Science news

Cancer Cell: A Pan-Cancer Proteogenomic Atlas of PI3K/AKT/mTOR Pathway Alterations (Zhang et al.) – an important contribution to the cancer literature; this study takes advantage of the recent completion of the data generation stage of the The Cancer Genoem Atlas (TCGA) and performs a systematic analysis of the PI3K/AKT/mTOR pathway in over 10,000 cancer, covering 32 different major cancer types. It examines mutated genes via whole-exome/genome sequencing, transcriptomics data (RNAseq) and candidate signalling data with reverse-phase protein arrays. It is a data-dense study, but I will just highlight a few points that were interesting to me. Although activities in the PI3K/AKT and mTOR pathways were highly correlated in multiple cancer, there were also instances with evidence for some decoupling. Moreover, this study provides some high-throughput functional characterisation of a larger set of activating PIK3CA mutations in two different immortalised cell lines; one caveat with this functional analysis, however, is the fact that it relies on overexpression of the mutated proteins. Nevertheless, as the setting is the same for all tested variants, it allows for direct comparisons among them to be made – and such comparisons are quite useful as there is very limited data on the functional significance of different PIK3CA mutations beyond the well-known hotspot variants. Overall, the large sample size used to generate this data provides substantial power to detect meaningful patterns that can be used to stratify variants in the clinical setting.

Nature: TRAF2 and OTUD7B govern a ubiquitin-dependent switch that regulates mTORC2 signalling (Wang et al.) – a key paper and really worth a read (or at least of key points as it is quite data dense!!). Probably one of the most comprehensive papers on mTORC2 that I have seen that also links it to relevant (patho)physiology. Very interesting that growth factors (incl. insulin) tip the balance between mTORC2 and mTORC1 formation, favouring mTORC2 which then drives increased AKT activation. Evidence provided that this is relevant in conditions of PI3K/AKT hyperactivation. Very interesting!! Also, noted that they use HEK293s in multiple experiments and manage to look at PI3K/AKT signalling after serum starving these for 16h.. Usually these cells exhibit hyperactivation of this pathway, but the control conditions here show no sign of this?

Science: A subcellular map of the human proteome (Thul et al.) – an important atlas-like resource, essentially an image-based map of the subcellular proteome based on transcriptomics, immunofluorescence and mass spectrometry. It is quite impressive, the data covers 12,0003 proteins using a panel of 22 human cell lines and 13,993 antibodies. Also, they have managed to get the images annotated through a Citizen Science approach via massive multiplayer game with participation from over 180,000 worldwide players! This dataset is actually quite important as it allows for more refined interaction networks to be constructed. The interactive resources can be accessed here: http://www.proteinatlas.org

Science: ATP as a biological hydrotrope (Patel et al.) – haven’t read beyond abstract, but interesting because it seems to suggest a role for ATP in protein solubilisation within cells. (Hydrotorope = amphiphilic molecules with low cooperativity and millimolar working concentrations, differentiating them from surfactants ➡ act to solubilise hydrophobic molecules in acqueous solutions).

Science Signalling: p53 dynamics in response to DNA damage vary across cell lines and are shaped by efficiency of DNA repair and activity of the kinase ATM (Stewart-Ornstein, J. and Lahav, G.) ➡ this study highlights an issue that is worth keeping in mind whenever a cell biology paper is examined: signalling dynamics do differ across cell lines, hence using a single cell lines as model system for a major phenomenon might not yield results that are broadly applicable. This paper has also got some mathematical modelling for those interested in that. I must admit that I have not read it in much detail and I am unable to comment on the computational approach.

Diabetes: Mechanisms of Insulin Resistance in Primary and Secondary Non-Alcoholic Fatty Liver (Jelenik et al.) ➡ can’t usually access, but here is the abstract:

“Non-alcoholic fatty liver disease (NAFLD) is associated with hepatic insulin resistance and may result primarily from increased hepatic de novo lipogenesis (PRIM) or secondarily from adipose-tissue lipolysis (SEC). We studied mice with hepatocyte- or adipocyte-specific sterol regulatory-element binding protein-1c (SREBP-1c) overexpression as models of PRIM and SEC. PRIM mice featured increased lipogenic gene expression in liver and adipose tissue. Their selective, liver-specific insulin resistance was associated with increased C18:1-diacylglycerol (DAG) content and protein kinase C (PKC)ε translocation. SEC mice had decreased hepatic ChREBP-mediated lipogenesis and featured portal/lobular inflammation along with total, whole-body insulin resistance. Hepatic mitochondrial respiration transiently increased and declined with aging along with higher muscle reactive oxygen species production. In conclusion, hepatic insulin resistance originates from lipotoxicity but not from lower mitochondrial capacity, which can even transiently adapt to increased peripheral lipolysis. Peripheral insulin resistance is prevented during increased hepatic lipogenesis, only if adipose tissue lipid storage capacity is preserved.”

