Integrated cross-species transcriptional network analysis of metastatic susceptibility

SMARCD1 is an essential expression-restricted metastasis modifier

Breast cancer is the most frequently diagnosed cancer worldwide, constituting 15% of cases in 2023. The predominant cause of breast cancer-related mortality is metastasis, and a lack of metastasis-targeted therapies perpetuates dismal outcomes for late-stage patients. By using meiotic genetics to study inherited transcriptional network regulation, we have identified, to the best of our knowledge, a new class of "essential expression-restricted" genes as potential candidates for metastasis-targeted therapeutics. Building upon previous work implicating the CCR4-NOT RNA deadenylase complex in metastasis, we demonstrate that RNA-binding proteins NANOS1, PUM2, and CPSF4 also regulate metastatic potential. Using various models and clinical data, we pinpoint Smarcd1 mRNA as a target of all three RNA-BPs. Strikingly, both high and low expression of Smarcd1 correlate with positive clinical outcomes, while intermediate expression significantly reduces the probability of survival. Applying the theory of "essential genes" from evolution, we identify 50 additional genes that require precise expression levels for metastasis to occur. Specifically, small perturbations in Smarcd1 expression significantly reduce metastasis in mouse models and alter splicing programs relevant to the ER+/HER2-enriched breast cancer. Identification subtype-specific essential expression-restricted metastasis modifiers introduces a novel class of genes that, when therapeutically "nudged" in either direction, may significantly improve late-stage breast cancer patients.

Telomere-related gene risk model for prognosis prediction in colorectal cancer

Background

Colorectal cancer (CRC) is the third-most prevalent cancer globally. The biological significance of telomeres in CRC carcinogenesis and progression is underscored by accumulating data. Nevertheless, not much is known about how telomere-related genes (TRGs) affect CRC prognosis. Therefore, the aim of this study was to investigate the role of TRGs in CRC prognosis.

Methods

We retrospectively obtained the expression profiles and clinical data of CRC patients from public databases. Utilizing least absolute shrinkage and selection operator (LASSO) regression analysis, we created a telomere-related risk model to predict survival outcomes, identifying ten telomere-related differentially expressed genes (TRDEGs). Based on TRDEGs, we stratified patients from The Cancer Genome Atlas (TCGA) into low- and high-risk subsets. Subsequently, we conducted comprehensive analyses, including survival assessment, immune cell infiltration, drug sensitivity, and prediction of molecular interactions using Kaplan-Meier curves, ESTIMATE, CIBERSORT, OncoPredict, and other approaches.

Results

The model showed exceptional predictive accuracy for survival. Significant differences in survival were observed between the two groups of participants grouped according to the model (P<0.001), and this difference was further confirmed in the external validation set (GSE39582) (P=0.004). Additionally, compared to the low-risk group, the high-risk group exhibited significantly advanced tumor node metastasis (TNM) stages, lower proportions of activated CD4+ T cells, effector memory CD4+ T cells, and memory B cells, but increased ratios of M2 macrophages and regulatory T cells (Tregs), elevated tumor immune dysfunction and exclusion (TIDE) scores, and diminished sensitivity to dabrafenib, lapatinib, camptothecin, docetaxel, and telomerase inhibitor IX, reflecting the signature's capacity to distinguish clinical pathological characteristics, immune environment, and drug efficacy. Finally, we validated the expression of the ten TRDEGs (ACACB, TPX2, SRPX, PPARGC1A, CD36, MMP3, NAT2, MMP10, HIGD1A, and MMP1) through quantitative real-time polymerase chain reaction (qRT-PCR) and found that compared to normal cells, the expression levels of ACACB, HIGD1A, NAT2, PPARGC1A, and TPX2 in CRC cells were elevated, whereas those of CD36, SRPX, MMP1, MMP3, and MMP10 were reduced.

Conclusions

Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.

Changes in spindle morphology driven by TPX2 overexpression in MYC-driven breast cancer cells

The MYC oncogene was previously shown to induce mitotic spindle defects, chromosome instability, and reliance on the microtubule-associated protein TPX2 to survive, but how TPX2 levels affect spindle morphology in cancer cells has not previously been examined in detail. We show that breast cancer cell lines expressing high levels of MYC and TPX2 possess shorter spindles with increased TPX2 localization at spindle poles. A similar effect was observed in non-transformed human RPE-1 cells compared to a tumor cell line (HeLa) that overexpresses MYC . These results demonstrate that TPX2 alters spindle length and morphology in cancer cells, which may contribute their ability to divide despite MYC-induced mitotic stress.

SMARCD1 is a "Goldilocks" metastasis modifier

Breast cancer is the most frequently diagnosed cancer worldwide, constituting around 15% of all diagnosed cancers in 2023. The predominant cause of breast cancer-related mortality is metastasis to distant essential organs, and a lack of metastasis-targeted therapies perpetuates dismal outcomes for late-stage patients. However, through our use of meiotic genetics to study inherited transcriptional network regulation, we have identified a new class of "Goldilocks" genes that are promising candidates for the development of metastasis-targeted therapeutics. Building upon previous work that implicated the CCR4-NOT RNA deadenylase complex in metastasis, we now demonstrate that the RNA-binding proteins (RNA-BPs) NANOS1, PUM2, and CPSF4 also regulate metastatic potential. Using cell lines, 3D culture, mouse models, and clinical data, we pinpoint Smarcd1 mRNA as a key target of all three RNA-BPs. Strikingly, both high and low expression of Smarcd1 is associated with positive clinical outcomes, while intermediate expression significantly reduces the probability of survival. Applying the theory of "essential genes" from evolution, we identify an additional 50 genes that span several cellular processes and must be maintained within a discrete window of expression for metastasis to occur. In the case of Smarcd1, small perturbations in its expression level significantly reduce metastasis in laboratory mouse models and alter splicing programs relevant to the ER+/HER2-enriched breast cancer subtype. The identification of subtype-specific "Goldilocks" metastasis modifier genes introduces a new class of genes and potential catalogue of novel targets that, when therapeutically "nudged" in either direction, may significantly improve late-stage patient outcomes.

