MP16-19 MECHANISMS UNDERLYING THE ASSOCIATION BETWEEN SARCOPENIA AND POOR ONCOLOGIC OUTCOMES IN CLEAR CELL RENAL CELL CARCINOMA
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Résumé
You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP16)1 Apr 2019MP16-19 MECHANISMS UNDERLYING THE ASSOCIATION BETWEEN SARCOPENIA AND POOR ONCOLOGIC OUTCOMES IN CLEAR CELL RENAL CELL CARCINOMA Alejandro Sanchez*, Fengshen Kuo, Stacey Petruzella, Oguz Akin, Michael Paris, Paul Russo, Timothy Chan, Marina Mourtzakis, Ari Hakimi, and Helena Furberg Alejandro Sanchez*Alejandro Sanchez* More articles by this author , Fengshen KuoFengshen Kuo More articles by this author , Stacey PetruzellaStacey Petruzella More articles by this author , Oguz AkinOguz Akin More articles by this author , Michael ParisMichael Paris More articles by this author , Paul RussoPaul Russo More articles by this author , Timothy ChanTimothy Chan More articles by this author , Marina MourtzakisMarina Mourtzakis More articles by this author , Ari HakimiAri Hakimi More articles by this author , and Helena FurbergHelena Furberg More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555355.36676.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Sarcopenia (low skeletal muscle mass) is independently associated with poor outcomes among patients with clear cell renal cell carcinoma (ccRCC). We examined gene expression differences among sarcopenic and non-sarcopenic patients to identify pathways that may explain this association. METHODS: 62 ccRCC patients treated by nephrectomy at Memorial Sloan Kettering Cancer Center were transcriptomically-profiled in The Cancer Genome Atlas. Computed tomography scans without contrast performed within 2 months of surgery were reviewed to determine skeletal muscle cross-sectional area. Sarcopenia (yes/no) was defined according to gender-specific international consensus definitions (skeletal muscle index of < 55 cm2/m2 for men and < 39 cm2/m2 for women). Baseline differences in clinicopathologic features were assessed using the Chi-squared test for categorical and t-test for continuous variables. Differential expression analyses were performed using the R package ″DESeq2″ (version 1.16.1). Gene set enrichment analyses (GSEA) were used to evaluate differences in Molecular Signatures Database hallmark gene sets (v6.0). Immune deconvolution using single-sample GSEA was utilized with previously published immune cell signatures (Bindea, et al.) to estimate immune cell infiltration. P-values were corrected for multiple testing (P-adjust) using the Benjamini-Hochberg method. RESULTS: The cohort was predominantly male (82%) and white (97%) and had localized disease (58%). Median age was 58.9 years (SD: 12.1). Overall, 47% were sarcopenic and these patients tended to be older (P<0.001), to be obese (P<0.001), and to present with higher AJCC stage (P=0.006). In primary tumor specimens, sarcopenic patients demonstrated increased expression of angiogenic, inflammatory (eg, IL-6, TNF-alpha), and epithelial mesenchymal transition programs (P-adjust<0.05). Furthermore, sarcopenic patients had higher macrophage (P=0.003) and Th17 immune cell infiltration (P=0.003). CONCLUSIONS: Our findings suggest that sarcopenic ccRCC patients harbor gene expression programs associated with more aggressive biology. Preliminary immune deconvolution analyses suggest that these patients have increased macrophage infiltration and decreased Th17 immune cell infiltration, both of which have been associated with worse prognosis in ccRCC. It is not clear whether sarcopenia is a cause or consequence of tumor aggressiveness. Validation of these results in a larger cohort of patients and orthogonal validation of immune deconvolution results using immunofluorescence is necessary. Source of Funding: Ruth L. Kirschstein Research Service Award T32CA082088 (AS). New York, NY; Waterloo, Canada; New York, NY; Waterloo, Canada; New York, NY© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e214-e214 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alejandro Sanchez* More articles by this author Fengshen Kuo More articles by this author Stacey Petruzella More articles by this author Oguz Akin More articles by this author Michael Paris More articles by this author Paul Russo More articles by this author Timothy Chan More articles by this author Marina Mourtzakis More articles by this author Ari Hakimi More articles by this author Helena Furberg More articles by this author Expand All Advertisement PDF downloadLoading ...
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,004 |
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 ».