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Week 2 in the Books!

Hello my fellow Abstract Watchers! It was yet another snowy week in Park City and my morale was low, so it was tough to do Abstract Watch daily (I didn't) even though it was a much-needed respite and reset. I did play catch-up towards the end of the week. I've found that this habit, like running, is about showing up, that some days are better than others, and even a little progress is still progress. Be kind to yourself, let yourself off the hook and if all you do is read the Abstract that is okay. You don't need to have some profound insight or comment or set a personal record, you just need to do it. It's good, it will make you feel better because you lived up to your own promise and you learned something new.

 

Once again I appreciated any papers that were either open access or had a preprint. That being said, I know that I am personally using the preprints just for that - for open access, not to accelerate my research (obviously). I think this is an important thing to keep in mind, that different people use preprints for different reasons. I very much appreciate journal curation, there is no way that I would be able to sift through a preprint server and pinpoint the biggest breakthroughs. This does *not* mean that I think we should stratify scientists based on a big breakthrough or an 'incrimental advance' - but again points to the needs of a specific population that I represent (probably also journalists and maybe even many scientists who just want to keep their finger on the pulse). I know there are other venues (Twitter recommendations, for instance), but those are (to me) another form of curation. 

 

I did notice that preprints were generally online 3-12 months ahead of the publication. Interestingly, time to publication was slower for eLife than for Molecular Cell and Nature. Perhaps that's not so unexpected and has to do with different mandates at different journals, but it does suggest to me that scientists use preprints for different reasons. I found it a little ironic that if preprints accelerate sharing findings prior to publication, *on the surface* they accelerate more for eLife than the 'prestige' journals. 

 

Because the reviews were available for the eLife paper, I did note that data were added to the published version compared to the preprint, but the title and abstract were identical.

 

Happy Reading!

 

Ang

 

AbstractWatch #7 Opposing roles of hepatic stellate cell subpopulations in hepatocarcinogenesis (no preprint, published in Nature) Patients with a chronic liver disease (e.g. cirrhosis, hepatitis, non-alcoholic fatty liver disease) develop scar tissue (fibrosis) and are at increased risk for liver cancer. Although fibrosis precedes cancer, how it causes cancer and, how to stop this process, were poorly understood. Hepatic stellate cells are the main source of liver fibroblasts, and the paper shows that they are enriched in the preneoplastic environment, closely interacting with hepatocytes (the source of liver cancer). They show that quiescent and cytokine-producing hepatic stellate cells express hepatocyte growth factor, which protected against hepatocyte death and liver cancer initiation, but activated myofibroblastic hepatic stellate cells expressed Type I collagen, which promoted hepatocyte proliferation and cancer initiation. Type I collagen led to increased stiffness and activation of the transcription co-activator TAZ (Hippo pathway) in pretumoural hepatocytes (promoting proliferation). Collagen also led to activation of discoidin domain receptor 1 in established tumours. An increased imbalance between cytokine-producing and myofibroblastic hepatic stellate cells in chronic liver disease was associated with increased liver cancer risk in patients. Restoring stellate cell balance likely won’t affect cancer progression (activated stellate cells did not seem to play a role in cancer progression once the tumour has developed), but it could reduce the risk of cancer initiation.  

 

AbstractWatch #8 Collagenolysis-dependent DDR1 signalling dictates pancreatic cancer outcome (preprint on biorxiv 6 months earlier than publication in Nature) Pancreatic ductal adenocarcinoma (PDAC) is a highly desmoplastic (causing or forming adhesions or fibrous connective tissue within a tumor) & aggressive cancer that frequently progresses and spreads by metastasis to the liver. Cancer-associated fibroblasts, the extracellular matrix and type I collagen (Col I) can support or restrain the progression of PDAC. The authors show that matrix-metalloprotease-cleaved Col I (cCol I) and intact Col I (iCol I) exert opposing effects on PDAC bioenergetics, tumour growth and metastasis. Whereas cCol I activates discoidin domain receptor 1 (DDR1)–NF-κB–p62–NRF2 mitochondrial biogenesis signaling pathway, to promote the growth of PDAC, iCol I triggers the degradation of DDR1 and restrains the growth of PDAC. Patients whose tumours are enriched for iCol I and express low levels of DDR1 and NRF2 have improved median survival compared to those whose tumours have high levels of cCol I, DDR1 and NRF2. Inhibition of the DDR1-stimulated expression of NF-κB or mitochondrial biogenesis blocks tumorigenesis in wild-type mice, but not in mice that express MMP-resistant Col I. Targeting the Col I–DDR1–NF-κB–NRF2 mitochondrial biogenesis pathway could provide therapeutic opportunities for a subset of patients.

