Hyaluronan-mediated motility receptor gene single nucleotide polymorphisms and risk of breast cancer

Hsa_circ_0005273 acts as a sponge of miR-509-3p to promote the malignant behaviors of breast cancer by regulating HMMR expression

BACKGROUND

Breast cancer (BC) is a common malignant tumor that threatens the health of women worldwide. Hsa_circ_0005273 has been identified as a carcinogenic factor in some solid tumors, including BC. However, the molecular mechanism of circ_0005273 in BC is poorly defined.

METHODS

The expression of circ_0005273, miR-509-3p, and hyaluronan-mediated motility receptor (HMMR) mRNA in BC was detected by quantitative real-time polymerase chain reaction. Cell proliferation, migration, invasion, and apoptosis were detected by 5-ethynyl-2'-deoxyuridine, transwell, and flow cytometry assays. The glycolysis level was detected via specific kits. Western blot was used to detect protein expression. Binding between miR-509-3p and circ_0005273 or HMMR was also verified by dual-luciferase reporter, RNA pull-down, and RNA immunoprecipitation assays. Xenograft tumor model was used to detect tumor changes in mice, and immunohistochemistry assay was employed to detect Ki-67 abundance.

RESULTS

Circ_0005273 was increased in BC tissues and cells. Circ_0005273 knockdown might inhibit BC cell proliferation, migration, invasion, glutamine metabolism, and induce apoptosis. Circ_0005273 was a miR-509-3p, and the repression role of circ_0005273 absence on BC cell development was weakened by miR-509-3p inhibitor or HMMR overexpression. Circ_0005273 up-regulated the expression of HMMR by sponging miR-509-3p. Additionally, circ_0005273 silencing might hinder tumor growth in vivo.

CONCLUSION

Circ_0005273 knockdown might repress BC cell malignant behaviors by regulating the miR-509-3p/HMMR axis, which might provide a potential therapeutic target for BC.

Modification of BRCA1-associated breast cancer risk by HMMR overexpression

Breast cancer risk for carriers of BRCA1 pathological variants is modified by genetic factors. Genetic variation in HMMR may contribute to this effect. However, the impact of risk modifiers on cancer biology remains undetermined and the biological basis of increased risk is poorly understood. Here, we depict an interplay of molecular, cellular, and tissue microenvironment alterations that increase BRCA1-associated breast cancer risk. Analysis of genome-wide association results suggests that diverse biological processes, including links to BRCA1-HMMR profiles, influence risk. HMMR overexpression in mouse mammary epithelium increases Brca1-mutant tumorigenesis by modulating the cancer cell phenotype and tumor microenvironment. Elevated HMMR activates AURKA and reduces ARPC2 localization in the mitotic cell cortex, which is correlated with micronucleation and activation of cGAS-STING and non-canonical NF-κB signaling. The initial tumorigenic events are genomic instability, epithelial-to-mesenchymal transition, and tissue infiltration of tumor-associated macrophages. The findings reveal a biological foundation for increased risk of BRCA1-associated breast cancer.

The cell cycle-related genes RHAMM, AURKA, TPX2, PLK1, and PLK4 are associated with the poor prognosis of breast cancer patients

Breast cancer is the third most common type of cancer diagnosed. Cell cycle is a complex but highly organized and controlled process, in which normal cells sense mitogenic growth signals that instruct them to enter and progress through their cell cycle. This process culminates in cell division generating two daughter cells with identical amounts of genetic material. Uncontrolled proliferation is one of the hallmarks of cancer. In this study, we analyzed the expression of the cell cycle-related genes receptor for hyaluronan (HA)-mediated motility (RHAMM), AURKA, TPX2, PLK1, and PLK4 and correlated them with the prognosis in a collective of 3952 breast cancer patients. A high messenger RNA expression of all studied genes correlated with a poor prognosis. Stratifying the patients according to the expression of hormonal receptors, we found that in patients with estrogen and progesterone receptor-positive and human epithelial growth factor receptor 2-negative tumors, and Luminal A and Luminal B tumors, the expression of the five analyzed genes correlates with worse survival. qPCR analysis of a panel of breast cancer cell lines representative of major molecular subtypes indicated a predominant expression in the luminal subtype. In vitro experiments showed that radiation influences the expression of the five analyzed genes both in luminal and triple-negative model cell lines. Functional analysis of MDA-MB-231 cells showed that small interfering RNA knockdown of PLK4 and TPX2 and pharmacological inhibition of PLK1 had an impact on the cell cycle and colony formation. Looking for a potential upstream regulation by microRNAs, we observed a differential expression of RHAMM, AURKA, TPX2, PLK1, and PLK4 after transfecting the MDA-MB-231 cells with three different microRNAs. Survival analysis of miR-34c-5p, miR-375, and miR-142-3p showed a different impact on the prognosis of breast cancer patients. Our study suggests that RHAMM, AURKA, TPX2, PLK1, and PLK4 can be used as potential targets for treatment or as a prognostic value in breast cancer patients.

