Hani Choudhry

Tumor hypoxia induces nuclear paraspeckle formation through HIF-2α dependent transcriptional activation of NEAT1 leading to cancer cell survival

Activation of cellular transcriptional responses, mediated by hypoxia-inducible factor (HIF), is common in many types of cancer, and generally confers a poor prognosis. Known to induce many hundreds of protein-coding genes, HIF has also recently been shown to be a key regulator of the non-coding transcriptional response. Here, we show that NEAT1 long non-coding RNA (lncRNA) is a direct transcriptional target of HIF in many breast cancer cell lines and in solid tumors. Unlike previously described lncRNAs, NEAT1 is regulated principally by HIF-2 rather than by HIF-1. NEAT1 is a nuclear lncRNA that is an essential structural component of paraspeckles and the hypoxic induction of NEAT1 induces paraspeckle formation in a manner that is dependent upon both NEAT1 and on HIF-2. Paraspeckles are multifunction nuclear structures that sequester transcriptionally active proteins as well as RNA transcripts that have been subjected to adenosine-to-inosine (A-to-I) editing. We show that the nuclear retention of one such transcript, F11R (also known as junctional adhesion molecule 1, JAM1), in hypoxia is dependent upon the hypoxic increase in NEAT1, thereby conferring a novel mechanism of HIF-dependent gene regulation. Induction of NEAT1 in hypoxia also leads to accelerated cellular proliferation, improved clonogenic survival and reduced apoptosis, all of which are hallmarks of increased tumorigenesis. Furthermore, in patients with breast cancer, high tumor NEAT1 expression correlates with poor survival. Taken together, these results indicate a new role for HIF transcriptional pathways in the regulation of nuclear structure and that this contributes to the pro-tumorigenic hypoxia-phenotype in breast cancer.

Extensive regulation of the non‐coding transcriptome by hypoxia: role of HIF in releasing paused RNApol2

Hypoxia is central to both ischaemic and neoplastic diseases. However, the non‐coding transcriptional response to hypoxia is largely uncharacterized. We undertook integrated genomic analyses of both non‐coding and coding transcripts using massively parallel sequencing and interfaced this data with pan‐genomic analyses of hypoxia‐inducible factor (HIF) and RNApol2 binding in hypoxic cells. These analyses revealed that all classes of RNA are profoundly regulated by hypoxia and implicated HIF as a major direct regulator of both the non‐coding and coding transcriptome, acting predominantly through release of pre‐bound promoter‐paused RNApol2. These findings indicate that the transcriptional response to hypoxia is substantially more extensive than previously considered.

The tumour hypoxia induced non-coding transcriptome.

Recent investigations have highlighted the importance of the non-coding genome in regions of hypoxia in tumours. Such regions are frequently found in solid tumours, and are associated with worse patient survival and therapy resistance. Hypoxia stabilises the transcription factors, hypoxia inducible factors (HIF1α and HIF2α) which coordinate transcriptomic changes that occur in hypoxia. The changes in gene expression induced by HIF1α and HIF2α contribute to many of the hallmarks of cancer phenotypes and enable tumour growth, survival and invasion in the hypoxic tumour microenvironment. Non-coding RNAs, in particular microRNAs (miRNAs), which regulate mRNA stability and translation, and long-non-coding RNAs (lncRNAs), which have diverse functions including chromatin modification and transcriptional regulation, are also important in enabling the key hypoxia regulated processes. They have roles in the regulation of metabolism, angiogenesis, autophagy, invasion and metastasis in the hypoxic microenvironment. Furthermore, HIF1α and HIF2α expression and stabilisation are also regulated by both miRNAs and lncRNAs. Here we review the recent developments in the expression, regulation and functions of miRNAs, lncRNAs and other non-coding RNA classes in tumour hypoxia.

