Publications by authors named "Joshy George"

75 Publications

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.

NAR Genom Bioinform 2021 Dec 8;3(4):lqab113. Epub 2021 Dec 8.

The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nargab/lqab113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8652379PMC
December 2021

High-throughput visual assessment of sleep stages in mice using machine learning.

Sleep 2021 Oct 29. Epub 2021 Oct 29.

The Jackson Laboratory, 600 Main Street, Bar Harbor, ME.

Study Objectives: Sleep is an important biological process that is perturbed in numerous diseases, and assessment its substages currently requires implantation of electrodes to carry out electroencephalogram/electromyogram (EEG/EMG) analysis. Although accurate, this method comes at a high cost of invasive surgery and experts trained to score EEG/EMG data. Here, we leverage modern computer vision methods to directly classify sleep substages from video data. This bypasses the need for surgery and expert scoring, provides a path to high-throughput studies of sleep in mice.

Methods: We collected synchronized high-resolution video and EEG/EMG data in 16 male C57BL/6J mice. We extracted features from the video that are time and frequency-based and used the human expert-scored EEG/EMG data to train a visual classifier. We investigated several classifiers and data augmentation methods.

Results: Our visual sleep classifier proved to be highly accurate in classifying wake, non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) states, and achieves an overall accuracy of 0.92 +/- 0.05 (mean +/- SD). We discover and genetically validate video features that correlate with breathing rates, and show low and high variability in NREM and REM sleep, respectively. Finally, we apply our methods to non-invasively detect that sleep stage disturbances induced by amphetamine administration.

Conclusions: We conclude that machine learning based visual classification of sleep is a viable alternative to EEG/EMG based scoring. Our results will enable non-invasive high-throughput sleep studies and will greatly reduce the barrier to screening mutant mice for abnormalities in sleep.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/sleep/zsab260DOI Listing
October 2021

Local versus systemic control of bone and skeletal muscle mass by components of the transforming growth factor-β signaling pathway.

Proc Natl Acad Sci U S A 2021 08;118(33)

The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032;

Skeletal muscle and bone homeostasis are regulated by members of the myostatin/GDF-11/activin branch of the transforming growth factor-β superfamily, which share many regulatory components, including inhibitory extracellular binding proteins and receptors that mediate signaling. Here, we present the results of genetic studies demonstrating a critical role for the binding protein follistatin (FST) in regulating both skeletal muscle and bone. Using an allelic series corresponding to varying expression levels of endogenous , we show that FST acts in an exquisitely dose-dependent manner to regulate both muscle mass and bone density. Moreover, by employing a genetic strategy to target expression only in the posterior (caudal) region of the animal, we show that the effects of loss are mostly restricted to the posterior region, implying that locally produced FST plays a much more important role than circulating FST with respect to regulation of muscle and bone. Finally, we show that targeting receptors for these ligands specifically in osteoblasts leads to dramatic increases in bone mass, with trabecular bone volume fraction being increased by 12- to 13-fold and bone mineral density being increased by 8- to 9-fold in humeri, femurs, and lumbar vertebrae. These findings demonstrate that bone, like muscle, has an enormous inherent capacity for growth that is normally kept in check by this signaling system and suggest that the extent to which this regulatory mechanism may be used throughout the body to regulate tissue mass may be more significant than previously appreciated.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.2111401118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379946PMC
August 2021

Predominance of genetically diverse ESBL Escherichia coli identified in resistance mapping of Vembanad Lake, the largest fresh-cum-brackishwater lake of India.

Environ Sci Pollut Res Int 2021 Dec 30;28(46):66206-66222. Epub 2021 Jul 30.

Microbiology, Fermentation and Biotechnology Division, ICAR-Central Institute of Fisheries Technology (ICAR-CIFT), Cochin, 682029, Kerala, India.

Antimicrobial resistance (AMR) burden in Escherichia coli along the 90 km stretch of Vembanad Lake, Kerala, India, was assessed. Seventy-seven percent of water samples drawn from 35 different stations of the lake harbored E. coli. Antibiotic susceptibility test performed on 116 E. coli isolates revealed resistance to ≥ one antibiotic with 39 AMR profiles in 81%, multidrug resistance in 30%, and extended spectrum β-lactamase (ESBL) producers in 32%. Of all the 15 antibiotics tested, the probability of isolating cefotaxime-resistant E. coli was the highest (P ≤ 0.05) in the lake. Genetically diverse ESBL types, namely bla, bla, bla, bla, bla, and bla, were identified in the lake. This is probably the first report in India for the presence of bla (bla) in the Vembanad Lake. ST11439 and single and double loci variants of ST443 and ST4533 were identified in multilocus sequence typing (MLST). Inc plasmids (B/O, F, W, I1, FIIA, HI1, P-1α, K/B, and N) identified in the lake evidences the resistance transmission potential of the E. coli isolated from the lake. Molecular typing (ERIC-PCR, MLST, and PBRT) delineated diverse E. coli, both between and within the sampling stations. Low multiple antibiotic resistance index (average MAR< 0.2) indicates a lower risk of the lake to the human population, but the occurrence of genetically diverse ESBL E. coli in the Vembanad Lake signals health hazards and necessitates pragmatic control measures.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11356-021-15110-yDOI Listing
December 2021

A revisited two-step microtiter plate assay: Optimization of in vitro multiplicity of infection (MOI) for Coliphage and Vibriophage.

