CN111796101B - Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途 - Google Patents

Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途 Download PDF

Info

Publication number
CN111796101B
CN111796101B CN202010675809.XA CN202010675809A CN111796101B CN 111796101 B CN111796101 B CN 111796101B CN 202010675809 A CN202010675809 A CN 202010675809A CN 111796101 B CN111796101 B CN 111796101B
Authority
CN
China
Prior art keywords
curative effect
protein
cypa
notch3
expression
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010675809.XA
Other languages
English (en)
Other versions
CN111796101A (zh
Inventor
黄河澄
李恩民
许鸿鹞
吴盛喜
陈夏浦
曾发敏
焦纪伟
吴国喜
楚曼宇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shantou central hospital
Original Assignee
Shantou central hospital
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shantou central hospital filed Critical Shantou central hospital
Priority to CN202010675809.XA priority Critical patent/CN111796101B/zh
Publication of CN111796101A publication Critical patent/CN111796101A/zh
Application granted granted Critical
Publication of CN111796101B publication Critical patent/CN111796101B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407Specifically defined cancers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57484Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57484Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G01N33/57496Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving intracellular compounds
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/705Assays involving receptors, cell surface antigens or cell surface determinants

Abstract

一种预测食管鳞癌同步放化疗疗效的数学模型的构建方法,包括如下步骤:(1)、分别对食管鳞癌患者组织的NOTCH3蛋白表达量和CYPA蛋白表达量进行评分;(2)、根据步骤(1)的结果,利用X‑tile软件分析NOTCH3蛋白表达量高低分界值和CYPA蛋白表达量高低分界值;接着,定义两种蛋白的疗效预测关系值;(3)、将步骤(2)得到的疗效预测关系值带入数学模型:患者同步放化疗总疗效预测值=NOTCH3蛋白的疗效预测关系值+CYPA蛋白的疗效预测关系值;(4)、进行预测疗效:若患者同步放化疗总疗效预测值等于2,则预测该患者同步放化疗疗效预测为敏感;若患者总疗效预测值小于2,则预测该患者同步放化疗疗效预测为抵抗。本发明能够预测食管鳞癌患者同步放化疗疗效。

