Biology subjects

Hicks, J.

Publications and source records attributed to Hicks, J..

28 records · Page 2Linked to original sources

bioRxiv2022

Progressive spreading of DNA methylation in the GSTP1 promoter CpG island across transitions from precursors to invasive prostate cancer

Glutathione S-transferase pi 1 (GSTP1) is lowly expressed in normal prostate luminal cells and becomes induced in most proliferative inflammatory atrophy lesions (PIA). GSTP1 becomes silenced in prostatic intraepithelial neoplasia (PIN) and prostate adenocarcinoma (CaP) via cytosine-phospho-guanine (CpG) island promoter hypermethylation. However, GSTP1 methylation patterns in PIA and PIN, and their relationship to patterns in CaP are poorly understood. We used bisulfite genomic sequencing to examine patterns of GSTP1 promoter CpG island methylation in laser capture microdissected benign, PIA, PIN, and CaP regions from 32 subjects that underwent radical prostatectomy. We analyzed 908 sequence clones across 24 normal epithelium, 37 PIA, 18 PIN, and 23 CaP regions, allowing assessment of 34,863 CpG sites with allelic phasing. Normal and PIA lesions were mostly unmethylated with 0.52 and 1.3% of total CpG sites methylated, respectively. PIN and CaP lesions had greater methylation with 24% and 51% of total CpG sites methylated, respectively. The degree of GSTP1 methylation showed progression from PIA << PIN < CaP. PIN lesions showed more partial methylation compared to CaP lesions. Partially methylated lesions were enriched for methylation changes at AP1 and SP1 transcription factor binding sites. These results demonstrate that methylation density in the GSTP1 CpG island in PIN was intermediate relative to that in normal prostate epithelium/PIA and CaP lesions. These results are consistent with gradual spreading of DNA methylation centered at the SP1/AP1 transcription factor binding sites in precursor lesions, with subsequent spreading of methylation across the entire CpG island in transition to CaP.

cancer biology↗

bioRxiv2021

PHENOTYPIC CHARACTERIZATION OF TWO NOVEL CELL LINE MODELS OF CASTRATION RESISTANT PROSTATE CANCER.

BACKGROUNDResistance to androgen deprivation therapies is a major driver of mortality in advanced prostate cancer. Therefore, there is a need to develop new pre-clinical models that allow the investigation of resistance mechanisms and the assessment of drugs for the treatment of castration resistant prostate cancer. METHODSWe generated two novel cell line models (LAPC4-CR and VCaP-CR) which were derived by passaging LAPC4 and VCaP cells in vivo and in vitro under castrate conditions. We performed detailed transcriptomic (RNA-seq) and proteomic analyses (SWATH-MS) to delineate expression differences between castration-sensitive and castration-resistant cell lines. Furthermore, we characterized the in vivo and in vitro growth characteristics of the novel cell line models. RESULTSThe two cell line derivatives LAPC4-CR and VCaP-CR showed castration resistant growth in vitro and in vivo which was only minimally inhibited by AR antagonists, enzalutamide and bicalutamide. High-dose androgen treatment resulted in significant growth arrest of VCaP-CR but not in LAPC4-CR cells. Both cell lines maintained AR expression, but exhibited distinct expression changes on the mRNA and protein level. Integrated analyses including data from LNCaP and the previously described castration resistant LNCaP-abl cells revealed an expression signature of castration resistance. CONCLUSIONSThe two novel cell line models LAPC4-CR and VCaP-CR and their comprehensive characterization on the RNA and protein level represent important resources to study the molecular mechanisms of castration resistance.

cancer biology↗

bioRxiv2021

OpenSense: An open-source toolbox for Inertial-Measurement-Unit-based measurement of lower extremity kinematics over long durations

