YAP1 positive small-cell lung cancer subtype is associated with the T-cell inflamed gene expression profile and confers good prognosis and long term survival.

Abstract

9019 Background: The dominant expression of transcription factors ASCL1, NeuroD1, YAP1 or POU2F3 characteristically defines four small cell lung cancer (SCLC) subtypes (SCLC-A, SCLC-N, SCLC-Y and SCLC-P). The clinical validation and biological relevance of these emerging SCLC subtypes is currently lacking. Methods: Using the Illumina TruSeq RNA Exome Kit, we generated RNA-Seq data from 61 cases of SCLC and pulmonary carcinoid to interrogate gene expression differences in SCLC subtypes as well as in survival outliers (top and bottom decile) matched for clinically relevant prognostic factors and treatment. We also assessed YAP1 protein expression in a blinded fashion by immunohistochemistry in 130 SCLC cases. Results: We successfully classified 68% of SCLC into one of the four SCLC subtypes whereas 81.5% of carcinoids did not fit into any of these categories. GSEA for differentially expressed genes between outlier subgroups showed significant upregulation of interferon gamma and interferon alpha response genes in late survivors. Moreover, a previously validated 18-gene T-cell inflamed gene expression profile was upregulated in late survivors and in the SCLC-Y subtype. Furthermore, the SCLC-Y subtype and late survivors showed higher expression of HLA gene family and reduced expression of cancer testis antigens. The median (95%CI) OS was 14 (4.3, 28.8), 16.7 (0.9, NA), 8.1 (2, 9.7) and 20.1 (0.6, 39.5) months respectively, for SCLC-A, N, P and Y subtypes. YAP-1 protein expression was positive in 17 of 130 (13%) SCLC cases. The majority of cases with positive YAP1 expression by immunohistochemistry, 12 of 17 cases (70.6%), were limited stage SCLC at the time of original diagnosis. Conclusions: SCLC subtypes have clinical implication as predictive and prognostic biomarker. SCLC-Y subtype is enriched for T-cell inflamed phenotype and long term survival, and may predict for clinical benefit of immunotherapy.