J Virol Methods 2021 08 8;294:114177. Epub 2021 May 8.

Visakhapatnam Research Centre of ICAR-Central Institute of Fisheries Technology (ICAR-CIFT), Visakhapatnam, 530003, Andhra Pradesh, India. Electronic address:

A 2-step microtiter plate assay was developed to simultaneously check wide values of MOIs of bacteriophages, ranging between MOI-0.0001 and MOI-10000 in the first step and optimize the most suitable MOI (lowest quantity of phage) for inhibiting the growth of the target bacteria in the second step. The results of the first step revealed that the effective MOI of coliphage-ɸ5 for controlling the growth of antimicrobial resistant (AMR) E. coli was between 4.36 and 43.6 for E.coli-EC-3; between 38.2 and 382 for E.coli-EC-7 and between 81.5 and 815 for E.coli-EC-11. The optimum MOI of coliphage-ɸ5 determined in the second step was 17.44, 191 and 326 for controlling the growth of E.coli-EC-3; E.coli-EC-7 and E.coli-EC-11, respectively. The effective MOI of vibriophage-ɸLV6 for controlling luminescent Vibrio harveyi in the first step was found to be between 18.3 and 183 and the optimum MOI as determined in the second step was 79. The sequential 2-step microtiter plate method yielded faster optimization of MOI and was economical compared to the conventional flask method. The measurement of OD values at 550 nm and 600 nm showed similar trend and replicate data from 5-wells and 3-wells yielded identical pattern indicating that the measuring absorbance data in 3-replicate wells at either OD or OD is sufficient to generate quantifiable phage lysis data. The 2-step microtiter plate assay finds application in phage therapy in human health care, agriculture and animal agriculture for determining the optimum MOIs for selected bacteriophages.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jviromet.2021.114177DOI Listing
August 2021

Human KIT+ myeloid cells facilitate visceral metastasis by melanoma.

J Exp Med 2021 06;218(6)

The Jackson Laboratory for Genomic Medicine, Farmington, CT.

Metastasis of melanoma significantly worsens prognosis; thus, therapeutic interventions that prevent metastasis could improve patient outcomes. Here, we show using humanized mice that colonization of distant visceral organs with melanoma is dependent upon a human CD33+CD11b+CD117+ progenitor cell subset comprising <4% of the human CD45+ leukocytes. Metastatic tumor-infiltrating CD33+ cells from patients and humanized (h)NSG-SGM3 mice showed converging transcriptional profiles. Single-cell RNA-seq analysis identified a gene signature of a KIT/CD117-expressing CD33+ subset that correlated with decreased overall survival in a TCGA melanoma cohort. Thus, human CD33+CD11b+CD117+ myeloid cells represent a novel candidate biomarker as well as a therapeutic target for metastatic melanoma.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1084/jem.20182163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056753PMC
June 2021

Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging.

Cancers (Basel) 2021 Mar 25;13(7). Epub 2021 Mar 25.

Tumorbank Ovarian Cancer Network, ENGOT biobank, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany.

Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profiles on the same paraffin-embedded tissue sections and distinguish HGSOC subtypes by proteomic signature. Finally, we devised a novel approach to annotate spectra of stromal origin. We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma-associated spectra provides tangible improvements to classification quality (AUC = 0.988). Moreover, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999). Here, we present a concept integrating MALDI-IMS with machine-learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for personalized treatment.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/cancers13071512DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036744PMC
March 2021

SFRP4 drives invasion in gastric cancer and is an early predictor of recurrence.

Gastric Cancer 2021 May 4;24(3):589-601. Epub 2020 Dec 4.

Upper Gastrointestinal Translational Research Laboratory, Peter MacCallum Cancer Centre, 305 Grattan St, Parkville, VIC, Australia.

Objective: Gastric cancer patients generally have a poor outcome, particularly those with advanced-stage disease which is defined by the increased invasion of cancer locally and is associated with higher metastatic potential. This study aimed to identify genes that were functional in the most fundamental hallmark of cancer, namely invasion. We then wanted to assess their value as biomarkers of gastric cancer progression and recurrence.

Design: Data from a cohort of patients profiled on cDNA expression arrays was interrogated using K-means analysis. This genomic approach classified the data based on patterns of gene expression allowing the identification of the genes most correlated with the invasion of GC. We evaluated the functional role of a key protein from this analysis in invasion and as a biomarker of recurrence after curative resection.

Results: Expression of secreted frizzled-related protein 4 (SFRP4) was identified as directly proportional to gastric cancer invasion. This finding was validated in multiple, independent datasets and its functional role in invasion was also confirmed using invasion assays. A change in serum levels of SFRP4 after curative resection, when coupled with AJCC stage, can accurately predict the risk of disease recurrence after curative therapy in an assay we termed PredictR.

Conclusions: This simple ELISA-based assay can help predict recurrence of disease after curative gastric cancer surgery irrespective of adjuvant therapy. The results require further evaluation in a prospective trial but would help in the rational prescription of cancer therapies and surveillance to prevent under or over treatment of patients after curative resection.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10120-020-01143-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064978PMC
May 2021

Poison Exon Splicing Regulates a Coordinated Network of SR Protein Expression during Differentiation and Tumorigenesis.

