{"id":"hum0455","version":1,"url":"https://humandbs.dbcls.jp/research/hum0455/v1","datePublished":"2025-08-04","versions":[{"version":1,"datePublished":"2025-08-04"},{"version":2,"datePublished":"2026-02-20"},{"version":3,"datePublished":"2026-04-09"},{"version":4,"datePublished":"2026-10-09"}],"title":{"ja":"肺がんの遺伝子異常、分子標的、薬剤感受性を予測する、組織形態、バイオマーカーの探索 / 肺癌の遺伝子異常とその生物学的意義の解析","en":"Explore genetic abnormalities, molecular targets, predictive of drug sensitivity, histomorphology, and biomarkers in lung cancer / Analysis of genetic abnormalities and their biological significance in lung cancer"},"summary":{"aims":{"ja":"小細胞がんと大細胞型神経内分泌がん（large cell neuroendocrine carcinoma：LCNEC）は高悪性度神経内分泌がん（high-grade neuroendocrine carcinomas：HGNEC）に分類される。HGNECは予後不良で、治療に対して高確率で耐性化する。小細胞がんはASCL1、NEUROD1、POU2F3、YAP1の4つの転写因子の発現量によってサブタイプ分類ができ、それぞれの予後が異なる。LCNECでは、4つの因子が腫瘍内で不均一に分布する傾向がある。この不均一さが治療抵抗性に関与しているという仮説のもと、不均一性を検討するために、全ゲノム解析（whole genome sequencing：WGS）解析や空間トランスクリプトーム解析を実施する。腫瘍組織の形態把握を基盤にして、一細胞レベルでの各因子の発現相関、cell-cell間での各種遺伝子発現の相互関係、免疫応答因子等の微小環境について解析することでHGNECの新たな治療標的の同定や治療抵抗性の解明を目指す。","en":"Small cell carcinoma and large cell neuroendocrine carcinoma (LCNEC) fall under high-grade neuroendocrine carcinomas (HGNEC). HGNEC, characterized by poor prognosis and high treatment resistance, presents subtypes withinSCLC based on ASCL1, NEUROD1, POU2F3, and YAP1 expression levels, each influencing prognosis differently. LCNEC exhibits heterogeneous distribution of these factors, hypothesized to contribute to treatment resistance. Incorporating whole-genome sequencing and spatial transcriptomics, we'll investigate this variability. Leveraging tumor tissue morphology, we'll analyze single-cell factor expression correlations and gene expressions in the microenvironment, aiming to identify new HGNEC therapeutic targets and understand treatment resistance."},"methods":{"ja":"【WGS】Illumina、NanoporeによるWGS\n【Xenium：High-performance in situ gene expression mapping】10xによる高性能 in situ 遺伝子発現マッピング\n【Visium】空間トランスクリプトームVisiumシークエンスデータ（10X Genomics）\n【snRNA-seq】核対象のシングルセルデータ（10XGenomics）\n【STOMICS】空間トランスクリプトームデータ（BGI）","en":"Whole-genome sequencing, High-performance in situ gene expression mapping Xenium (10x Genomics), Visium Spatial Gene Expression data (10X Genomics), Single-cell RNA sequencing data derived from nuclei (10X Genomics), STOMICS spatial transcritome data (BGI)"},"targets":{"ja":"筑波大学および自治医科大学附属病院で手術を行われた肺神経内分泌がん10＋10＋13症例","en":"Samples from 10 + 10 + 13 patients with pulmonary neuroendocrine carcinoma operated on at the University of Tsukuba and Jichi Medical University Hospital"},"url":{"ja":null,"en":null}},"listingSummary":{},"releaseNote":{"ja":"・肺神経内分泌がん10症例の凍結検体（腫瘍組織および非腫瘍組織のペア）より抽出したDNAを用いたWGS解析データをfastqファイルにて提供する。\n・肺神経内分泌がん1症例のFFPE検体（腫瘍組織）に対して実施したXenium高性能in situ遺伝子発現マッピングデータをcsv、h5、html、json、mtx、tiff、parquet、tsv、xenium、zarrファイルにて提供する。","en":"-DNAs extracted from frozen specimens from 10 patients with pulmonary neuroendocrine carcinoma were used for whole-genome sequencing analysis. Fastq files are provided.\n- FFPE specimen (tumor sample) of a patient with pulmonary neuroendocrine carcinoma were used for Xenium In Situ Gene Expression Assay. Csv, h5, html, json, mtx, tiff, parquet, tsv, xenium, and zarr files are provided."},"dataProviders":[{"name":{"ja":"松原 大祐","en":"Daisuke Matsubara"},"organization":{"name":{"ja":"筑波大学 診断病理学","en":"Department of diagnostic pathology, The university of Tsukuba"}}}],"researchProjects":[],"grants":[{"title":{"ja":"ロングリード技術による肺がんゲノム・エピゲノム不均一性と微小環境ストレスの関係性解明に関する研究開発","en":"Study of heterogeneity of genomic and epigenomic aberrations and association with microenvironment in lung cancer tissues"},"agency":{"ja":"日本医療研究開発機構（AMED） 次世代がん医療加速化研究事業","en":"Project for Promotion of Cancer Research and Therapeutic Evolution, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP24ama221522"]}],"relatedPublications":[{"title":"Clinicopathologic, Cellular, and Molecular Analyses of Pulmonary Neuroendocrine Carcinoma With High Expression of Hepatocyte Nuclear Factor 4 Alpha","doi":"https://doi.org/10.1016/j.labinv.2025.104210","datasets":["JGAD000865","JGAD000866"]}],"datasets":["JGAD000865","JGAD000866"],"controlledAccessUsers":[]}