ANTITUMORAL POTENTIAL OF GREEN MICROALGAE EXTRACTS IN CHRONIC MYELOID LEUKEMIA (CML) IN VITRO MODEL
Notice bibliographique
Résumé
Bioprospected microalgae collected from Northern Ontario, Canada water bodies have been shown to produce bioactive molecules, including carotenoids, polysaccharides, vitamins, and lipids with high pharmacological potential. Several studies in Canada with these microalgae have confirmed extracts with antioxidant, antimicrobial, and anticancer activity. Chronic myeloid leukemia (CML) is a clonal hematopoietic stem cell disorder and accounts for approximately 30% of the incidence of adult leukemias. Despite the use of tyrosine kinase inhibitors (TKIs) has improved the treatment and the prognosis of patients with CML therapeutic failures and adverse effects make treatment difficult, highlighting the need for the study of new molecules with antileukemic potential. This study aims to evaluate the in vitro antileukemic potential of different microalgae extracts in the K-562 cell line. Bioprospected microalgae strains S5, P981 ( Coccomyxa sp .), LL1 ( Scenedesmus sp .), LL2A, and CC ( Chlamydomonas sp .) were cultivated for 14 days in Bold's Basal Medium (BBM) with pH 7 under 16 hr:8 hr light-dark cycles, at 25°C, and were kept continuously agitated at 150 rpm. The microalgae were then harvested and methanol, ethanol, and aqueous extraction were performed on each strain. Tubes were placed under vacuum to evaporate the remaining solvent and the crude extract was weighted, DMSO was added to obtain a stock solution of microalgae extracts (ME) at 10 mg/mL. The CML in vitro model K-562 was plated in a 96-well plate and the microalgae extracts were added in a single dose (100 μg/mL) or in a concentration-response curve (200 μg/mL – 3.125 μg/mL) for 72 hours for evaluate the viability and the Half-maximal inhibitory concentration (IC 50 ) of the most cytotoxic ME, respectively by the MTT method. Fifteen extracts were produced, the ethanolic extracts from CC, LL2A, and P981 presented the highest inhibition percentages in the CML cell line, being 53.67 %, 54.69 %, and 47.09 %, respectively, and were chosen for the definition of the IC 50 . The extracts showed high antileukemic activity, being 80.22 μg/mL for CC, 91.93 μg/mL for LL2A, and 96.18 μg/mL for P918 ethanolic MEs. Previous studies from bioprospected microalgae collected from Northern Ontario have shown their antimicrobial, antiviral, antioxidant as well as antitumoral activity against ovarian and breast cancer cell lines. Ethanolic extracts possess compounds such as alkaloids, flavonoids, glycosides, terpenoids, tannins, saponins, and reducing sugars being sources of compounds with pharmaceutical properties. Our results demonstrated the antileukemic activity with an IC 50 of 80 – 96 μg/mL, corroborating with other studies in vitro . The initial results attested that the ethanolic extracts derived from green microalgae presented high antileukemic potential in the CML in vitro model, showing a promising source of new compounds with pharmacological activity. Further research is needed to visualize which compounds are present in the ethanolic ME that can confer its antileukemic activity and to better describe their mechanism of action in vitro and in vivo .
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».