Genes That Predict Poor Prognosis in Breast Cancer via Bioinformatical Analysis

Background

Breast cancer is one of the most commonly diagnosed cancers all over the world, and it is now the leading cause of cancer death among females. The aim of this study was to find DEGs (differentially expressed genes) which can predict poor prognosis in breast cancer and be effective targets for breast cancer patients via bioinformatical analysis.

Methods

GSE86374, GSE5364, and GSE70947 were chosen from the GEO database. DEGs between breast cancer tissues and normal breast tissues were picked out by GEO2R and Venn diagram software. Then, DAVID (Database for Annotation, Visualization, and Integrated Discovery) was used to analyze these DEGs in gene ontology (GO) including molecular function (MF), cellular component (CC), and biological process (BP) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. Next, STRING (Search Tool for the Retrieval of Interacting Genes) was used to investigate potential protein-protein interaction (PPI) relationships among DEGs and these DEGs were analyzed by Molecular Complex Detection (MCODE) in Cytoscape. After that, UALCAN, GEPIA (gene expression profiling interactive analysis), and KM (Kaplan-Meier plotter) were used for the prognostic information and core genes were qualified.

Results

There were 96 upregulated genes and 98 downregulated genes in this study. 55 upregulated genes were selected as hub genes in the PPI network. For validation in UALCAN, GEPIA, and KM, 5 core genes (KIF4A, RACGAP1, CKS2, SHCBP1, and HMMR) were found to highly expressed in breast cancer tissues with poor prognosis. They differentially expressed between different subclasses of breast cancer.

Conclusion

These five genes (KIF4A, RACGAP1, CKS2, SHCBP1, and HMMR) could be potential targets for therapy in breast cancer and prediction of prognosis on the basis of bioinformatical analysis.

Identification of the association between HMMR expression and progression of hepatocellular carcinoma via construction of a co-expression network

The aim of the present study was to identify key genes involved in the progression of hepatocellular carcinoma (HCC). According to the theory of the multistep process of hepatocarcinogenesis and weighted gene co-expression network analysis, hub genes associated with the progression of HCC were identified using the gene expression profiles of patients with normal to chronic hepatitis/cirrhosis and dysplastic nodules to HCC. An independent dataset was used to verify the association between hub gene and clinical phenotype. The diagnostic and prognostic value of hub genes regarding HCC were evaluated. Gene set enrichment analysis (GSEA) was performed to explore the function of hub genes. A co-expression gene module positively associated with HCC progression was identified. Combined with a protein-protein interaction (PPI) network, a total of 10 common hub genes common to both the module of interest and the PPI network were selected as hub genes. Hyaluronan mediated motility receptor (HMMR) was selected as the candidate gene and was significantly upregulated in HCC at the mRNA and protein expression levels. HMMR is a promising diagnostic biomarker for HCC, and is also associated with its progression. The expression of HMMR was positively correlated with HCC tumor grade, pathological stage, tumor stage and Ishak score. The expression of HMMR was an independent prognostic factor compared with clinicopathological features. Patients with high expression levels of HMMR exhibited a less favorable prognosis. GSEA identified 6 representative gene sets that were associated with cancer. Overall, HMMR may serve an important role in HCC and may have potential as a biomarker of HCC diagnosis and progression.