 

Ang take: While I liked both these papers above, it seemed we already knew that fibroblasts, ECM and the microenvironment could exert opposing effects. These papers provide some insight into when and how, but again what they found seems consistent with published literature. So for me, I wasn’t sure about Nature per se but of course am happy for them and think these advances are important 😊 I could be missing something, and did note the convergence of collagen activating DDR1 in both liver & pancreatic cancer that might get to shared molecular mechanisms & therapies (& the convergence is perhaps more interesting given that pancreatic cancer – like many cancers – metastasize to liver, so one wonders if the homing of cancers to liver might involve DDR1 and a hospitable microenvironment for these cancer cells in liver…)

 

AbstractWatch #9 Condensed-phase signaling can expand kinase specificity and respond to macromolecular crowding (preprint on biorxiv 10 months earlier than publication in Molecular Cell) Phase separation can concentrate biomolecules and accelerate reactions. However, it is difficult to understand the impact of condensation on biological regulation because mutations that disrupt LLPS or that perturb recruitment of clients to condensates can have pleiotropic effects. For example, while it is possible to mutate a protein sequence such that it fails to undergo LLPS, any associated loss of activity could be due to this loss of condensation or equally could be due to an unrelated loss of intrinsic protein function. To overcome this problem - orthogonal reconstitution of the condensation behavior. For example, reconstituting the activity and phase separation of microtubule nucleation factor TPX2 with an orthogonal disordered domain demonstrated the importance of phase-separation per se in microtubulenucleation (King and Petry, 2020).

"We engineered new phosphorylation reactions within synthetic condensates. We recruited several kinases and substrates as clients into multiple types of synthetic condensates. These kinases included the MAP kinases, ERK1 and Fus3, and the Cyclin Dependent Kinase 1, Cdk1. We generally found increased activity and broadened kinase specificity. Phosphorylation dynamics within condensates were rapid and could drive cell-cycle-dependent localization changes. High client concentration within condensates was important but not the main factor for efficient phosphorylation. Rather, the availability of many excess client-binding sites together with a flexible scaffold was crucial. Phosphorylation within condensates was also modulated by changes in macromolecular crowding. Finally, the phosphorylation of the Alzheimer’s-disease-associated protein Tau by cyclin-dependent kinase 2 was accelerated within condensates. Thus, condensates enable new signaling connections and can create sensors that respond to the biophysical properties of the cytoplasm."

 

"Condensates facilitate phosphoregulatory network rewiring. Beyond mass-action, condensate flexibility and high-densities of client binding sites are important for efficient condensed-phase signaling. Synthetic condensed-phase signaling can respond to biophysical changes. For example, the mechanisms that sense mechanical compression remain poorly understood (Delarue et al., 2018), but mechanical compression leads to increases in macromolecular crowding and we have now demonstrated that the macromolecular crowding can modulate phosphorylation rates within condensates. It will be exciting to investigate whether kinases in endogenous condensates can transduce mechanical information through these biophysical mechanisms."

Ang take: Personally I found this SUPER cool, that condensates can change substrates & networks (maybe we knew this?) and that this could provide a link between biophysical changes & signaling & gene expression. That to me has a lot of implications in development & disease.

AbstractWatch #10 Machine learning on syngeneic mouse tumor profiles to model clinical immunotherapy response (no preprint but open access in Science Advances)Most patients with cancer are refractory to immune checkpoint blockade (ICB) therapy, and proper patient stratification remains an open question. Primary patient data suffer from high heterogeneity, low accessibility, and lack of proper controls. In contrast, syngeneic mouse tumor models enable controlled experiments with ICB treatments. Using transcriptomic and experimental variables from >700 ICB-treated/control syngeneic mouse tumors, we developed a machine learning framework to model tumor immunity and identify factors influencing ICB response. Projected on human immunotherapy trial data, we found that the model can predict clinical ICB response. We further applied the model to predicting ICB-responsive/resistant cancer types in The Cancer Genome Atlas, which agreed well with existing clinical reports. Last, feature analysis implicated factors associated with ICB response. In summary, our computational framework based on mouse tumor data reliably stratified patients regarding ICB response, informed resistance mechanisms, and has the potential for wide applications in disease treatment studies.

Metagene_25 is enriched in melanoma, which has a high response rate to anti-PD1. The top-ranked genes in metagene_25 were Pdcd1, Cd8b1, and Cd3g (Fig. 5A), representative of CTL infiltration. Gene set enrichment analysis of genes in metagene_25 identified pathways of immunoregulatory interactions and antigen processing and presentation. Metagene_25 also shows a positive correlation with improved patient survival and increased CD8+ T cell infiltration. This is consistent with existing knowledge that higher antigen presentation and T cell infiltration in melanoma underlie its superior immune response and that higher intratumoral immune activity correlates with a better prognosis.

