Current tobacco and water‐pipe smoking enhance human cancer invasion and metastasis
Notice bibliographique
Résumé
We want to congratulate the authors of the article “Smoking at diagnosis and survival in cancer patients”1 for their input in cancer research on this very important topic. This analysis is based on 5,185 cancer patients in the USA, including 13 sites of cancer disease containing at least 100 patients diagnosed after a median follow-up of 12 years. They reported that current tobacco smoking increased overall mortality (OM) and disease-specific mortality (DSM) risk when compared with former or never smoking patients, using Cox proportional hazards analysis. More specifically, they revealed that current smoking increased mortality risks in lung, head and neck, prostate as well as leukemia in men and breast, ovary, uterus and melanoma in women. This study also showed that current smoking was not associated with any survival benefits in any disease site. Finally, their data confirm that current smoking increase long-term OM and DSM. On the other hand, it is established that metastatic carcinomas are responsible for the majority of cancer-related deaths, either directly due to tumour invasion of critical organs or indirectly due to complications of therapy to control tumour growth and spread. In parallel, epithelial–mesenchymal transition (EMT) describes the dedifferentiation switch between polarized epithelial cancer cells and contractile and motile mesenchymal (invasive) cells during cancer progression and metastasis.2 For instance, epithelial-like cancer cells “carcinoma cells” in the primary tumour can initiate a multi-step process whereby cells down-regulate the expression patterns of intracellular proteins, such as E-cadherin, catenins, ZO1 as well as claudins and up-regulate signaling pathways and proteins, such as N-cadherin and vimentin associated with a more motile, mesenchymal phenotype. Such changes lead to the progression of EMT which incites the reduction in cell–cell adhesion and enhances migratory capacity.2, 3 Interestingly, earlier studies, including ours, demonstrated that epidermal growth factor receptor (EGF-R) activation provokes the development of EMT in several human carcinomas especially lung cancer. Meanwhile, it has been well documented that EGF-R mutations, that occur under the effect of tobacco smoking,4 and consequently its activation is involved in the development of numerous human carcinomas.3 More interestingly, recent studies found that tobacco smoking including nicotine induces the development of EMT and deregulates its key genes, such as E-cadherin and catenins, which subsequently provoke cell invasion and metastasis of lung cancer.5, 6 Alternatively, water-pipe smoking (WPS) is common especially in the Eastern Mediterranean Region, as it is believed that 20% of adult people living in these countries smoke water-pipe.7 Moreover, WPS has recently been spreading among young people in the western countries including the United States and Canada.8, 9 Smoke from water-pipes contains most of the compounds that are also present in cigarette smoke, although in different proportions.10 More importantly, the longer duration of a WPS session leads to a much higher yield of toxic molecules than cigarette smoking.9, 10 Thus, we believe that current water-pipe and tobacco smoking are important risk factors in the initiation of cancer invasion and metastasis through the EMT event and deregulation of its key genes. However, more molecular and cellular biological studies are necessary to determine the exact role of tobacco and WPS in the progression of several human carcinomas. The authors are thankful to Mrs A. Kassab for her critical reading of the letter. Yours sincerely, Etienne Mfoumou Zhang Li Ala-Eddin Al Moustafa Etienne Mfoumou*, Zhang Li , Ala-Eddin Al Moustafa* §, * Department of Mechanical Engineering, Concordia University, Montreal, Quebec, Canada, Department of Urology, Zhong Shan Hospital of Shanghai, China, Syrian Research Cancer Centre of the Syrian Society against Cancer, § Department of Oncology, McGill University, Montreal, Quebec, Canada.
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 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) | 0,008 | 0,001 |
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 ».