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自动量化的肿瘤-间质比预测胃癌新辅助化疗疗效
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作者 仇文涛 李振辉 +4 位作者 焦一平 王向学 张深燕 吴琳 徐军 《中国肿瘤临床》 CAS CSCD 北大核心 2023年第23期1203-1210,共8页
目的:探讨通过深度学习的方法来全自动定量评估术前活检标本的肿瘤-间质比(tumor-stroma ratio,TSR)是否可以预测胃癌患者新辅助化疗(neoadjuvant chemotherapy,NAC)疗效。方法:选取2013年3月至2020年3月在云南省肿瘤医院接受NAC治疗的... 目的:探讨通过深度学习的方法来全自动定量评估术前活检标本的肿瘤-间质比(tumor-stroma ratio,TSR)是否可以预测胃癌患者新辅助化疗(neoadjuvant chemotherapy,NAC)疗效。方法:选取2013年3月至2020年3月在云南省肿瘤医院接受NAC治疗的胃癌患者的术前活检切片148张和手术切除切片43张。构建肿瘤区域分割模型和上皮-间质分割模型,使用手术切除切片训练和评估模型,在活检切片上预测,取二者预测结果的交集,根据TSR的定义得到TSR值。根据术后病理学肿瘤退缩分级(tumor regression grade,TRG)将所有患者分为反应良好者(TRG 0~1)和反应不良者(TRG 2~3)。采用单因素和多因素回归分析TSR与胃癌新辅助化疗疗效的相关性。结果:肿瘤组织分割模型的IOU(intersection over union)为0.94,上皮-间质分割模型的IOU为0.88。以44.93%和70.22%作为TSR的临界值,将患者分为低、中、高间质比组,三组之间反应良好者比例具有显著性差异(P<0.05)。多因素分析显示,TSR是治疗前对胃癌NAC反应的独立预测因子(OR=0.10,95%CI:0.03~0.32)。使用常规临床信息预测治疗响应的基础上,加入TSR三分类等级作为治疗响应的预测变量时,曲线下面积(area under curve,AUC)可从0.71提升至0.85。结论:该模型能够在病理切片上自动分割肿瘤区域、上皮区域和间质区域,并能够自动、准确的计算出TSR,同时发现基于此方法自动计算的TSR可以预测NAC疗效。 展开更多
关键词 肿瘤-间质比 新辅助化疗 语义分割 肿瘤微环境 病理缓解
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Quantitative Evaluation of Aldo-keto Reductase Expression in Hepatocellular Carcinoma (HCC) Cell Lines
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作者 Lei Yang Ju zhang +3 位作者 shenyan zhang Weiwei Dong Xiaomin Lou Siqi Liu 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2013年第4期230-240,共11页
The involvement of aldo-keto reductases (AKRs) in tumorigenesis is widely reported, but their roles in the pathological process are not generally recognized due to inconsistent measure- ments of their expression. To... The involvement of aldo-keto reductases (AKRs) in tumorigenesis is widely reported, but their roles in the pathological process are not generally recognized due to inconsistent measure- ments of their expression. To overcome this problem, we simultaneously employed real-time PCR to examine gene expression and multiple reaction monitoring (MRM) of mass spectrometry (MS) to examine the protein expression of AKRs in five different hepatic cell lines. These include one rela- tively normal hepatic cell line, L-02, and four hepatocellular carcinoma (HCC) cell lines, HepG2, HUH7, BEL7402 and SMMC7721. The results of real-time PCR showed that expression of genes encoding the AKR1C family members rather than AKR1A and AKR1B was associated with tumor, and most of genes encoding AKRs were highly expressed in HUH7. Similar observations were obtained through MRM. Different from HUH7, the protein abundance of AKR1A and AKR1B was relatively consistent among the other four hepatic cell lines, while protein expression of AKR1C varied significantly compared to L-02. Therefore, we conclude that the abundant distri- bution of AKR 1C proteins is likely to be associated with liver tumorigenesis, and the AKR expres- sion status in HuH7 is completely different from other liver cancer cell lines. This study, for the first time, provided both overall and quantitative information regarding the expression of AKRs at both mRNA and protein levels in hepatic cell lines. Our observations put the previous use of AKRs as a biomarker into question since it is only consistent with our data from HUH7. Furthermore, the data presented herein demonstrated that quantitative evaluation and comparisons within a protein fam- ily at both mRNA and protein levels were feasible using current techniques. 展开更多
关键词 Aldo-keto reductase HCC Quantitative analysis Real-time PCR Multiple reaction monitoring
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