Endoplasmic reticulum stress and cell death in mTORC1-overactive cells is induced by nelfinavir and enhanced by chloroquine

Inappropriate activation of mammalian/mechanistic target of rapamycin complex 1 (mTORC1) is common in cancer and has many cellular consequences including elevated endoplasmic reticulum (ER) stress. Cells employ autophagy as a critical compensatory survival mechanism during ER stress. This study utilised drug-induced ER stress through nelfinavir in order to examine ER stress tolerance in cell lines with hyper-active mTORC1 signalling. Our initial findings in wild type cells showed nelfinavir inhibited mTORC1 signalling and upregulated autophagy, as determined by decreased rpS6 and S6K1 phosphorylation, and SQTSM1 protein expression, respectively. Contrastingly, cells with hyper-active mTORC1 displayed basally elevated levels of ER stress which was greatly exaggerated following nelfinavir treatment, seen through increased CHOP mRNA and XBP1 splicing. To further enhance the effects of nelfinavir, we introduced chloroquine as an autophagy inhibitor. Combination of nelfinavir and chloroquine significantly increased ER stress and caused selective cell death in multiple cell line models with hyper-active mTORC1, whilst control cells with normalised mTORC1 signalling tolerated treatment. By comparing chloroquine to other autophagy inhibitors, we uncovered that selective toxicity invoked by chloroquine was independent of autophagy inhibition yet entrapment of chloroquine to acidified lysosomal/endosomal compartments was necessary for cytotoxicity. Our research demonstrates that combination of nelfinavir and chloroquine has therapeutic potential for treatment of mTORC1-driven tumours

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Loss of tuberous sclerosis complex 2 sensitizes tumors to nelfinavir−bortezomib therapy to intensify endoplasmic reticulum stress-induced cell death

Cancer cells lose homeostatic flexibility because of mutations and dysregulated signaling pathways involved in maintaining homeostasis. Tuberous Sclerosis Complex 1 (TSC1) and TSC2 play a fundamental role in cell homeostasis, where signal transduction through TSC1/TSC2 is often compromised in cancer, leading to aberrant activation of mechanistic target of rapamycin complex 1 (mTORC1). mTORC1 hyperactivation increases the basal level of endoplasmic reticulum (ER) stress via an accumulation of unfolded protein, due to heightened de novo protein translation and repression of autophagy. We exploit this intrinsic vulnerability of tumor cells lacking TSC2, by treating with nelvinavir to further enhance ER stress while inhibiting the proteasome with bortezomib to prevent effective protein removal. We show that TSC2-deficient cells are highly dependent on the proteosomal degradation pathway for survival. Combined treatment with nelfinavir and bortezomib at clinically relevant drug concentrations show synergy in selectively killing TSC2-deficient cells with limited toxicity in control cells. This drug combination inhibited tumor formation in xenograft mouse models and patient-derived cell models of TSC and caused tumor spheroid death in 3D culture. Importantly, 3D culture assays differentiated between the cytostatic effects of the mTORC1 inhibitor, rapamycin, and the cytotoxic effects of the nelfinavir/bortezomib combination. Through RNA sequencing, we determined that nelfinavir and bortezomib tip the balance of ER protein homeostasis of the already ER-stressed TSC2-deficient cells in favor of cell death. These findings have clinical relevance in stratified medicine to treat tumors that have compromised signaling through TSC and are inflexible in their capacity to restore ER homeostasis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Biological heterogeneity in idiopathic pulmonary arterial hypertension identified through unsupervised transcriptomic profiling of whole blood

Idiopathic pulmonary arterial hypertension (IPAH) is a rare but fatal disease diagnosed by right heart catheterisation and the exclusion of other forms of pulmonary arterial hypertension, producing a heterogeneous population with varied treatment response. Here we show unsupervised machine learning identification of three major patient subgroups that account for 92% of the cohort, each with unique whole blood transcriptomic and clinical feature signatures. These subgroups are associated with poor, moderate, and good prognosis. The poor prognosis subgroup is associated with upregulation of the ALAS2 and downregulation of several immunoglobulin genes, while the good prognosis subgroup is defined by upregulation of the bone morphogenetic protein signalling regulator NOG, and the C/C variant of HLA-DPA1/DPB1 (independently associated with survival). These findings independently validated provide evidence for the existence of 3 major subgroups (endophenotypes) within the IPAH classification, could improve risk stratification and provide molecular insights into the pathogenesis of IPAH

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.peer-reviewe