normal tissues.

Conclusions

Overall, we propose that 8 genes (PECAM1, CDK1, MKI67, SPP1, TOP2A, CHEK1, CCNB1, and RRM2) might be novel hub genes strongly associated with the progression and prognosis of LUAD.

Expression of H3K4me3 and H3K9ac in breast cancer

PURPOSE

Breast cancer is the leading cause of cancer death in females. Histone modifications have been shown to have an influence on the gene expression. This study focusses on the histone modifications H3K9ac and H3K4me3 in breast cancer and their impact on survival METHODS: H3K4me3 and H3K9ac expression was immunohistochemically examined in 235 tissue samples.

RESULTS

Positive estrogen receptor status was correlated with a higher IRS of the nuclear (p = 0.033), and of the cytoplasmic H3K4me3 staining (p = 0.009). H3K9ac intensity was associated to the Her2 status (p = 0.045) and to poor prognosis in cells with positive Ki67 status (p = 0.013). A high intensity of nuclear H3K4me3 staining was found to be correlated with a lower 10-year-survival (p = 0.026) and with lower breast cancer-specific survival (p = 0.004). High percentage score (> 190) of H3K9ac expression was correlated to worse breast cancer-specific survival (p = 0.005). Shorter progression-free survival was found in patients with nuclear (p = 0.013) and cytoplasmic H3K4me3expression (p = 0.024) and H3K9ac expression (p = 0.023).

CONCLUSION

This analysis provides new evidence of histone modifications in breast cancer. High H3K4me3 and H3K9ac expression was correlated with survival rates. Further investigation of histone modifications in breast cancer could lead to a more profound understanding of the molecular mechanisms of cancer development and could result in new therapeutic strategies.

The genomic landscape of metastasis in treatment-naïve breast cancer models

Metastasis remains the principle cause of mortality for breast cancer and presents a critical challenge because secondary lesions are often refractory to conventional treatments. While specific genetic alterations are tightly linked to primary tumor development and progression, the role of genetic alteration in the metastatic process is not well-understood. The theory of tumor evolution postulated by Peter Nowell in 1976 has yet to be proven in the context of metastasis. Therefore, in order to investigate how somatic evolution contributes to breast cancer metastasis, we performed exome, whole genome, and RNA sequencing of matched metastatic and primary tumors from pre-clinical mouse models of breast cancer. Here we show that in a treatment-naïve setting, recurrent single nucleotide variants and copy number variation, but not gene fusion events, play key metastasis-driving roles in breast cancer. For instance, we identified recurrent mutations in Kras, a known driver of colorectal and lung tumorigenesis that has not been previously implicated in breast cancer metastasis. However, in a set of in vivo proof-of-concept experiments we show that the Kras G12D mutation is sufficient to significantly promote metastasis using three syngeneic allograft models. The work herein confirms the existence of metastasis-driving mutations and presents a novel framework to identify actionable metastasis-targeted therapies.

miR-485-5p inhibits the progression of breast cancer cells by negatively regulating MUC1

OBJECTIVE

To investigate the mechanism of miR-485-5p inhibiting breast cancer cells by targeting MUC1.

METHODS

Differentially expressed genes (DEGs) in breast cancer tissues were analyzed using breast cancer tissue microarrays (TMA) in the GEO database. Differential expression of MUC1 in breast cancer tissue samples was detected by TCGA database. qRT-PCR was used to detect the expression of MUC1 and miR-485-5p in human normal breast epithelial cell lines and human breast cancer cell lines. Bioinformatics was applied to analyze targeted binding site of miR-485-5p and MUC1 and their targeted relationship was identified by dual luciferase assay. The proliferation ability of breast cancer cells was detected by CCK-8 assay. Cell apoptosis was detected by flow cytometry. The ability of cell migration was measured by scratch healing test. Transwell assay was used to detect the invasion ability of cells. The protein expression levels of MUC1 and EMT-related molecules (E-cadherin, N-cadherin and Vimentin) were detected by Western blot.

