The Problems of Civil Law in China and Japan

千葉大学大学院人文社会科学研究科研究プロジェクト報告書第171集『中日における民法現代化の課題』 小賀野晶一

Thlaspi japonicum Boiss.

原著和名: タカネグンバイ科名: アブラナ科 = Cruciferae採集地: 北海道 夕張岳 (北海道 石狩 夕張岳)採集日: 1957/8/1採集者: 萩庭丈壽整理番号: JH900235国立科学博物館整理番号: TNS-VS-99413

Additional file 1: Figure S1. of A novel integrated gene coexpression analysis approach reveals a prognostic three-transcription-factor signature for glioma molecular subtypes

Cophenetic correlation coefficients of nonnegative matrix factorization (NMF) clustering method with 88 seed signatures. (TIF 6064 kb

Additional file 17: Figure S9. of A novel integrated gene coexpression analysis approach reveals a prognostic three-transcription-factor signature for glioma molecular subtypes

The p-value distribution of survival analysis of clustering results by three-random-gene signatures. (TIF 995 kb

Additional file 9: Figure S4. of A novel integrated gene coexpression analysis approach reveals a prognostic three-transcription-factor signature for glioma molecular subtypes

Comparison of 3-TF signature subtypes and morphologically defined glioma subtypes in Tiantan data. (TIF 2631 kb

Integrated Analysis of Transcriptome in Cancer Patient-Derived Xenografts

<div><p>Patient-derived xenograft (PDX) tumor model is a powerful technology in evaluating anti-cancer drugs and facilitating personalized medicines. Multiple research centers and commercial companies have put huge efforts into building PDX mouse models. However, PDX models have not been widely available and their molecular features have not been systematically characterized. In this study, we provided a comprehensive survey of PDX transcriptome by integrating analysis of 58 patients involving 8 different tumors. The median correlation coefficient between patients and xenografts is 0.94, which is higher than that between patients and cell line panel or between patients with the same tumor. Major differential gene expressions in PDX occur in the engraftment of human tumor tissue into mice, while gene expressions are relatively stable over passages. 48 genes are frequently differentially expressed in PDX mice of multiple cancers. They are enriched in extracellular matrix and immune response, and some are reported as targets for anticancer drugs. A simulation study showed that expression change between PDX and patient tumor (6%) would result in acceptable change in drug sensitivity (3%). Our findings demonstrate that PDX mice represent the gene-expression and drug-response features of primary tumors effectively, and it is recommended to monitoring the overall expression profiles and drug target genes in clinical application.</p></div

GEO expression datasets used in this study.

<p>GEO expression datasets used in this study.</p

Expression correlation analysis for human cancer patients and PDX mouse models.

<p>(A) Heatmap showing the Spearman's rank correlation coefficient (SRCC) of 8 cancers in 9 GEO datasets. F0 indicates cancer patient biopsy, F1 is the 1^st passage PDX, F2 is the 2^nd passage PDX, …, F? is the PDX whose passage is unclear. (B) Boxplot showing the distribution of SRCC. The red line is the mean minus 1.5 standard deviations. (C) Comparison of the similarity between “human tumor VS. xenograft” (blue) and “xenograft VS. xenograft” (red).</p

Differentially expressed genes in multiple cancer datasets.

<p>(A). Genes in “human tumor VS. xenograft” comparisons in five datasets. (B) Genes in “human tumor VS. xenograft” comparisons, only using three datasets in the same platform GPL570. (C) Genes in “xenograft VS. xenograft” comparisons.</p

Functional enrichment of differentially expressed genes in “human tumor VS. xenograft”.

<p>^a) The percentage that this function was significantly enriched (Benjamini P-value < 0.01) when analyzing differential gene sets in each “human tumor VS. xenograft” pair.</p><p>Functional enrichment of differentially expressed genes in “human tumor VS. xenograft”.</p