Nature Cell Biology Endoglin prevents vascular malformation by regulating flow-induced cell migration and specification through VEGFR2 signalling (Jin et al.)

Cell Reports: Widespread Mitotic Bookmarking by Histone Marks and Transcription Factors in Pluripotent Stem Cells (Liu et al.) – interesting paper that demonstrates that one of the mechanisms whereby the core stemness factor OCT4 maintains pluripotency is by bookmarking stemness genes during mitosis, i.e. a memory mechanisms that allows for re-expression of these genes when mitosis is completed. This is important in stem cells due to their unusual cell cycle characteristics (10-12h cycling, no G0 phase and very short G1 phase). I find one of their approaches quite cool – testing the effect of specifically degrading OCT4 during mitosis by fusing OCT4 to a Cyclin destruction box.

Nature Protocols: FISH-Flow, a protocol for the concurrent detection of mRNA and protein in single cells using fluorescence in situ hybridization and flow cytometry (Arrigucci et al.) note that this is only applicable for non-adherent cell types at the moment)

eLife: Addressing the ethical issues raised by synthetic human entities with embryo-like features (Aach et al.) – interesting read, I think…

 

 

 

This week’s interesting science

Nature: Common genetic variation drives molecular heterogeneity in human iPSCs (Kilpinen et al.). The first results form the large-scale HipSci initiative funded by Wellcome.

A very interesting Nature study on vascular development and how it is regulated by FGF-dependent control of metabolism (glycolysis) via Myc: FGF-dependent metabolic control of vascular development (Yu et al. 2017). Here is a copy of the final conclusion of the paper: The FGF/MYC/HK2-dependent regulation of vascular development is unexpected. Previously, FGF activity has been linked to prevention of endothelium-to-mesenchymal transition both in the lymphatic is unexpected. Previously, FGF activity has been linked to prevention of endothelium-to-mesenchymal transition both in the lymphatic16 and in the systemic vasculature17, injury response18 and maintenance of endothelium-to-mesenchymal transition both in the lymphatic and in the systemic vasculature, injury response18 and maintenance of vascular integrity19. While the FGFR1 and FGFR3 are the receptors and in the systemic vasculature17, injury response18 and maintenance of vascular integrity19. While the FGFR1 and FGFR3 are the receptors involved, which of the 22 FGF family members is responsible for the required FGF signalling input is not known. In summary, FGF signalling regulates blood and lymphatic vascular development through control of endothelial metabolism driven by MYC-dependent regula-tion of HK2 expression. Therapeutic targeting of this FGF–MYC–HK2 pathway may open new possibilities for treatment of diseases associated with insufficient or excessive vascular growth.

Just out in Nature Medicine: Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients (Zehir et al. 2017) ➡ Interesting recurrence of certain well-known oncogenes (e.g. PIK3CA) across a range of tumour types, irrespective of lineage, but also very interesting to see how mutations in certain oncogenes are absent from specific tumour histotypes. TP53 mutations top the list and correlate positively with more aggressive cancers. Most of the TP53 mutations were inactivating due to truncation or altered splicing. Second on the list is KRAS G12 followed by PIK3CA H1047R and E545K.

Cell Metabolism: PPARδ Promotes Running Endurance by Preserving Glucose (Fan et al. 2017). Just skimmed through, looks quite comprehensive. PPARd orchestrates the transcriptional switch to fat utilisation and glucose sparing in response to exercise.

Cell Metabolism: DNA-PK Promotes the Mitochondrial, Metabolic, and Physical Decline that Occurs During Aging (Park et al. 2017) – a mechanism that involves phosphorylation of Hsp90 and inhibition of AMPK.

An interesting paper in Cell (Stem Cell Lineage Infidelity Drives Wound Repair and Cancer by Ge et al.) that uncovers how tumour cells hijack normal wound repair processes which under normal circumstances allow for transient stem cell lineage infidelity. In contrast, a pre-cancerous stem cells are locked into this plastic state, giving rise to excessive growth and ultimately full-blown cancer.

