bims-pideca Biomed News
on Class IA PI3K signalling in development and cancer
Issue of 2020‒12‒27
seven papers selected by
Ralitsa Radostinova Madsen
University College London Cancer Institute


  1. Mol Cell. 2020 Dec 15. pii: S1097-2765(20)30827-3. [Epub ahead of print]
    Rinaldi G, Pranzini E, Van Elsen J, Broekaert D, Funk CM, Planque M, Doglioni G, Altea-Manzano P, Rossi M, Geldhof V, Teoh ST, Ross C, Hunter KW, Lunt SY, Grünewald TGP, Fendt SM.
      In tumors, nutrient availability and metabolism are known to be important modulators of growth signaling. However, it remains elusive whether cancer cells that are growing out in the metastatic niche rely on the same nutrients and metabolic pathways to activate growth signaling as cancer cells within the primary tumor. We discovered that breast-cancer-derived lung metastases, but not the corresponding primary breast tumors, use the serine biosynthesis pathway to support mTORC1 growth signaling. Mechanistically, pyruvate uptake through Mct2 supported mTORC1 signaling by fueling serine biosynthesis-derived α-ketoglutarate production in breast-cancer-derived lung metastases. Consequently, expression of the serine biosynthesis enzyme PHGDH was required for sensitivity to the mTORC1 inhibitor rapamycin in breast-cancer-derived lung tumors, but not in primary breast tumors. In summary, we provide in vivo evidence that the metabolic and nutrient requirements to activate growth signaling differ between the lung metastatic niche and the primary breast cancer site.
    Keywords:  MCT2; PHGDH; breast cancer; lung environment; mTORC1; metastasis formation; pyruvate; serine biosynthesis; α-ketoglutarate
    DOI:  https://doi.org/10.1016/j.molcel.2020.11.027
  2. EMBO Rep. 2020 Dec 20. e51239
    Fong MY, Yan W, Ghassemian M, Wu X, Zhou X, Cao M, Jiang L, Wang J, Liu X, Zhang J, Wang SE.
      Metabolic reprogramming of non-cancer cells residing in a tumor microenvironment, as a result of the adaptations to cancer-derived metabolic and non-metabolic factors, is an emerging aspect of cancer-host interaction. We show that in normal and cancer-associated fibroblasts, breast cancer-secreted extracellular vesicles suppress mTOR signaling upon amino acid stimulation to globally reduce mRNA translation. This is through delivery of cancer-derived miR-105 and miR-204, which target RAGC, a component of Rag GTPases that regulate mTORC1 signaling. Following amino acid starvation and subsequent re-feeding, 13 C-arginine labeling of de novo synthesized proteins shows selective translation of proteins that cluster to specific cellular functional pathways. The repertoire of these newly synthesized proteins is altered in fibroblasts treated with cancer-derived extracellular vesicles, in addition to the overall suppressed protein synthesis. In human breast tumors, RAGC protein levels are inversely correlated with miR-105 in the stroma. Our results suggest that through educating fibroblasts to reduce and re-prioritize mRNA translation, cancer cells rewire the metabolic fluxes of amino acid pool and dynamically regulate stroma-produced proteins during periodic nutrient fluctuations.
    Keywords:  breast cancer; extracellular vesicles; mRNA translation; mTORC1; microRNA
    DOI:  https://doi.org/10.15252/embr.202051239
  3. J Physiol. 2020 Dec 21.
    Vaupel P, Multhoff G.
      Contrary to Warburg's original thesis, accelerated aerobic glycolysis is not a primary, permanent and universal consequence of dysfunctional/impaired mitochondria compensating for poor ATP-yield per mole of glucose. Instead, in most tumours the Warburg effect is an essential part of a "selfish" metabolic reprogramming, which results from the interplay between (normoxic/hypoxic) HIF-1-overexpression, oncogene activation (cMyc, Ras), loss of function of tumour suppressors (mutant-p53, mutant-PTEN, microRNAs and sirtuins with suppressor functions), activated (PI3K/Akt/mTORC1, Ras/Raf/Mek/Erk/cMyc, Jak/Stat3) or deactivated (LKB1/AMPK) signalling pathways, components of the tumour microenvironment, and HIF-1-cooperations with epigenetic mechanisms. Molecular and functional processes of the Warburg effect include: (a) considerably accelerated glycolytic fluxes, (b) adequate ATP generation per unit time to maintain energy homeostasis and electrochemical gradients, (c) backup and diversion of glycolytic intermediates facilitating the biosynthesis of nucleotides, non-essential amino acids, lipids and hexosamines, (d) inhibition of pyruvate entry into mitochondria, (e) excessive formation and accumulation of lactate which stimulates tumour growth and suppression of anti-tumour immunity; in addition, lactate can serve as an energy source for normoxic cancer cells and drives malignant progression and resistances to conventional therapies, (f) cytosolic lactate is mainly exported through upregulated lactate-proton symporters (MCT4), working together with other H+ -transporters, and carbonic anhydrases (CAII, CAIX) which hydrate CO2 from oxidative metabolism to form H+ and bicarbonate, (g) in concert with poor vascular drainage these proton export mechanisms are responsible for extracellular acidification, driving malignant progression and resistances to conventional therapies, (h) maintenance of the cellular redox homeostasis and low ROS formation, and (i) HIF-1 overexpression, mutant-p53 and mutant-PTEN which inhibit mitochondrial biogenesis and functions, negatively impacting cellular respiration rate. The glycolytic switch is an early event in oncogenesis and primarily supports cell survival. All in all, the Warburg effect, i.e., aerobic glycolysis in the presence of oxygen and -in principle- functioning mitochondria, constitutes a major driver of the cancer progression machinery, resistance to conventional therapies, and poor patient outcome. However, as evidenced during the last two decades, in a minority of tumours primary mitochondrial defects can play a key role promoting the Warburg effect and tumour progression due to mutations in some Krebs cycle enzymes and mitochondrial ROS overproduction. Abstract figure legend Driving processes causing the Warburg effect during carcinogenesis (upper part), and mechanisms/consequences of metabolic reprogramming in Warburg phenotypes (lower part) leading to survival advantages, malignant progression and, ultimately, poor patient outcome. This article is protected by copyright. All rights reserved.
    Keywords:  Warburg effect; aerobic glycolysis; glycolytic phenotype; lactate accumulation; metabolic reprogramming; tumour acidosis; tumour glucose metabolism; tumour mitochondria
    DOI:  https://doi.org/10.1113/JP278810
  4. Mol Cell. 2020 Dec 10. pii: S1097-2765(20)30836-4. [Epub ahead of print]
    Kim SH, Choi JH, Wang P, Go CD, Hesketh GG, Gingras AC, Jafarnejad SM, Sonenberg N.
      Mechanistic target of rapamycin complex 1 (mTORC1) controls cell growth and proliferation by sensing fluctuations in environmental cues such as nutrients, growth factors, and energy levels. The Rag GTPases (Rags) serve as a critical module that signals amino acid (AA) availability to modulate mTORC1 localization and activity. Recent studies have demonstrated how AAs regulate mTORC1 activity through Rags. Here, we uncover an unconventional pathway that activates mTORC1 in response to variations in threonine (Thr) levels via mitochondrial threonyl-tRNA synthetase TARS2. TARS2 interacts with inactive Rags, particularly GTP-RagC, leading to increased GTP loading of RagA. mTORC1 activity in cells lacking TARS2 is resistant to Thr repletion, showing that TARS2 is necessary for Thr-dependent mTORC1 activation. The requirement of TARS2, but not cytoplasmic threonyl-tRNA synthetase TARS, for this effect demonstrates an additional layer of complexity in the regulation of mTORC1 activity.
    Keywords:  Rag GTPases; TARS2; amino acid; aminoacyl-tRNA synthetase; mTORC1; threonine
    DOI:  https://doi.org/10.1016/j.molcel.2020.11.036
  5. Nat Cancer. 2020 Mar;1(3): 359-369
    Hulton CH, Costa EA, Shah NS, Quintanal-Villalonga A, Heller G, de Stanchina E, Rudin CM, Poirier JT.
      Patient-derived xenografts are high fidelity in vivo tumor models that accurately reflect many key aspects of human cancer. In contrast to either cancer cell lines or genetically engineered mouse models, the utility of PDXs has been limited by the inability to perform targeted genome editing of these tumors. To address this limitation, we have developed methods for CRISPR-Cas9 editing of PDXs using a tightly regulated, inducible Cas9 vector that does not require in vitro culture for selection of transduced cells. We demonstrate the utility of this platform in PDXs (1) to analyze genetic dependencies by targeted gene disruption and (2) to analyze mechanisms of acquired drug resistance by site-specific gene editing using templated homology-directed repair. This flexible system has broad application to other explant models and substantially augments the utility of PDXs as genetically programmable models of human cancer.
    DOI:  https://doi.org/10.1038/s43018-020-0040-8
  6. Nat Biotechnol. 2020 Dec 21.
    Chen W, Zhao Y, Chen X, Yang Z, Xu X, Bi Y, Chen V, Li J, Choi H, Ernest B, Tran B, Mehta M, Kumar P, Farmer A, Mir A, Mehra UA, Li JL, Moos M, Xiao W, Wang C.
      Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study.
    DOI:  https://doi.org/10.1038/s41587-020-00748-9
  7. Semin Cancer Biol. 2020 Dec 16. pii: S1044-579X(20)30269-8. [Epub ahead of print]
    Erenpreisa J, Salmina K, Anatskaya O, Cragg MS.
      The fundamental understanding of how Cancer initiates, persists and then progresses is evolving. High-resolution technologies, including single-cell mutation and gene expression measurements, are now attainable, providing an ever-increasing insight into the molecular details. However, this higher resolution has shown that somatic mutation theory itself cannot explain the extraordinary resistance of cancer to extinction. There is a need for a more Systems-based framework of understanding cancer complexity, which in particular explains the regulation of gene expression during cell-fate decisions. Cancer displays a series of paradoxes. Here we attempt to approach them from the view-point of adaptive exploration of gene regulatory networks at the edge of order and chaos, where cell-fate is changed by oscillations between alternative regulators of cellular senescence and reprogramming operating through self-organisation. On this background, the role of polyploidy in accessing the phylogenetically pre-programmed "oncofetal attractor" state, related to unicellularity, and the de-selection of unsuitable variants at the brink of cell survival is highlighted. The concepts of the embryological and atavistic theory of cancer, cancer cell "life-cycle", and cancer aneuploidy paradox are dissected under this lense. Finally, we challenge researchers to consider that cancer "defects'' are mostly the adaptation tools of survival programs that have arisen during evolution and are intrinsic of cancer. Recognition of these features should help in the development of more successful anti-cancer treatments.
    Keywords:  Aneuploidy; Bivalency; Cancer atavism; Cancer “life-cycle”; Reversible polyploidy; Self-organisation
    DOI:  https://doi.org/10.1016/j.semcancer.2020.12.009