Transcriptomic Modulation Reveals the Specific Cellular Response in Chinese Sea Bass (Lateolabrax maculatus) Gills under Salinity Change and Alkalinity Stress

Salinity and alkalinity are among the important factors affecting the distribution, survival, growth and physiology of aquatic animals. Chinese sea bass (Lateolabrax maculatus) is an important aquaculture fish species in China that can widely adapt to diverse salinities from freshwater (FW) to seawater (SW) but moderately adapt to highly alkaline water (AW). In this study, juvenile L. maculatus were exposed to salinity change (SW to FW) and alkalinity stress (FW to AW). Coordinated transcriptomic responses in L. maculatus gills were investigated and based on the weighted gene co-expression network analysis (WGCNA), 8 and 11 stress-responsive modules (SRMs) were identified for salinity change and alkalinity stress, respectively, which revealed a cascade of cellular responses to oxidative and osmotic stress in L. maculatus gills. Specifically, four upregulated SRMs were enriched with induced differentially expressed genes (DEGs) for alkalinity stress, mainly corresponding to the functions of "extracellular matrix" and "anatomical structure", indicating a strong cellular response to alkaline water. Both "antioxidative activity" and "immune response" functions were enriched in the downregulated alkaline SRMs, which comprised inhibited alkaline specific DEGs, revealing the severely disrupted immune and antioxidative functions under alkalinity stress. These alkaline-specific responses were not revealed in the salinity change groups with only moderately inhibited osmoregulation and induced antioxidative response in L. maculatus gills. Therefore, the results revealed the diverse and correlated regulation of the cellular process and stress response in saline-alkaline water, which may have arisen through the functional divergence and adaptive recruitment of the co-expression genes and will provide vital insights for the development of L. maculatus cultivation in alkaline water.

PARP1 proximity proteomics reveals interaction partners at stressed replication forks

PARP1 mediates poly-ADP-ribosylation of proteins on chromatin in response to different types of DNA lesions. PARP inhibitors are used for the treatment of BRCA1/2-deficient breast, ovarian, and prostate cancer. Loss of DNA replication fork protection is proposed as one mechanism that contributes to the vulnerability of BRCA1/2-deficient cells to PARP inhibitors. However, the mechanisms that regulate PARP1 activity at stressed replication forks remain poorly understood. Here, we performed proximity proteomics of PARP1 and isolation of proteins on stressed replication forks to map putative PARP1 regulators. We identified TPX2 as a direct PARP1-binding protein that regulates the auto-ADP-ribosylation activity of PARP1. TPX2 interacts with DNA damage response proteins and promotes homology-directed repair of DNA double-strand breaks. Moreover, TPX2 mRNA levels are increased in BRCA1/2-mutated breast and prostate cancers, and high TPX2 expression levels correlate with the sensitivity of cancer cells to PARP-trapping inhibitors. We propose that TPX2 confers a mitosis-independent function in the cellular response to replication stress by interacting with PARP1.

TIMM13 as a prognostic biomarker and associated with immune infiltration in skin cutaneous melanoma (SKCM)

Objective

Providing protection against aggregation and guiding hydrophobic precursors through the mitochondria’s intermembrane space, this protein functions as a chaperone-like protein. SLC25A12 is imported by TIMM8 as a result of its interaction with TIMM13. In spite of this, it is still unknown how TIMM13 interacts with skin cutaneous melanoma (SKCM) and tumor-infiltrating lymphocytes (TILs).

Methods

Aberrant expression of TIMM13 in SKCM and its clinical outcome was evaluated with the help of multiple databases, including the Xiantao tool (https://www.xiantao.love/), HPA, and UALCAN. TISIDB and Tumor Immune Estimation Resources (TIMER) databases were applied to explore the association between TIMM13 and tumor infiltration immune cells. OS nomogram was constructed, and model performance was examined. Finally, TIMM13 protein expression was validated by immunohistochemistry (IHC).

Results

TIMM13 expression was higher in SKCM samples than in peritumor samples. TIMM13 was strongly associated with sample type, subgroup, cancer stage, lymph node stage, and worse survival. Further, upregulation of TIMM13 was significantly associated with immunoregulators, and chemokines, as well as T cells, B cells, monocytes, neutrophils, macrophages, and T-cell regulators. An analysis of bioinformatic data uncovered that TIMM13 expression was strongly associated with PD1 (T-cell exhaustion marker). The nomogram showed good predictive performance based on calibration plot. TIMM13 was highly expressed in melanoma tissue samples than in normal samples.

Conclusion

In brief, TIMM13 may be a prognostic biomarker for SKCM. It might modulate the tumor immune microenvironment and lead to a poorer prognosis. In addition, it is necessary to study the targeted therapy of TIMM13.

Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics

Background

Osteosarcoma (OS) metastasis is the most common cause of cancer-related mortality, however, no sufficient clinical biomarkers have been identified. In this study, we identified five genes to help predict metastasis at diagnosis.

Methods

We performed weighted gene co-expression network analysis (WGCNA) to identify the most relevant gene modules associated with OS metastasis. An important machine learning algorithm, the support vector machine (SVM), was employed to predict key genes for classifying the OS metastasis phenotype. Finally, we investigated the clinical significance of key genes and their enriched pathways.

Results

Eighteen modules were identified in WGCNA, among which the pink, red, brown, blue, and turquoise modules demonstrated good preservation. In the five modules, the brown and red modules were highly correlated with OS metastasis. Genes in the two modules closely interacted in protein–protein interaction networks and were therefore chosen for further analysis. Genes in the two modules were primarily enriched in the biological processes associated with tumorigenesis and development. Furthermore, 65 differentially expressed genes were identified as common hub genes in both WGCNA and protein–protein interaction networks. SVM classifiers with the maximum area under the curve were based on 30 and 15 genes in the brown and red modules, respectively. The clinical significance of the 45 hub genes was analyzed. Of the 45 genes, 17 were found to be significantly correlated with survival time. Finally, 5/17 genes, including ADAP2 (P = 0.0094), LCP2 (P = 0.013), ARHGAP25 (P = 0.0049), CD53 (P = 0.016), and TLR7 (P = 0.04) were significantly correlated with the metastatic phenotype. In vitro verification, western blotting, wound healing analyses, transwell invasion assays, proliferation assays, and colony formation assays indicated that ARHGAP25 promoted OS cell migration, invasion, proliferation, and epithelial–mesenchymal transition.

Conclusion

We identified five genes, namely ADAP2, LCP2, ARHGAP25, CD53, and TLR7, as candidate biomarkers for the prediction of OS metastasis; ARHGAP25 inhibits MG63 OS cell growth, migration, and invasion in vitro, indicating that ARHGAP25 can serve as a promising specific and prognostic biomarker for OS metastasis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02308-w.