BackgroundThe ability to measure joint kinematics in natural environments over long durations using inertial measurement units (IMUs) could enable at-home monitoring and personalized treatment of neurological and musculoskeletal disorders. However, drift, or the accumulation of error over time, inhibits the accurate measurement of movement over long durations. We sought to develop an open-source workflow to estimate lower extremity joint kinematics from IMU data that was accurate, and capable of assessing and mitigating drift. MethodsWe computed IMU-based estimates of kinematics using sensor fusion and an inverse kinematics approach with a constrained biomechanical model. We measured kinematics for 11 subjects as they performed two 10-minute trials: walking and a repeated sequence of varied lower-extremity movements. To validate the approach, we compared the joint angles computed with IMU orientations to the joint angles computed from optical motion capture using root mean square (RMS) difference and Pearson correlations, and estimated drift using a linear regression on each subjects RMS differences over time. ResultsIMU-based kinematic estimates agreed with optical motion capture; median RMS differences over all subjects and all minutes were between 3-6 degrees for all joint angles except hip rotation and correlation coefficients were moderate to strong (r = 0.60 to 0.87). We observed minimal drift in the RMS differences over ten minutes; the average slopes of the linear fits to these data were near zero (-0.14 to 0.17 deg/min). ConclusionsOur workflow produced joint kinematics consistent with those estimated by optical motion capture, and could mitigate kinematic drift even in the trials of continuous walking without rest, obviating the need for explicit sensor recalibration (e.g. sitting or standing still for a few seconds or zero-velocity updates) used in current drift-mitigation approaches. This could enable long-duration measurements, bringing the field one step closer to estimating kinematics in natural environments.

bioengineering↗

bioRxiv2021

P2X4 Purinergic Receptors as a Therapeutic Target in Aggressive Prostate Cancer

Prostate cancer (PCa) remains a leading cause of cancer-related deaths in American men and treatment options for metastatic PCa are limited. There is a critical need to identify new mechanisms that contribute to PCa progression, that distinguish benign from lethal disease, and that have potential for therapeutic targeting. P2X4 belongs to the P2 purinergic receptor family that is commonly upregulated in cancer and is associated with poorer outcomes. Herein, we report that the P2X4 purinergic receptor is overexpressed in PCa, associated with PCa metastasis, and a driver of tumor development in vivo. We observed P2X4 protein expression primarily in epithelial cells of the prostate, a subset of CD66+ neutrophils, and most CD68+ macrophages. Our analysis of tissue microarrays representing 491 PCa cases demonstrated significantly elevated P2X4 expression in cancer compared to benign tissue spots, in prostatic intraepithelial neoplasia, in cancer from White compared to Black men, and in PCa with ERG positivity or with PTEN loss. High P2X4 expression in benign tissues was likewise associated with the development of metastasis after radical prostatectomy. Treatment with P2X4-specific agonist CTP increased transwell migration and invasion of PC3, DU145, and CWR22Rv1 PCa cells. P2X4 antagonist 5-BDBD treatment resulted in a dose-dependent decrease in viability of PC3, DU145, LNCaP, CWR22Rv1, TRAMP-C2, Myc-CaP, BMPC1, and BMPC2 cells and decreased DU145 cell migration and invasion. Knockdown of P2X4 attenuated growth, migration, and invasion of PCa cells. Finally, knockdown of P2X4 in Myc-CaP cells resulted in significantly attenuated subcutaneous allograft growth in FVB/NJ mice. Collectively, these data strongly support a role for the P2X4 purinergic receptor in PCa aggressiveness and identifies P2X4 as a candidate for therapeutic targeting.

cancer biology↗

bioRxiv2020

Discovery of A New Class of Integrin Antibodies for Fibrosis

Lung fibrosis, or the scarring of the lung, is a devastating disease with huge unmet medical need. There are limited treatment options and its prognosis is worse than most types of cancer. We previously discovered that MK-0429 is an equipotent pan-inhibitor of all v integrins that reduces proteinuria and kidney fibrosis in a preclinical model. In the present study, we further demonstrated that MK-0429 significantly inhibits fibrosis progression in a bleomycin-induced lung injury model. In search of newer integrin inhibitors for fibrosis, we characterized monoclonal antibodies discovered using Adimabs yeast display platform. We identified several potent neutralizing integrin antibodies with unique human and mouse cross-reactivity. Among these, Ab-31 blocked the binding of multiple v integrins to their ligands with IC50s comparable to those of MK-0429. Furthermore, both MK-0429 and Ab-31 suppressed integrin-mediated cell adhesion and latent TGF{beta} activation. In IPF patient lung fibroblasts, TGF{beta} treatment induced profound SMA expression in phenotypic imaging assays and Ab-31 demonstrated superior in vitro activity at inhibiting SMA expression, suggesting that the integrin antibody is able to modulate TGF{beta} action though mechanisms beyond the inhibition of latent TGF{beta} activation. Together, our results highlight the potential to develop newer integrin therapeutics for the treatment of fibrotic lung diseases. One Sentence Summarytargeting integrin in lung fibrosis

pharmacology and toxicology↗

bioRxiv2019

Agricultural and geographic factors shaped the North American 2015 highly pathogenic avian influenza H5N2 outbreak

