bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2022‒11‒20
fourteen papers selected by
Ralitsa Radostinova Madsen
University College London Cancer Institute


  1. Nat Rev Drug Discov. 2022 Nov 14.
      Lipid phosphoinositides are master regulators of almost all aspects of a cell's life and death and are generated by the tightly regulated activity of phosphoinositide kinases. Although extensive efforts have focused on drugging class I phosphoinositide 3-kinases (PI3Ks), recent years have revealed opportunities for targeting almost all phosphoinositide kinases in human diseases, including cancer, immunodeficiencies, viral infection and neurodegenerative disease. This has led to widespread efforts in the clinical development of potent and selective inhibitors of phosphoinositide kinases. This Review summarizes our current understanding of the molecular basis for the involvement of phosphoinositide kinases in disease and assesses the preclinical and clinical development of phosphoinositide kinase inhibitors.
    DOI:  https://doi.org/10.1038/s41573-022-00582-5
  2. Cell Mol Life Sci. 2022 Nov 15. 79(12): 594
      Class I phosphoinositide 3-kinases (PI3Ks) are a family of lipid kinases. They are super elevated in many human cancer types and exert their main cellular functions by activating Akt to trigger an array of distinct responses, affecting metabolism and cell polarity. The signal equally plays important roles in cardiovascular pathophysiology. PI3K is required for cardiogenesis and regulation of cardiac structure and function. Overexpression of PI3K governs the development of cardiac pressure overload adaptation and compensatory hypertrophy. Therefore, inhibition of PI3K shortens life span, enhances cardiac dysfunction and pathological hypertrophy. The inverse inhibition effect, however, desirably destroys many cancer cells by blocking several aspects of the tumorigenesis phenotype. Given the contrasting effects in cardio-oncology; the best therapeutic strategy to target PI3K in cancer, while maintaining or rather increasing cardiac safety is under intense investigational scrutiny. To improve our molecular understanding towards identifying cardiac safety signalling of PI3K and/or better therapeutic strategy for cancer treatment, this article reviews PI3K signalling in cardio-oncology. PI3K signalling at the interface of metabolism, inflammation and immunity, and autonomic innervation networks were examined. Examples were then given of cardiovascular drugs that target the networks, being repurposed for cancer treatment. This was followed by an intersection scheme of the networks that can be functionalised with machine learning for safety and risk prediction, diagnoses, and defining new novel encouraging leads and targets for clinical translation. This will hopefully overcome the challenges of the one-signalling-one-health-outcome alliance, and expand our knowledge of the totality of PI3K signalling in cardio-oncology.
    Keywords:  Cancer therapy; Cardiovascular complications; Cellular signalling; Kinase inhibitors; Molecular overlap; Multidisciplinary care
    DOI:  https://doi.org/10.1007/s00018-022-04627-1
  3. Nat Commun. 2022 Nov 16. 13(1): 7012
      PIK3CA mutations are highly prevalent in solid tumors. Targeting phosphatidylinositol 3-kinase α is therefore an attractive strategy for treating cancers harboring PIK3CA mutations. Here, we report the results from a phase Ia, open label, dose-escalation and -expansion study (NCT03544905) of CYH33, a highly selective PI3Kα inhibitor, in advanced solid tumors. The primary outcomes were the safety, tolerability, maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D) of CYH33. The secondary outcomes included evaluation of pharmacokinetics, preliminary efficacy and changes in pharmacodynamic biomarkers in response to CYH33 treatment. The exploratory outcome was the relationship between the efficacy of CYH33 treatment and tumor biomarker status, including PIK3CA mutations. A total of 51 patients (19 in the dose escalation stage and 32 in the dose expansion stage) including 36 (70.6%) patients (4 in the dose escalation stage and 32 in the dose expansion stage) with PIK3CA mutations received CYH33 1-60 mg. The MTD of CYH33 was 40 mg once daily, which was also selected as the RP2D. The most common grade 3/4 treatment-related adverse events were hyperglycemia, rash, platelet count decreased, peripheral edema, and fatigue. Forty-two out of 51 patients were evaluable for response, the confirmed objective response rate was 11.9% (5/42). Among 36 patients harboring PIK3CA mutations, 28 patients were evaluable for response, the confirmed objective response rate was 14.3% (4/28). In conclusion, CYH33 exhibits a manageable safety profile and preliminary anti-tumor efficacy in solid tumors harboring PIK3CA mutations.