Phosphorylation-dependent BRD4 dimerization and implications for therapeutic inhibition of BET family proteins

Bromodomain-containing protein 4 (BRD4) is an epigenetic reader and oncology drug target that regulates gene transcription through binding to acetylated chromatin via bromodomains. Phosphorylation by casein kinase II (CK2) regulates BRD4 function, is necessary for active transcription and is involved in resistance to BRD4 drug inhibition in triple-negative breast cancer. Here, we provide the first biophysical analysis of BRD4 phospho-regulation. Using integrative structural biology, we show that phosphorylation by CK2 modulates the dimerization of human BRD4. We identify two conserved regions, a coiled-coil motif and the Basic-residue enriched Interaction Domain (BID), essential for the BRD4 structural rearrangement, which we term the phosphorylation-dependent dimerization domain (PDD). Finally, we demonstrate that bivalent inhibitors induce a conformational change within BRD4 dimers in vitro and in cancer cells. Our results enable the proposal of a model for BRD4 activation critical for the characterization of its protein-protein interaction network and for the development of more specific therapeutics.

RNA sequencing identified novel target genes for Adansonia digitata in breast and colon cancer cells

Adansonia digitata exhibits numerous beneficial effects. In the current study, we investigated the anti-cancer effects of four different extracts of A. digitata (polar and non-polar extracts of fruit powder and fibers) on the proliferation of human colon cancer (HCT116), human breast cancer (MCF-7), and human ovarian cancer (OVCAR-3 and OVCAR-4) cell lines. RNA sequencing revealed the influence of the effective A. digitata fraction on the gene expression profiles of responsive cells. The results indicated that only the polar extract of the A. digitata fibers exhibited anti-proliferative activities against HCT116 and MCF-7 cells, but not ovarian cancer cells. Moreover, the polar extract of the fibers resulted in the modulation of the expression of multiple genes in HCT116 and MCF-7 cells. We propose that casein kinase 2 alpha 3 (CSNK2A3) is a novel casein kinase 2 (CSNK2) isoform in HCT116 cells and report, for the first time, the potential involvement of FYVE, RhoGEF, and PH domain-containing 3 (FGD3) in colon cancer. Together, these findings provide evidence supporting the anti-cancer potential of the polar extract of A. digitata fibers in this experimental model of breast and colon cancers.

Deciphering the nexus between the tumor immune microenvironment and DNA methylation in subgrouping estrogen receptor-positive breast cancer

BACKGROUND

Based on variable DNA methylation (DNAm), estrogen receptor (ER)-positive breast cancer (BRCA) is composed of two major subtypes, with the hypomethylated subgroup displaying good survival. Evidence indicates that the tumor microenvironment (TME) plays an important role in tumor progression and metastasis; however, its role and biological characteristics in DNAm-based subtypes of ER-positive BRCA remain largely unknown.

METHODS

Transcriptome data and matched clinical information of BRCA were downloaded from the Cancer Genome Atlas. Immune (ISs) and stromal scores (SSs) of BRCA patients were calculated using the ESTIMATE algorithm. Inferred fractions of 22 types of infiltrating immune cells of BRCA were collected from the Cancer Immunome Atlas.

RESULTS

The hypomethylated ER-positive BRCA subtype displayed high ISs, echoing the finding that higher ISs are associated with good BRCA survival. In addition, we analyzed the differentially expressed genes between the hypo-high-IS and hyper-low-IS BRCA subtypes in ER-positive patients and identified a co-expressed gene module (i.e., red module) enriched in immune-related biological processes (e.g., leukocyte activation involved in immune response). Moreover, four hub genes (i.e., PLEK, CD53, EVI2B, and CD4) in this module showed significant association between their expression and ER-positive BRCA survival.

CONCLUSIONS

We found differences in the tumor immune microenvironment (TIME) between DNAm-based BRCA subgroups in ER-positive patients and identified a specific module and hub genes involved to these differences. These findings elucidate the immunological basis for ER-positive BRCA progression and classification and provide potential gene biomarkers and targets for ER-positive BRCA diagnosis and treatment.

New immunological potential markers for triple negative breast cancer: IL18R1, CD53, TRIM, Jaw1, LTB, PTPRCAP

Breast cancer (BC) is the second leading cause of cancer death in women worldwide, and settings of specific prognostic factors and efficacious therapies are made difficult by phenotypic heterogeneity of BC subtypes. Therefore, there is a current urgent need to define novel predictive genetic predictors that may be useful for stratifying patients with distinct prognostic outcomes. Here, we looked for novel molecular signatures for triple negative breast cancers (TNBCs). By a bioinformatic approach, we identified a panel of genes, whose expression was positively correlated with disease-free survival in TNBC patients, namely IL18R1, CD53, TRIM, Jaw1, LTB, and PTPRCAP, showing specific immune expression profiles linked to survival prediction; most of these genes are indeed expressed in immune cells and are required for productive lymphocyte activation. According to our hypothesis, these genes were not, or poorly, expressed in different TNBC cell lines, derived from either primary breast tumours or metastatic pleural effusions. This conclusion was further supported in vivo, as immuno-histochemical analysis on biopsies of TNBC invasive ductal carcinomas highlighted differential expression of these six genes in cancer cells, as well as in intra- and peri-tumoral infiltrating lymphocytes. Our data open to the possibility that inter-tumour heterogeneity of immune markers might have predictive value; further investigations are recommended in order to establish the real power of cancer-related immune profiles as prognostic factors.

High nuclear TPX2 expression correlates with TP53 mutation and poor clinical behavior in a large breast cancer cohort, but is not an independent predictor of chromosomal instability

BACKGROUND

Targeting Protein for Xenopus Kinesin Like Protein 2 (TPX2) is a microtubule associated protein that functions in mitotic spindle assembly. TPX2 also localizes to the nucleus where it functions in DNA damage repair during S-phase. We and others have previously shown that TPX2 RNA levels are strongly associated with chromosomal instability (CIN) in breast and other cancers, and TPX2 RNA levels have been demonstrated to correlate with aggressive behavior and poor clinical outcome across a range of solid malignancies, including breast cancer.

METHODS

We perform TPX2 IHC on a cohort of 253 primary breast cancers and adopt a clinically amenable scoring system to separate tumors into low, intermediate, or high TPX2 expression. We then correlate TPX2 expression against diverse pathologic parameters and important measures of clinical outcome, including disease-specific and overall survival. We link TPX2 expression to TP53 mutation and evaluate whether TPX2 is an independent predictor of chromosomal instability (CIN).