RESULTS

MUC1 was highly expressed in breast cancer tissue samples and breast cancer cell lines, while miR-485-5p was lowly expressed. Overexpression of miR-485-5p inhibits cell viability and invasion and migration of breast cancer cell line MCF-7 and promotes apoptosis. The same results were obtained by silencing the expression of MUC1. MiR-485-5p targets to bind to the 3'-UTR region of MUC1 and negatively regulates the expression of MUC1. Overexpressing MUC1 while overexpressing miR-485-5p reversed the inhibitory effect of miR-485-5p on breast cancer and inhibited EMT.

CONCLUSION

MiR-485-5p can down-regulate the expression of MUC1, thus inhibit the proliferation, invasion and migration of breast cancer cells and promote cell apoptosis.

A survey of gene expression meta-analysis: methods and applications

The increasing use of high-throughput gene expression quantification technologies over the last two decades and the fact that most of the published studies are stored in public databases has triggered an explosion of studies available through public repositories. All this information offers an invaluable resource for reuse to generate new knowledge and scientific findings. In this context, great interest has been focused on meta-analysis methods to integrate and jointly analyze different gene expression datasets. In this work, we describe the main steps in the gene expression meta-analysis, from data preparation to the state-of-the art statistical methods. We also analyze the main types of applications and problems that can be approached in gene expression meta-analysis studies and provide a comparative overview of the available software and bioinformatics tools. Moreover, a practical guide for choosing the most appropriate method in each case is also provided.

Aberrant WNT/CTNNB1 Signaling as a Therapeutic Target in Human Breast Cancer: Weighing the Evidence

WNT signaling is crucial for tissue morphogenesis during development in all multicellular animals. After birth, WNT/CTNNB1 responsive stem cells are responsible for tissue homeostasis in various organs and hyperactive WNT/CTNNB1 signaling is observed in many different human cancers. The first link between WNT signaling and breast cancer was established almost 40 years ago, when Wnt1 was identified as a proto-oncogene capable of driving mammary tumor formation in mice. Since that discovery, there has been a dedicated search for aberrant WNT signaling in human breast cancer. However, much debate and controversy persist regarding the importance of WNT signaling for the initiation, progression or maintenance of different breast cancer subtypes. As the first drugs designed to block functional WNT signaling have entered clinical trials, many questions about the role of aberrant WNT signaling in human breast cancer remain. Here, we discuss three major research gaps in this area. First, we still lack a basic understanding of the function of WNT signaling in normal human breast development and physiology. Second, the overall extent and precise effect of (epi)genetic changes affecting the WNT pathway in different breast cancer subtypes are still unknown. Which underlying molecular and cell biological mechanisms are disrupted as a result also awaits further scrutiny. Third, we survey the current status of targeted therapeutics that are aimed at interfering with the WNT pathway in breast cancer patients and highlight the importance and complexity of selecting the subset of patients that may benefit from treatment.

Identification of potential key genes for HER-2 positive breast cancer based on bioinformatics analysis

BACKGROUNDS

HER-2 positive breast cancer is a subtype of breast cancer with poor clinical outcome. The aim of this study was to identify differentially expressed genes (DEGs) for HER-2 positive breast cancer and elucidate the potential interactions among them.

MATERIAL AND METHODS

Three gene expression profiles (GSE29431, GSE45827, and GSE65194) were derived from the Gene Expression Omnibus (GEO) database. GEO2R tool was applied to obtain DEGs between HER-2 positive breast cancer and normal breast tissues. Gene ontology (GO) annotation analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery (David) online tool. Protein-protein interaction (PPI) network, hub gene identification and module analysis was conducted by Cytoscape software. Online Kaplan-Meier plotter survival analysis tool was also used to investigate the prognostic values of hub genes in HER-2 positive breast cancer patients.

RESULTS

A total of 54 upregulated DEGs and 269 downregulated DEGs were identified. Among them, 10 hub genes including CCNB1, RAC1, TOP2A, KIF20A, RRM2, ASPM, NUSAP1, BIRC5, BUB1B, and CEP55 demonstrated by connectivity degree in the PPI network were screened out. In Kaplan-Meier plotter survival analysis, the overexpression of RAC1 and RRM2 were shown to be associated with an unfavorable prognosis in HER-2 positive breast cancer patients.