Capture‐C reveals preformed chromatin interactions between HIF‐binding sites and distant promoters

Hypoxia‐inducible factor (HIF) directs an extensive transcriptional cascade that transduces numerous adaptive responses to hypoxia. Pan‐genomic analyses, using chromatin immunoprecipitation and transcript profiling, have revealed large numbers of HIF‐binding sites that are generally associated with hypoxia‐inducible transcripts, even over long chromosomal distances. However, these studies do not define the specific targets of HIF‐binding sites and do not reveal how induction of HIF affects chromatin conformation over distantly connected functional elements. To address these questions, we deployed a recently developed chromosome conformation assay that enables simultaneous high‐resolution analyses from multiple viewpoints. These assays defined specific long‐range interactions between intergenic HIF‐binding regions and one or more promoters of hypoxia‐inducible genes, revealing the existence of multiple enhancer–promoter, promoter–enhancer, and enhancer–enhancer interactions. However, neither short‐term activation of HIF by hypoxia, nor long‐term stabilization of HIF in von Hippel–Lindau (VHL)‐defective cells greatly alters these interactions, indicating that at least under these conditions, HIF can operate on preexisting patterns of chromatin–chromatin interactions that define potential transcriptional targets and permit rapid gene activation by hypoxic stress.

Hypoxic regulation of the noncoding genome and NEAT1.

Activation of hypoxia pathways is both associated with and contributes to an aggressive phenotype across multiple types of solid cancers. The regulation of gene transcription by hypoxia-inducible factor (HIF) is a key element in this response. HIF directly upregulates the expression of many hundreds of protein-coding genes, which act to both improve oxygen delivery and to reduce oxygen demand. However, it is now becoming apparent that many classes of noncoding RNAs are also regulated by hypoxia, with several (e.g. micro RNAs, long noncoding RNAs and antisense RNAs) under direct transcriptional regulation by HIF. These hypoxia-regulated, noncoding RNAs may act as effectors of the indirect response to HIF by acting on specific coding transcripts or by affecting generic RNA-processing pathways. In addition, noncoding RNAs may also act as modulators of the HIF pathway, either by integrating other physiological responses or, in the case of HIF-regulated, noncoding RNAs, by providing negative or positive feedback and feedforward loops that affect upstream or downstream components of the HIF cascade. These hypoxia-regulated, noncoding transcripts play important roles in the aggressive hypoxic phenotype observed in cancer.

Advances in Hypoxia-Inducible Factor Biology

Hypoxia-inducible factor (HIF), a central regulator for detecting and adapting to cellular oxygen levels, transcriptionally activates genes modulating oxygen homeostasis and metabolic activation. Beyond this, HIF influences many other processes. Hypoxia, in part through HIF-dependent mechanisms, influences epigenetic factors, including DNA methylation and histone acetylation, which modulate hypoxia-responsive gene expression in cells. Hypoxia profoundly affects expression of many noncoding RNAs classes that have clinicopathological implications in cancer. HIF can regulate noncoding RNAs production, while, conversely, noncoding RNAs can modulate HIF expression. There is recent evidence for crosstalk between circadian rhythms and hypoxia-induced signaling, suggesting involvement of molecular clocks in adaptation to fluxes in nutrient and oxygen sensing. HIF induces increased production of cellular vesicles facilitating intercellular communication at a distance-for example, promoting angiogenesis in hypoxic tumors. Understanding the complex networks underlying cellular and genomic regulation in response to hypoxia via HIF may identify novel and specific therapeutic targets.

Acoustic and hybrid 3D-printed electrochemical biosensors for the real-time immunodetection of liver cancer cells (HepG2)

This study presents an efficient acoustic and hybrid three-dimensional (3D)-printed electrochemical biosensors for the detection of liver cancer cells. The biosensors function by recognizing the highly expressed tumor marker CD133, which is located on the surface of liver cancer cells. Detection was achieved by recrystallizing a recombinant S-layer fusion protein (rSbpA/ZZ) on the surface of the sensors. The fused ZZ-domain enables immobilization of the anti-CD133 antibody in a defined manner. These highly accessible anti-CD133 antibodies were employed as a sensing layer, thereby enabling the efficient detection of liver cancer cells (HepG2). The recognition of HepG2 cells was investigated in situ using a quartz crystal microbalance with dissipation monitoring (QCM-D), which enabled the label-free, real-time detection of living cells on the modified sensor surface under controlled conditions. Furthermore, the hybrid 3D additive printing strategy for biosensors facilitates both rapid development and small-scale manufacturing. The hybrid strategy of combining 3D-printed parts and more traditionally fabricated parts enables the use of optimal materials: a ceramic substrate with noble metals for the sensing element and 3D-printed capillary channels to guide and constrain the clinical sample. Cyclic voltammetry (CV) measurements confirmed the efficiency of the fabricated sensors. Most importantly, these sensors offer low-cost and disposable detection platforms for real-world applications. Thus, as demonstrated in this study, both fabricated acoustic and electrochemical sensing platforms can detect cancer cells and therefore may have further potential in other clinical applications and drug-screening studies.

miRNAs as Circulating Biomarkers for Alzheimer's Disease and Parkinson's Disease.

