MP16-19 MECHANISMS UNDERLYING THE ASSOCIATION BETWEEN SARCOPENIA AND POOR ONCOLOGIC OUTCOMES IN CLEAR CELL RENAL CELL CARCINOMA
Bibliographic record
Abstract
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 ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".