Biology subjects

Speicher, D. W.

Publications and source records attributed to Speicher, D. W..

4 recordsLinked to original sources

bioRxiv2023

Age-related increases in fibroblasts-secreted IGFBP2 increase melanoma cell invasion and lipid synthesis.

Aged melanoma patients (>65 years old) have more aggressive disease relative to young patients (<55 years old) for reasons that are not completely understood. Analysis of the young and aged secretome from human dermal fibroblasts identified >5-fold levels of insulin-like growth factor binding protein 2 (IGFBP2) in the aged fibroblast secretome. IGFBP2 functionally triggers upregulation of the PI3K-dependent fatty acid biosynthesis program in melanoma cells through increases in FASN. Melanoma cells co-cultured with aged dermal fibroblasts have higher levels of lipids relative to young dermal fibroblasts, which can be lowered by silencing IGFBP2 expression in fibroblasts, prior to treating with conditioned media. Conversely, ectopically treating melanoma cells with recombinant IGFBP2 in the presence of conditioned media from young fibroblasts, promoted lipid synthesis and accumulation in the melanoma cells. Neutralizing IGFBP2 in vitro reduces migration and invasion in melanoma cells, and in vivo studies demonstrate that neutralizing IGFBP2 in syngeneic aged mice, ablates tumor growth as well as metastasis. Conversely, ectopic treatment of young mice with IGFBP2 in young mice increases tumor growth and metastasis. Our data reveal that aged dermal fibroblasts increase melanoma cell aggressiveness through increased secretion of IGFBP2, stressing the importance of considering age when designing studies and treatment. SignificanceThe aged microenvironment drives metastasis in melanoma cells. This study reports that IGFBP2 secretion by aged fibroblasts induces FASN in melanoma cells and drives metastasis. Neutralizing IGFBP2 decreases melanoma tumor growth and metastasis.

cancer biology↗

bioRxiv2022

Regulation of EBNA1 Protein Stability by PLOD1 Lysine Hydroxylase

Epstein-Barr virus (EBV) is a ubiquitous human {gamma}-herpesvirus that is causally associated with various malignancies and autoimmune disease. Epstein-Barr Nuclear Antigen 1 (EBNA1) is the viral-encoded DNA binding protein required for viral episome maintenance and DNA replication during latent infection in proliferating cells. EBNA1 is known to be a highly stable protein, but its mechanism of protein stability is not completely understood. Proteomic analysis of EBNA1 revealed interaction with Procollagen Lysine-2 Oxoglutarate 5 Dioxygenase (PLOD) family of proteins. Depletion of PLOD1 by shRNA or inhibition with small molecule inhibitors 2,-2 dipyridyl resulted in the loss of EBNA1 protein levels, along with a selective growth inhibition of EBV-positive lymphoid cells. PLOD1 depletion also caused a loss of EBV episomes from latently infected cells and inhibited oriP-dependent DNA replication. We used mass spectrometry to identify EBNA1 peptides with lysine hydroxylation at K460 or K461. Mutation of K460 to alanine or arginine abrogates EBNA1-driven DNA replication of oriP, while K461 mutations enhanced replication. These findings suggest that PLOD1 is a novel post-translational regulator of EBNA1 protein stability and function in viral plasmid replication, episome maintenance and host cell survival. ImportanceEBNA1 is essential for EBV latent infection and implicated in viral pathogenesis. We found that EBNA1 interacts with PLOD family of lysine hydroxylases and that this interaction is required for EBNA1 protein stability and function in viral persistence during viral latent infection. Identification of PLOD1 regulation of EBNA1 protein stability provide new opportunity to target EBNA1 for degradation in EBV associated disease.

molecular biology↗

bioRxiv2021

Selective abrogation of S6K2 maps lipid homeostasis as a survival vulnerability in MAPKi-resistant NRASmut melanoma

Although oncogenic NRAS activates MAPK signaling, inhibition of the MAPK pathway is not therapeutically efficacious in NRAS-mutant tumors. Here we report that silencing the ribosomal protein S6 kinase 2 (S6K2), while preserving the activity of S6K1, perturbs lipid metabolism, enhances fatty acid unsaturation, and triggers lethal lipid peroxidation selectively in NRAS-mutant melanoma cells that are resistant to MAPK inhibition. S6K2 depletion induces ER stress, and PPAR activation, triggering cell death selectively in MAPKi-resistant melanoma. We show that combining PPAR agonists and polyunsaturated fatty acids phenocopies the effects of S6K2 abrogation, blocking tumor growth in PDX and immunocompetent mouse pre-clinical models. Collectively, our study establishes S6K2 and its effector subnetwork as promising targets for NRAS-mutant melanoma that are resistant to global MAPK pathway inhibitors. One Sentence SummaryS6K2 is a vulnerability in MAPK inhibitor-resistant NRAS-mutant melanoma

cancer biology↗

bioRxiv2019

Uncovering thousands of new HLA antigens and phosphopeptides with deep learning-based sequence-mask-search de novo peptide sequencing framework

Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpected processing of RNAs and proteins. De novo peptide sequencing approaches address this limitation but often suffer from low accuracy and require extensive validation by experts. Here, we develop SMSNet, a deep learning-based hybrid de novo peptide sequencing framework that achieves >95% amino acid accuracy while retaining good identification coverage. Applications of SMSNet on landmark proteomics and peptideomics studies reveal over 10,000 previously uncharacterized HLA antigens and phosphopeptides and in conjunction with database-search methods, expand the coverage of peptide identification by almost 30%. The power to accurately identify new peptides of SMSNet would make it an invaluable tool for any future proteomics and peptidomics studies - especially cancer neoantigen discovery and proteome characterization of non-model organisms.

bioinformatics↗