Description

NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂在预测 癌症治疗疗效的用途
技术领域
本发明涉及医学生物检测技术领域,具体涉及NOTCH3蛋白表达量检测试剂联合CYPA蛋白表达量检测试剂在预测食管鳞癌同步放化疗疗效的用途以及该用途的数学模型构建方法。
背景技术
食管癌是全球第七大常见恶性肿瘤,且是引起癌症相关死亡的第六大原因。中国是食管癌的高发国家,发病率约占世界食管癌发病率的46.6%,在河南、新疆及潮汕沿海地区有着较高的发病率。病理分型以食管鳞癌为主,食管癌患者的5年生存率仅为15~25%,这严重威胁人民的生命与健康安全。因为早期食管癌无特异性的临床表现,当患者出现进行性吞咽困难等明显不适的临床症状而就诊时,病情已发展至中晚期。对于食管癌患者,早期首选手术治疗,术后5年生存率>90%,而对于无远处转移的中晚期食管鳞癌患者首选手术治疗,对于不能或不愿进行手术治疗的中晚期食管鳞癌患者首选同步放化疗。显然,同步放化疗是食管鳞癌治疗的重要方式,然而患者放化疗后存在疗效差异,甚至可能由于过度治疗造成患者生活质量下降、生存时间缩短。因此,食管鳞癌的同步放化疗,迫切需要能较为准确预测治疗效果究竟为敏感还是抵抗,用以帮助临床医师根据患者综合情况制定合理的治疗方案,避免过度治疗,延长患者生存期。达到精准放化疗,以改善患者预后,提高患者的远期生存。
另一方面,CYPA蛋白(Cyclophilin A)属于亲环蛋白家族中的一员,主要在细胞浆中表达,已有研究表明CYPA蛋白在小细胞肺癌、乳腺癌、结直肠癌、鳞状细胞癌等多种肿瘤中高表达;而NOTCH3蛋白是NOTCH蛋白家族的第三亚型,有研究表明NOTCH3信号在多种肿瘤中高表达。但在此以前,尚未有应用蛋白质组预测食管鳞癌同步放化疗敏感性的研究。
发明内容
本发明的目的是为了解决上述问题而提供一种NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂在预测癌症治疗疗效的用途以及该用途的数学模型构建方法,以便预测食管鳞癌同步放化疗疗效。
其目的可按照以下方案实现:
一种NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂在预测癌症治疗疗效的用途,所述的癌症治疗是指食管鳞癌同步放化疗。
一种预测食管鳞癌同步放化疗疗效的数学模型的构建方法,其特征在于包括如下步骤:
(1)、取食管鳞癌患者活检组织进行石蜡包埋并切片处理,采用免疫组织化学的实验方法并使用NOTCH3蛋白表达量检测试剂和CYPA蛋白表达量检测试剂,分别对食管鳞癌患者组织的NOTCH3蛋白表达量和CYPA蛋白表达量进行评分,其评分标准如下:NOTCH3蛋白表达量评分=P1×I1,CYPA蛋白量表达评分=P2×I2
其中,P1为检测样本切片NOTCH3蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I1为NOTCH3蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分; P2为检测样本切片CYPA蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I2为CYPA蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分;
(2)、根据步骤(1)的结果,利用X-tile软件分析NOTCH3蛋白表达量高低分界值和CYPA蛋白表达量高低分界值; 接着,定义两种蛋白的疗效预测关系值:若NOTCH3蛋白表达量评分等于或低于对应的表达量高低分界值,则NOTCH3蛋白定为低表达,且定义NOTCH3蛋白的疗效预测关系值为1;若NOTCH3蛋白表达量评分高于对应的表达量高低分界值,则NOTCH3蛋白定为高表达,且定义NOTCH3蛋白的疗效预测关系值为0;若CYPA蛋白表达量评分等于或低于对应的表达量高低分界值,则CYPA蛋白定为低表达,且定义CYPA蛋白的疗效预测关系值为1;若CYPA蛋白表达量评分高于对应的表达量高低分界值,则CYPA蛋白定为高表达,且定义CYPA蛋白的疗效预测关系值为0;
(3)、将步骤(2)得到的疗效预测关系值带入数学模型:患者同步放化疗总疗效预测值=NOTCH3蛋白的疗效预测关系值+CYPA蛋白的疗效预测关系值;
(4)、进行预测疗效:若患者同步放化疗总疗效预测值等于2,则预测该患者同步放化疗疗效预测为敏感;若患者总疗效预测值小于2,则预测该患者同步放化疗疗效预测为抵抗。
所谓蛋白的疗效预测关系值,是指食管鳞癌患者的某一种蛋白的表达量与该患者同步放化疗疗效预测的关系值。
本发明具有以下优点和效果:
一、本发明利用NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂为预测食管鳞癌同步放化疗疗效,为该疗效预测提供了新的途径,能较好地预测食管鳞癌同步放化疗疗效,区分食管鳞癌患者中对放化疗敏感或抵抗的人群,以便延长应用同步放化疗治疗的食管鳞癌患者生存期,改善预后。
二、本发明联合两种蛋白标志物进行预测,预测结果的敏感性和特异性更高(较依靠单一指标的预测而言),使得食管鳞癌同步放化疗疗效预测更为精准。
具体实施方式
实施例一
一种NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂在预测癌症疗效的用途,所述的癌症治疗是指食管鳞癌同步放化疗。
本发明在该实施例一的实际操作中,将NOTCH3蛋白表达量检测剂联合CYPA蛋白表达量检测剂用于18例食管鳞癌患者同步放化疗的疗效,该18例食管鳞癌患者收治于汕头市中心医院肿瘤放疗科,为Ⅲ~Ⅳ期初病例,所有患者均经电子胃镜和病理诊断为食管鳞癌,并且均接受同步放化疗治疗,所涉及的所有实验是在中山大学附属汕头市中心医院伦理委员会和汕头大学医学院伦理委员会的许可下进行的。先收集各食管鳞癌患者治疗前的活检组织,然后通过利用NOTCH3蛋白表达量检测试剂、CYPA蛋白表达量检测试剂制作试剂盒,分别检测各食管鳞癌患者的NOTCH3蛋白表达量和CYPA蛋白表达量,并各根据各患者蛋白表达量高低,预测各食管鳞癌患者的疗效为敏感还是抵抗。