Mol Cell 2020 11 10;80(4):648-665.e9. Epub 2020 Nov 10.

The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA; Institute for Systems Genomics, UConn Health, Farmington, CT, USA. Electronic address:

The RNA isoform repertoire is regulated by splicing factor (SF) expression, and alterations in SF levels are associated with disease. SFs contain ultraconserved poison exon (PE) sequences that exhibit greater identity across species than nearby coding exons, but their physiological role and molecular regulation is incompletely understood. We show that PEs in serine-arginine-rich (SR) proteins, a family of 14 essential SFs, are differentially spliced during induced pluripotent stem cell (iPSC) differentiation and in tumors versus normal tissues. We uncover an extensive cross-regulatory network of SR proteins controlling their expression via alternative splicing coupled to nonsense-mediated decay. We define sequences that regulate PE inclusion and protein expression of the oncogenic SF TRA2β using an RNA-targeting CRISPR screen. We demonstrate location dependency of RS domain activity on regulation of TRA2β-PE using CRISPR artificial SFs. Finally, we develop splice-switching antisense oligonucleotides to reverse the increased skipping of TRA2β-PE detected in breast tumors, altering breast cancer cell viability, proliferation, and migration.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.molcel.2020.10.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7680420PMC
November 2020

Comprehensive Molecular Characterization of Adenocarcinoma of the Gastroesophageal Junction Between Esophageal and Gastric Adenocarcinomas.

Ann Surg 2020 Oct 19. Epub 2020 Oct 19.

Department of Surgery, Seoul National University College of Medicine, Seoul, Korea.

Objective: To investigate the molecular characteristics of AGEJ compared with EAC and gastric adenocarcinoma.

Summary Of Background Data: Classification of AGEJ based on differential molecular characteristics between EAC and gastric adenocarcinoma has been long-standing controversy but rarely conducted due to anatomical ambiguity and epidemiologic difference.

Methods: The molecular classification model with Bayesian compound covariate predictor was developed based on differential mRNA expression of EAC (N = 78) and GCFB (N = 102) from the Cancer Genome Atlas (TCGA) cohort. AGEJ/cardia (N = 48) in TCGA cohort and AGEJ/upper third GC (N = 46 pairs) in Seoul National University cohort were classified into the EAC-like or GCFB-like groups whose genomic, transcriptomic, and proteomic characteristics were compared.

Results: AGEJ in both cohorts was similarly classified as EAC-like (31.2%) or GCFB-like (68.8%) based on the 400-gene classifier. The GCFB-like group showed significantly activated phosphoinositide 3-kinase-AKT signaling with decreased expression of ERBB2. The EAC-like group presented significantly different alternative splicing including the skipped exon of RPS24, a significantly higher copy number amplification including ERBB2 amplification, and increased protein expression of ERBB2 and EGFR compared with GCFB-like group. High-throughput 3D drug test using independent cell lines revealed that the EAC-like group showed a significantly better response to lapatinib than the GCFB-like group (P = 0.015).

Conclusions: AGEJ was the combined entity of the EAC-like and GCFB-like groups with consistently different molecular characteristics in both Seoul National University and TCGA cohorts. The EAC-like group with a high Bayesian compound covariate predictor score could be effectively targeted by dual inhibition of ERBB2 and EGFR.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/SLA.0000000000004303DOI Listing
October 2020

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine 2020 Nov 9;61:103030. Epub 2020 Oct 9.

The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA; The Jackson Laboratory Cancer Center, Bar Harbor, ME, USA. Electronic address:

Background: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's primary cancer remains fundamental to their treatment, CUP patients are significantly disadvantaged and most have a poor survival outcome. Developing robust and accessible diagnostic methods for resolving cancer tissue of origin, therefore, has significant value for CUP patients.

Methods: We developed an RNA-based classifier called CUP-AI-Dx that utilizes a 1D Inception convolutional neural network (1D-Inception) model to infer a tumor's primary tissue of origin. CUP-AI-Dx was trained using the transcriptional profiles of 18,217 primary tumours representing 32 cancer types from The Cancer Genome Atlas project (TCGA) and International Cancer Genome Consortium (ICGC). Gene expression data was ordered by gene chromosomal coordinates as input to the 1D-CNN model, and the model utilizes multiple convolutional kernels with different configurations simultaneously to improve generality. The model was optimized through extensive hyperparameter tuning, including different max-pooling layers and dropout settings. For 11 tumour types, we also developed a random forest model that can classify the tumour's molecular subtype according to prior TCGA studies. The optimised CUP-AI-Dx tissue of origin classifier was tested on 394 metastatic samples from 11 tumour types from TCGA and 92 formalin-fixed paraffin-embedded (FFPE) samples representing 18 cancer types from two clinical laboratories. The CUP-AI-Dx molecular subtype was also independently tested on independent ovarian and breast cancer microarray datasets FINDINGS: CUP-AI-Dx identifies the primary site with an overall top-1-accuracy of 98.54% in cross-validation and 96.70% on a test dataset. When applied to two independent clinical-grade RNA-seq datasets generated from two different institutes from the US and Australia, our model predicted the primary site with a top-1-accuracy of 86.96% and 72.46% respectively.

Interpretation: The CUP-AI-Dx predicts tumour primary site and molecular subtype with high accuracy and therefore can be used to assist the diagnostic work-up of cancers of unknown primary or uncertain origin using a common and accessible genomics platform.