Metagene_31 is enriched in liver cancer, which has a low response rate to ICB treatment . The top genes in metagene_31 include Col2a1, Col9a1/2, and Sox8, and enriched pathways include extracellular matrix (ECM)–receptor interactions and collagens. Sox8 is a transcription factor involved in embryogenesis and is highly expressed in most hepatocellular carcinomas, where it has been shown to promote tumor cell proliferation. Tumor Immune Dysfunction and Exclusion (TIDE) analysis suggested that Sox8 is highly expressed in alternatively activated M2 tumor-associated macrophages (TAMs), which restrict intratumoral CTL infiltration. Col2a1 encodes the alpha-1 chain of type II collagen, a component of the ECM. Collagen induction has also been reported to confer immune evasion by physically impeding CTL infiltration. Moreover, metagene_31 level was positively correlated with the gene signature of alternatively activated M2 TAMs , which suppress CTL response.

AML was predicted to have a high response rate to anti-PD1, whereas GBM was predicted to have a low response rate. Metagene_19 is among the most differentially enriched metagene in these two cancer types. We reasoned that metagene_19 might be one of the major factors underlying the response in LAML and resistance in GBM. Closer examination of top-ranked genes in metagene_19 identified Trim12a and Trim5, two ortholog ubiquitin E3 ligases involved in autophagy. Autophagy has been reported to regulate antigen presentation in cancer cells and phagocytosis in antigen-presenting cells, which collectively coordinate antitumor immune responses. Moreover, our recent work using in vivo CRISPR screens identified multiple ubiquitin E3 ligases as potential regulators of ICB response through their modulation of the myeloid composition in the tumor microenvironment. Therefore, our study raises the possibility that Trim12a and Trim5 might also be involved in the proinflammatory immune responses.

Ang take: I liked this demonstration – I’m not sure if we learned a ton of new concepts/mechanisms that explain the response to immunotherapy (or lack of it) but the approach using machine learning and syngeneic mouse models to explain clinical observations is a nice proof of principle and paves the way for prospective studies (I think 😉 ).

AbstractWatch #11 SAMHD1 controls innate immunity by regulating condensation of immunogenic self RNA (preprint posted 3 months earlier than publication in Molecular Cell) Recognition of pathogen-derived foreign nucleic acids is central to innate immune defense. This requires discrimination between structurally highly similar self and nonself nucleic acids to avoid aberrant inflammatory responses as in the autoinflammatory disorder Aicardi-Goutières syndrome (AGS). How vast amounts of self RNA are shielded from immune recognition to prevent autoinflammation is not fully understood. Here, we show that human SAM-domain- and HD-domain-containing protein 1 (SAMHD1), one of the AGS-causing genes, functions as a single-stranded RNA (ssRNA) 3′exonuclease, the lack of which causes cellular RNA accumulation. Increased ssRNA in cells leads to dissolution of RNA-protein condensates, which otherwise sequester immunogenic double-stranded RNA (dsRNA). Release of sequestered dsRNA from condensates triggers activation of antiviral type I interferon via retinoic-acid-inducible gene I-like receptors. Our results establish SAMHD1 as a key regulator of cellular RNA homeostasis and demonstrate that buffering of immunogenic self RNA by condensates regulates innate immune responses.

Model: in normal cells, the RNase activity of SAMHD1 controls cellular levels of ssRNA, which together with RNA-binding proteins, are required for condensate formation by phase separation. In SAMHD1 deficiency, unmetabolized ssRNA accumulates, impeding formation of condensates which sequester dsRNA. This leads to release of dsRNA from condensates with subsequent activation of RLR-dependent type I IFN signalling.

One protein that is frequently found in an abnormally aggregated state in these disorders is the nuclear protein TDP-43 (Mackenzie and Rademakers, 2008). Interestingly, TDP-43-deficient cells were recently shown to accumulate dsRNA leading to type I IFN activation and cell death (Dunker et al., 2021). This suggests that specific RNA-binding proteins such as TDP-43 could function as RNA sequestering molecules that confine dsRNA to specific condensates. Importantly, our findings demonstrate that not only enhanced condensate formation, but also a lack of condensate formation can cause human disease, underpinning the critical role of compartmentalization through phase separation for normal cell function and highlighting the emerging role of phase separation in the regulation of innate immune responses (Du and Chen, 2018; Hu et al., 2019; Zhou et al., 2021)

Ang take: Loved this abstract/paper because of the identification of a disease mechanism involving RNA metabolism and phase separation. Kind of links to the other Molecular Cell paper above, regarding signaling & condensates. I know phase separation is a total buzzword but these 2 papers to me point out that we have a lot left to learn regarding their physiological & disease relevance and their formation.

AbstractWatch #12 Alternative RNA splicing modulates ribosomal composition and determines the spatial phenotype of glioblastoma cells (no preprint, published in NCB) Glioblastoma (GBM) is characterized by exceptionally high intratumoral heterogeneity. However, the molecular mechanisms underlying the origin of different GBM cell populations remain unclear. Here, we found that the compositions of ribosomes of GBM cells differ in the tumour core and edge. The acidic pH in the core switches mRNA splicing of the ribosomal gene RPL22L1 from RPL22L1a towards the RPL22L1b isoform. This allows cells in the core to survive acidosis, increases stemness and correlates with worse patient outcome. RPL22L1b in the core promotes RNA splicing by interacting with lncMALAT1 in the nucleus and inducing its degradation. (Wikipedia 😊: MALAT 1 is metastasis associated lung adenocarcinoma transcript 1, identified in multiple types of physiological processes, such as alternative splicing, nuclear organization, epigenetic modulating of gene expression, and has been linked to various pathological processes, ranging from diabetes complications to cancers)

In the tumour edge region, RPL22L1a interacts with ribosomes in the cytoplasm and upregulates the translation of multiple messenger RNAs including TP53.

The RPL22L1 isoform switch is regulated by SRSF4 and they identified a compound that inhibits this process and decreases tumour growth.

Ang take: Looks interesting – my questions would be:

• How does RPL22L1b in the tumor core allow cells to survive acidosis & increase stemness? (it wasn’t clear to me this was through translation (e.g. reduced translation of p53?), or through splicing via lncMALAT1?
• I would have thought reduced MALAT1 in the core would be good for the patient & prognosis, given that elevated MALAT1 is typically associated with worse outcome and is a cancer marker.
• Does the compound that inhibits the isoform switch reduce tumor growth via that mechanism? What are the effects of SRSF4 knockdown?
• Why or how does pH affect SRSF4 to trigger alternative splicing of RPL22L1?

Nevertheless – I find the concept that pH can trigger alternative splicing of ribosomal components and cellular phenotypes (& stemness!) very interesting. Has implications for differentiation & reprogramming in physiological and applied contexts, for ribosomopathies, and for tumor evolution. This was definitely an abstract where I’d love to see the paper, I had a lot of questions about just what was shown, but the implications to many different concepts is compelling in my view.

AbstractWatch #13 Disrupted-in-schizophrenia-1 is required for normal pyramidal cell–interneuron communication and assembly dynamics in the prefrontal cortex (preprint posted 11 months earlier than publication in eLife, analyses & recordings added to published version) We interrogated prefrontal circuit function in mice lacking Disrupted-in-schizophrenia-1 (Disc1-mutant mice), a risk factor for psychiatric disorders. Single-unit recordings in awake mice revealed reduced average firing rates of fast-spiking interneurons (INTs), including optogenetically identified parvalbumin-positive cells, and a lower proportion of INTs phase-coupled to ongoing gamma oscillations. Moreover, we observed decreased spike transmission efficacy at local pyramidal cell (PYR)-INT connections in vivo, suggesting a reduced excitatory effect of local glutamatergic inputs as a potential mechanism of lower INT rates. On the network level, impaired INT function resulted in altered activation of PYR assemblies: While assembly activations defined as coactivations within 25 ms were observed equally often, the expression strength of individual assembly patterns was significantly higher in Disc1-mutant mice. Our data, thus, reveal a role of Disc1 in shaping the properties of prefrontal assembly patterns by setting INT responsiveness to glutamatergic drive.

Abnormalities of glutamatergic neurotransmission are already linked to many major psychiatric disorders e.g., schizophrenia, bipolar disorder, and major depressive disorder). Fast-spiking parvalbumin-positive interneurons (PVIs), are known to contribute to neuronal network synchronization at gamma frequencies, show task-dependent tuning during working memory, and are required for the proper execution of working memory. But information is still lacking on PVIs’ activity in the prefrontal cortex of working memory-deficient Disc1-mutant mice. This gap of knowledge limits the understanding of pathophysiology and development of new therapies for mental diseases. This paper provides the first in vivo electrophysiological characterization of fast-spiking INT and PVI activity in Disc1-mutant mice. Extending upon previous electrophysiological Disc1 studies (Sauer et al., 2015; Chini et al., 2020; Delevich et al., 2020; Kaefer et al., 2019), it shows that the average discharge rates of INTs are reduced in vivo by ~44%, whereas PYR activity is unaltered.

Ang take: Will this substantially inform new treatment strategies? Abnormal PVI function is already a proposed pathophysiological mechanism of schizophrenia and other major psychiatric disorders. I think this is likely a beautiful and satisfying paper for the field – I want to use words like ‘descriptive’, ‘correlative’ but I hesitate to say those things because they have negative connotations, which I think is truly ridiculous in science. We need descriptions, we need correlations. They improve our understanding of things and allow us to ask more mechanistic and detailed questions. eLife seems like a great fit & venue 😊