ZNF282 (Zinc finger protein 282), a novel E2F1 co-activator, promotes esophageal squamous cell carcinoma

A Transcription Factor ZNF384, Regulated by LINC00265, Activates the Expression of IFI30 to Stimulate Malignant Progression in Glioma

Glioma remains one of the most challenging primary brain malignancies to treat. Long noncoding RNAs (lncRNAs) and mRNAs (mRNAs) are implicated in regulating the malignant phenotypes of cancers including glioma. This study aimed to elucidate the functions and mechanisms of lncRNA LINC00265 and mRNA IFI30 in the pathogenesis of glioma. Quantitative real-time polymerase chain reaction (RT-qPCR) analysis revealed the upregulated expression of LINC00265 and IFI30 in glioma cells compared to normal human astrocytes. Western blot (WB) quantified the associated proteins. Glioma stemness and epithelial-to-mesenchymal transition (EMT) were assessed by aldehyde dehydrogenase 1 (ALDH1) activity, sphere formation, and WB. Mechanistic and rescue assays evaluated the LINC00265/miR-let-7d-5p/IFI30/ZNF384/IGF2BP2 axis. The results demonstrated that LINC00265 and IFI30 were highly expressed in glioma cells, promoting stemness and EMT. ZNF384 was identified as a transcription factor that upregulates IFI30. Moreover, LINC00265 elevated ZNF384 by sponging miR-let-7d-5p and recruiting IGF2BP2. In conclusion, LINC00265 and IFI30 act as oncogenes in glioma by driving stemness and EMT, underscoring their potential as therapeutic targets.

Transcriptional co-activators: emerging roles in signaling pathways and potential therapeutic targets for diseases

Specific cell states in metazoans are established by the symphony of gene expression programs that necessitate intricate synergic interactions between transcription factors and the co-activators. Deregulation of these regulatory molecules is associated with cell state transitions, which in turn is accountable for diverse maladies, including developmental disorders, metabolic disorders, and most significantly, cancer. A decade back most transcription factors, the key enablers of disease development, were historically viewed as 'undruggable'; however, in the intervening years, a wealth of literature validated that they can be targeted indirectly through transcriptional co-activators, their confederates in various physiological and molecular processes. These co-activators, along with transcription factors, have the ability to initiate and modulate transcription of diverse genes necessary for normal physiological functions, whereby, deregulation of such interactions may foster tissue-specific disease phenotype. Hence, it is essential to analyze how these co-activators modulate specific multilateral processes in coordination with other factors. The proposed review attempts to elaborate an in-depth account of the transcription co-activators, their involvement in transcription regulation, and context-specific contributions to pathophysiological conditions. This review also addresses an issue that has not been dealt with in a comprehensive manner and hopes to direct attention towards future research that will encompass patient-friendly therapeutic strategies, where drugs targeting co-activators will have enhanced benefits and reduced side effects. Additional insights into currently available therapeutic interventions and the associated constraints will eventually reveal multitudes of advanced therapeutic targets aiming for disease amelioration and good patient prognosis.

Take a walk on the KRAB side

Canonical Krüppel-associated box (KRAB)-containing zinc finger proteins (KZFPs) act as major repressors of transposable elements (TEs) via the KRAB-mediated recruitment of the heterochromatin scaffold KRAB-associated protein (KAP)1. KZFP genes emerged some 420 million years ago in the last common ancestor of coelacanth, lungfish, and tetrapods, and dramatically expanded to give rise to lineage-specific repertoires in contemporary species paralleling their TE load and turnover. However, the KRAB domain displays sequence and function variations that reveal repeated diversions from a linear TE-KZFP trajectory. This Review summarizes current knowledge on the evolution of KZFPs and discusses how ancestral noncanonical KZFPs endowed with variant KRAB, SCAN or DUF3669 domains have been utilized to achieve KAP1-independent functions.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

Metagenomic and single-cell RNA-Seq survey of the Helicobacter pylori-infected stomach in asymptomatic individuals