Funding: NIH R35 GM133562, NCI P30 CA034196, Victorian Cancer Agency Australia.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ebiom.2020.103030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7553237PMC
November 2020

Targeting myostatin/activin A protects against skeletal muscle and bone loss during spaceflight.

Proc Natl Acad Sci U S A 2020 09 8;117(38):23942-23951. Epub 2020 Sep 8.

Department of Pediatrics, University of Connecticut School of Medicine, Farmington, CT 06030.

Among the physiological consequences of extended spaceflight are loss of skeletal muscle and bone mass. One signaling pathway that plays an important role in maintaining muscle and bone homeostasis is that regulated by the secreted signaling proteins, myostatin (MSTN) and activin A. Here, we used both genetic and pharmacological approaches to investigate the effect of targeting MSTN/activin A signaling in mice that were sent to the International Space Station. mice lost significant muscle and bone mass during the 33 d spent in microgravity. Muscle weights of mice, which are about twice those of mice, were largely maintained during spaceflight. Systemic inhibition of MSTN/activin A signaling using a soluble form of the activin type IIB receptor (ACVR2B), which can bind each of these ligands, led to dramatic increases in both muscle and bone mass, with effects being comparable in ground and flight mice. Exposure to microgravity and treatment with the soluble receptor each led to alterations in numerous signaling pathways, which were reflected in changes in levels of key signaling components in the blood as well as their RNA expression levels in muscle and bone. These findings have implications for therapeutic strategies to combat the concomitant muscle and bone loss occurring in people afflicted with disuse atrophy on Earth as well as in astronauts in space, especially during prolonged missions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1073/pnas.2014716117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7519220PMC
September 2020

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

Clin Cancer Res 2020 10 17;26(20):5411-5423. Epub 2020 Jun 17.

Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia.

Purpose: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features.

Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting.

Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations.

Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications..
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/1078-0432.CCR-20-0103DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7572656PMC
October 2020

ABCC4/MRP4 contributes to the aggressiveness of Myc-associated epithelial ovarian cancer.

Int J Cancer 2020 10 8;147(8):2225-2238. Epub 2020 May 8.

Children's Cancer Institute Australia, Lowy Cancer Research Centre, UNSW Australia, Kensington, New South Wales, Australia.

Epithelial ovarian cancer (EOC) is a complex disease comprising discrete histological and molecular subtypes, for which survival rates remain unacceptably low. Tailored approaches for this deadly heterogeneous disease are urgently needed. Efflux pumps belonging to the ATP-binding cassette (ABC) family of transporters are known for roles in both drug resistance and cancer biology and are also highly targetable. Here we have investigated the association of ABCC4/MRP4 expression to clinical outcome and its biological function in endometrioid and serous tumors, common histological subtypes of EOC. We found high expression of ABCC4/MRP4, previously shown to be directly regulated by c-Myc/N-Myc, was associated with poor prognosis in endometrioid EOC (P = .001) as well as in a subset of serous EOC with a "high-MYCN" profile (C5/proliferative; P = .019). Transient siRNA-mediated suppression of MRP4 in EOC cells led to reduced growth, migration and invasion, with the effects being most pronounced in endometrioid and C5-like serous cells compared to non-C5 serous EOC cells. Sustained knockdown of MRP4 also sensitized endometrioid cells to MRP4 substrate drugs. Furthermore, suppression of MRP4 decreased the growth of patient-derived EOC cells in vivo. Together, our findings provide the first evidence that MRP4 plays an important role in the biology of Myc-associated ovarian tumors and highlight this transporter as a potential therapeutic target for EOC.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/ijc.33005DOI Listing
October 2020

Differential Functions of Splicing Factors in Mammary Transformation and Breast Cancer Metastasis.

Cell Rep 2019 11;29(9):2672-2688.e7

The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Institute for Systems Genomics, UConn Health, Farmington, CT, USA; Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA. Electronic address:

Misregulation of alternative splicing is a hallmark of human tumors, yet to what extent and how it contributes to malignancy are only beginning to be unraveled. Here, we define which members of the splicing factor SR and SR-like families contribute to breast cancer and uncover differences and redundancies in their targets and biological functions. We identify splicing factors frequently altered in human breast tumors and assay their oncogenic functions using breast organoid models. We demonstrate that not all splicing factors affect mammary tumorigenesis in MCF-10A cells. Specifically, the upregulation of SRSF4, SRSF6, or TRA2β disrupts acinar morphogenesis and promotes cell proliferation and invasion in MCF-10A cells. By characterizing the targets of these oncogenic splicing factors, we identify shared spliced isoforms associated with well-established cancer hallmarks. Finally, we demonstrate that TRA2β is regulated by the MYC oncogene, plays a role in metastasis maintenance in vivo, and its levels correlate with breast cancer patient survival.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.celrep.2019.10.110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6936330PMC
November 2019

Genomic data analysis workflows for tumors from patient-derived xenografts (PDXs): challenges and guidelines.

BMC Med Genomics 2019 07 1;12(1):92. Epub 2019 Jul 1.

The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, 04609, USA.