实施例二
一种预测食管鳞癌同步放化疗疗效的数学模型的构建方法,依次包括如下步骤:
(1)、取实施例一的18例食管鳞癌活检组织进行石蜡包埋并切片处理,采用免疫组织化学的实验方法并使用NOTCH3蛋白表达量检测试剂(在该实施例中,NOTCH3蛋白表达量检测试剂采用NOTCH3抗体,来自国CST公司,编号#5276S)和CYPA蛋白表达量检测试剂(在该实施例中,CYPA蛋白表达量检测试剂采用Cyclophilin A 抗体,来自国proteintech公司,编号为10720-1-AP),分别对食管鳞癌患者组织的NOTCH3蛋白表达量和CYPA蛋白表达量进行评分,其评分标准如下:NOTCH3蛋白表达量评分=P1×I1,CYPA蛋白量表达评分=P2×I2;其中,P1为检测样本切片NOTCH3蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I1为NOTCH3蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分; P2为检测样本切片CYPA蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I2为CYPA蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分;
上述18例患者的两种蛋白表达量评分值如下表1:
表1:18例患者的两种蛋白表达量评分值
Figure DEST_PATH_IMAGE001
(2)、根据步骤(1)的结果,利用X-tile软件分析NOTCH3蛋白表达量高低分界值和CYPA蛋白表达量高低分界值; 在该实施例中,经过X-tile软件的分析,NOTCH3蛋白表达量高低分界值为3,CYPA蛋白表达量高低分界值为6;上述18位患者的任意一位,若其NOTCH3蛋白表达量评分等于或低于对应的表达量高低分界值3,则该患者的NOTCH3蛋白定为低表达,且该患者的NOTCH3蛋白的疗效预测关系值定义为1;上述18位患者的任意一位,若其NOTCH3蛋白表达量评分高于对应的表达量高低分界值3,则该患者的NOTCH3蛋白定为高表达,且该患者的NOTCH3蛋白的疗效预测关系值定义为0;上述18位患者的任意一位,若其CYPA蛋白表达量评分等于或低于对应的表达量高低分界值6,则该患者的CYPA蛋白定为低表达,且该患者的CYPA蛋白的疗效预测关系值定义为1;上述18位患者的任意一位,若其CYPA蛋白表达量评分高于对应的表达量高低分界值6,则该患者的CYPA蛋白定为高表达,且该患者的CYPA蛋白的疗效预测关系值定义为0;18位患者的疗效预测关系值具体结果如下表2:
表2:18位患者的疗效预测关系值
Figure DEST_PATH_IMAGE002
(3)、将步骤(2)得到的疗效预测关系值带入数学模型:患者总疗效预测值=NOTCH3蛋白表达量的疗效预测关系值+CYPA蛋白表达量的疗效预测关系值;结果如下表3:
表3:18位患者的总疗效预测值
Figure DEST_PATH_IMAGE003
(4)、进行预测疗效:若患者总疗效预测值等于2,则预测该患者同步放化疗疗效为敏感;若患者总疗效预测值小于2,则预测该患者同步放化疗疗效为抵抗。上述18位患者同步放化疗疗效预测结果如下表4:
表4:18位患者同步放化疗疗效的疗效预测结果
Figure DEST_PATH_IMAGE004
上述18例患者在汕头市中心医院进行同步放化疗治疗,治疗完成后均有入院再次复查,进行疗效评估。按照1981年第三届全国放射学术会议(郑州)治疗组通过的食管癌放疗后X线诊断标准分为四级,Ⅰ级:病变完全消失,食管壁软而光滑,蠕动及扩张良好,粘膜纹理清楚可见。Ⅱ级:病变基本消失,食管壁规则,钡剂能顺利通过,但管壁仍僵硬或狭窄。Ⅲ级:病变明显好转,食管病灶退缩一半以上,没有明显扭曲、成角或突出腔外的溃疡,稠的钡剂能通过。Ⅳ级:病变残留或恶化,病灶消退不到一半,或成角、扭曲明显或有突出腔外的溃疡,钡剂通过极差。
本发明定为:Ⅰ级为完全缓解(CR),Ⅱ级为部分缓解(PR),Ⅲ级为疾病稳定(SD),Ⅳ级为疾病进展(PD)。阳性淋巴结病灶按实体瘤疗效评价标准(response evaluationcriteria in solid tumors, RECIST)1.1 版进行评价。
各患者按照上述标准的进行实际疗效综合评价,若患者放化疗治疗后 3月内未出现局部进展、淋巴结进展及远处转移者(即完全缓解者),定义实际疗效结果为敏感;患者治疗后 3月内出现局部进展、淋巴结进展及远处转移者(即部分缓解或疾病稳定或疾病进展者)定义实际疗效结果为抵抗。
18位患者的实际疗效结果如下表5:
表5:18位患者的同步放化疗疗效实际疗效结果
Figure DEST_PATH_IMAGE005
综合上述疗效预测结果(表4)和实际疗效结果(表5)进行比较,可构建如下蛋白表达量预测患者同步放化疗疗效的评价表(表6)。
表6:蛋白表达量预测患者同步放化疗疗效的评价
Figure DEST_PATH_IMAGE006
综合上述结果,计算各评价结果如下:
灵敏度=9/10=90%,即实际疗效为抵抗且被预测为抵抗患者的概率为90%;
特异度=6/8=75%,即实际疗效为敏感且被预测为敏感患者的概率为75%;
正确率=(9+6)/18=83.3%,即预测结果与实际结果符合的概率为83.3%。
上述结果表明:NOTCH3蛋白与CYPA蛋白作为多分子联合预测模型时,能较好地区分对放化疗敏感和抵抗的人群。因此, 本发明首次采用NOTCH3和CYPA蛋白联合检测进行预测,能较好预测食管鳞癌患者同步放化疗的敏感性,为预测食管鳞癌同步放化疗疗效预测提供了理论依据和临床基础,继而辅助临床医师选择治疗手段,避免食管鳞患者过度治疗,提高食管鳞癌患者的生存质量,延长患者的生存时间有着重要意义,本发明具有创造性。