Gene-to-gene interactions and the association of TP53, XRCC1, TNFα, HMMR, MDM2 and PALB2 with breast cancer in Kyrgyz females

BACKGROUND

At present, little is known about the genetic background of breast cancer (BC) in Kyrgyz. Therefore, the aim of this study was to assess gene-to-gene interactions and the contribution of p.Arg72Pro (TP53 gene), p.Gln399Arg (XRCC1 gene), p.Arg194Trp (XRCC1 gene), g.4682G > A (TNFα gene), p.Val353Ala (HMMR gene), c.14 + 309 T > G (MDM2 gene) and g.38444 T > G (PALB2 gene) polymorphic loci in breast cancer (BC) risk in females of Kyrgyz ethnicity.

METHODS

The case-control study comprised 103 females with histologically verified BC and 102 controls with no cancer. We used polymerase chain reaction-based restriction fragment length polymorphism to genotype polymorphic loci.

RESULTS

Gln/Arg heterozygous variant of XRCC1 gene's p.Gln399Arg locus, as well as combined carriage of Arg/Gln//Arg/Pro of XRCC1/TP53; Arg/Gln//T/T of XRCC1/MDM2; Arg/Gln//G/G and Arg/Gln//G/A of XRCC1/TNFα, Arg/Gln//T/T of XRCC1/PALB2; Arg/Gln//Arg/Arg and Arg/Gln//Arg/Trp for p.Gln399Arg and p.Arg194Trp polymorphic loci of XRCC1 were associated with BC in Kyrgyz females.

CONCLUSION

TP53, XRCC1, TNFα, HMMR, MDM2 and PALB2 genes' polymorphic site combinations appear to be candidate markers of genetic predisposition to BC in Kyrgyz population and prompt targeted personalized care.

SCNrank: spectral clustering for network-based ranking to reveal potential drug targets and its application in pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy. Due to its wide heterogeneity, PDAC acts aggressively and responds poorly to most chemotherapies, causing an urgent need for the development of new therapeutic strategies. Cell lines have been used as the foundation for drug development and disease modeling. CRISPR-Cas9 plays a key role in every step-in drug discovery: from target identification and validation to preclinical cancer cell testing. Using cell-line models and CRISPR-Cas9 technology together make drug target prediction feasible. However, there is still a large gap between predicted results and actionable targets in real tumors. Biological network models provide great modus to mimic genetic interactions in real biological systems, which can benefit gene perturbation studies and potential target identification for treating PDAC. Nevertheless, building a network model that takes cell-line data and CRISPR-Cas9 data as input to accurately predict potential targets that will respond well on real tissue remains unsolved.

Methods

We developed a novel algorithm ‘Spectral Clustering for Network-based target Ranking’ (SCNrank) that systematically integrates three types of data: expression profiles from tumor tissue, normal tissue and cell-line PDAC; protein-protein interaction network (PPI); and CRISPR-Cas9 data to prioritize potential drug targets for PDAC. The whole algorithm can be classified into three steps: 1. using STRING PPI network skeleton, SCNrank constructs tissue-specific networks with PDAC tumor and normal pancreas tissues from expression profiles; 2. With the same network skeleton, SCNrank constructs cell-line-specific networks using the cell-line PDAC expression profiles and CRISPR-Cas 9 data from pancreatic cancer cell-lines; 3. SCNrank applies a novel spectral clustering approach to reduce data dimension and generate gene clusters that carry common features from both networks. Finally, SCNrank applies a scoring scheme called ‘Target Influence score’ (TI), which estimates a given target’s influence towards the cluster it belongs to, for scoring and ranking each drug target.

Results

We applied SCNrank to analyze 263 expression profiles, CRPSPR-Cas9 data from 22 different pancreatic cancer cell-lines and the STRING protein-protein interaction (PPI) network. With SCNrank, we successfully constructed an integrated tissue PDAC network and an integrated cell-line PDAC network, both of which contain 4414 selected genes that are overexpressed in tumor tissue samples. After clustering, 4414 genes are distributed into 198 clusters, which include 367 targets of FDA approved drugs. These drug targets are all scored and ranked by their TI scores, which we defined to measure their influence towards the network. We validated top-ranked targets in three aspects: Firstly, mapping them onto the existing clinical drug targets of PDAC to measure the concordance. Secondly, we performed enrichment analysis to these drug targets and the clusters there are within, to reveal functional associations between clusters and PDAC; Thirdly, we performed survival analysis for the top-ranked targets to connect targets with clinical outcomes. Survival analysis reveals that overexpression of three top-ranked genes, PGK1, HMMR and POLE2, significantly increases the risk of death in PDAC patients.