Background: Patient-derived xenograft (PDX) models are in vivo models of human cancer that have been used for translational cancer research and therapy selection for individual patients. The Jackson Laboratory (JAX) PDX resource comprises 455 models originating from 34 different primary sites (as of 05/08/2019). The models undergo rigorous quality control and are genomically characterized to identify somatic mutations, copy number alterations, and transcriptional profiles. Bioinformatics workflows for analyzing genomic data obtained from human tumors engrafted in a mouse host (i.e., Patient-Derived Xenografts; PDXs) must address challenges such as discriminating between mouse and human sequence reads and accurately identifying somatic mutations and copy number alterations when paired non-tumor DNA from the patient is not available for comparison.

Results: We report here data analysis workflows and guidelines that address these challenges and achieve reliable identification of somatic mutations, copy number alterations, and transcriptomic profiles of tumors from PDX models that lack genomic data from paired non-tumor tissue for comparison. Our workflows incorporate commonly used software and public databases but are tailored to address the specific challenges of PDX genomics data analysis through parameter tuning and customized data filters and result in improved accuracy for the detection of somatic alterations in PDX models. We also report a gene expression-based classifier that can identify EBV-transformed tumors. We validated our analytical approaches using data simulations and demonstrated the overall concordance of the genomic properties of xenograft tumors with data from primary human tumors in The Cancer Genome Atlas (TCGA).

Conclusions: The analysis workflows that we have developed to accurately predict somatic profiles of tumors from PDX models that lack normal tissue for comparison enable the identification of the key oncogenic genomic and expression signatures to support model selection and/or biomarker development in therapeutic studies. A reference implementation of our analysis recommendations is available at https://github.com/TheJacksonLaboratory/PDX-Analysis-Workflows .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12920-019-0551-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6604205PMC
July 2019

A computational method to aid the design and analysis of single cell RNA-seq experiments for cell type identification.

BMC Bioinformatics 2019 Jun 6;20(Suppl 11):275. Epub 2019 Jun 6.

The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.

Background: The advent of single cell RNA sequencing (scRNA-seq) enabled researchers to study transcriptomic activity within individual cells and identify inherent cell types in the sample. Although numerous computational tools have been developed to analyze single cell transcriptomes, there are no published studies and analytical packages available to guide experimental design and to devise suitable analysis procedure for cell type identification.

Results: We have developed an empirical methodology to address this important gap in single cell experimental design and analysis into an easy-to-use tool called SCEED (Single Cell Empirical Experimental Design and analysis). With SCEED, user can choose a variety of combinations of tools for analysis, conduct performance analysis of analytical procedures and choose the best procedure, and estimate sample size (number of cells to be profiled) required for a given analytical procedure at varying levels of cell type rarity and other experimental parameters. Using SCEED, we examined 3 single cell algorithms using 48 simulated single cell datasets that were generated for varying number of cell types and their proportions, number of genes expressed per cell, number of marker genes and their fold change, and number of single cells successfully profiled in the experiment.

Conclusions: Based on our study, we found that when marker genes are expressed at fold change of 4 or more, either Seurat or SIMLR algorithm can be used to analyze single cell dataset for any number of single cells isolated (minimum 1000 single cells were tested). However, when marker genes are expected to be only up to fold change of 2, choice of the single cell algorithm is dependent on the number of single cells isolated and rarity of cell types to be identified. In conclusion, our work allows the assessment of various single cell methods and also aids in the design of single cell experiments.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12859-019-2817-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6551246PMC
June 2019

Elements of a successful hospital-based deceased donation programme in India: Zero to eighty-five in two years.

Natl Med J India 2018 Jul-Aug;31(4):201-205

Department of Hospital Administration, Lakeshore Hospital, Kochi, Kerala, India.

Background: Legislation has made organ donation after brain death (DBD) possible in India since 1994. However, no organs are donated in most parts of the country; the national organ donation rate is estimated at between 0.08 and 0.34 donors per million population-one of the lowest in the world.

Methods: A 350-bedded private hospital in Kochi started its DBD programme in September 2013 with a structured approach based on counselling of family members of critically ill individuals. A counsellor trained to diagnose family dynamics, and recognize different stages of the grieving process, chose the right time, and the correct family member to whom the donation request could be made. Regular debriefing sessions of the core team consisting of a transplant surgeon, a transplant coordinator, an ICU counsellor and a unit administrator resulted in setting up systems that supported families of patients with catastrophic brain injury, and created an environment conducive to obtaining consent.

Results: A total of 85 organ donations took place in the first 24 months (September 2013 to September 2015) of instituting the programme.

Conclusion: It is possible with hospital-based teamwork and a structured approach to consistently elicit organ donation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.4103/0970-258X.258217DOI Listing
October 2019

High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts.

Sci Rep 2018 12 18;8(1):17937. Epub 2018 Dec 18.

The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06030, USA.