CONCLUSIONS

This present study identified a number of potential target genes and pathways which might impact the oncogenesis and progression of HER-2 positive breast cancer. These findings could provide new insights into the detection of novel diagnostic and therapeutic biomarkers for this disease.

Gene expression comparison between primary triple-negative breast cancer and paired axillary and sentinel lymph node metastasis

Few studies examine the genomics of axillary lymph node (ALN) metastasis in triple-negative breast cancer (TNBC). The aim was to characterize and compare gene expression patterns of primary breast cancers and paired ALN metastases. Patients with stage 2-3 ER/PR negative, HER2 negative TNBC with ALN macrometastasis without neo-adjuvant therapy were selected. Tumor-specific area was isolated from breast and ALN tissue sections. Gene expression of 2567 cancer-associated genes was analyzed with the HTG EdgeSeq system coupled with Illumina next-generation sequencing (NGS). Seventeen pairs of TNBC and autologous ALN metastasis were analyzed. Compared with the primary, ALN metastasis had 257 statistically significant differentially expressed genes, including 123 upregulated genes and 134 downregulated genes. Notably, there was an upregulation of anti-apoptosis and survival signaling genes (BIRC3, TCL1A, FLT3, and VCAM1) in the ALN metastasis. There was also an upregulation of chemotaxis genes (CCL19, CCL21, CXCL13, and TNFSF11). The most striking feature is the downregulation of genes known to regulate cell microenvironment interaction (MMP2, MMP 3, MMP 7, MMP 11, MMP14, COL1A1, COL1A2, COL3A1, COL5A1, COL5A2, COL6A6, COL11A1, and COL17A1). In TNBC, ALN metastases have a distinct gene expression profile. Genes associated with anti-apoptosis, survival responses, and chemotaxis are upregulated, and genes associated with regulation of extracellular matrix are downregulated when compared to autologous primary cancer. TNBC cells metastatic to lymph nodes undergo a change in order to metastasize and survive in the new microenvironment, which may lead to insights into the metastatic process.

Socioeconomic inequalities in metastasis, recurrence, stage and grade of breast cancer: a hospital-based retrospective cohort study

Introduction

This study aims to estimate the Socio-Economic Status (SES) inequality on the metastasis, recurrence, stage and grade in Breast Cancer (BC).

Methods

This retrospective cohort study conducted on 411 BC patients in Arak, Iran. Asset-based questionnaire used to estimate the household SES. For calculate of SES inequality was used from Concentration Index (C). Moreover for investigate the association between recurrence and metastasis with other variables were used from multilevel logistic regression and analysis of variance were used to investigate the relationship between SES and other variables. The data were analyzed with Stata (v.13) software.

Results

Results of analysis of variance showed statistical significant relationship between SES with, insurance, surgery, grade, stage, recurrence and metastasis (p-value < 0.05). Moreover the Odds Ratio (OR) were significant of recurrence with age, academic level of education, supplementary insurance history of BC in first-degree relatives, stage and grade, also, metastasis with age of > 80 years, insurance, supplementary insurance, history of BC in first-degree relatives, chemotherapy, radiotherapy, stage and grade four. The total C index obtained 0.015 (0.002, 0.026), 0.011 (0.003, 0.031), – 0.014 (– 0.034, – 0.001) and – 0.042 (– 0.061, – 0.002) for metastasis, recurrence, stage and grade of BC respectively.

Conclusions

Our results showed evidence of inequality in the metastasis, recurrence, stage and grade in BC patients.