    DOI:  https://doi.org/10.1038/s41467-022-34782-9
  4. iScience. 2022 Nov 18. 25(11): 105458
      mTORC1 is aberrantly activated in cancer and in the genetic tumor syndrome tuberous sclerosis complex (TSC), which is caused by loss-of-function mutations in the TSC complex, a negative regulator of mTORC1. Clinically approved mTORC1 inhibitors, such as rapamycin, elicit a cytostatic effect that fails to eliminate tumors and is rapidly reversible. We sought to determine the effects of mTORC1 on the core regulators of intrinsic apoptosis. In TSC2-deficient cells and tumors, we find that mTORC1 inhibitors shift cellular dependence from MCL-1 to BCL-2 and BCL-XL for survival, thereby altering susceptibility to BH3 mimetics that target specific pro-survival BCL-2 proteins. The BCL-2/BCL-XL inhibitor ABT-263 synergizes with rapamycin to induce apoptosis in TSC-deficient cells and in a mouse tumor model of TSC, resulting in a more complete and durable response. These data expose a therapeutic vulnerability in regulation of the apoptotic machinery downstream of mTORC1 that promotes a cytotoxic response to rapamycin.
    Keywords:  Biological sciences; Cancer; Cell biology; Molecular biology
    DOI:  https://doi.org/10.1016/j.isci.2022.105458
  5. Stem Cell Reports. 2022 Nov 08. pii: S2213-6711(22)00509-4. [Epub ahead of print]
      Cellular conversion can be induced by perturbing a handful of key transcription factors (TFs). Replacement of direct manipulation of key TFs with chemical compounds offers a less laborious and safer strategy to drive cellular conversion for regenerative medicine. Nevertheless, identifying optimal chemical compounds currently requires large-scale screening of chemical libraries, which is resource intensive. Existing computational methods aim at predicting cell conversion TFs, but there are no methods for identifying chemical compounds targeting these TFs. Here, we develop a single cell-based platform (SiPer) to systematically prioritize chemical compounds targeting desired TFs to guide cellular conversions. SiPer integrates a large compendium of chemical perturbations on non-cancer cells with a network model and predicted known and novel chemical compounds in diverse cell conversion examples. Importantly, we applied SiPer to develop a highly efficient protocol for human hepatic maturation. Overall, SiPer provides a valuable resource to efficiently identify chemical compounds for cell conversion.
    Keywords:  cellular conversion; chemical compound; scRNA-seq; transcription factors
    DOI:  https://doi.org/10.1016/j.stemcr.2022.10.013
  6. Blood. 2022 Nov 18. pii: blood.2022018546. [Epub ahead of print]
      Activated phosphoinositide 3-kinase delta syndrome (APDS) is an inborn error of immunity with clinical manifestations including infections, lymphoproliferation, autoimmunity, enteropathy, bronchiectasis, increased risk of lymphoma, and early mortality. Hyperactive PI3Kδ signaling causes APDS and is selectively targeted with leniolisib, an oral, small molecule inhibitor of PI3Kδ. Here, 31 patients with APDS aged ≥12 years were enrolled in a global, phase 3, triple-blinded trial and randomized 2:1 to receive 70-mg leniolisib or placebo twice daily for 12 weeks. Co-primary outcomes were differences from baseline in index lymph node size and in percentage of naïve B cells in peripheral blood, assessed as proxies for immune dysregulation and deficiency. Both primary outcomes were met: the difference in the adjusted mean change (95% CI) between leniolisib and placebo for lymph node size was -0.25 (-0.38, -0.12; P=0.0006; N=26) and for percentage of naïve B cells was 37.30 (24.06, 50.54; P=0.0002; N=13). Leniolisib reduced spleen volume compared to placebo (adjusted mean difference in 3-dimensional volume [cm3], -186; 95% CI, -297 to -76.2; P=0.0020) and improved key immune cell subsets. Fewer patients receiving leniolisib reported study treatment-related adverse events (mostly grades 1-2) compared to those receiving placebo (23.8% vs 30.0%). Overall, leniolisib was well tolerated and significant improvement over placebo was notable in the co-primary endpoints, reducing lymphadenopathy and increasing the percentage of naïve B cells, reflecting a favorable impact on the immune dysregulation and deficiency seen in patients with APDS. (Funded by DIR/NIAID, Novartis, and Pharming Group, NV; ClinicalTrials.gov identifier: NCT02435173.).