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertainty <3%. For one patient, we discovered two predominant subclones that were granularly intermixed in all 48 co-derived xenograft samples. These two subclones exhibited differential chemotherapy sensitivity-when xenografts were treated with cisplatin for 3 weeks, the post-treatment volume change was proportional to the post-treatment ratio of subclones on a xenograft-to-xenograft basis. A subsequent cohort in which xenografts were treated with cisplatin, allowed a drug holiday, then treated a second time continued to exhibit this proportionality. In contrast, xenografts from other treatment cohorts, spatially dissected xenograft fragments, and cell cultures evolved in diverse ways but with substantial population bottlenecks. These results show that ecosystems susceptible to successive retreatment can arise spontaneously in breast cancer in spite of a background of irregular subclonal bottlenecks, and our work provides to our knowledge the first quantification of the population genetics of such a system. Intriguingly, in such an ecosystem the ratio of common subclones is predictive of the state of treatment susceptibility, showing how measurements of subclonal heterogeneity could guide treatment for some patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-018-36184-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298990PMC
December 2018

IL1 Receptor Antagonist Controls Transcriptional Signature of Inflammation in Patients with Metastatic Breast Cancer.

Cancer Res 2018 09 16;78(18):5243-5258. Epub 2018 Jul 16.

Baylor Institute for Immunology Research, Baylor Research Institute, Dallas, Texas.

Inflammation affects tumor immune surveillance and resistance to therapy. Here, we show that production of IL1β in primary breast cancer tumors is linked with advanced disease and originates from tumor-infiltrating CD11c myeloid cells. IL1β production is triggered by cancer cell membrane-derived TGFβ. Neutralizing TGFβ or IL1 receptor prevents breast cancer progression in humanized mouse model. Patients with metastatic HER2 breast cancer display a transcriptional signature of inflammation in the blood leukocytes, which is attenuated after IL1 blockade. When present in primary breast cancer tumors, this signature discriminates patients with poor clinical outcomes in two independent public datasets (TCGA and METABRIC). IL1β orchestrates tumor-promoting inflammation in breast cancer and can be targeted in patients using an IL1 receptor antagonist. .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-18-0413DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391892PMC
September 2018

Tracing source, distribution and health risk of potentially harmful elements (PHEs) in street dust of Durgapur, India.

Ecotoxicol Environ Saf 2018 Jun 22;154:280-293. Epub 2018 Feb 22.

Department of Environmental Studies, Institute of Science (Siksha-Bhavana), Visva-Bharati, Santiniketan 731235, West Bengal, India. Electronic address:

Street dust samples from Durgapur, the steel city of eastern India, were collected from five different land use patterns, i.e., national highways, urban residential area, sensitive area, industrial area and busy traffic zone during summer, monsoon, and winter to analyze the pollution characteristics, chemical fractionation, source apportionment and health risk of heavy metals (HMs). The samples were fractionated into ≤ 53 µm and analyzed for potentially harmful elements (PHEs) viz. Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn. Summer season indicated higher concentrations of PHEs when compared to the other two seasons. Mean enrichment factor (EF), geo-accumulation index (Igeo), and contamination factor (CF) were high for Cd followed by Pb during all the three season in Durgapur. Chemical fractionation was executed in order to obtain distribution patterns of PHEs and to evaluate their bioavailable fractions in street dust samples. Mn was found to be highly bioavailable and bioavailability of the PHEs were in the order of Mn > Zn > Pb > Ni > Cd > Cu > Fe > Cr. Principal Component Analysis (PCA), cluster analysis, correlation analysis indicated the main sources of PHEs could be industrial, especially coal powered thermal plant, iron and steel industries and cement industries and vehicular. Multivariate analysis of variance (MANOVA) indicated that sites, seasons and their interaction were significantly affected by different PHEs as a whole. The health risk was calculated with total metal as well as mobile fraction of PHEs, which indicated that the actual non-carcinogenic risk due to bioavailable PHEs was less (HI < 1) when compared to total concentrations of PHEs. Carcinogenic risk was observed for total Cr in street dust (Child: 4.6E-06; Adult: 3.6E-06).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ecoenv.2018.02.042DOI Listing
June 2018

Homologous Recombination DNA Repair Pathway Disruption and Retinoblastoma Protein Loss Are Associated with Exceptional Survival in High-Grade Serous Ovarian Cancer.

Clin Cancer Res 2018 02 23;24(3):569-580. Epub 2017 Oct 23.

Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.

Women with epithelial ovarian cancer generally have a poor prognosis; however, a subset of patients has an unexpected dramatic and durable response to treatment. We sought to identify clinical, pathological, and molecular determinants of exceptional survival in women with high-grade serous cancer (HGSC), a disease associated with the majority of ovarian cancer deaths. We evaluated the histories of 2,283 ovarian cancer patients and, after applying stringent clinical and pathological selection criteria, identified 96 with HGSC that represented significant outliers in terms of treatment response and overall survival. Patient samples were characterized immunohistochemically and by genome sequencing. Different patterns of clinical response were seen: long progression-free survival (Long-PFS), multiple objective responses to chemotherapy (Multiple Responder), and/or greater than 10-year overall survival (Long-Term Survivors). Pathogenic germline and somatic mutations in genes involved in homologous recombination (HR) repair were enriched in all three groups relative to a population-based series. However, 29% of 10-year survivors lacked an identifiable HR pathway alteration, and tumors from these patients had increased Ki-67 staining. CD8 tumor-infiltrating lymphocytes were more commonly present in Long-Term Survivors. RB1 loss was associated with long progression-free and overall survival. HR deficiency and RB1 loss were correlated, and co-occurrence was significantly associated with prolonged survival. There was diversity in the clinical trajectory of exceptional survivors associated with multiple molecular determinants of exceptional outcome in HGSC patients. Concurrent HR deficiency and RB1 loss were associated with favorable outcomes, suggesting that co-occurrence of specific mutations might mediate durable responses in such patients. .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/1078-0432.CCR-17-1621DOI Listing
February 2018

The chromatin accessibility signature of human immune aging stems from CD8 T cells.