Nature Protocols: Assessment of engineered cells using CellNet and RNA-seq (Radley et al. 2007) – a how-to-guide for the computational platform CellNet, which allows one to upload one RNAseq data from a particular cell type / stage and compare it to large datasets on different cell types. This should be very useful for estimation of cell fate transitions in response to different differentiation perturbations.

 

eLife: Synthetically modified guide RNA and donor DNA are a versatile platform for CRISPR-Cas9 engineering (Lee et al. 2017). These guys test different modifications of sgRNAs and ssODN repair templates and show that they can be tolerated. For instance, they tag the ssODN with an Alexa-647 which allows them to enrich for cells that have been successfully transfected with the repair template. They also manage to fuse the sgRNA and ssODN template to each other, complex these with Cas9 (RNP), and show that this improved cellular delivery based on cationic polymers. However, note that despite this improval the efficiency of gene editing is still lower compared to nucleofection/electroporation under comparable conditions.

Nature Methods: CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets (Tsai et al. 2017). A new genome-wide method is described for the assessment of CRISPR off-target effects in vitro and following tag integration into host cell DNA. Much more sensitive compared to previous methods that achieved whole-genome assessment of off-target effects. A second study in Nature Methods reports on a different method (SITE-seq) that also aims to profile genome-wide off-target effects with high sensitivity: Mapping the genomic landscape of CRISPR–Cas9 cleavage (Cameron et al. 2017). However, the specificity of Cas9-mediated gene editing in a cell will also be highly cell-specific and depend  on the concentration of enzyme and additional components that are delivered for gene editing (sgRNA, ssODN etc.). The effect of increasing sgRNA and Cas9 concentrations in vitro is assessed in the biochemical assay reported by Cameron et al. Both of the above methods achieve a much higher sensitivity of off-target site detection because they specifically enriched for DNA fragments associated with Cas9 cleavage prior to sequencing (i.e. all the random background is removed). Once such off-targets are identified genome-wide, they can be interrogated in any cell line that has been edited – many will, however, remain intact in the cell because of the effects of chromatin on target accessibility as well as cell-specific DNA repair mechanisms.

 

The science round-up of the week

Nature & Nature++

The implications of this Nature paper from last week are major for the stem cell community: Human pluripotent stem cells recurrently acquire and expand dominant negative P53 mutations (Merkle et al. 2017).

Nature Genetics: Adiposity amplifies the genetic risk of fatty liver disease conferred by multiple loci (Stender et al. 2017)

Nature Genetics: Pathogenic variants that alter protein code often disrupt splicing (Soemedi et al. 2017). Copied from abstract: “We analyzed 4,964 published disease-causing exonic mutations using a massively parallel splicing assay (MaPSy), which showed an 81% concordance rate with splicing in patient tissue. Approximately 10% of exonic mutations altered splicing, mostly by disrupting multiple stages of spliceosome assembly. We present a large-scale characterization of exonic splicing mutations using a new technology that facilitates variant classification and keeps pace with variant discovery.” I can’t even imagine how expensive this study must have been…

Nature Reviews Endocrinology: Metric for glycaemic control – from HbA2c to continuous glucose monitoring. Copied from abstract so you can decide if relevant or not: “I focus on markers of average glycaemia and the utility and/or shortcomings of HbA1c as a ‘gold-standard’ metric of glycaemic control; the notion that glucose variability is characterized by two principal dimensions, amplitude and time; measures of glucose variability that are based on either self-monitoring of blood glucose data or continuous glucose monitoring (CGM); and the control of average glycaemia and glucose variability through the use of pharmacological agents or closed-loop control systems commonly referred to as the ‘artificial pancreas’. I conclude that HbA1c and the various available metrics of glucose variability reflect the management of diabetes mellitus on different timescales, ranging from months (for HbA1c) to minutes (for CGM).”