Helicobacter pylori colonization of the gastric niche can persist for years in asymptomatic individuals. To deeply characterize the host-microbiota environment in H. pylori-infected (HPI) stomachs, we collected human gastric tissues and performed metagenomic sequencing, single-cell RNA-Seq (scRNA-Seq), flow cytometry, and fluorescent microscopy. HPI asymptomatic individuals had dramatic changes in the composition of gastric microbiome and immune cells compared with noninfected individuals. Metagenomic analysis uncovered pathway alterations related to metabolism and immune response. scRNA-Seq and flow cytometry data revealed that, in contrast to murine stomachs, ILC2s are virtually absent in the human gastric mucosa, whereas ILC3s are the dominant population. Specifically, proportion of NKp44+ ILC3s out of total ILCs were highly increased in the gastric mucosa of asymptomatic HPI individuals, and correlated with the abundance of selected microbial taxa. In addition, CD11c+ myeloid cells and activated CD4+ T cells and B cells were expanded in HPI individuals. B cells of HPI individuals acquired an activated phenotype and progressed into a highly proliferating germinal-center stage and plasmablast maturation, which correlated with the presence of tertiary lymphoid structures within the gastric lamina propria. Our study provides a comprehensive atlas of the gastric mucosa-associated microbiome and immune cell landscape when comparing asymptomatic HPI and uninfected individuals.

Neighborhood characteristics and breast tumor methylation: using epigenomics to explore cancer outcome disparities

BACKGROUND

Social exposures may drive epigenetic alterations that affect racial disparities in breast cancer outcomes. This study examined the association between neighborhood-level factors and DNA methylation in non-Hispanic Black and White women diagnosed with breast cancer.

METHODS

Genome-wide DNA methylation was measured using the EPIC array in the tumor tissue of 96 women. Linear regression models were used to examine the association between nine neighborhood-level factors and methylation, regressing β values for each cytosine-phosphate guanine dinucleotide (CpG) site on neighborhood-level factors while adjusting for covariates. Neighborhood data were obtained from the Opportunity Atlas. We used a false discovery rate (FDR) threshold < 0.05, and for CpGs below this threshold, we examined interactions with race. We employed multivariable Cox proportional-hazards models to estimate whether aberrant methylation was associated with all-cause mortality.

RESULTS

26 of the CpG sites were associated with job density or college education (FDR < 0.05). Further exploration of these 26 CpG sites revealed no interactions by race, but a single probe in TMEM204 was associated with all-cause mortality.

CONCLUSION

We identified novel associations between neighborhood-level factors and the breast tumor DNA methylome. Our data are the first to show that dysregulation in neighborhood associated CpG sites may be associated with all-cause mortality. Neighborhood-level factors may contribute to differential tumor methylation in genes related to tumor progression and metastasis. This contributes to the increasing body of evidence that area-level factors (such as neighborhood characteristics) may play an important role in cancer disparities through modulation of the breast tumor epigenome.

Identifying Methylation Pattern and Genes Associated with Breast Cancer Subtypes

Breast cancer is regarded worldwide as a severe human disease. Various genetic variations, including hereditary and somatic mutations, contribute to the initiation and progression of this disease. The diagnostic parameters of breast cancer are not limited to the conventional protein content and can include newly discovered genetic variants and even genetic modification patterns such as methylation and microRNA. In addition, breast cancer detection extends to detailed breast cancer stratifications to provide subtype-specific indications for further personalized treatment. One genome-wide expression–methylation quantitative trait loci analysis confirmed that different breast cancer subtypes have various methylation patterns. However, recognizing clinically applied (methylation) biomarkers is difficult due to the large number of differentially methylated genes. In this study, we attempted to re-screen a small group of functional biomarkers for the identification and distinction of different breast cancer subtypes with advanced machine learning methods. The findings may contribute to biomarker identification for different breast cancer subtypes and provide a new perspective for differential pathogenesis in breast cancer subtypes.

Drug Repositioning Inferred from E2F1-Coregulator Interactions Studies for the Prevention and Treatment of Metastatic Cancers

Metastasis management remains a long-standing challenge. High abundance of E2F1 triggers tumor progression by developing protein-protein interactions (PPI) with coregulators that enhance its potential to activate a network of prometastatic transcriptional targets.

Methods: To identify E2F1-coregulators, we integrated high-throughput Co-immunoprecipitation (IP)/mass spectometry, GST-pull-down assays, and structure modeling. Potential inhibitors of PPI discovered were found by bioinformatics-based pharmacophore modeling, and transcriptome profiling was conducted to screen for coregulated downstream targets. Expression and target gene regulation was validated using qRT-PCR, immunoblotting, chromatin IP, and luciferase assays. Finally, the impact of the E2F1-coregulator complex and its inhibiting drug on metastasis was investigated in vitro in different cancer entities and two mouse metastasis models.

Results: We unveiled that E2F1 forms coactivator complexes with metastasis-associated protein 1 (MTA1) which, in turn, is directly upregulated by E2F1. The E2F1:MTA1 complex potentiates hyaluronan synthase 2 (HAS2) expression, increases hyaluronan production and promotes cell motility. Disruption of this prometastatic E2F1:MTA1 interaction reduces hyaluronan synthesis and infiltration of tumor-associated macrophages in the tumor microenvironment, thereby suppressing metastasis. We further demonstrate that E2F1:MTA1 assembly is abrogated by small-molecule, FDA-approved drugs. Treatment of E2F1/MTA1-positive, highly aggressive, circulating melanoma cells and orthotopic pancreatic tumors with argatroban prevents metastasis and cancer relapses in vivo through perturbation of the E2F1:MTA1/HAS2 axis.

Conclusion: Our results propose argatroban as an innovative, E2F-coregulator-based, antimetastatic drug. Cancer patients with the infaust E2F1/MTA1/HAS2 signature will likely benefit from drug repositioning.

Microarray expression profile analysis of aberrant long non-coding RNAs in esophageal squamous cell carcinoma

Increasing evidence indicates that long non-coding RNA (lncRNA) plays an important role in tumorigenesis. However, the function and regulatory mechanism of lncRNAs are still unclear in esophageal squamous cell carcinoma (ESCC). To address this challenge, we screened lncRNAs expression profiles in 3 pairs of ESCC and matched non-cancerous tissues by microarray assay and identified the relationship between lncRNAs expression in ESCC tissue and clinicopathological characteristics and prognosis of patients with ESCC. We found 182 lncRNAs that were significantly differently expressed in ESCC tissues versus the matched non-cancerous tissues. Gene ontology and pathway analysis results suggested that the primary biological processes of these genes were involved in extracellular matrix, immune responses, cell differentiation and cell proliferation. Through cis and trans analyzing, we found 4 lncRNAs (ENST00000480669, NONHSAT104436, NONHSAT126998 and NONHSAT112918) may play important roles in tumorigenesis of ESCC. The four lncRNAs were checked in 73 patients with ESCC. The results showed that they mainly related to tumor metastasis. Kaplan-Meier survival analysis showed that high expression of NONHSAT104436, NONHSAT126998 and low expression of ENST00000480669 were related to poor 3-year overall survival (P=0.003, 0.032 and 0.040, respectively). Multivariate analysis showed that NONHSAT104436 was an independent prognostic factor (P=0.017). Thus we concluded that, lncRNAs showed differently expression patterns in ESCC versus matched non-cancerous tissues, and aberrantly expressed lncRNA may play important roles in ESCC development and progression. Interestingly, the overexpression of NONHSAT104436 was tightly correlated with distant metastasis and, poor survival rate, which might indicate that NONHSAT104436 might play a very important part in ESCC tumor progression.

Spotting the enemy within: Targeted silencing of foreign DNA in mammalian genomes by the Krüppel-associated box zinc finger protein family

Tandem C2H2-type zinc finger proteins (ZFPs) constitute the largest transcription factor family in animals. Tandem-ZFPs bind DNA in a sequence-specific manner through arrays of multiple zinc finger domains that allow high flexibility and specificity in target recognition. In tetrapods, a large proportion of tandem-ZFPs contain Krüppel-associated-box (KRAB) repression domains, which are able to induce epigenetic silencing through the KAP1 corepressor. The KRAB-ZFP family continuously amplified in tetrapods through segmental gene duplications, often accompanied by deletions, duplications, and mutations of the zinc finger domains. As a result, tetrapod genomes contain unique sets of KRAB-ZFP genes, consisting of ancient and recently evolved family members. Although several hundred human and mouse KRAB-ZFPs have been identified or predicted, the biological functions of most KRAB-ZFP family members have gone unexplored. Furthermore, the evolutionary forces driving the extraordinary KRAB-ZFP expansion and diversification have remained mysterious for decades. In this review, we highlight recent studies that associate KRAB-ZFPs with the repression of parasitic DNA elements in the mammalian germ line and discuss the hypothesis that the KRAB-ZFP family primarily evolved as an adaptive genomic surveillance system against foreign DNA. Finally, we comment on the computational, genetic, and biochemical challenges of studying KRAB-ZFPs and attempt to predict how these challenges may be soon overcome.