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Cancer and Transplantation Intersect at the Mammalian Target of Rapamycin

2007· letter· en· W2077455909 on OpenAlexaff
Allan S. MacDonald

Bibliographic record

VenueTransplantation · 2007
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTransplantationCancerMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

The paper by Gomez-Camerero et al. in this issue, “Use of everolimus as a rescue immunosuppressive therapy in liver transplantation,” adds to a growing literature on mammalian target of rapamycin (mTOR) inhibitor use in cancer. It is of interest because of the spectrum of cancers treated and because of the comparison to a similar group of cancers in liver recipients not switched. All 10 patients switched from a calcineurin inhibitor (CNI) to everolimus (EVR) had remissions. Despite three deaths (two not from cancer), the average survival exceeded 20 months compared to 5.3 months in controls. Both groups had conventional treatments (surgery, radiation, and chemotherapy). Rapamycins are as immunosuppressive as CNIs, yet they reduce the risk of cancer in transplant recipients compared to CNIs (1) and they appear useful for treating new cancers. Unraveling the actions of rapamycin has increased our understanding of growth pathways of normal and cancer cells. Growth factors including insulin-like growth factor-1, platelet-derived growth factor (PDGF), epidermal growth factor (EGF), and vascular endothelial growth factor (VEGF) stimulate cell growth and division by initiating a cascade of events beginning when they engage their receptors. This results in activation of phosphotidyl-inositol-3 kinase (PI3K), which converts PIP2 to PIP3, a step inhibited by PTEN (Phosphatase and Tensin homologue, mutated or deleted in many cancers). PIP3 attracts PDK1 and Akt (protein kinase B) to the membrane and they in turn uncouple an inhibitor complex TSC1/TSC2 (tuberous sclerosis complex 1/ 2) releasing Rheb (Ras homolog enriched in brain) a GTPase which then activates mTOR. mTOR integrates this signaling pathway with amino acid availability and the energy status of the cell and controls translation initiation through phosphorylation activation of the ribosomal protein S6 kinase and in turn of ribosomal protein S6 increasing ribosomal generation. It also phosphorylates 4E-binding protein 1 (4E-BP-1), releasing its inhibitory effect on the eukaryotic initiation factor 4E (eIF4E) an activator of cyclins and their kinases (Fig. 1).FIGURE 1.: mTOR signaling pathway. KEGG diagram from Kanehisa Laboratories in the Bioinformatics Center, Kyoto University and the Human Genome Center of the University of Tokyo.Cyclin-D levels rise as well as its regulator p21. p21 facilitates the assembly of a complex containing cyclins, cyclin-dependant kinases, p21, and proliferating cell nuclear antigen (PCNA); this complex catalyzes Rb (retinoblastoma protein) phosphorylation releasing its inhibition of cell-cycle progression. Rapamycin can decrease p21 synthesis and increase the levels of p27, an inhibitor of cdks. This effect can be reversed by an excess of cyclin-D and cancers that have over-expression of cyclin-D should be insensitive to mTOR inhibition. p53 as the guardian protecting cells from inappropriate growth is intimately involved in the mTOR pathway including augmentation of the inhibitory actions of PTEN and indirectly of TSC1/2. Elimination of p53 activity is the commonest cancer perturbation and this often keeps the Akt/ mTOR pathway in overdrive. mTOR itself inhibits p53 by promoting the translation of Mdm2, a negative regulator of p53. Adequate oxygenation is another prerequisite for cell division. Hypoxia-inducible factor (HIF), a transcription factor for VEGF, whose concentration is normally reduced by a product of the Von Hippel-Lindau gene (mutated in many cancers), is overexpressed in hypoxic tumors. It acts on TSC 1/2, upregulating mTOR which in turn results in excess production of both VEGF and its receptor and other angiogenic stimulators PDGF, TGF-alpha, and FGF, all blocked by rapamycins. Growth factor driven Akt activation accumulates glucose transporters to the cell membrane independently of mTOR but mTOR controls glucose levels. Thus the important signals that tell a cell to grow and divide—as well as those telling it that it has the wherewithal to do so (amino acids, energy from glucose, and oxygen)—converge through mTOR. Rapamycin blocks mTOR preventing cell-cycle progression from G-1 to S. Cancer increases activity in these pathways, or subverts the control factors that normally constrain them. Two of Gomez-Camarero et al.’s patients developed Kaposi’s sarcoma. The causative herpes virus (KSHV) encodes an oncogene which is incorporated into the genome of infected cells inducing the appearance of a ligand-independent G-protein receptor (vGPCR) at the cytoplasmic membrane. It is constitutively active and it turns on the Akt/mTOR pathway. vGPCR is present in only a few cells in Kaposi’s lesions but all its cells express elevated