Comparison of lung adenocarcinoma and squamous cell carcinoma genomes reveals distinct regions of amplification on chromosome 3q
Notice bibliographique
Résumé
879 Lung cancer is a leading cause of cancer death worldwide. Non-small cell lung cancer (NSCLC) is the major disease type, with squamous cell carcinoma (SqCC) and adenocarcinoma (AC) as the two main sub-types. SqCC and AC are distinguished by differences in their histopathological and molecular characteristics: SqCC develops more rapidly and is located in the central airways, whereas AC is thought to originate from the epithelium of the lung periphery. Previous findings suggest that, although a similar degree of genetic imbalance exists for AC and SqCC, each type is characterized by a unique pattern of genomic imbalance. Objective: To comprehensively identify the underlying differences in genetic alteration patterns between SqCC and AC, we performed genome-wide tiling resolution array CGH analysis. Novel variations in copy number detected by this high resolution technology may reveal cancer-related loci and will provide potential targets for diagnosis and treatment. Design, Materials and Methods: DNA was isolated from 15 AC cell lines and 9 SqCC cell lines. Sample DNA and a pooled reference genomic DNA sample were differentially labeled and applied to the submegabase resolution tiling-set (SMRT) array for CGH analysis. This array consists of >32,000 overlapping human bacterial artificial chromosome clones that span the entire human genome, allowing true genome-wide assessment of copy number changes for a given sample. SMRT array data was assessed using multiple software applications (SeeGH, weighted frequency, aCGH smooth) and alterations in identified regions are presently be validated by fluorescent in situ hybridization using loci specific probes. Results: In total, 24 whole genome array CGH profiles of lung cancer cell lines were generated. Numerous novel, subtype-specific chromosomal alterations were observed. This included differences of alteration at chromosome arms 2q, 6q, 8q, 9q, 12q, 13q and 16p. Of specific interest were the different locations of chromosomal amplification at 3q in the sub-types. AC showed frequent gains between 3q13 and 3q22 while SqCC displayed a similar frequency at 3q23-3q26. These regions have previously been implicated in lung cancer but not mapped according to sub-type. Further analysis of genes within distinct altered regions will determine if these loci help drive the development of different lung cancer subtypes. Conclusions: Tiling resolution array CGH analysis of AC and SqCC lung cancers revealed both shared and subtype-specific regions of DNA copy aberration, suggesting that differences in tumor genomes help define distinct disease subtypes. Further characterization of the novel aberrations and minimal regions we have identified will implicate additional genes in the two tumorigenesis processes and help tailor disease diagnosis. Supported by NCI SPORE CA 70907, NCI Contract N01-85188 and Genome 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,002 | 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 ».