The 2014 - 2015 highly pathogenic avian influenza (HPAI) H5NX outbreak represents the largest and most expensive HPAI outbreak in the United States to date. Despite extensive traditional and molecular epidemiological studies, factors associated with the spread of HPAI among midwestern poultry premises remain unclear. To better understand the dynamics of this outbreak, 182 full genome HPAI H5N2 sequences isolated from commercial layer chicken and turkey production premises were analyzed using evolutionary models modified to incorporate epidemiological and geographic information. Epidemiological compartmental models constructed in a phylogenetic framework provided evidence that poultry type acted as a barrier to the transmission of virus among midwestern poultry farms. Furthermore, after initial introduction, a continuous external source of virus was not needed to explain the propagation of HPAI cases within the commercial poultry industries. Discrete trait diffusion models indicated that within state viral transitions occurred more frequently than inter-state transitions. Distance, road density and proportion of water coverage were all supported as associated with viral transition between county groups (Bayes Factor > 3.0). Together these findings indicate that the midwestern poultry industries were not a single homogenous population, but rather, the outbreak was shaped by poultry sectors and geographic factors.\n\nAUTHOR SUMMARYThe highly pathogenic avian influenza outbreak among poultry farms in the midwestern United States appears to be influenced by agricultural and geographic factors. After initial introduction of the virus into the poultry industries, no further introductions (such as from a wild bird reservoir) were necessary to explain the continuation of the outbreak from March to June 2015. Additionally, evidence suggests that proximity increases the chances of viral movement between two locations. While many hypotheses have been proposed to explain the transmission of virus among poultry farms, the support for road density as an important driver of viral movement suggests human-mediated viral transportation played a key role in the spread of the highly pathogenic H5N2 outbreak in North America.

epidemiology↗

bioRxiv2018

A Pentatricopeptide Repeat Protein in the Plasmodium apicoplast is essential and shows sequence-specific RNA binding

The malaria parasite Plasmodium and other apicomplexans such as Toxoplasma evolved from photosynthetic organisms and contain an essential, remnant plastid termed the apicoplast. Transcription of the apicoplast genome is polycistronic with extensive RNA processing. Little is known about the mechanism of post-transcriptional processing. In plant chloroplasts, post-transcriptional RNA processing is controlled by multiple pentatricopeptide repeat (PPR) proteins. Here, we present the biochemical characterisation of the single apicoplast-targeted PPR protein. Apicoplast PPR1 is essential, and binds specific RNA sequences corresponding with previously characterized RNA processing sites. We identify the specific binding motif of PPR1. In RNAse protection assays, PPR1 shields apicoplast transcripts from ribonuclease degradation. Our results show that apicoplast RNA processing is under the control of a single protein, thus presenting an Achilles heel for the development of new anti-malarial drugs.

microbiology↗

bioRxiv2018

SMURF-seq for fast, multiplexed copy number profiling with long-read sequencers

We present SMURF-seq, a protocol to efficiently sequence short DNA molecules on a long-read sequencer by randomly ligating them to form long molecules. Applying SMURF-seq using Oxford Nanopore Technologies MinION yields up to 30 countable fragments per read at present, which generates multiple copy number profiles in a single run at a reduced time and cost. More broadly, SMURF-seq expands the utility of long-read sequencers for read-counting applications, which do not benefit from increased read length.

genomics↗

bioRxiv2017

SAKE (Single-cell RNA-Seq Analysis and Klustering Evaluation) Identifies Markers of Resistance to Targeted BRAF Inhibitors in Melanoma Cell Populations

Single-cell RNA-Seqs (scRNA-Seq) unprecedented cellular resolution at a genome wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-Seq datasets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present SAKE (Single-cell RNA-Seq Analysis and Klustering Evaluation): a robust method for scRNA-Seq analysis that provides quantitative statistical metrics at each step of the scRNA-Seq analysis pipeline including metrics for: the determination of the number of clusters present, the likelihood that each cell belongs to a given cluster, and the association of each gene marker in determining cluster membership. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-Seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. In addition, we compare integrated genomic and transcriptomic markers to show that resistance can arise stochastically within multiple distinct clonal populations.

genomics↗

bioRxiv2017

Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences, and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available with nearly 20,000 variants present, most of which were missed by prior efforts. Surrounding the important HER2 locus, we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the transcriptome and sheds new light on the complexity of cancer progression.

genomics↗