Expression of Oncogenic Drivers in 3D Cell Culture Depends on Nuclear ATP Synthesis by NUDT5

The growth of cancer cells as oncospheres in three-dimensional (3D) culture provides a robust cell model for understanding cancer progression, as well as for early drug discovery and validation. We have previously described a novel pathway in breast cancer cells, whereby ADP (Adenosine diphosphate)-ribose derived from hydrolysis of poly (ADP-Ribose) and pyrophosphate (PPi) are converted to ATP, catalysed by the enzyme NUDT5 (nucleotide diphosphate hydrolase type 5). Overexpression of the NUDT5 gene in breast and other cancer types is associated with poor prognosis, increased risk of recurrence and metastasis. In order to understand the role of NUDT5 in cancer cell growth, we performed phenotypic and global expression analysis in breast cancer cells grown as oncospheres. Comparison of two-dimensional (2D) versus 3D cancer cell cultures from different tissues of origin suggest that NUDT5 increases the aggressiveness of the disease via the modulation of several key driver genes, including ubiquitin specific peptidase 22 (USP22), RAB35B, focadhesin (FOCAD) and prostagladin E synthase (PTGES). NUDT5 functions as a master regulator of key oncogenic pathways and of genes involved in cell adhesion, cancer stem cell (CSC) maintenance and epithelial to mesenchyme transition (EMT). Inhibiting the enzymatic activities of NUDT5 prevents oncosphere formation and precludes the activation of cancer driver genes. These findings highlight NUDT5 as an upstream regulator of tumour drivers and may provide a biomarker for cancer stratification, as well as a novel target for drug discovery for combinatorial drug regimens for the treatment of aggressive cancer types and metastasis.

TBL1XR1 is involved in c-Met-mediated tumorigenesis of human nonsmall cell lung cancer

Nonsmall cell lung carcinoma (NSCLC) contributes to the highest number of cancer deaths globally. Metastases and chemoresistance are two major confounders to the treatment efficacy in NSCLC. Transducin (β)-like 1 X-linked receptor 1 (TBL1XR1) has been associated with high rates of metastases in breast, gastric, and stomach cancers. However, the role of TBL1XR1 in lung cancers remains underexplored. We selected matched and cancerous lung tissues to establish the upregulation of TBL1XR1. Using in vitro assays, we assessed the influence of TBL1XR1 on various cancer phenotypes, namely cell proliferation, chemoresistance, invasion, and metastases in a CRISPR-Cas9-mediated knock out model (A549 cells), and H460 cell lines overexpressing TBL1XR1. We found that TBL1XR1 is overexpressed in NSCLC tissue and patient sera in comparison to paired adjacent normal tissue. Overexpression of TBL1XR1 in NSCLC cell lines mediates cell survival, proliferation, and metastases. TBL1XR1 was found to regulate MEK and Akt pathways through their master regulator c-Met. We observed that activation of c-Met is downregulated in the absence of TBL1XR1. Our study strengthens the contention that TBL1XR1 is a biomarker for prognosis of NSCLC. It may also be considered as an adjunct or core therapeutic target to overcome cisplatin resistance in lung cancers.

A study of mechanistic mapping of novel SNPs to male breast cancer

Alterations in BRCA2, PALB2, CHEK2, and p53 genes have been identified for their association with male breast cancer in various studies. The incidence of male breast cancer in India is consistent with its global rate. The present study was carried out with an aim to evaluate the genetic alterations in male breast cancer patients from Malwa region of Punjab, India. Four male breast cancer patients belonging to different families were recruited from Guru Gobind Singh Medical College and Hospital, Faridkot, India. A total of 51 genes reported with implications in the pathogenesis of breast cancer were screened using next generation sequencing. Germline variations were found in BRCA1, BRCA2, PMS2, p53, and PALB2 genes, previously reported to be associated with MBC as well as FBC. In addition to these, 13 novel missense alterations were detected in eight genes including STK11, FZR1, PALB2, BRCA2, NF2, BAP1, BARD1, and CHEK2. Impact of these missense alterations on structure and function of protein was also analyzed through molecular dynamics simulation. Structural analysis of these single nucleotide polymorphisms (SNPs) revealed significant impact on the encoded protein functioning.

Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value

Glioblastoma is a common malignant tumor in the central nervous system with an extremely poor outcome; understanding the mechanisms of glioblastoma at the molecular level is essential for clinical treatment. In the present study, we used bioinformatics analysis to identify potential biomarkers associated with prognosis in glioblastoma and elucidate the underlying mechanisms. The result revealed that 552 common genes were differentially expressed between glioblastoma and normal tissues based on TCGA, GSE4290, and GSE 50161 datasets. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction (PPI) network were carried out to gain insight into the actions of differentially expressed genes (DEGs). As a result, 20 genes (CALB1, CDC20, CDCA8, CDK1, CEP55, DLGAP5, KIF20A, KIF4A, NDC80, PBK, RRM2, SYN1, SYP, SYT1, TPX2, TTK, VEGFA, BDNF, GNG3, and TOP2A) were found as hub genes via CytoHubba in Cytoscape and functioned mainly by participating in cell cycle and p53 signaling pathway; among them, RRM2 and CEP55 were considered to have relationship with the prognosis of glioblastoma, especially RRM2. High expression of RRM2 was consistent with shorter overall survival time. In conclusion, our study displayed the bioinformatic analysis methods in screening potential oncogenes in glioblastoma and underlying mechanisms. What is more is that we successfully identified RRM2 as a novel biomarker linked with prognosis, which might be expected to be a promising target for the therapy of glioblastoma.

Soy Foods Might Weaken the Sensitivity of Tamoxifen in Premenopausal Patients With Lumina A Subtype of Breast Cancer

BACKGROUND

Based on estrogen active substances, many women consume soy foods in the belief that it could prevent breast cancer (BC). Women with different molecular subtypes would be likely to have diverse reactions to soy foods, especially those with the estrogen-receptor-positive (ER⁺) subtype. The aim of the current study is to identify the differentially expressed genes (DEGs) on soy foods in premenopausal patients with Lumina A subtype of BC (LABC) after soy food treatment, and to further investigate the critical molecule change.

MATERIALS AND METHODS

GSE58792 retrieved from Gene Expression Omnibus was analyzed to obtain DEGs using GEO2R. Gene Ontology and pathway enrichment analysis were performed using FunRich and GeneMINIA. Overall survival of critical genes was performed by the Kaplan-Meier plotter online tool.

RESULTS

A total of 108 DEGs were obtained from the dataset, among which 35 were up-regulated and 73 down-regulated. Soy foods significantly reduced the expression of TFF3, TFF1, GATA3, and ESR1, which were related to the activity of the ER-related pathway and the sensitivity of tamoxifen. Furthermore, the lower expressions of TOX3, FSIP1, ESR1, and CLGN were related to prolonged survival time of patients with BC. The most significant signaling pathways were epithelial-to-mesenchymal transition in up-regulated DEGs, mesenchymal-to-epithelial transition, and mammary gland alveolus development in down-regulated DEGs, which were all related to the development and prognosis of BC.

CONCLUSIONS

Soy foods could dramatically alter the ER-related gene profile in LABC. Particularly, down-regulated DEGs of TFF3, TFF1, GATA3, and ESR1 might weaken the sensitivity of tamoxifen and increase the efficacy of neoadjuvant chemotherapy in premenopausal patients with LABC.

Alternatively activated NUSAP1 promotes tumor growth and indicates poor prognosis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies with high mortality. The key genes involved in initiation and development of HCC is not entirely clear.

METHODS

We performed a meta-analysis of available transcriptome data from 6 independent HCC datasets [5 datasets from the Gene Expression Omnibus (GEO) and 1 dataset from The Cancer Genome Atlas (TCGA)]. The associations of the nucleolar and spindle-associated protein 1 (NUSAP1) expression level with clinicopathological factors and survival times were analyzed. Two representative HCC cell models were built to observe the proliferation capacity of HCC cells when NUSAP1 expression was inhibited by shNUSAP1.

RESULTS

Based on the transcriptome and survival data in the GEO and TCGA databases, NUSAP1 gene was markedly upregulated in HCC. High expression of NUSAP1 in HCC is related to the iCluster1 molecular subgroup, poor survival, poor tumor differentiation and TNM stage. Additionally, pathway analysis based on RNAseq data suggested that NUSAP1 could activate the expression of genes involves in cell proliferation. Furthermore, downregulation of NUSAP1 expression could significantly inhibit the proliferation of SMMC-7721 and Huh7 cells in vitro.

CONCLUSIONS

Our study provides evidence that NUSAP1 may serve as a candidate prognostic marker and a target for future therapeutic intervention in HCC.