J Exp Med 2017 Oct 13;214(10):3123-3144. Epub 2017 Sep 13.

The Jackson Laboratory for Genomic Medicine, Farmington, CT

Aging is linked to deficiencies in immune responses and increased systemic inflammation. To unravel the regulatory programs behind these changes, we applied systems immunology approaches and profiled chromatin accessibility and the transcriptome in PBMCs and purified monocytes, B cells, and T cells. Analysis of samples from 77 young and elderly donors revealed a novel and robust aging signature in PBMCs, with simultaneous systematic chromatin closing at promoters and enhancers associated with T cell signaling and a potentially stochastic chromatin opening mostly found at quiescent and repressed sites. Combined analyses of chromatin accessibility and the transcriptome uncovered immune molecules activated/inactivated with aging and identified the silencing of the gene and the IL-7 signaling pathway genes as potential biomarkers. This signature is borne by memory CD8 T cells, which exhibited an aging-related loss in binding of NF-κB and STAT factors. Thus, our study provides a unique and comprehensive approach to identifying candidate biomarkers and provides mechanistic insights into aging-associated immunodeficiency.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1084/jem.20170416DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5626401PMC
October 2017

S100A4 Is a Biomarker and Regulator of Glioma Stem Cells That Is Critical for Mesenchymal Transition in Glioblastoma.

Cancer Res 2017 10 14;77(19):5360-5373. Epub 2017 Aug 14.

The Jackson Laboratory, Bar Harbor, Maine.

Glioma stem cells (GSC) and epithelial-mesenchymal transition (EMT) are strongly associated with therapy resistance and tumor recurrence, but the underlying mechanisms are incompletely understood. Here, we show that S100A4 is a novel biomarker of GSCs. S100A4 cells in gliomas are enriched with cancer cells that have tumor-initiating and sphere-forming abilities, with the majority located in perivascular niches where GSCs are found. Selective ablation of S100A4-expressing cells was sufficient to block tumor growth and We also identified S100A4 as a critical regulator of GSC self-renewal in mouse and patient-derived glioma tumorspheres. In contrast with previous reports of S100A4 as a reporter of EMT, we discovered that S100A4 is an upstream regulator of the master EMT regulators and along with other mesenchymal transition regulators in glioblastoma. Overall, our results establish S100A4 as a central node in a molecular network that controls stemness and EMT in glioblastoma, suggesting S100A4 as a candidate therapeutic target. .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-17-1294DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5626628PMC
October 2017

and Mutations Co-occur and Cooperate in Low-Grade Serous Ovarian Carcinomas.

Cancer Res 2017 08 23;77(16):4268-4278. Epub 2017 Jun 23.

Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia.

Low-grade serous ovarian carcinomas (LGSC) are associated with a poor response to chemotherapy and are molecularly characterized by RAS pathway activation. Using exome and whole genome sequencing, we identified recurrent mutations in the protein translational regulator and in , and RAS pathway mutations were mutually exclusive; however, we found significant co-occurrence of mutations in and Missense mutations were clustered at the N-terminus of the protein in a region associated with its role in ensuring translational initiation fidelity. Coexpression of mutant and proteins promoted proliferation and clonogenic survival in LGSC cells, providing the first example of co-occurring, growth-promoting mutational events in ovarian cancer. .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-16-2224DOI Listing
August 2017

Expression and function of ABCG2 and XIAP in glioblastomas.

J Neurooncol 2017 05 21;133(1):47-57. Epub 2017 Apr 21.

The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA.

Despite multimodal treatment that includes surgery, radiation and chemotherapy, virtually all glioblastomas (GBM) recur, indicating that these interventions are insufficient to eradicate all malignant cells. To identify potential new therapeutic targets in GBMs, we examined the expression and function of proteins that are associated with therapy resistance and cancer cell survival. We measured the expression of eight such proteins in 50 GBM samples by immunohistochemistry and analyzed patient survival. We report that GBM patients with high expression of ABCG2 (also called BCRP) or XIAP at the protein level had worse survival than those with low expression. The adjusted hazard ratio for ABCG2 was 2.35 and for XIAP was 2.65. Since glioma stem cells (GSCs) have been shown to be more resistant than bulk tumor cells to anti-cancer therapies and to express high levels of these proteins, we also sought to determine if ABCG2 and XIAP have functional roles in GSCs. We used small molecule inhibitors to treat patient-derived GBM tumorspheres in vitro and observed that inhibitors of ABCG2, Ko143 and fumitremorgin, significantly reduced self-renewal. These results suggest that ABCG2 and XIAP proteins may be useful indicators of patient survival and that inhibition of ABCG2 may be a promising therapeutic strategy in GBMs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11060-017-2422-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5627495PMC
May 2017

Bioavailability and health risk of some potentially toxic elements (Cd, Cu, Pb and Zn) in street dust of Asansol, India.

Ecotoxicol Environ Saf 2017 Apr 9;138:231-241. Epub 2017 Jan 9.

