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The Vaginal Microbiome and Cervical Cancer Screening in Low- and Middle-Income Countries 中低收入国家阴道微生物组与癌症筛查
Pub Date : 2019-10-09 DOI: 10.1200/jgo.19.15000
S. Mehta
Globally, cervical cancer affects more than a half-million women each year, with disproportionate incidence and mortality for women in low- and middle-income countries. Early detection through cervical cancer screening saves lives but is hampered by poor coverage, suboptimal detection accuracy, and lack of access to and delays in effective treatment. Emerging evidence that indicates how the vaginal microbiome can modify progression of human papillomavirus (HPV) infection and cervical cancer pathogenesis is surveyed. This presentation features a discussion of how the vaginal microbiome may affect cervical cancer screening and how cervical cancer screening may incorporate vaginal microbiome health in low- and middle-income countries. Vaginal dysbiosis as a clinical syndrome may be called bacterial vaginosis (BV), a condition that represents a shift from a Lactobacillus-dominant vaginal microbiome to one that is polymicrobial and often associated with increased mucosal inflammation. Meta-analyses and prospective studies demonstrate an association between vaginal dysbiosis and increased risk of HPV incidence and persistence and high-grade lesions and cancer. Increasing vaginal microbiome diversity is associated with progression of cervical intraepithelial neoplasia. Vaginal microbiota that are associated with greater likelihood of HPV detection in molecular studies are also commonly associated with BV. There are numerous challenges to incorporating microbiome measurement in population-level cervical cancer screening and unanswered research questions on its immediate utility. BV may serve as a measure of vaginal microbiome health, although there are no guidelines or recommendations for regular BV screening and treatment. Ongoing and planned longitudinal studies should evaluate BV screening in association with high-risk HPV, results of cervical cancer screening, and progression of cervical intraepithelial neoplasia to assess the utility of BV screening and treatment as an adjunct to cervical cancer screening and potential intervention.
在全球范围内,癌症每年影响50多万妇女,中低收入国家妇女的发病率和死亡率不成比例。通过宫颈癌症筛查进行早期检测可以挽救生命,但由于覆盖率低、检测精度低、缺乏有效治疗机会和延误而受到阻碍。调查了表明阴道微生物组如何改变人乳头瘤病毒(HPV)感染和宫颈癌症发病机制的新证据。本专题讨论了阴道微生物组如何影响癌症宫颈筛查,以及癌症宫颈筛查如何结合低收入和中等收入国家的阴道微生物组健康。阴道微生态失调作为一种临床综合征,可被称为细菌性阴道病(BV),这种情况代表着从乳杆菌占主导地位的阴道微生物组向多微生物组的转变,通常与粘膜炎症增加有关。Meta-analysis和前瞻性研究表明,阴道生态失调与HPV发病率和持续性、高级别病变和癌症风险增加之间存在关联。阴道微生物组多样性的增加与宫颈上皮内瘤变的进展有关。在分子研究中,与更大的HPV检测可能性相关的阴道微生物群通常也与BV相关。在人群层面的宫颈癌症筛查中结合微生物组测量存在许多挑战,其直接用途的研究问题尚未得到解答。BV可以作为阴道微生物组健康的衡量标准,尽管没有定期进行BV筛查和治疗的指南或建议。正在进行和计划进行的纵向研究应评估BV筛查与高危HPV、宫颈癌症筛查结果和宫颈上皮内瘤变进展的关系,以评估BV筛查和治疗作为宫颈癌症筛查和潜在干预的辅助手段的效用。
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引用次数: 0
Usability and Effectiveness of a Smartphone Application for Tracking Oncology Patients in Gaborone, Botswana 可用性和有效性的智能手机应用程序跟踪肿瘤患者在哈博罗内,博茨瓦纳
Pub Date : 2019-10-09 DOI: 10.1200/jgo.19.20000
Sidrah Shah, B. Monare, Sandra Urusaro, R. Bhatia, Sherman Preet Singh, T. Ralefala, Givy Dhaliwal, S. Grover
Most cancer diagnoses are expected to be in low- and middle-income countries (LMICs) by 2025, and 65% of cancer deaths occur in LMICs. Treatment adherence and patient monitoring are essential to cancer care but are often not possible in LMICs. OP Care, a smartphone application developed to fill this gap, stores medical records virtually and texts appointment reminders to patients. This study assessed its usability and effectiveness. OP Care was piloted at Princess Marina Hospital in Gaborone, Botswana. The study was a cross-sectional study using surveys. All providers using the application were surveyed, along with all patients who were previously enrolled in the application and attended the gynecologic oncology clinic during the 3-week survey period. Staff demographics, reaction, opinions on usability, and patients’ reactions to appointment reminders were collected. Answers were recorded on a 1 (not at all) to 7 (extremely so) scale. Primary outcomes were the application’s usability and the effectiveness of the text reminders. The University of Pennsylvania Institutional Review Board and the Ministry of Health and Wellness in Botswana gave approval for the study. Patients provided written consent before enrollment. Nine staff and 15 patients were surveyed. Staff included three doctors and six nurses, all of whom own a smartphone and use a computer at home. Most staff (78%) did not feel OP Care would increase their work burden and were willing to use the application if implemented permanently (median response, 6; interquartile range [IQR], 1). Most usability questions (17 of 19), such as “I feel comfortable using this system,” scored a median of 6. Most patients believed that the reminder text messages were helpful (median, 6; IQR, 1) but wanted the text reminders to be in the Setswana language (median, 7; IQR, 1). High usability scores indicate the application is adaptable to other clinics. Although patients appreciate OP Care, the option for call and text reminders in Setswana is indicated. A potential limitation is that patients for whom the appointment reminders were not helpful were not necessarily included, because only patients in the clinic were surveyed. Strengths were inclusion of all involved staff, uniformity in survey administration, and inclusion of numerical analysis.
