MétaCan
Menu
Retour à la cohorte
Enregistrement W2013421664 · doi:10.4161/cc.25305

MicroRNA-regulated stress response in cancer and its clinical implications

2013· editorial· en· W2013421664 sur OpenAlexafffund
Haoran Li, Burton B. Yang

Notice bibliographique

RevueCell Cycle · 2013
Typeeditorial
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMicroRNA in disease regulation
Établissements canadiensHealth Sciences CentreSunnybrook HospitalUniversity of TorontoSunnybrook Health Science Centre
Organismes subventionnairesHeart and Stroke Foundation of Canada
Mots-clésBiologymicroRNAAngiogenesisCarcinogenesisContext (archaeology)Cancer researchCancerCell cycleCancer cellCell biologyStem cellImmunologyGenetics

Résumé

récupéré en direct d'OpenAlex

During the process of tumorigenesis, the microenvironments of cancer cells are constantly undergoing changes and remodeling. Such changes and remodeling can lead to shortage of blood supply, reactive immune responses and damage to cellular components (Fig. 1). Any environmental fluctuations leading to deviations from physiological homeostasis are considered as stress to cancer cells. It is well known that strategies taken to modulate stress signaling are critical to tumor development. This also marks a distinction of malignant cells from normal ones. Currently, evolving evidence suggests that microRNAs play key roles in stress response mediation.1 MicroRNAs have been shown to exert diverse functions in cancer cell proliferation, cell cycle progression, invasion and angiogenesis.2-4 Notably, microRNAs regulate cellular metabolism in a cell-specific and context-dependent manner. Figure 1. By targeting multiple pathways, microRNA networks such as miR-17-associated pathway play a key role in regulating stress response of cancer cells. These stresses may come from chemotherapy treatment, lack of blood supply, cell apoptosis ... Recent research from our lab has gained insight into this issue, using glioblastoma cells as a model to test the context-dependent functions of microRNA. Glioblastoma is characterized by aggressive angiogenesis and the generation of tumor stem-like cells (TSCs), making it an optimal candidate to test TSC-related phenotypes. Initially, we found that microRNA miR-378 accumulated in glioblastoma U87 cells when deprived of serum in vitro, and miR-378, in turn, contributed to tumor angiogenesis in vivo.5 This led us to further examine alterations to the microRNA network when cancer cells were starved. Under these conditions, we found a group of microRNAs upregulated therein, including miR-17.6 MiR-17 has a controversial role in different cancers: it can function either as an oncomir or as a tumor-suppressor depending on the tumor type. Glioblastoma cells overexpressing miR-17 appeared “highly adaptive” as compared with the other cancerous cells. Under favorable conditions, the proliferative capacity of miR-17-expressing cells decreased. By reducing their metabolic rate, such growth retardation could protect them from serum-starvation. As a result, these cells showed increased survival under serum-free conditions. Moreover, miR-17-expressing cells became more resistant to treatments with cytotoxic reagents, since most chemotherapeutic drugs function by diminishing highly proliferative tumor cells. These effects appeared to be the consequence of miR-17 targeting MDM2 and PTEN. Through the negative regulation of p53, MDM2 acts as an oncogene, and suppression of MDM2 resulted in reduced proliferation. However, PTEN is a tumor suppressor gene that dominates the PTEN/Akt/HIF-1alpha pathway. Downregulating PTEN caused activation of HIF-1alpha, which contributed to tumor survival and angiogenesis. Interestingly, HIF-1alpha expression was only stabilized under stressed conditions and acted as a sensor to detect environmental fluctuation. Activation of HIF-1alpha in response to chemotherapy not only prolonged glioblastoma cell survival, but also accelerated the transformation of TSCs. Tumor stem-like cells have been identified as one of the most important causes of tumor recurrence. It is believed that a subpopulation of cancer cells is capable of preserving their tumorigenicity after cytotoxic chemotherapy. But how these cells remain undamaged after treatment is not readily explained by current theory. The glioblastoma TSCs show characteristic overexpression of miR-17, which restricts cell growth to an indolent pattern. Interestingly however, these cells were more able to resist drug treatment and generate secondary colonies. Particularly under stressed conditions, TSCs were enriched in glioblastoma cells overexpressing miR-17. These cells showed a greater ability to induce angiogenesis when the nutritional supply was decreased, which may contribute to evasion of traditional chemotherapeutic treatment. Thus, the effects of miR-17 in glioblastoma are 2-fold. First, by shifting the metabolic requirements during periods of tumor growth, these malignant cells can evade traditional chemotherapy regimens. Second, increased angiogenic capacity allows these cancer cells to rapidly regrow through increased tumor vascularization. The realization that microRNAs play a dual role in glioblastoma cells will provide a new perspective to our understanding of stress responses in cancer. To adapt to fluctuations in environmental stress, microRNA networks can balance signaling by targeting both positive and negative regulators of tumor progression.7 Any changes leading to imbalanced signaling might trigger the responses of microRNAs accordingly. The heterogeneity of cancer lies not only in its genetic diversity, but also in its wide array of modifications at the post-transcriptional level, indeed posing a new challenge in developing cancer therapeutics. For example, traditional therapy may fail to eliminate miR-17-overexpressing cancer cells, which are inherently resistant to current drug treatments. Targeted therapy might also lead to acquired drug resistance if microRNA altered the therapeutic target secondary to survival pressure. Anti-angiogenic therapy is commonly used in treating advanced glioblastoma patients, but drug resistance has been observed frequently. The finding that miR-17 contributes to glioblastoma angiogenesis by over-inducing expression of VEGF provides another possible mechanism of resistance to anti-angiogenic therapy. Subpopulations of cancer cells with stem cell-like properties have been shown to give rise to secondary tumors following traditional chemotherapy. Understanding the contributions of miRNA to these phenotypes will be valuable. For example, glioblastoma patients with high levels of miR-17 might benefit more from surgical resection, instead of chemotherapy. To address microRNA-induced drug resistance, our lab has developed an anti-miRNA sponge that can efficiently decrease specific microRNA activity in vitro and in vivo.2 The ability of microRNAs to mediate TSC functioning highlights the importance of understanding microRNA networks in cancer progression. Much work needs to be done to uncover the intricacies of miRNA functioning. Understanding the mechanism may provide unprecedented opportunity in targeted cancer therapy.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,278
Score d'incertitude au seuil0,988

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,315
Écart entre enseignants0,302 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2013
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueCell CycleMême sujetMicroRNA in disease regulationTravaux en français237 207