RESULTS

We find that TPX2 nuclear expression strongly correlates with high grade morphology, elevated clinical stage, negative ER and PR status, and both disease-specific and overall survival. We also show that increased TPX2 nuclear expression correlates with elevated ploidy, supernumerary centrosomes, and TP53 mutation. TPX2 nuclear expression correlates with CIN via univariate analyses but is not independently predictive when compared to ploidy, Ki67, TP53 mutational status, centrosome number, and patient age.

CONCLUSIONS

Our findings demonstrate a strong correlation between TPX2 nuclear expression and aggressive tumor behavior, and show that TPX2 overexpression frequently occurs in the setting of TP53 mutation and elevated ploidy. However, TPX2 expression is not an independent predictor of CIN where it fails to outperform existing clinical and pathologic metrics.

Investigation of miRNA and mRNA Co-expression Network in Ependymoma

Ependymoma (EPN) is a rare primary tumor of the central nervous system (CNS) that affects both children and adults. Despite the definition and classification of distinct molecular subgroups, there remains a group of EPNs with a balanced genome, which makes it difficult to predict a prognosis of patients with EPN. The role of miRNA-mRNA network on EPN is still poorly understood. We assessed the involvement of miRNA-mRNA pairs in EPN by applying a weighted co-expression network analysis (WGCNA) approach. Using whole genome expression profile analysis followed by functional enrichment, we detected hub genes involved in active proliferation and DNA replication of nerve cells. Key genes including CYP11B1, KRT33B, RUNX1T1, SIK1, MAP3K4, MLANA, and SFRP5 identified in co-expression networks were regulated by miR-15a and miR-24-1. These seven miRNA-mRNA pairs were considered to influence not only pathways in cancer and tumor suppression process, but also MAPK, NF-kappaB, and WNT signaling pathways which were associated with tumorigenesis and development. This study provides a novel insight into potential diagnostic biomarkers of EPN and may have value in choosing therapeutic targets with clinical utility.

MYC Dysregulates Mitosis, Revealing Cancer Vulnerabilities

Tumors that overexpress the MYC oncogene are frequently aneuploid, a state associated with highly aggressive cancers and tumor evolution. However, how MYC causes aneuploidy is not well understood. Here, we show that MYC overexpression induces mitotic spindle assembly defects and chromosomal instability (CIN) through effects on microtubule nucleation and organization. Attenuating MYC expression reverses mitotic defects, even in established tumor cell lines, indicating an ongoing role for MYC in CIN. MYC reprograms mitotic gene expression, and we identify TPX2 to be permissive for spindle assembly in MYC-high cells. TPX2 depletion blocks mitotic progression, induces cell death, and prevents tumor growth. Further elevating TPX2 expression reduces mitotic defects in MYC-high cells. MYC and TPX2 expression may be useful biomarkers to stratify patients for anti-mitotic therapies. Our studies implicate MYC as a regulator of mitosis and suggest that blocking MYC activity can attenuate the emergence of CIN and tumor evolution.

Discovering Rare Genes Contributing to Cancer Stemness and Invasive Potential by GBM Single-Cell Transcriptional Analysis

Single-cell RNA sequencing presents the sophisticated delineation of cell transcriptomes in many cancer types and highlights the tumor heterogeneity at higher resolution, which provides a new chance to explore the molecular mechanism in a minority of cells. In this study, we utilized publicly available single-cell RNA-seq data to discover and comprehensively dissect rare genes existing in few glioblastoma (GBM) cells. Moreover, we designed a framework to systematically identify 51 rare protein-coding genes (PCGs) and 47 rare long non-coding RNAs (lncRNAs) in GBM. Patients with high expression levels of rare genes like CYB5R2 and TPPP3 had worse overall survival and disease-free survival, implying their potential implication in GBM progression and prognosis. We found that these rare genes tended to be specifically expressed in GBM cancer stem cells, which emphasized their ability to characterize stem-like cancer cells and implied their contribution to GBM growth. Furthermore, rare genes were enriched in a 17-cell subset, which was located in an individual branch of the pseudotime trajectory of cancer progression and exhibited high cell cycle activity and invasive potential. Our study captures the rare genes highly expressed in few cells, deepens our understanding of special states during GBM tumorigenesis and progression such as cancer stemness and invasion, and proposes potential targets for cancer therapy.

CEP55 promotes the proliferation, migration and invasion of esophageal squamous cell carcinoma via the PI3K/Akt pathway

Background

Centrosomal protein 55 (CEP55) is an important prognostic biomarker that plays an essential role in the proliferation, migration and invasion of multiple tumors. We aimed to investigate the prognostic value of CEP55 in pN0 esophageal squamous cell carcinoma (ESCC) and explore its biological function in ESCC cells.

Methods

We used immunohistochemistry and Western blot analysis to detect the expression of CEP55 in ESCC. Furthermore, both in vitro and in vivo assays were used to determine the effect of CEP55 on malignant behavior in ESCC cells.

Results

As expected, we found that CEP55 was overexpressed in ESCC. Univariate and multivariate analyses demonstrated that patients with CEP55 overexpression had a poor prognosis. Additionally, the abilities of proliferation, migration and invasion of cells, as well as the epithelial–mesenchymal transition markers, were all altered with the changed CEP55 expression levels in ESCC cells. Further study elucidated that CEP55 facilitated ESCC via the PI3K/Akt pathway. Blockade of this pathway markedly attenuated CEP55-mediated proliferation, migration, invasion and epithelial–mesenchymal transition of ESCC cells.

Conclusion

Oncogenic CEP55 correlates with a poor prognosis by regulating tumor cell proliferation, migration and invasion via the PI3K/Akt pathway. It can serve as a promising prognostic biomarker and therapeutic target of pN0 ESCC after Ivor-Lewis esophagectomy.

An integrative functional genomics framework for effective identification of novel regulatory variants in genome-phenome studies

BACKGROUND

Genome-phenome studies have identified thousands of variants that are statistically associated with disease or traits; however, their functional roles are largely unclear. A comprehensive investigation of regulatory mechanisms and the gene regulatory networks between phenome-wide association study (PheWAS) and genome-wide association study (GWAS) is needed to identify novel regulatory variants contributing to risk for human diseases.

METHODS

In this study, we developed an integrative functional genomics framework that maps 215,107 significant single nucleotide polymorphism (SNP) traits generated from the PheWAS Catalog and 28,870 genome-wide significant SNP traits collected from the GWAS Catalog into a global human genome regulatory map via incorporating various functional annotation data, including transcription factor (TF)-based motifs, promoters, enhancers, and expression quantitative trait loci (eQTLs) generated from four major functional genomics databases: FANTOM5, ENCODE, NIH Roadmap, and Genotype-Tissue Expression (GTEx). In addition, we performed a tissue-specific regulatory circuit analysis through the integration of the identified regulatory variants and tissue-specific gene expression profiles in 7051 samples across 32 tissues from GTEx.

RESULTS

We found that the disease-associated loci in both the PheWAS and GWAS Catalogs were significantly enriched with functional SNPs. The integration of functional annotations significantly improved the power of detecting novel associations in PheWAS, through which we found a number of functional associations with strong regulatory evidence in the PheWAS Catalog. Finally, we constructed tissue-specific regulatory circuits for several complex traits: mental diseases, autoimmune diseases, and cancer, via exploring tissue-specific TF-promoter/enhancer-target gene interaction networks. We uncovered several promising tissue-specific regulatory TFs or genes for Alzheimer's disease (e.g. ZIC1 and STX1B) and asthma (e.g. CSF3 and IL1RL1).

CONCLUSIONS

This study offers powerful tools for exploring the functional consequences of variants generated from genome-phenome association studies in terms of their mechanisms on affecting multiple complex diseases and traits.

Mitochondrial Haplotype Alters Mammary Cancer Tumorigenicity and Metastasis in an Oncogenic Driver-Dependent Manner

Using a novel mouse model, a mitochondrial-nuclear exchange model termed MNX, we tested the hypothesis that inherited mitochondrial haplotypes alter primary tumor latency and metastatic efficiency. Male FVB/N-Tg(MMTVneu)202Mul/J (Her2) transgenic mice were bred to female MNX mice having FVB/NJ nuclear DNA with either FVB/NJ, C57BL/6J, or BALB/cJ mtDNA. Pups receiving the C57BL/6J or BALB/cJ mitochondrial genome (i.e., females crossed with Her2 males) showed significantly (P < 0.001) longer tumor latency (262 vs. 293 vs. 225 days), fewer pulmonary metastases (5 vs. 7 vs. 15), and differences in size of lung metastases (1.2 vs. 1.4 vs. 1.0 mm diameter) compared with FVB/NJ mtDNA. Although polyoma virus middle T-driven tumors showed altered primary and metastatic profiles in previous studies, depending upon nuclear and mtDNA haplotype, the magnitude and direction of changes were not the same in the HER2-driven mammary carcinomas. Collectively, these results establish mitochondrial polymorphisms as quantitative trait loci in mammary carcinogenesis, and they implicate distinct interactions between tumor drivers and mitochondria as critical modifiers of tumorigenicity and metastasis. Cancer Res; 77(24); 6941-9. ©2017 AACR.

The Short Isoform of BRD4 Promotes HIV-1 Latency by Engaging Repressive SWI/SNF Chromatin-Remodeling Complexes

BET proteins commonly activate cellular gene expression, yet inhibiting their recruitment paradoxically reactivates latent HIV-1 transcription. Here we identify the short isoform of BET family member BRD4 (BRD4S) as a corepressor of HIV-1 transcription. We found that BRD4S was enriched in chromatin fractions of latently infected T cells, and it was more rapidly displaced from chromatin upon BET inhibition than the long isoform. BET inhibition induced marked nucleosome remodeling at the latent HIV-1 promoter, which was dependent on the activity of BRG1-associated factors (BAF), an SWI/SNF chromatin-remodeling complex with known repressive functions in HIV-1 transcription. BRD4S directly bound BRG1, a catalytic subunit of BAF, via its bromodomain and extraterminal (ET) domain, and this isoform was necessary for BRG1 recruitment to latent HIV-1 chromatin. Using chromatin immunoprecipitation sequencing (ChIP-seq) combined with assay for transposase-accessible chromatin coupled to high-throughput sequencing (ATAC-seq) data, we found that the latent HIV-1 promoter phenotypically resembles endogenous long terminal repeat (LTR) sequences, pointing to a select role of BRD4S-BRG1 complexes in genomic silencing of invasive retroelements.

RNA-Seq based genome-wide analysis reveals loss of inter-chromosomal regulation in breast cancer

Breast cancer is a complex heterogeneous disease. Common hallmark features of cancer can be found. Their origin may be traced back to their intricate relationships governing regulatory programs during the development of this disease. To unveil distinctive features of the transcriptional regulation program in breast cancer, a pipeline for RNA-seq analysis in 780 breast cancer and 101 healthy breast samples, at gene expression and network level, was implemented. Inter-chromosomal relationships between genes resulted strikingly scarce in a cancer network, in comparison to its healthy counterpart. We suggest that inter-chromosomal regulation loss may be a novel feature in breast cancer. Additional evidence was obtained by independent validation in microarray and Hi-C data as well as supplementary computational analyses. Functional analysis showed upregulation in processes related to cell cycle and division; while migration, adhesion and cell-to-cell communication, were downregulated. Both the BRCA1 DNA repairing signalling and the Estrogen-mediated G1/S phase entry pathways were found upregulated. In addition, a synergistic underexpression of the γ-protocadherin complex, located at Chr5q31 is also shown. This region has previously been reported to be hypermethylated in breast cancer. These findings altogether provide further evidence for the central role of transcriptional regulatory programs in shaping malignant phenotypes.

Placental transcriptome co-expression analysis reveals conserved regulatory programs across gestation

BACKGROUND

Mammalian development in utero is absolutely dependent on proper placental development, which is ultimately regulated by the placental genome. The regulation of the placental genome can be directly studied by exploring the underlying organisation of the placental transcriptome through a systematic analysis of gene-wise co-expression relationships.

RESULTS

In this study, we performed a comprehensive analysis of human placental co-expression using RNA sequencing and intergrated multiple transcriptome datasets spanning human gestation. We identified modules of co-expressed genes that are preserved across human gestation, and also identifed modules conserved in the mouse indicating conserved molecular networks involved in placental development and gene expression patterns more specific to late gestation. Analysis of co-expressed gene flanking sequences indicated that conserved co-expression modules in the placenta are regulated by a core set of transcription factors, including ZNF423 and EBF1. Additionally, we identified a gene co-expression module enriched for genes implicated in the pregnancy pathology preeclampsia. By using an independnet transcriptome dataset, we show that these co-expressed genes are differentially expressed in preeclampsia.

CONCLUSIONS

This study represents a comprehensive characterisation of placental co-expression and provides insight into potential transcriptional regulators that govern conserved molecular programs fundamental to placental development.

Resources for Systems Genetics

A key characteristic of systems genetics is its reliance on populations that vary to a greater or lesser degree in genetic complexity-from highly admixed populations such as the Collaborative Cross and Diversity Outcross to relatively simple crosses such as sets of consomic strains and reduced complexity crosses. This protocol is intended to help investigators make more informed decisions about choices of resources given different types of questions. We consider factors such as costs, availability, and ease of breeding for common scenarios. In general, we recommend using complementary resources and minimizing depth of resampling of any given genome or strain.

Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering

Identifying latent structure in high-dimensional genomic data is essential for exploring biological processes. Here, we consider recovering gene co-expression networks from gene expression data, where each network encodes relationships between genes that are co-regulated by shared biological mechanisms. To do this, we develop a Bayesian statistical model for biclustering to infer subsets of co-regulated genes that covary in all of the samples or in only a subset of the samples. Our biclustering method, BicMix, allows overcomplete representations of the data, computational tractability, and joint modeling of unknown confounders and biological signals. Compared with related biclustering methods, BicMix recovers latent structure with higher precision across diverse simulation scenarios as compared to state-of-the-art biclustering methods. Further, we develop a principled method to recover context specific gene co-expression networks from the estimated sparse biclustering matrices. We apply BicMix to breast cancer gene expression data and to gene expression data from a cardiovascular study cohort, and we recover gene co-expression networks that are differential across ER+ and ER- samples and across male and female samples. We apply BicMix to the Genotype-Tissue Expression (GTEx) pilot data, and we find tissue specific gene networks. We validate these findings by using our tissue specific networks to identify trans-eQTLs specific to one of four primary tissues.

An Integrated Genome-Wide Systems Genetics Screen for Breast Cancer Metastasis Susceptibility Genes

Metastasis remains the primary cause of patient morbidity and mortality in solid tumors and is due to the action of a large number of tumor-autonomous and non-autonomous factors. Here we report the results of a genome-wide integrated strategy to identify novel metastasis susceptibility candidate genes and molecular pathways in breast cancer metastasis. This analysis implicates a number of transcriptional regulators and suggests cell-mediated immunity is an important determinant. Moreover, the analysis identified novel or FDA-approved drugs as potentially useful for anti-metastatic therapy. Further explorations implementing this strategy may therefore provide a variety of information for clinical applications in the control and treatment of advanced neoplastic disease.

Metastasis, the spread and growth of tumor cells from the original tumor to secondary sites throughout the body, is the primary cause of cancer-related death for most solid tumor types. The process of metastasis is very complex, requiring multiple individual steps and the cooperation of different cell types during the dissemination and proliferation steps. Many genes are involved in this process, but at present few have been identified and characterized. In this study, we have integrated multiple genome-wide analysis methods to try to identify large numbers of candidate metastasis-associated genes and pathways based on a highly metastatic mouse model. Using this strategy, we have identified a number of genes that predict outcome of human breast cancer. These genes implicate specific molecular and cellular pathways in the metastatic process that might be used to intervene in the process. Furthermore, this integrated analysis implicates pre-existing drugs that might be re-purposed to help prevent or reduce metastatic burden in patients. The combined results obtained from this analytical strategy therefore provide an important platform for further genome-wide analysis into the etiology of metastatic disease.

Taking Bioinformatics to Systems Medicine

Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.

Derivation of a fifteen gene prognostic panel for six cancers

The hallmarks of cancer deem biological pathways and molecules to be conserved. This approach may be useful for deriving a prognostic gene signature. Weighted Gene Co-expression Network Analysis of gene expression datasets in eleven cancer types identified modules of highly correlated genes and interactive networks conserved across glioblastoma, breast, ovary, colon, rectal and lung cancers, from which a universal classifier for tumor stratification was extracted. Specific conserved gene modules were validated across different microarray platforms and datasets. Strikingly, preserved genes within these modules defined regulatory networks associated with immune regulation, cell differentiation, metastases, cell migration, metastases, oncogenic transformation, and resistance to apoptosis and senescence, with AIF1 and PRRX1 being suggested to be master regulators governing these biological processes. A universal classifier from these conserved networks enabled execution of common set of principles across different cancers that revealed distinct, differential correlation of biological functions with patient survival in a cancer-specific manner. Correlation analysis further identified a panel of 15 risk genes with potential prognostic value, termed as the GBOCRL-IIPr panel [(GBM-Breast-Ovary-Colon-Rectal-Lung)–Immune–Invasion–Prognosis], that surprisingly, were not amongst the master regulators or important network hubs. This panel may now be integrated in predicting patient outcomes in the six cancers.

Beyond cytokinesis: the emerging roles of CEP55 in tumorigenesis

CEP55 was initially identified as a pivotal component of abscission, the final stage of cytokinesis, serving to regulate the physical separation of two daughter cells. Over the past 10 years, several studies have illuminated additional roles for CEP55 including regulating the PI3K/AKT pathway and midbody fate. Concurrently, CEP55 has been studied in the context of cancers including those of the breast, lung, colon and liver. CEP55 overexpression has been found to significantly correlate with tumor stage, aggressiveness, metastasis and poor prognosis across multiple tumor types and therefore has been included as part of several prognostic 'gene signatures' for cancer. Here by discussing in depth the functions of CEP55 across different effector pathways, and also its roles as a biomarker and driver of tumorigenesis, we assemble an exhaustive review, thus commemorating a decade of research on CEP55.

Functional analysis of prognostic gene expression network genes in metastatic breast cancer models

Identification of conserved co-expression networks is a useful tool for clustering groups of genes enriched for common molecular or cellular functions [1]. The relative importance of genes within networks can frequently be inferred by the degree of connectivity, with those displaying high connectivity being significantly more likely to be associated with specific molecular functions [2]. Previously we utilized cross-species network analysis to identify two network modules that were significantly associated with distant metastasis free survival in breast cancer. Here, we validate one of the highly connected genes as a metastasis associated gene. Tpx2, the most highly connected gene within a proliferation network specifically prognostic for estrogen receptor positive (ER+) breast cancers, enhances metastatic disease, but in a tumor autonomous, proliferation-independent manner. Histologic analysis suggests instead that variation of TPX2 levels within disseminated tumor cells may influence the transition between dormant to actively proliferating cells in the secondary site. These results support the co-expression network approach for identification of new metastasis-associated genes to provide new information regarding the etiology of breast cancer progression and metastatic disease.

TPX2: of spindle assembly, DNA damage response, and cancer

For more than 15 years, TPX2 has been studied as a factor critical for mitosis and spindle assembly. These functions of TPX2 are attributed to its Ran-regulated microtubule-associated protein properties and to its control of the Aurora A kinase. Overexpressed in cancers, TPX2 is being established as marker for the diagnosis and prognosis of malignancies. During interphase, TPX2 resides preferentially in the nucleus where its function had remained elusive until recently. The latest finding that TPX2 plays a role in amplification of the DNA damage response, combined with the characterization of TPX2 knockout mice, open new perspectives to understand the biology of this protein. This review provides an historic overview of the discovery of TPX2 and summarizes its cytoskeletal and signaling roles with relevance to cancer therapies. Finally, the review aims to reconcile discrepancies between the experimental and pathological effects of TPX2 overexpression and advances new roles for compartmentalized TPX2.

A genomic analysis of mouse models of breast cancer reveals molecular features of mouse models and relationships to human breast cancer

INTRODUCTION

Genomic variability limits the efficacy of breast cancer therapy. To simplify the study of the molecular complexity of breast cancer, researchers have used mouse mammary tumor models. However, the degree to which mouse models model human breast cancer and are reflective of the human heterogeneity has yet to be demonstrated with gene expression studies on a large scale.

METHODS

To this end, we have built a database consisting of 1,172 mouse mammary tumor samples from 26 different major oncogenic mouse mammary tumor models.

RESULTS

In this dataset we identified heterogeneity within mouse models and noted a surprising amount of interrelatedness between models, despite differences in the tumor initiating oncogene. Making comparisons between models, we identified differentially expressed genes with alteration correlating with initiating events in each model. Using annotation tools, we identified transcription factors with a high likelihood of activity within these models. Gene signatures predicted activation of major cell signaling pathways in each model, predictions that correlated with previous genetic studies. Finally, we noted relationships between mouse models and human breast cancer at both the level of gene expression and predicted signal pathway activity. Importantly, we identified individual mouse models that recapitulate human breast cancer heterogeneity at the level of gene expression.

CONCLUSIONS

This work underscores the importance of fully characterizing mouse tumor biology at molecular, histological and genomic levels before a valid comparison to human breast cancer may be drawn and provides an important bioinformatic resource.

Gene co-expression analysis identifies common modules related to prognosis and drug resistance in cancer cell lines

To discover a common gene co-expression network in cancer cell, we applied weighted gene co-expression network analysis to transcriptional profiles of 917 cancer cell lines. Fourteen biologically meaningful modules were identified, including cytoskeleton, cell cycle, RNA splicing, signaling pathway, transcription, translation and others. These modules were robust in an independent human cancer microarray dataset. Furthermore, we collected 11 independent cancer microarray datasets, and correlated these modules with clinical outcome. Most of these modules could predict patient survival in one or more cancer types. Some modules were predictive of relapse, metastasis and drug resistance. Novel regulatory mechanisms were also implicated. In summary, our findings, for the first time, provide a modular map for cancer cell lines, new targets for therapy and modules for regulatory mechanism of cancer development and drug resistance.

Microtubule-dependent regulation of mitotic protein degradation

Accurate cell division depends on tightly regulated ubiquitylation events catalyzed by the anaphase-promoting complex (APC/C). Among its many substrates, the APC/C triggers the degradation of proteins that stabilize the mitotic spindle, and loss or accumulation of such spindle assembly factors can result in aneuploidy and cancer. Although critical for cell division, it has remained poorly understood how the timing of spindle assembly factor degradation is established during mitosis. Here, we report that active spindle assembly factors are protected from APC/C-dependent degradation by microtubules. In contrast, those molecules that are not bound to microtubules are highly susceptible to proteolysis and turned over immediately after APC/C activation. The correct timing of spindle assembly factor degradation, as achieved by this regulatory circuit, is required for accurate spindle structure and function. We propose that the localized stabilization of APC/C substrates provides a mechanism for the selective disposal of cell-cycle regulators that have fulfilled their mitotic roles.

Genetic variation in the major mitotic checkpoint genes and risk of breast cancer: a multigenic study on cancer susceptibility

The mitotic checkpoint system is a mechanism essential for maintaining genomic stability and defects which have been linked to cancer development. We conducted this hospital-based case-control study to investigate whether genetic variants in three major spindle checkpoint genes (BUB3, MAD2L1, and BUB1) had any bearing on an individual risk of breast cancer (BC). A total of 462 incident BC patients and 529 cancer-free controls were enrolled in this study. Results showed that neither variants in BUB3 nor variants in MAD2L1 caused any significant effect on the risk of BC. However, the variant rs12623473 in BUB1 was significantly associated with increased BC risk with the odds ratio (OR) of 1.30 (95 % confidence interval (CI) 1.03-1.64) under the allelic model. The estimated population attributable risk of one copy of the risk allele for developing BC was 10.3 %. The bioinformatics analysis suggested that this variant may regulate the transcriptional ability of BUB1.

Should EMT of Cancer Cells Be Understood as Epithelial-Myeloid Transition?

Cancer cells express epithelial markers, and when progressing in malignancy they may express markers of the mesenchymal cell type. Therefore an epithelial-mesenchymal transition of the cancer cells is assumed. However the mesenchymal markers can equally well be interpreted as myeloid markers since they are common in both types of cell lineages. Moreover, cancer cells express multiple specific markers of the myeloid lineages thus giving rise to the hypothesis that the transition of cancer cells may be from epithelial to myeloid cells and not to mesenchymal cells. This interpretation would better explain why cancer cells, often already in their primary cancer site, frequently show properties common to those of macrophages, platelets and pre-/osteoclasts.

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis.

Targeting oxidative stress in embryonal rhabdomyosarcoma

Rhabdomyosarcoma is a soft-tissue sarcoma with molecular and cellular features of developing skeletal muscle. Rhabdomyosarcoma has two major histologic subtypes, embryonal and alveolar, each with distinct clinical, molecular, and genetic features. Genomic analysis shows that embryonal tumors have more structural and copy number variations than alveolar tumors. Mutations in the RAS/NF1 pathway are significantly associated with intermediate- and high-risk embryonal rhabdomyosarcomas (ERMS). In contrast, alveolar rhabdomyosarcomas (ARMS) have fewer genetic lesions overall and no known recurrently mutated cancer consensus genes. To identify therapeutics for ERMS, we developed and characterized orthotopic xenografts of tumors that were sequenced in our study. High-throughput screening of primary cultures derived from those xenografts identified oxidative stress as a pathway of therapeutic relevance for ERMS.

Genetic background may contribute to PAM50 gene expression breast cancer subtype assignments

Recent advances in genome wide transcriptional analysis have provided greater insights into the etiology and heterogeneity of breast cancer. Molecular signatures have been developed that stratify the conventional estrogen receptor positive or negative categories into subtypes that are associated with differing clinical outcomes. It is thought that the expression patterns of the molecular subtypes primarily reflect cell-of-origin or tumor driver mutations. In this study however, using a genetically engineered mouse mammary tumor model we demonstrate that the PAM50 subtype signature of tumors driven by a common oncogenic event can be significantly influenced by the genetic background on which the tumor arises. These results have important implications for interpretation of "snapshot" expression profiles, as well as suggesting that incorporation of genetic background effects may allow investigation into phenotypes not initially anticipated in individual mouse models of cancer.

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

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

Mitotic Stress and Chromosomal Instability in Cancer: The Case for TPX2

Cell cycle deregulation is a common motif in human cancer, and multiple therapeutic strategies are aimed to prevent tumor cell proliferation. Whereas most current therapies are designed to arrest cell cycle progression either in G1/S or in mitosis, new proposals include targeting the intrinsic chromosomal instability (CIN, an increased rate of gain or losses of chromosomes during cell division) or aneuploidy (a genomic composition that differs from diploid) that many tumor cells display. Why tumors cells are chromosomally unstable or aneuploid and what are the consequences of these alterations are not completely clear at present. Several mitotic regulators are overexpressed as a consequence of oncogenic alterations, and they are likely to alter the proper regulation of chromosome segregation in cancer cells. In this review, we propose the relevance of TPX2, a mitotic regulator involved in the formation of the mitotic spindle, in oncogene-induced mitotic stress. This protein, as well as its partner Aurora-A, is frequently overexpressed in human cancer, and its deregulation may participate not only in chromosome numeric aberrations but also in other forms of genomic instability in cancer cells.

In silico discovery of mitosis regulation networks associated with early distant metastases in estrogen receptor positive breast cancers

The aim of this study was to perform comparative analysis of multiple public datasets of gene expression in order to identify common genes as potential prognostic biomarkers. Additionally, the study sought to identify biological processes and pathways that are most significantly associated with early distant metastases (<5 years) in women with estrogen receptor-positive (ER+) breast tumors. Datasets from three published studies were selected for in silico analysis of gene expression profiles of ER+ breast cancer, using time to distant metastasis as the clinical endpoint. A subset of 44 differently expressed genes (DEGs) was found common to all three studies and characterized by mitotic checkpoint genes and pathways that regulate mitotic spindle and chromosome dynamics. DEG promoter regions were enriched with NFY binding sites. Analysis of miRNA target sites identified significant enrichment of miR-192, miR-193B, and miR-16-1 targets. Aberrant mitotic regulation could drive increased genomic instability leading to a progression towards an early onset metastatic phenotype. The relative importance of mitotic instability may reflect the clinical utility of mitotic poisons in metastatic breast cancer, including poisons such as the taxanes, epothilones, and vinca alkaloids.

Chromosomal gain promotes formation of a steep RanGTP gradient that drives mitosis in aneuploid cells

The chromosome-centered RanGTP gradient, which is strongly reduced in slow-growing normal cells, is amplified by chromosomal gain and is required for mitosis in rapidly growing aneuploid cells.

Many mitotic factors were shown to be activated by Ran guanosine triphosphatase. Previous studies in Xenopus laevis egg extracts and in highly proliferative cells showed that mitotic chromosomes were surrounded by steep Ran guanosine triphosphate (GTP) concentration gradients, indicating that RanGTP-activated factors promote spindle assembly around chromosomes. However, the mitotic role of Ran in normal differentiated cells is not known. In this paper, we show that although the steep mitotic RanGTP gradients were present in rapidly growing cell lines and were required for chromosome congression in mitotic HeLa cells, the gradients were strongly reduced in slow-growing primary cells, such as HFF-1 fibroblasts. The overexpression of RCC1, the guanine nucleotide exchange factor for Ran, induced steeper mitotic RanGTP gradients in HFF-1 cells, showing the critical role of RCC1 levels in the regulation of mitosis by Ran. Remarkably, in vitro fusion of HFF-1 cells produced cells with steep mitotic RanGTP gradients comparable to HeLa cells, indicating that chromosomal gain can promote mitosis in aneuploid cancer cells via Ran.

Allelic variation and differential expression of the mSIN3A histone deacetylase complex gene Arid4b promote mammary tumor growth and metastasis

Accumulating evidence suggests that breast cancer metastatic progression is modified by germline polymorphism, although specific modifier genes have remained largely undefined. In the current study, we employ the MMTV-PyMT transgenic mouse model and the AKXD panel of recombinant inbred mice to identify AT-rich interactive domain 4B (Arid4b; NM_194262) as a breast cancer progression modifier gene. Ectopic expression of Arid4b promoted primary tumor growth in vivo as well as increased migration and invasion in vitro, and the phenotype was associated with polymorphisms identified between the AKR/J and DBA/2J alleles as predicted by our genetic analyses. Stable shRNA-mediated knockdown of Arid4b caused a significant reduction in pulmonary metastases, validating a role for Arid4b as a metastasis modifier gene. ARID4B physically interacts with the breast cancer metastasis suppressor BRMS1, and we detected differential binding of the Arid4b alleles to histone deacetylase complex members mSIN3A and mSDS3, suggesting that the mechanism of Arid4b action likely involves interactions with chromatin modifying complexes. Downregulation of the conserved Tpx2 gene network, which is comprised of many factors regulating cell cycle and mitotic spindle biology, was observed concomitant with loss of metastatic efficiency in Arid4b knockdown cells. Consistent with our genetic analysis and in vivo experiments in our mouse model system, ARID4B expression was also an independent predictor of distant metastasis-free survival in breast cancer patients with ER+ tumors. These studies support a causative role of ARID4B in metastatic progression of breast cancer.