Local and systemic immunity predict survival in patients with pulmonary sarcomatoid carcinoma.
Erin SchenkJennifer BolandAaron MansfieldMarie Christine AubryAllan B DietzPublished in: Medical oncology (Northwood, London, England) (2017)
Pulmonary sarcomatoid cancer (PSC) is a rare, aggressive subtype of non-small cell lung cancer, and measures of local and systemic immunity as biomarkers are incompletely known. We performed this study to characterize the leukocyte composition within the tumor, stroma, and peripheral blood in patients with PSC and correlated our findings with overall survival. Tissue from 30 patients diagnosed with PSC was evaluated by IHC for the presence of CD3+, CD14+, and CD19+ cells and PD-L1 expression. A lymphocyte-to-monocyte ratio (LMR) was calculated for the tumor microenvironment (TME) and peripheral blood. Survival analyses were performed based on IHC scores or groups defined by receiver operating characteristic curve cutoffs. CD3+ and CD14+ cells were found throughout the TME. CD19+ cells were almost exclusive to the stroma and correlated with superior overall survival (HR 0.40, 95% CI 0.21-0.72, p = 0.003). Most patients expressed PD-L1 on the tumor and/or the infiltrating immune cells, but neither the presence nor PD-L1 expression level impacted survival. A more prolific immune infiltration of the TME was associated with improved survival (HR 0.82, 95% CI 0.70-0.98, p = 0.029). PSC patients with a TME LMR ≥1.2 had a median survival of 1598 versus 488 days for a TME LMR <1.2 (p = 0.010). In the peripheral blood, an LMR ≥2.3 was associated with improved median survival (1579 vs. 332 days, p < 0.001). Our data demonstrate multiple measures of the local and systemic immunity are associated with patient survival in PSC.
Keyphrases
- peripheral blood
- free survival
- induced apoptosis
- end stage renal disease
- ejection fraction
- newly diagnosed
- pulmonary hypertension
- signaling pathway
- immune response
- squamous cell carcinoma
- machine learning
- dendritic cells
- peritoneal dialysis
- deep learning
- cell proliferation
- young adults
- lymph node metastasis
- pi k akt
- big data
- nk cells