    DOI:  https://doi.org/10.1182/blood.2022018546
  7. Elife. 2022 Nov 17. pii: e79250. [Epub ahead of print]11
      Obesity is generally associated with insulin resistance in liver and muscle and increased risk of developing type 2 diabetes, however there is a population of obese people that remain insulin sensitive. Similarly, recent work suggests that mice fed high carbohydrate diets can become obese without apparent glucose intolerance. To investigate this phenomenon further, we fed mice either a high fat (Hi-F) or high starch (Hi-ST) diet and measured adiposity, glucose tolerance, insulin sensitivity and tissue lipids compared to control mice fed a standard laboratory chow. Both Hi-ST and Hi-F mice accumulated a similar amount of fat and tissue triglyceride compared to chow-fed mice. However while Hi-F diet mice developed glucose intolerance as well as liver and muscle insulin resistance (assessed via euglycemic/hyperinsulinemic clamp), obese Hi-ST mice maintained glucose tolerance and insulin action similar to lean, chow-fed controls. This preservation of insulin action despite obesity in Hi-ST mice was associated with differences in de novo lipogenesis and levels of C22:0 ceramide in liver and C18:0 ceramide in muscle. This indicates that dietary manipulation can influence insulin action independently of the level of adiposity and that the presence of specific ceramide species correlate with these differences.
    Keywords:  cell biology; mouse
    DOI:  https://doi.org/10.7554/eLife.79250
  8. Cell Commun Signal. 2022 Nov 14. 20(1): 179
      BACKGROUND: The aim of the present study was to determine the role of individual PHLPP isoforms in insulin signaling and insulin resistance in neuronal cells.METHODS: PHLPP isoforms were either silenced or overexpressed individually, and the effects were observed on individual Akt isoforms, AS160 and on neuronal glucose uptake, under insulin sensitive and resistant conditions. To determine PHLPP regulation itself, we tested effect of scaffold protein, Scribble, on PHLPP isoforms and neuronal glucose uptake.
    RESULTS: We observed elevated expression of both PHLPP1 and PHLPP2 in insulin resistant neuronal cells (Neuro-2A, mouse neuroblastoma; SHSY-5Y, human neuroblastoma) as well as in the whole brain lysates of high-fat-diet mediated diabetic mice. In insulin sensitive condition, PHLPP isoforms differentially affected activation of all Akt isoforms, wherein PHLPP1 regulated serine phosphorylation of Akt2 and Akt3, while PHLPP2 regulated Akt1 and Akt3. This PHLPP mediated Akt isoform specific regulation activated AS160 affecting glucose uptake. Under insulin resistant condition, a similar trend of results were observed in Akt isoforms, AS160 and glucose uptake. Over-expressed PHLPP isoforms combined with elevated endogenous expression under insulin resistant condition drastically affected downstream signaling, reducing neuronal glucose uptake. No compensation was observed amongst PHLPP isoforms under all conditions tested, indicating independent roles and pointing towards possible scaffolding interactions behind isoform specificity. Silencing of Scribble, a scaffolding protein known to interact with PHLPP, affected cellular localization of both PHLPP1 and PHLPP2, and caused increase in glucose uptake.
    CONCLUSIONS: PHLPP isoforms play independent roles via Scribble in regulating Akt isoforms differentially, affecting AS160 and neuronal glucose uptake. Video abstract.
    Keywords:  AS160; Akt1; Akt2; Akt3; Glucose uptake; Neuronal insulin resistance; Neuronal insulin signaling; PHLPP1; PHLPP2; Scribble
    DOI:  https://doi.org/10.1186/s12964-022-00987-0
  9. Nat Commun. 2022 Nov 14. 13(1): 6918
      High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g., CellTiter-Glo®). Here we describe a public domain Dye Drop method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.
    DOI:  https://doi.org/10.1038/s41467-022-34536-7
  10. Cell Syst. 2022 Nov 16. pii: S2405-4712(22)00402-1. [Epub ahead of print]13(11): 911-923.e9
      Morphological and gene expression profiling can cost-effectively capture thousands of features in thousands of samples across perturbations by disease, mutation, or drug treatments, but it is unclear to what extent the two modalities capture overlapping versus complementary information. Here, using both the L1000 and Cell Painting assays to profile gene expression and cell morphology, respectively, we perturb human A549 lung cancer cells with 1,327 small molecules from the Drug Repurposing Hub across six doses, providing a data resource including dose-response data from both assays. The two assays capture both shared and complementary information for mapping cell state. Cell Painting profiles from compound perturbations are more reproducible and show more diversity but measure fewer distinct groups of features. Applying unsupervised and supervised methods to predict compound mechanisms of action (MOAs) and gene targets, we find that the two assays not only provide a partially shared but also a complementary view of drug mechanisms. Given the numerous applications of profiling in biology, our analyses provide guidance for planning experiments that profile cells for detecting distinct cell types, disease phenotypes, and response to chemical or genetic perturbations.
    Keywords:  Cell Painting; L1000; benchmark; drug discovery; high-dimensional profiling; images; systems biology
    DOI:  https://doi.org/10.1016/j.cels.2022.10.001
  11. J Cell Commun Signal. 2022 Nov 15.
      Lipin-1 is a protein that plays a critical role in many cellular functions. At molecular level, it acts as a phosphatidic acid phosphohydrolase and a transcriptional coactivator. The functions of lipin-1 are largely dependent upon its subcellular localization, post-translational modifications like phosphorylation and acetylation, and also on its interaction with other proteins such as 14-3-3. However, the kinases and phosphatases that are responsible for these post translational modifications are not entirely known. Using bioinformatics and other biochemical approaches, we demonstrate lipin-1 as a novel target for AKT1 and LKB1. While AKT1 stabilizes lipin-1, LKB1 causes its degradation. Interestingly, our findings further show that lipin-1 enhances AKT1 activity as can be seen by increased phosphorylation of the substrates of AKT1. Taken together, our results suggest that lipin-1 plays an important role in the regulation of PI3K-AKT-mTOR pathway, which is dysregulated in majority of cancers. Therefore, understating the role of lipin-1 may provide new and important insights into the regulation and functions of the PI3K-mTOR pathway, which is one of the major targets for anti-cancer drug development strategies.
    Keywords:  AKT; Adipocyte differentiation; LKB1; Lipin1; PI3 kinase pathway
    DOI:  https://doi.org/10.1007/s12079-022-00708-9
  12. Cell Metab. 2022 Nov 08. pii: S1550-4131(22)00489-2. [Epub ahead of print]
      Impairment of translation can lead to collisions of ribosomes, which constitute an activation platform for several ribosomal stress-surveillance pathways. Among these is the ribotoxic stress response (RSR), where ribosomal sensing by the MAP3K ZAKα leads to activation of p38 and JNK kinases. Despite these insights, the physiological ramifications of ribosomal impairment and downstream RSR signaling remain elusive. Here, we show that stalling of ribosomes is sufficient to activate ZAKα. In response to amino acid deprivation and full nutrient starvation, RSR impacts on the ensuing metabolic responses in cells, nematodes, and mice. The RSR-regulated responses in these model systems include regulation of AMPK and mTOR signaling, survival under starvation conditions, stress hormone production, and regulation of blood sugar control. In addition, ZAK-/- male mice present a lean phenotype. Our work highlights impaired ribosomes as metabolic signals and demonstrates a role for RSR signaling in metabolic regulation.
    Keywords:  AMPK; FGF21; ZAK-alpha; amino acid starvation; mTOR; metabolic regulation; mouse models; ribosome collision; ribotoxic stress response
    DOI:  https://doi.org/10.1016/j.cmet.2022.10.011
  13. Nucleic Acids Res. 2022 Nov 18. pii: gkac1021. [Epub ahead of print]
      PDCM Finder (www.cancermodels.org) is a cancer research platform that aggregates clinical, genomic and functional data from patient-derived xenografts, organoids and cell lines. It was launched in April 2022 as a successor of the PDX Finder portal, which focused solely on patient-derived xenograft models. Currently the portal has over 6200 models across 13 cancer types, including rare paediatric models (17%) and models from minority ethnic backgrounds (33%), making it the largest free to consumer and open access resource of this kind. The PDCM Finder standardises, harmonises and integrates the complex and diverse data associated with PDCMs for the cancer community and displays over 90 million data points across a variety of data types (clinical metadata, molecular and treatment-based). PDCM data is FAIR and underpins the generation and testing of new hypotheses in cancer mechanisms and personalised medicine development.
    DOI:  https://doi.org/10.1093/nar/gkac1021
  14. Math Biosci. 2022 Oct 28. pii: S0025-5564(22)00115-8. [Epub ahead of print]354 108926
      Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the extent to which our hypotheses agree with reality. But doing so in a systematic way is becoming increasingly challenging as our hypotheses become more detailed, and our data becomes more complex. Mathematical methods are therefore gaining in importance across the life- and biomedical sciences. Mathematical models allow us to test our understanding, make testable predictions about future behaviour, and gain insights into how we can control the behaviour of biological systems. It has been argued that mathematical methods can be of great benefit to biologists to make sense of data. But mathematics and mathematicians are set to benefit equally from considering the often bewildering complexity inherent to living systems. Here we present a small selection of open problems and challenges in mathematical biology. We have chosen these open problems because they are of both biological and mathematical interest.
    Keywords:  Automated model development; Model selection; Multi-scale modelling; Systems modelling
    DOI:  https://doi.org/10.1016/j.mbs.2022.108926