PO.BCS01.08 · 生物信息与计算

有胰腺癌病史的肺肿瘤的分子诊断：基于空间分析的鉴别标志物及对侵袭性黏液腺癌的功能性见解

Molecular diagnosis of lung tumors with a history of pancreatic cancer: Spatial profiling-based differential markers and functional insights into invasive mucinous adenocarcinoma

编号 4166 展板 16 时间 4/21 09:00–12:00 区域 Section 3 主讲 Ryunosuke Fujii, MD

分会场 Digital Pathology 3

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作者与单位 Authors & Affiliations

Ryunosuke Fujii¹, Kousei Ishimura¹, Kazuhiko Shien¹, Shuta Tomida², Kenta Manabe¹, Shunsuke Mori¹, Kazuya Hisamatsu¹, Ryota Fujiwara¹, Atsushi Matsuoka¹, Ryo Yoshichika¹, Kazuhiro Okada¹, Yuma Fukumoto¹, Haruchika Yamamoto¹, Kumi Nakajima¹, Shin Tanaka¹, Hidejiro Torigoe¹, Ken Suzawa¹, Kentaroh Miyoshi¹, Mikio Okazaki¹, Seiichiro Sugimoto¹, Hirofumi Inoue², Kosei Takagi³, Hidetaka Yamamoto⁴, Shinichi Toyooka¹

¹Thoracic, Breast and Endocrinological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan,²Center for Comprehensive Genomic Medicine, Okayama University Hospital, Okayama, Japan,³Gastroenterological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan,⁴Pathology and Oncology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan

摘要 Abstract

中文摘要

背景：将胰腺癌肺转移（PCLM）与原发性肺癌，尤其是侵袭性黏液腺癌（IMA）相鉴别，有时因其病理相似性（如黏液产生）而颇为困难。本研究旨在识别用于区分IMA与PCLM的诊断标志物，并利用空间多组学分析阐明黏液性肺腺癌的分子发病机制。方法：我们对手术切除的肺肿瘤（来自9例有胰腺癌病史的患者和3例无此病史的IMA患者）使用GeoMx数字空间分析仪进行空间解析转录组学分析。在每个样本的肿瘤成分中选择多个感兴趣区域（ROI）。基于GeoMx结果，在组织标本上通过免疫组化（IHC）进行验证。随后，使用肺腺癌细胞系进行功能分析。结果：通过空间转录组学分析，UGT2B15阳性和S100A4阴性被提示为区分IMA与PCLM的候选标志物。这些蛋白的表达状态在组织标本上通过IHC得到确认。转录因子分析提示HNF1A参与IMA中UGT2B15的表达，使用肺癌细胞系的功能分析也证实了这些关联。结论：我们识别出UGT2B15和S100A4作为区分IMA与PCLM的潜在候选标志物。研究提示转录因子HNF1A参与了IMA中UGT2B15的表达。

查看英文原文 English abstract

Background: Differentiating pancreatic cancer lung metastasis (PCLM) from primary lung cancer, particularly invasive mucinous adenocarcinoma (IMA), sometimes be difficult due to their pathological similarities such as mucin production. This study aimed to identify diagnostic markers for distinguishing IMA from PCLM and to elucidate the molecular pathogenesis of mucinous lung adenocarcinoma using spatial multi-omics analyses. Methods: We performed spatially resolved transcriptomics by GeoMx digital spatial profiler on surgically resected lung tumors, from nine patients with a history of pancreatic cancer and three patients of IMA without such history. Multiple regions of interest (ROIs) were selected in tumor components from each sample. Based on GeoMx results, validation was performed by immunohistochemistry (IHC) on tissue specimens. Subsequently, functional analysis was conducted using the lung adenocarcinoma cell line. Results: By spatial transcriptomics profiling, positive UGT2B15 and negative S100A4 were suggested as candidate markers for distinguishing IMA from PCLM. The expression status of these proteins were confirmed by IHC on tissue specimens. Transcription factor analyses suggested that HNF1A was involved in UGT2B15 expression in the IMA, and functional analyses using lung cancer cell lines also demonstrated these associations. Conclusion: We identified UGT2B15 and S100A4 as potential candidate markers for distinguishing IMA from PCLM. The involvement of the transcription factor HNF1A in the expression of UGT2B15 in the IMA was suggested.

利益披露 Disclosure

R. Fujii, None.. K. Ishimura, None.. K. Shien, None.. S. Tomida, None.. K. Manabe, None.. S. Mori, None.. K. Hisamatsu, None.. R. Fujiwara, None.. A. Matsuoka, None.. R. Yoshichika, None.. K. Okada, None.. Y. Fukumoto, None.. H. Yamamoto, None.. K. Nakajima, None.. S. Tanaka, None.. H. Torigoe, None.. K. Suzawa, None.. K. Miyoshi, None.. M. Okazaki, None.. S. Sugimoto, None.. H. Inoue, None.. K. Takagi, None.. H. Yamamoto, None.. S. Toyooka, None.

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