Conclusion

SCNrank is an unbiased algorithm that systematically integrates multiple types of omics data to do potential drug target selection and ranking. SCNrank shows great capability in predicting drug targets for PDAC. Pancreatic cancer-associated gene candidates predicted by our SCNrank approach have the potential to guide genetics-based anti-pancreatic drug discovery.

Hyaluronan Mediated Motility Receptor (HMMR) Encodes an Evolutionarily Conserved Homeostasis, Mitosis, and Meiosis Regulator Rather than a Hyaluronan Receptor

Hyaluronan is an extracellular matrix component that absorbs water in tissues and engages cell surface receptors, like Cluster of Differentiation 44 (CD44), to promote cellular growth and movement. Consequently, CD44 demarks stem cells in normal tissues and tumor-initiating cells isolated from neoplastic tissues. Hyaluronan mediated motility receptor (HMMR, also known as RHAMM) is another one of few defined hyaluronan receptors. HMMR is also associated with neoplastic processes and its role in cancer progression is often attributed to hyaluronan-mediated signaling. But, HMMR is an intracellular, microtubule-associated, spindle assembly factor that localizes protein complexes to augment the activities of mitotic kinases, like polo-like kinase 1 and Aurora kinase A, and control dynein and kinesin motor activities. Expression of HMMR is elevated in cells prior to and during mitosis and tissues with detectable HMMR expression tend to be highly proliferative, including neoplastic tissues. Moreover, HMMR is a breast cancer susceptibility gene product. Here, we briefly review the associations between HMMR and tumorigenesis as well as the structure and evolution of HMMR, which identifies Hmmr-like gene products in several insect species that do not produce hyaluronan. This review supports the designation of HMMR as a homeostasis, mitosis, and meiosis regulator, and clarifies how its dysfunction may promote the tumorigenic process and cancer progression.

Novel Biomarkers Associated With Progression and Prognosis of Bladder Cancer Identified by Co-expression Analysis

Our study's goal was to screen novel biomarkers that could accurately predict the progression and prognosis of bladder cancer (BC). Firstly, we used the Gene Expression Omnibus (GEO) dataset GSE37815 to screen differentially expressed genes (DEGs). Secondly, we used the DEGs to construct a co-expression network by weighted gene co-expression network analysis (WGCNA) in GSE71576. We then screened the brown module, which was significantly correlated with the histologic grade (r = 0.85, p = 1e-12) of BC. We conducted functional annotation on all genes of the brown module and found that the genes of the brown module were mainly significantly enriched in "cell cycle" correlation pathways. Next, we screened out two real hub genes (ANLN, HMMR) by combining WGCNA, protein-protein interaction (PPI) network and survival analysis. Finally, we combined the GEO datasets (GSE13507, GSE37815, GSE31684, GSE71576). Oncomine, Human Protein Atlas (HPA), and The Cancer Genome Atlas (TCGA) dataset to confirm the predict value of the real hub genes for BC progression and prognosis. A gene-set enrichment analysis (GSEA) revealed that the real hub genes were mainly enriched in "bladder cancer" and "cell cycle" pathways. A survival analysis showed that they were of great significance in predicting the prognosis of BC. In summary, our study screened and confirmed that two biomarkers could accurately predict the progression and prognosis of BC, which is of great significance for both stratification therapy and the mechanism study of BC.

Assessing associations between the AURKA-HMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04-1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03-1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted pinteraction values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers.

Cellular heterogeneity profiling by hyaluronan probes reveals an invasive but slow-growing breast tumor subset

Tumor heterogeneity confounds cancer diagnosis and the outcome of therapy, necessitating analysis of tumor cell subsets within the tumor mass. Elevated expression of hyaluronan (HA) and HA receptors, receptor for HA-mediated motility (RHAMM)/HA-mediated motility receptor and cluster designation 44 (CD44), in breast tumors correlates with poor outcome. We hypothesized that a probe for detecting HA-HA receptor interactions may reveal breast cancer (BCa) cell heterogeneity relevant to tumor progression. A fluorescent HA (F-HA) probe containing a mixture of polymer sizes typical of tumor microenvironments (10-480 kDa), multiplexed profiling, and flow cytometry were used to monitor HA binding to BCa cell lines of different molecular subtypes. Formulae were developed to quantify binding heterogeneity and to measure invasion in vivo. Two subsets exhibiting differential binding (HA(-/low) vs. HA(high)) were isolated and characterized for morphology, growth, and invasion in culture and as xenografts in vivo. F-HA-binding amounts and degree of heterogeneity varied with BCa subtype, were highest in the malignant basal-like cell lines, and decreased upon reversion to a nonmalignant phenotype. Binding amounts correlated with CD44 and RHAMM displayed but binding heterogeneity appeared to arise from a differential ability of HA receptor-positive subpopulations to interact with F-HA. HA(high) subpopulations exhibited significantly higher local invasion and lung micrometastases but, unexpectedly, lower proliferation than either unsorted parental cells or the HA(-/low) subpopulation. Querying F-HA binding to aggressive tumor cells reveals a previously undetected form of heterogeneity that predicts invasive/metastatic behavior and that may aid both early identification of cancer patients susceptible to metastasis, and detection/therapy of invasive BCa subpopulations.

Interplay between BRCA1 and RHAMM regulates epithelial apicobasal polarization and may influence risk of breast cancer

Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.

How does a protein with dual mitotic spindle and extracellular matrix receptor functions affect tumor susceptibility and progression?

The mechanisms responsible for the oncogenic effects of the hyaluronan (HA) receptor and mitotic spindle binding protein, RHAMM, are poorly understood. On one hand, extracellular RHAMM interacts with HA and cellsurface receptors such as CD44 to coordinately activate the MAPK/ERK1,2 pathway, thus contributing to the spread and proliferation of tumor cells. On the other hand, intracellular RHAMM decorates mitotic spindles and is necessary for spindle formation and progression through G2/M and overexpression or loss of RHAMM can result in multipole spindles and chromosome missegregation. The deregulation of these intracellular functions could lead to genomic instability and fuel tumor progression. This suggests that both extracellular and intracellular RHAMM can promote tumor progression. Intracellular RHAMM can bind directly to ERK1 to form complexes with ERK2, MEK1 and ERK1,2 substrates, and we present a model whereby RHAMM's function is as a scaffold protein, controlling activation and targeting of ERK1,2 to specific substrates.

RHAMM promotes interphase microtubule instability and mitotic spindle integrity through MEK1/ERK1/2 activity

An oncogenic form of RHAMM (receptor for hyaluronan-mediated motility, mouse, amino acids 163-794 termed RHAMM(Delta163)) is a cell surface hyaluronan receptor and mitotic spindle protein that is highly expressed in aggressive human cancers. Its regulation of mitotic spindle integrity is thought to contribute to tumor progression, but the molecular mechanisms underlying this function have not previously been defined. Here, we report that intracellular RHAMM(Delta163) modifies the stability of interphase and mitotic spindle microtubules through ERK1/2 activity. RHAMM(-/-) mouse embryonic fibroblasts exhibit strongly acetylated interphase microtubules, multi-pole mitotic spindles, aberrant chromosome segregation, and inappropriate cytokinesis during mitosis. These defects are rescued by either expression of RHAMM or mutant active MEK1. Mutational analyses show that RHAMM(Delta163) binds to alpha- and beta-tubulin protein via a carboxyl-terminal leucine zipper, but in vitro analyses indicate this interaction does not directly contribute to tubulin polymerization/stability. Co-immunoprecipitation and pulldown assays reveal complexes of RHAMM(Delta163), ERK1/2-MEK1, and alpha- and beta-tubulin and demonstrate direct binding of RHAMM(Delta163) to ERK1 via a D-site motif. In vitro kinase analyses, expression of mutant RHAMM(Delta163) defective in ERK1 binding in mouse embryonic fibroblasts, and blocking MEK1 activity collectively confirm that the effect of RHAMM(Delta163) on interphase and mitotic spindle microtubules is mediated by ERK1/2 activity. Our results suggest a model wherein intracellular RHAMM(Delta163) functions as an adaptor protein to control microtubule polymerization during interphase and mitosis as a result of localizing ERK1/2-MEK1 complexes to their tubulin-associated substrates.