Nature Cell Biology: Cell Competition with normal epithelial cells promotes apical extrusion of transformed cells through metabolic changes (Kon et al. 2017). This very interesting for the benign-malignant paradox that refers to the occurrence of cancerous mutations in benign disease without further progression to cancer. Here is a copy of the abstract (I read the paper, and it seems solid experimentally although they perform all the wrong statistics throughout!!): “Recent studies have revealed that newly emerging transformed cells are often apically extruded from epithelial tissues. During this process, normal epithelial cells can recognize and actively eliminate transformed cells, a process called epithelial defence against cancer (EDAC). Here, we show that mitochondrial membrane potential is diminished in RasV12-transformed cells when they are surrounded by normal cells. In addition, glucose uptake is elevated, leading to higher lactate production. The mitochondrial dysfunction is driven by upregulation of pyruvate dehydrogenase kinase 4 (PDK4), which positively regulates elimination of RasV12-transformed cells. Furthermore, EDAC from the surrounding normal cells, involving filamin, drives the Warburg-effect-like metabolic alteration. Moreover, using a cell-competition mouse model, we demonstrate that PDK-mediated metabolic changes promote the elimination of RasV12-transformed cells from intestinal epithelia. These data indicate that non-cell-autonomous metabolic modulation is a crucial regulator for cell competition, shedding light on the unexplored events at the initial stage of carcinogenesis.” There is a news & and views as well: “Metabolic changes promote rejection of oncogenic cells.”

Nature Cell Biology: Metabolic control of primed human pluripotent stem cell fate and function by the miR-200c-SIRT2 axis (Cha et al. 2017). After a quick skim, seems OK overall, except that I don’t trust the qPCR results because of the way they are represented. Would be great if people could stop normalising to samples where a gene is not expressed anyway (we have all been taught basic maths and know that you can’t divide by 0)… Not an attack on this study only, but on most qPCR studies these days. There is also a news&views on this paper in Nature Cell Biology as well (SIRT2 and glycolytic enzyme acetylation in pluripotent stem cells). What is interesting, though, is this whole concept of a glycolytic-acetyl-coA switch that could interact with the epigenetics of stem cells and their cell fate decisions.

Nature Cell Biology: SWELL1 is a regulator of adipocyte size, insulin signalling and glucose homeostasis. Can’t actually access the actual article 😦 It says aop, not sure what it means, though.

Cell Metabolism 

For those of us with a sweet tooth (a pathological tendency to snack!!),  FGF21 Is a Sugar-Induced Hormone Associated with Sweet Intake and Preference in Humans (Søberg, Sandholt et al. 2017). The gist of it is that there are human genetic variants in FGF21 that increase sweet preference, but surprisingly they do not correlate with obesity/diabetes. I found some of the points in the Introduction interesting – those regarding the difference between mouse and human FGF21 biology. So a word of caution when it comes to metabolism and species-specific differences!

From the Japanese iPSCs experts on the effect of metabolism on pluripotency states, published in Cell Metabolism: Hybrid Cellular Metabolism Coordinated by Zic3 and Esrrb Synergistically Enhances Induction of Naive Pluripotency (Sone et al. 2017). Currently, a hot topic in the stem cell field is the notion of naive vs primed pluripotency. Human iPSCs and ESCs are thought to be “primed”, i.e. more lineage-restricted and corresponding to the post-implantation epiblast state, compared to mouse counterparts which correspond to pre-implantation embryonic cells. Mouse ESCs can be induced to become even more naive (so can human ESCs/iPSCs as of recently) with certain small molecules or by genetic perturbation. Interestingly, whereas more primed stem cells rely on glycolysis, and low rates of oxidative phosphorylation, naive pluripotency seems to require both glycolysis and oxidative phosphorylation. This balance is now shown to depend on the synergy between the transcription factors Zic3 and Esrrb which both activate glycolysis genes, but have opposite effects on OXPHOS. It is really interesting to follow the metabolic theme in stem cells – the ability of cells to shift their metabolism is emerging as an important prerequisite for appropriate cell fate regulation. Also, although this study determines that both glycolysis and OXPHOS need to be ON for efficient reprogramming of mouse fibroblasts to naive stem cells, it still doesn’t have the answer as to why this is the case. Technically, this study is also quite neat – done well! Although quite interesting to see raw Ct values being reported as opposed to log-transformed derivatives (BUT great that the spread of the data is shown properly and SDs are used!).

A review on “Autophagy and Tumour Metabolism” (Kimmelman & White, 2017) ➡ interesting, examining both cell-autonomous and non-cell-autonomous effects. This field is also seeing a shift in perception, recognising that autophagy may be tumour-suppressive at the early stages of tumour initiation, but promote tumour growth at later stages (possibly due to systemic interactions of the cancer with non-cancerous tissues).

A review of “Metabolic Flexibility in Health and Disease” (Goodpaster & Sparks, 2017) that will interest quite a few people as it examines fasting/refeeding paradigms and emphasises the role of skeletal muscle and adipose tissue. It also briefly examines evidence for and against the importance of individual tissues for the development of insulin resistance.