Akt. Activation of Akt/mTOR induces the secretion of angiogenic factors especially VEGF which then acts in an autocrine and paracrine manner to induce cell growth and VEGF production both in infected cells and their neighbors, endothelial cells being most sensitive. Blocking mTOR turns off VEGF signaling and production. Uninfected tumor cells activated but prevented from progressing enter apoptotic pathways and are eliminated. In early stage, Kaposi’s infected cells regress, but as the number and size of lesions in this highly proliferative cancer increase other mutations are likely to be resistant to rapamycins. This would explain the incomplete remissions in those Kaposi patients seen by Lebbe et al. (2) where sirolimus treatment was delayed for 24 to 124 months. The explanation for regression of lymphoma with rapamycins is complex. Sindhi (3) successfully switched posttransplant lymphoproliferative disease children to sirolimus (SIR) titrating the level of the drug against viral load, reducing the dose if virus titers rose, increasing it for signs of increased immune activity. E-B virus infected B-cells are ordinarily held in check by EBV-specific T-cells. If these are incapacitated by transplant drugs infected B-cells are unleashed and express the products of the hitherto latent genes, one of which, latent membrane protein-1 (LMP-1) functions like a growth receptor and another mimics IL-11 activating the Akt/mTOR pathway and driving cell proliferation. Although there are many important oncogenic derangements in these B-cells related to loss of apoptotic pathways, mTOR blockade when added to other strategies is beneficial. Similar overactivity of Akt/mTOR has been described for other lymphomas and the rapamycins are clinically effective. Despite experimental evidence that the Ras/cRaf/MEK1/2/ERK1/2 signaling is more important in hepatocellular carcinoma (HCC), mTOR inhibitors reduce recurrences (4) and induce remissions. Upregulation of PI3k/Akt/mTOR signaling has been demonstrated in human HCC, but antiapoptotic abnormalities are more characteristic. High VEGF and VEGFR levels are usually present and at least in part explain the effectiveness of SIR/EVR. PI3K/Akt/mTOR signaling is constitutively active in lung cancers of all types and growth factor receptors such as FGF, VEGF, PDGF, EGF, and HER-2 neu are over expressed. Some cancers also have deficient LKB-1, a kinase which prevents growth in low energy conditions by strengthening the mTOR inhibition of the TSC1/2 complex. A stromal component of lung cancers, fibronectin inhibits LKB-1 and stimulates Akt/mTOR activity. It is becoming apparent that mTOR drugs have different consequences in cancer cells than in normal immune cells. In the latter they seem to be reversibly cytostatic and permissive, whereas in malignant cells, especially those missing tumor suppressors like p53, p21 or PTEN, effects are profound. It is also apparent that predicting outcomes based on cell culture experiments underestimates the effects of mTOR inhibition on solid tumors. They sensitize cancer cells to the effects of radiation and chemotherapeutic agents like taxols, platinols, epirubcin, etc. Drugs targeting PI3K activating receptors including erlotinib, herceptin, etc. are likely to augment mTOR inhibition. Over 90 rapamycin cancer trials are now listed at www.ClinicalTrials.gov. Milestones in mTOR inhibition in cancer include the reports by Kneteman et al. (4) on the reduction in HCC relapses in liver recipients, by Sindhi et al. (3) on the treatment of PTLD in transplanted children, by Campistol et al. (5) on Kaposi’s sarcoma, and the analyses of the clinical trials data base by Mathew et al. (6), and the registry data by Kauffman et al. (1), confirming the prescience of Suran Sehgal, the inventor of rapamycin. From slender yet compelling evidence, some tentative guidelines might be drawn. Liver transplant recipients with preexisting HCC should be treated and maintained on SIR/EVR with minimal or no CNI, as should those with hepatitis C virus. It may also be appropriate for any organ recipient with a previous history of cancer. Smokers, those with sun-damaged skin, or those with familial cancer risks might well be considered. In patients who incur a posttransplant malignancy, an immediate switch from CNIs to SIR/EVR is advisable along with adjunctive therapies where indicated. The doses of SIR/EVR used in transplantation seem to be effective in cancer. SIR has had a negative press lately probably because of the bad company it keeps (CNIs). Despite the positive clinical trials, less than 10% of primary transplant patients in the United States receive SIR/EVR. In light of the high incidence of cancer after transplantation, the place of mTOR inhibitors in clinical transplantation needs reassessment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0090.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.263
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2007
Admission routes1
Has abstractyes

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