Detection of biomarkers for neurodegenerative disorders (NDDs) within brain tissues of Alzheimers disease (AD) and Parkinsons disease (PD) patients has always been hampered by our inability to access and biopsy tissue of key brain regions implicated in disease occurrence and progression. Currently, diagnosis of NDDs is principally based on clinical observations of symptoms that present at later stages of disease progression, followed by neuroimaging and, possibly, CSF evaluation. One way to potentially detect and diagnose NDDs at a far earlier stage is to screen for abnormal levels of specific disease markers within the peripheral circulation of patients with NDDs. Increasing evidence suggests that there is dysregulation of microRNAs (miRNAs) in NDDs. Peripheral blood mononuclear cells, as well as biofluids, such as plasma, serum, urine and cerebrospinal fluid, contain miRNAs that can be identified and quantified. Circulating miRNAs within blood and other biofluids may thus be characterized and used as non-invasive, diagnostic biomarkers that facilitate the early detection of disease and potentially the continual monitoring of disease progression for NDDs such as AD and PD. Plainly, such a screen is only possible with a clear understanding of which miRNAs change with disease, and when these changes occur during the progression of AD and PD. Such information is becoming increasingly available and, in the near future, may not only support disease diagnosis, but provide the opportunity to evaluate therapeutic interventions earlier in the disease process.

Signalling pathways in UHRF1-dependent regulation of tumor suppressor genes in cancer

Epigenetic silencing of tumor suppressor genes (TSGs) through DNA methylation and histone changes is a main hallmark of cancer. Ubiquitin-like with PHD and RING Finger domains 1 (UHRF1) is a potent oncogene overexpressed in various solid and haematological tumors and its high expression levels are associated with decreased expression of several TSGs including p16INK4A, BRCA1, PPARG and KiSS1. Using its several functional domains, UHRF1 creates a strong coordinated dialogue between DNA methylation and histone post-translation modification changes causing the epigenetic silencing of TSGs which allows cancer cells to escape apoptosis. To ensure the silencing of TSGs during cell division, UHRF1 recruits several enzymes including histone deacetylase 1 (HDAC1), DNA methyltransferase 1 (DNMT1) and histone lysine methyltransferases G9a and Suv39H1 to the right place at the right moment. Several in vitro and in vivo works have reported the direct implication of the epigenetic player UHRF1 in tumorigenesis through the repression of TSGs expression and suggested UHRF1 as a promising target for cancer treatment. This review describes the molecular mechanisms underlying UHRF1 regulation in cancer and discusses its importance as a therapeutic target to induce the reactivation of TSGs and subsequent apoptosis.

Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations

Protein stability is a requisite in the field of biotechnology, cell biology and drug design. To understand effects of amino acid substitutions, computational models are preferred to save time and expenses. As a systemically important, highly abundant, stable protein, the knowledge of Cu/Zn Superoxide dismutase1 (SOD1) is important, making it a suitable test case for genotype-phenotype correlation in understanding ALS. Here, we report performance of eight protein stability calculators (PoPMuSiC 3.1, I-Mutant 2.0, I-Mutant 3.0, CUPSAT, FoldX, mCSM, BeatMusic and ENCoM) against 54 experimental stability changes due to mutations of SOD1. Four different high-resolution structures were used to test structure sensitivity that may affect protein calculations. Bland-Altman plot was also used to assess agreement between stability analyses. Overall, PoPMuSiC and FoldX emerge as the best methods in this benchmark. The relative performance of all the eight methods was very much structure independent, and also displayed less structural sensitivity. We also analyzed patient’s data in relation to experimental and computed protein stabilities for mutations of human SOD1. Correlation between disease phenotypes and stability changes suggest that the changes in SOD1 stability correlate with ALS patient survival times. Thus, the results clearly demonstrate the importance of protein stability in SOD1 pathogenicity.