Claims (1)

1.一种预测食管鳞癌同步放化疗疗效的数学模型的构建方法,其特征在于包括如下步骤:
(1)、取食管鳞癌患者活检组织进行石蜡包埋并切片处理,采用免疫组织化学的实验方法并使用NOTCH3蛋白表达量检测试剂和CYPA蛋白表达量检测试剂,分别对食管鳞癌患者组织的NOTCH3蛋白表达量和CYPA蛋白表达量进行评分,其评分标准如下:NOTCH3蛋白表达量评分=P1×I1,CYPA蛋白量表达评分=P2×I2
其中,P1为检测样本切片NOTCH3蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I1为NOTCH3蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分; P2为检测样本切片CYPA蛋白阳性表达面积百分比,表达面积<5%为0分,5%至<25%为1分,25%至<50%为2分,50%至<75%为3分,>75%为4分; I2为CYPA蛋白染色强度评分,阴性为0分,弱阳性为1分,阳性为2分,强阳性为3分;
(2)、根据步骤(1)的结果,利用X-tile软件分析NOTCH3蛋白表达量高低分界值和CYPA蛋白表达量高低分界值; 接着,定义两种蛋白的疗效预测关系值:若NOTCH3蛋白表达量评分等于或低于对应的表达量高低分界值,则NOTCH3蛋白定为低表达,且定义NOTCH3蛋白的疗效预测关系值为1;若NOTCH3蛋白表达量评分高于对应的表达量高低分界值,则NOTCH3蛋白定为高表达,且定义NOTCH3蛋白的疗效预测关系值为0;若CYPA蛋白表达量评分等于或低于对应的表达量高低分界值,则CYPA蛋白定为低表达,且定义CYPA蛋白的疗效预测关系值为1;若CYPA蛋白表达量评分高于对应的表达量高低分界值,则CYPA蛋白定为高表达,且定义CYPA蛋白的疗效预测关系值为0;
(3)、将步骤(2)得到的疗效预测关系值带入数学模型:患者同步放化疗总疗效预测值=NOTCH3蛋白的疗效预测关系值+CYPA蛋白的疗效预测关系值;
(4)、进行预测疗效:若患者同步放化疗总疗效预测值等于2,则预测该患者同步放化疗疗效预测为敏感;若患者总疗效预测值小于2,则预测该患者同步放化疗疗效预测为抵抗。
CN202010675809.XA 2020-07-14 2020-07-14 Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途 Active CN111796101B (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010675809.XA CN111796101B (zh) 2020-07-14 2020-07-14 Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010675809.XA CN111796101B (zh) 2020-07-14 2020-07-14 Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途

Publications (2)

Publication Number Publication Date
CN111796101A CN111796101A (zh) 2020-10-20
CN111796101B true CN111796101B (zh) 2022-08-26

Family

ID=72807030

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010675809.XA Active CN111796101B (zh) 2020-07-14 2020-07-14 Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途

Country Status (1)

Country Link
CN (1) CN111796101B (zh)

