Healthcare data are rapidly evolving with the introduction of new modalities and an exponential increase in volume. Current health data storage and communication services face major obstacles in terms of privacy, security, and operational efficiency in the face of this new data landscape. Blockchain technology, characterized by its immutability, auditability, and decentralization, is emerging as a promising solution. However, integrating blockchain into existing systems presents significant challenges, particularly regarding data privacy and scalability. This review aims to provide a comprehensive understanding of how blockchain technology can transform the biomedical sector, potentially making healthcare data management more secure and efficient.

The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.

There are major efforts underway to make genome sequencing a routine part of clinical practice. A critical barrier to these is achieving practical solutions for data ownership and integrity. Blockchain provides solutions to these challenges in other realms, such as finance. However, its use in genomics is stymied due to the difficulty in storing large-scale data on-chain, slow transaction speeds, and limitations on querying. To overcome these roadblocks, we developed a private blockchain network to store genomic variants and reference-aligned reads on-chain. It uses nested database indexing with an accompanying tool suite to rapidly access and analyze the data.

The efficacy of ALVAC-based HIV and SIV vaccines in humans and macaques correlates with antibodies to envelope variable region 2 (V2). We show here that vaccine-induced antibodies to SIV variable region 1 (V1) inhibit anti-V2 antibody-mediated cytotoxicity and reverse their ability to block V2 peptide interaction with the α4β7 integrin. SIV vaccines engineered to delete V1 and favor an α helix, rather than a β sheet V2 conformation, induced V2-specific ADCC correlating with decreased risk of SIV acquisition. Removal of V1 from the HIV-1 clade A/E A244 envelope resulted in decreased binding to antibodies recognizing V2 in the β sheet conformation. Thus, deletion of V1 in HIV envelope immunogens may improve antibody responses to V2 virus vulnerability sites and increase the efficacy of HIV vaccine candidates.

[This corrects the article DOI: 10.1016/j.csbj.2018.09.003.].

Cullin-RING ligases (CRLs) control key cellular processes by promoting ubiquitylation of a multitude of soluble cytosolic and nuclear proteins. Subsets of CRL complexes are recruited and activated locally at cellular membranes; however, few CRL functions and substrates at these distinct cellular compartments are known. Here, we use a proteomic screen to identify proteins that are ubiquitylated at cellular membranes and found that Lunapark, an endoplasmic reticulum (ER)-shaping protein localized to ER three-way junctions, is ubiquitylated by the CRL3(KLHL12) ubiquitin ligase. We demonstrate that Lunapark interacts with mechanistic target of rapamycin complex-1 (mTORC1), a central cellular regulator that coordinates growth and metabolism with environmental conditions. We show that mTORC1 binds Lunapark specifically at three-way junctions, and lysosomes, where mTORC1 is activated, make contact with three-way junctions where Lunapark resides. Inhibition of Lunapark ubiquitylation results in neurodevelopmental defects indicating that KLHL12-dependent ubiquitylation of Lunapark is required for normal growth and development.

AIM:High-throughput phenotypic screens have emerged as a promising avenue for small-molecule drug discovery. The challenge faced in high-throughput phenotypic screens is target deconvolution once a small molecule hit is identified. Chemogenomics libraries have emerged as an important tool for meeting this challenge. Here, we investigate their target-specificity by deriving a 'polypharmacology index' for broad chemogenomics screening libraries.METHODS:All known targets of all the compounds in each library were plotted as a histogram and fitted to a Boltzmann distribution, whose linearized slope is indicative of the overall polypharmacology of the library.RESULTS & CONCLUSION:Comparison of libraries clearly distinguished the most target-specific library, which might be assumed to be more useful for target deconvolution in a phenotypic screen.

Cellular stress signals activate adaptive signaling pathways of the mammalian integrated stress response (ISR), of which the unfolded protein response (UPR) is a subset. These pathways converge at the phosporylation of eIF2α. Drug-like, potent and selective chemical inhibitors (valid chemical probes) targeting major ISR kinases have been previously identified, with the exception of GCN2. We synthesized and evaluated a series of GCN2 inhibitors based on a triazolo[4,5-d]pyrimidine scaffold. Several compounds potently inhibited GCN2 in vitro and displayed good selectivity over the related kinases PERK, HRI, and IRE1. The compounds inhibited phosporylation of eIF2α in HEK293T cells with an IC50 < 150 nM, validating them as chemical probes for cellular studies. These probes were screened against the National Cancer Institute NCI-60 human cancer cell line panel. Uniform growth inhibition was observed in the leukemia group of cell lines. Growth inhibition in the most sensitive cell lines coincided with high GCN2 mRNA expression levels. Oncomine analysis revealed high GCN2 expression accompanied by lower asparagine synthetase (ASNS) expression in patient-derived acute lymphoblastic leukemias with B-Cell origins (B-ALL) as well. Notably, asparaginase, which depletes amino acids and triggers GCN2 activity, is a licensed, first-line B-ALL treatment. Thus, we hypothesize that leukemias exhibiting high GCN2 expression and low ASNS expression may be susceptible to pharmacologic GCN2 inhibition.

Skp2 is a member of the F-box family of proteins that serve as substrate-specific adaptors in Skp1-CUL1-ROC1-F-box (SCF) E3 ubiquitin ligases. Skp2 (Fbxl1) directly binds to the tumor suppressor p27 in the context of the SCFSkp2 E3 ubiquitin ligase to ubiquitylate and target-phosphorylated p27 for proteasomal degradation. As p27 is a powerful suppressor of growth in a variety of cells, and as Skp2 is also overexpressed in many human cancers, Skp2 is considered an oncogene and an intriguing drug target. However, despite 20 years of investigation, a valid chemical inhibitor of Skp2-mediated degradation of p27 has not been identified. Recently, an increasing number of compounds designed to have this bioactivity have been reported. Here, we conduct a meta-analysis of the evidence regarding bioactivity, structure, and medicinal chemistry in order to evaluate and compare these Skp2 inhibitor compounds. Despite chemically diverse compounds with a wide array of Skp2-mediated p27 ubiquitylation inhibition properties reported by several independent groups, no current chemical probe formally qualifies as a validated pharmaceutical hit compound. This finding suggests that our knowledge of the structural biochemistry of the Skp2-p27 complex remains incomplete and highlights the need for novel modes of inquiry.

Abstract Cellular stress signals activate adaptive signaling pathways of the mammalian integrated stress response (ISR), which converge at the phosporylation of eIF2α. Drug-like chemical inhibitors targeting major ISR kinases have been identified, with the exception of GCN2. We synthesized and evaluated a series of GCN2 inhibitors based on a triazolo[4,5-d]pyrimidine scaffold. Several compounds potently inhibited GCN2 in vitro in orthogonal assays and displayed good selectivity over the related kinases PERK, HRI, and IRE1. The compounds had low solubility at pH 7.4, but sufficient permeability to inhibit phosporylation of eIF2α in HEK293T cells with an IC50 < 150 nM. In a screen of the NCI-60 cancer cell line panel, the leukemia cells were the only group of cancer cell lines to uniformly exhibit growth inhibition. Given the previously reported genetic association of Gcn2 with resistance to asparaginase, which is a first line clinical leukemia therapy, pharmacologic inhibition of Gcn2 may overcome resistance to asparaginase treatment in leukemia. Citation Format: Lea Lough, Dan Sherman, Eric Ni, Palaniraja Thandapani, Ioannis Aifantis, Timothy Cardozo. Evaluation of GCN2 chemical probes: Activity in leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2385.

Genome sequencing studies have revealed a number of cancer-associated mutations in the telomere-binding factor POT1. Here, we show that when combined with p53 deficiency, depletion of murine POT1a in common lymphoid progenitor cells fosters genetic instability, accelerates the onset, and increases the severity of T cell lymphomas. In parallel, we examined human and mouse cells carrying POT1 mutations found in cutaneous T cell lymphoma (CTCL) patients. Inhibition of POT1 activates ATR-dependent DNA damage signaling and induces telomere fragility, replication fork stalling, and telomere elongation. Our data suggest that these phenotypes are linked to impaired CST (CTC1-STN1-TEN1) function at telomeres. Lastly, we show that proliferation of cancer cells lacking POT1 is enabled by the attenuation of the ATR kinase pathway. These results uncover a role for defective telomere replication during tumorigenesis.

Molecular profiling of human diseases has been approached at the genetic (DNA), expression (RNA), and proteomic (protein) levels. An important goal of these efforts is to map observed molecular patterns to specific, mechanistic organic entities, such as loci in the genome, individual RNA molecules or defined proteins or protein assemblies. Importantly, such maps have been historically approached in the more intuitive context of a theoretical individual cell, but diseases are better described in reality using an in vivo framework, namely a library of several tissue‐specific maps. In this article, we review the existing data atlases that can be used for this purpose and identify critical gaps that could move the field forward from cellular to in vivo dimensions. WIREs Syst Biol Med 2016, 8:472–484. doi: 10.1002/wsbm.1354This article is categorized under: Biological Mechanisms > Chemical Biology Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > Proteomics Methods