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Abstract 5715: Epigenomic profiling identifies distinct neuroendocrine subtypes in lung cancer with neuroendocrine differentiation

Lung cancer is the leading cause of cancer-related death worldwide, among which high-grade neuroendocrine tumors including small-cell lung cancer (SCLC) and pulmonary large-cell neuroendocrine carcinoma (LCNEC) are especially aggressive with a dismal prognosis. Although molecular subtypes of SCLC ba...

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Published in:Cancer research (Chicago, Ill.) Ill.), 2022-06, Vol.82 (12_Supplement), p.5715-5715
Main Authors: Sato, Takashi, Hamamoto, Junko, Emoto, Katsura, Fukushima, Takahiro, Sugihara, Kai, Shirasawa, Masayuki, Nakahara, Yoshiro, Igawa, Satoshi, Murakumo, Yoshiki, Kohno, Takashi, Shiraishi, Kouya, Yasuda, Hiroyuki, Soejima, Kenzo, Watanabe, Hideo, Naoki, Katsuhiko
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Language:English
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Summary:Lung cancer is the leading cause of cancer-related death worldwide, among which high-grade neuroendocrine tumors including small-cell lung cancer (SCLC) and pulmonary large-cell neuroendocrine carcinoma (LCNEC) are especially aggressive with a dismal prognosis. Although molecular subtypes of SCLC based on the expression of lineage transcription factors such as ASCL1, NEUROD1, POU2F3 and YAP1 have been identified and explored recently, LCNEC has not been well characterized so far, and in clinic, patients with LCNEC have been treated with both chemotherapy regimens for SCLC and regimens for non-small cell lung cancer. To make efficient treatment strategies for LCNEC, further advances in molecular characterization of LCNEC are warranted. Therefore, in this study, we aimed to elucidate the heterogeneity of neuroendocrine differentiation in lung cancer with LCNEC components by using epigenomic profiling. We investigated super-enhancer profiles of 24 formalin-fixed paraffin-embedded tumor tissues from patients with primary lung cancer containing LCNEC components. Unsupervised hierarchical clustering of these specimens using H3K27 acetylation signals over super-enhancer regions near transcriptional regulators identified four distinct clusters. Principal component analysis supported this classification. Immunohistochemical staining for ASCL1, NEUROD1, POU2F3 and YAP1 on these tissues was also performed and the staining results were compatible with our epigenomic profiling. Cluster 1 tissues were positive for ASCL1 and NKX2-1 while the high expression of POU2F3 or YAP1 was found in some samples among Cluster 3 and Cluster 4. None of the four transcription factors were positive in Cluster 2. Additional genomic profiling revealed no clear associations between the clusters and genetic alterations such as RB1 loss and STK11 loss. Neuroendocrine markers synaptophysin, chromogranin A and CD56 were found to be more commonly positive in tissues among Cluster 1. These findings suggest the existence of the distinct differentiation subtypes of lung cancer with LCNEC components, different from the previously reported classifications, which provides new insight into the regulation of neuroendocrine differentiation in lung cancer. Citation Format: Takashi Sato, Junko Hamamoto, Katsura Emoto, Takahiro Fukushima, Kai Sugihara, Masayuki Shirasawa, Yoshiro Nakahara, Satoshi Igawa, Yoshiki Murakumo, Takashi Kohno, Kouya Shiraishi, Hiroyuki Yasuda, Kenzo Soejima, Hideo Watanabe, Katsu
ISSN:1538-7445
1538-7445
DOI:10.1158/1538-7445.AM2022-5715