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
NZ577992A (en) * 2006-11-28 2012-09-28 Pictor Ltd Assay membrane and method of use thereof
JP5367490B2 (ja) * 2009-07-29 2013-12-11 古河電気工業株式会社 イムノクロマト法用テストストリップ
AU2014293011A1 (en) * 2013-07-26 2016-03-17 Race Oncology Ltd. Compositions to improve the therapeutic benefit of bisantrene
PT3105317T (pt) * 2014-02-14 2019-02-27 Cellectis Células para imunoterapia manipuladas para atuar sobre antigénios presentes tanto em células imunitárias como em células patológicas
CN105067811A (zh) * 2015-07-22 2015-11-18 中国农业大学 基于荧光微球免疫层析法检测t-2毒素的产品及其制备方法
JP6736437B2 (ja) * 2016-09-20 2020-08-05 積水メディカル株式会社 イムノクロマトグラフィー検出キット
CN108318685A (zh) * 2018-05-04 2018-07-24 广州敏捷生物技术有限公司 用于检测犬冠状病毒抗原的免疫荧光层析检测卡与制备方法
CN109541209B (zh) * 2018-09-26 2022-07-08 汕头大学医学院 食管鳞状细胞癌微环境细胞标志物分子模型及其应用
CN109342727B (zh) * 2018-10-15 2021-11-12 汕头大学医学院附属肿瘤医院 食管鳞状细胞癌自身抗体分子标志物模型及其应用

Also Published As

Publication number Publication date
CN111796101A (zh) 2020-10-20

Similar Documents

Publication Publication Date Title
Fang et al. Diagnostic sensitivity of NLR and PLR in early diagnosis of gastric cancer
KR102561377B1 (ko) 마커 분자를 기반으로 화학요법으로 치료되어야 하는 개체를 식별하는 방법 및 관련 용도
Zhang et al. The pretreatment albumin to globulin ratio, a validated biomarker, predicts prognosis in hepatocellular carcinoma
Zu et al. Integration of platelet features in blood and platelet rich plasma for detection of lung cancer
Wuxiao et al. A prognostic model to predict survival in stage III colon cancer patients based on histological grade, preoperative carcinoembryonic antigen level and the neutrophil lymphocyte ratio
CN111796101B (zh) Notch3蛋白表达量检测剂联合cypa蛋白表达量检测剂在预测癌症治疗疗效的用途
Fan et al. The diagnostic value of determination of serum GOLPH3 associated with CA125, CA19. 9 in patients with ovarian cancer.
Deveci et al. Correlation of systemic immune-inflammation index and neutrophil-to-lymphocyte ratio with histopathological findings in patients with tongue cancer
CN115656511A (zh) 用于消化系统肿瘤体外诊断的标志物及试剂盒
Luo et al. Strategies for five tumour markers in the screening and diagnosis of female breast cancer
Cheng et al. Circulating tumor cells as diagnostic markers of early gastric cancer and gastric precancerous lesions
Jin et al. Predictive factors analysis for malignant peritoneal mesothelioma
Zhang et al. HALP score based on hemoglobin, albumin, lymphocyte and platelet can predict the prognosis of tongue squamous cell carcinoma patients
Shui et al. Relationship between cyclooxygenase-2 (COX-2) content and prognosis in nasopharyngeal carcinoma before and after radiochemotherapy
Liu et al. The Number of Intraoperative Intestinal Venous Circulating Tumor Cells Is a Prognostic Factor for Colorectal Cancer Patients
Su et al. High serum squamous cell carcinoma antigen level associated with remission of mild/moderate dysplasia of the esophagus: A nested case–control study
Demir et al. C-reactive protein to albumin ratio is an indicator of poor prognostic for patients with biliary tract cancer
Çimen et al. Role of Inflammatory Response Biomarkers, Monocytes, and Platelets as Prognostic Indicators in Lung Cancer Patients Presenting with Malignant Pleural Effusion.
Lin et al. TFE3 gene rearrangement and protein expression contribute to a poor prognosis of renal cell carcinoma
AL-Aflwky et al. Correlation of the Interlukein-8 with Breast Cancer Patients in Iraqi Woman’s
Núñez Rodríguez et al. Findings in the distal and proximal colon in colonoscopy screening after positive FIT and related pre-procedure factors
Ji et al. Combination of procalcitonin, C‑reaction protein and carcinoembryonic antigens for discriminating between benign and malignant pleural effusions
Masaki et al. Colonoscopic treatment of colon cancers
Telli et al. Can Preoperative Complete Blood Count Parameters and Tumor Markers Predict The Differential Diagnosis of Mucinous Ovarian Tumors?
Montes de Jesus et al. Unexplained increase of serum carcinoembryonic antigen: don’t forget the thyroid!

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant