bioRxiv Science⌕ Search

Biology subjects

Pham, H.

Publications and source records attributed to Pham, H..

2 recordsLinked to original sources
bioRxiv2018

STAT3 promotes melanoma metastasis by CEBP-induced repression of the MITF pigmentation pathway

Metastatic melanoma is hallmarked by its ability to switch oncogenic MITF expression. Here we tested the impact of STAT3 on melanoma onset and progression in association with MITF expression levels. We established a mouse melanoma model for deleting Stat3 specifically in melanocytes with specific expression of human hyperactive NRASQ61K in an Ink4a deficient background. Mice with tissue specific Stat3 deletion showed an early onset of disease, but displayed significantly diminished lung metastases. Whole genome expression profiling also revealed a reduced invasion phenotype, which was functionally confirmed in 3D melanoma model systems. Notably, loss or knockdown of STAT3 in mouse or human cells resulted in up-regulation of MITF and induction of cell proliferation. Mechanistically we show that STAT3 induced CEBPa/b expression was sufficient to suppress MITF transcription. Epigenetic analysis by ATAC-seq confirmed that STAT3 enabled CEBPa/b binding to the MITF enhancer region thereby silencing it. We conclude that STAT3 is a metastasis driver in melanoma able to antagonize the MITF oncogene via direct induction of CEBP family member transcription facilitating RAS-RAF-driven melanoma metastasis.\n\nList of Abbreviations\n\nATAC-seq, Assay for Transposase-Accessible Chromatin using sequencing; CEBP, CAAT Box Enhancer Binding Protein; CRE, Cre recombinase; EGF, Epidermal Growth Factor; GEO, Gene Expression Omnibus; GSEA, Gene Set Enrichment Analysis; HSC70, Heat Shock 70 kDa protein; IHC, Immunohistochemistry; IL-6, Interleukin-6; JAK, Janus Kinase; MITF, Microphthalmia-Associated Transcription Factor; NSG, NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice; OSM, Oncostatin M; PDGF, Platelet-Derived Growth Factor; pS, phosphoserine; pY, phosphotyrosine; RAS, Rat Sarcoma; RAF, Rapidly Accelerated Fibrosarcoma; RTK, Receptor Tyrosine Kinase; RT-PCR, Reverse Transcription Polymerase Chain Reaction; S100b, Calcium Binding Protein S100 beta; shRNA, short hairpin RNA; SOX10, Sex Determining Region Y-10; STAT, Signal Transducer and Activator of Transcription; TCGA, The Cancer Genome Atlas; TMA, Tissue Micro Array

cancer biology↗
bioRxiv2018

A Multiplex Droplet Digital PCR Assay for Quantification of HTLV-1c DNA Proviral Load and T-Cells from Blood and Respiratory Exudates Sampled in a Remote Setting

During human T-cell leukemia virus type-1 (HTLV-1) infection the frequency of cells harboring an integrated copy of viral cDNA, the proviral load (PVL), is the main risk factor for progression of HTLV-1-associated diseases. Accurate quantification of provirus by droplet digital PCR (ddPCR) is a powerful diagnostic tool with emerging uses for monitoring viral expression. Current ddPCR techniques quantify HTLV-1 PVL in terms of whole genomic cellular material, while the main target of HTLV-1 infection is the CD4+ and CD8+ T-cell. Our understanding of HTLV-1 proliferation and the amount of viral burden present in different compartments is limited. Recently a sensitive ddPCR assay was applied to quantifying T-cells by measuring loss of germline T-cell receptor genes as method of distinguishing non-T-cell from recombined T-cell DNA. In this study, we demonstrated and validated novel applications of the duplex ddPCR assay to quantify T-cells from various sources of human gDNA extracted from frozen material (PBMCs, bronchoalveolar lavage, and induced sputum) from a cohort of remote Indigenous Australians and then compared the T-cell measurements by ddPCR to the prevailing standard method of flow cytometry. The HTLV-1c PVL was then calculated in terms of extracted T-cell gDNA from various compartments. Because HTLV-1c preferentially infects CD4+ T-cells, and the amount of viral burden correlates with HTLV-1c disease pathogenesis, application of this ddPCR assay to accurately measure HTLV-1c-infected T-cells can be of greater importance for clinical diagnostics, prognostics as well as monitoring therapeutic applications.

microbiology↗