Department of Environmental Studies, Institute of Science(Siksha-Bhavana),Visva-Bharati, Santiniketan, West Bengal 731235, India. Electronic address:

Street dust samples were collected from five different types of land use patterns (busy traffic zone, urban residential area, national highways, industrial area and sensitive area) in a medium sized industrial city Asansol, India. The samples were fractionated into ≤53µm and analyzed for potential toxic elements (PTEs) viz. Zn, Cd, Pb and Cu. The mean total concentration of Zn, Cd, Pb and Cu in the urban street dust samples were 192, 0.75, 110 and 132mgkg respectively. Chemical speciation was performed for PTEs to evaluate the bio-available fractions. Cu was mostly associated with organic matter phase while Zn, Pb and Cd with residual phase. Mean mobility factor (MF) for heavy metals in Asansol was Zn (54.6%)>Pb (49.1%)>Cu (25.3%)>Cd (22.7%). Geo-chemical indices such as Enrichment Factor (EF), geo-accumulation index (Igeo) and contamination Factor (CF) were in the order of Pb>Cd>Zn>Cu. Cluster analysis was done to understand the similarities among the sites. The risks of all metals was calculated with mobile fraction, which indicated actual risk due to PTEs was less (HI<1).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ecoenv.2017.01.008DOI Listing
April 2017

A Myc Activity Signature Predicts Poor Clinical Outcomes in Myc-Associated Cancers.

Cancer Res 2017 02 6;77(4):971-981. Epub 2016 Dec 6.

Children's Cancer Institute Australia, Lowy Cancer Research Centre, University of New South Wales Australia, Kensington, New South Wales, Australia.

Myc transcriptional activity is frequently deregulated in human cancers, but a Myc-driven gene signature with prognostic ability across multiple tumor types remains lacking. Here, we selected 18 Myc-regulated genes from published studies of Myc family targets in epithelial ovarian cancer (EOC) and neuroblastoma. A Myc family activity score derived from the 18 genes was correlated to // expression in a panel of 35 cancer cell lines. The prognostic ability of this signature was evaluated in neuroblastoma, medulloblastoma, diffuse large B-cell lymphoma (DLBCL), and EOC microarray gene expression datasets using Kaplan-Meier and multivariate Cox regression analyses and was further validated in 42 primary neuroblastomas using qPCR. Cell lines with high , and/or gene expression exhibited elevated expression of the signature genes. Survival analysis showed that the signature was associated with poor outcome independently of well-defined prognostic factors in neuroblastoma, breast cancer, DLBCL, and medulloblastoma. In EOC, the 18-gene Myc activity signature was capable of identifying a group of patients with poor prognosis in a "high-" molecular subtype but not in the overall cohort. The predictive ability of this signature was reproduced using qPCR analysis of an independent cohort of neuroblastomas, including a subset of tumors without amplification. These data reveal an 18-gene Myc activity signature that is highly predictive of poor prognosis in diverse Myc-associated malignancies and suggest its potential clinical application in the identification of Myc-driven tumors that might respond to Myc-targeted therapies. .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/0008-5472.CAN-15-2906DOI Listing
February 2017

Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes.

Genome Res 2017 02 18;27(2):208-222. Epub 2016 Nov 18.

The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA.

Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1101/gr.212720.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5287227PMC
February 2017

Computational inference of a genomic pluripotency signature in human and mouse stem cells.

Biol Direct 2016 09 17;11:47. Epub 2016 Sep 17.

The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, 06032, USA.

Unlabelled: Recent analyses of next-generation sequencing datasets have shown that cell-specific regulatory elements in stem cells are marked with distinguishable patterns of transcription factor (TF) binding and epigenetic marks. For example, we recently demonstrated that promoters of cell-specific genes are covered with expanded trimethylation of histone H3 at lysine 4 (H3K4me3) marks (i.e., broad H3K4me3 domains). Moreover, binding of specific TFs, such as OCT4, NANOG, and SOX2, have been shown to play a critical role in maintaining the pluripotency of stem cells. Despite these observations, a systematic exploration of genomic and epigenomic features of stem-cell-specific gene promoters has not been conducted. Advanced machine-learning models can capture distinguishable genomic and epigenomic characteristics of stem-cell-specific promoters by taking advantage of the wealth of publicly available datasets. Here, we propose a three-step framework to discover novel data characteristics of high-throughput next generation sequencing datasets that distinguish pluripotency genes in human and mouse embryonic stem cells (ESCs). Our framework involves: i) feature extraction to identify novel features of genomic datasets; ii) feature selection using a logistic regression model combined with the Least Absolute Shrinkage and Selection Operator (LASSO) method to find the most critical datasets and features; and iii) cross validation with features selected using LASSO method to assess the predictive power of selected data features in distinguishing pluripotency genes. We show that specific epigenetic marks, and specific features of these marks, are enriched at pluripotency gene promoters. Moreover, we also assess both the individual and combined effect of TF binding, epigenetic mark deposition, gene expression datasets for marking pluripotency genes. Our findings are consistent with the existence of a conserved, complex and integrative genomic signature in ESCs that can be exploited to flag important candidate pluripotency genes. They also validate our computational framework for fostering a deeper understanding of genomic datasets in stem cells, in the future, could be extended to study cell-type-specific genomic landscapes in other cell types.

Reviewers: This article was reviewed by Zoltan Gaspari and Piotr Zielenkiewicz.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13062-016-0148-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5027095PMC
September 2016
-->