到2025年,大多数癌症诊断预计将发生在低收入和中等收入国家(LMIC),65%的癌症死亡发生在LMIC。坚持治疗和患者监测对癌症护理至关重要,但在LMIC中通常是不可能的。OP Care是一款为填补这一空白而开发的智能手机应用程序,它可以虚拟存储医疗记录,并向患者发送预约提醒短信。这项研究评估了它的可用性和有效性。OP Care在博茨瓦纳哈博罗内的公主码头医院进行了试点。这项研究是一项横断面调查研究。所有使用该应用程序的提供者以及之前参与该应用程序并在3周调查期内参加妇科肿瘤诊所的所有患者都接受了调查。收集工作人员的人口统计、反应、对可用性的意见以及患者对预约提醒的反应。答案被记录在1(一点也不)到7(非常)的范围内。主要结果是应用程序的可用性和文本提醒的有效性。宾夕法尼亚大学机构审查委员会和博茨瓦纳卫生与健康部批准了这项研究。患者在入组前提供书面同意书。调查了9名工作人员和15名患者。工作人员包括三名医生和六名护士,他们都有一部智能手机,在家里使用电脑。大多数员工(78%)不认为OP Care会增加他们的工作负担,如果永久实施,他们愿意使用该应用程序(中位响应,6;四分位间距[IQR],1)。大多数可用性问题(19个问题中的17个),如“我觉得使用这个系统很舒服”,得分中值为6。大多数患者认为提醒短信是有帮助的(中位数,6;IQR,1),但希望短信提醒使用塞茨瓦纳语(中位数,7;IQR)。高可用性分数表明该应用程序适用于其他诊所。尽管患者很欣赏OP Care,但在Setswana有电话和短信提醒的选项。一个潜在的限制是,预约提醒对患者没有帮助的患者不一定包括在内,因为只有诊所的患者接受了调查。优势是包括所有相关工作人员,统一调查管理,并包括数字分析。
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引用次数: 1
Knowledge and Screening Practices for Cervical Cancer Among Urban Poor Communities in Ibadan, Nigeria 尼日利亚伊巴丹城市贫困社区癌症知识和筛查实践
Pub Date : 2019-10-09 DOI: 10.1200/jgo.19.10000
Y. John-Akinola, M. Oluwasanu, O. Oladepo
Prevalence of cervical cancer remains high in sub-Saharan Africa, including Nigeria. Literature has documented knowledge of cervical cancer as important in promoting the adoption of preventive strategies, including screening, but most research has focused on women and health organization settings. This study assessed knowledge and screening practices of cervical cancer among male and female adults in urban poor communities in Ibadan, Oyo State, Nigeria. A cross-sectional study was carried out in two urban poor community settings in Ibadan. Data were collected from 250 randomly selected consenting respondents in each of the two communities (N = 500). Data were collected with an electronic device using the electronic data capture tool (Open Data Kit) database. Descriptive statistics were summarized using frequencies and percentages for categorical variables, and mean and standard deviation were used for continuous variables. Knowledge was scored on a scale of 0 to 39 points (0 to 18, low knowledge; 19 to 23, fair knowledge; 24 to 39, high knowledge). Associations between variables were tested using χ2. Mean age of respondents was 35.36 years (± 12.24). The majority of respondents were female (70.6%), and more than half (52.6%) had completed secondary school education. The majority had never heard of the Papanicolaou test (93.6%) or cervical cancer screening (91.2%), and only 10% had ever heard of the human papillomavirus vaccine for the prevention of cervical cancer. The majority had low knowledge of cervical cancer (77.2%); knowledge included detection, symptoms, and risk factors for cervical cancer. Only 7.4% of females had ever heard of the Papanicolaou test, and few women (4%) had ever been screened for cervical cancer using the Papanicolaou test. Only one woman (0.2%) had been screened for cervical cancer using visual inspection with acetic acid, and four (0.8%) had ever taken human papillomavirus vaccine for protection against cervical cancer. There was a significant association between knowledge of cervical cancer and employment status of respondents (χ2 = 11.19; P < .05). Health promotion interventions and strategies for awareness creation about cervical cancer and screening practices should be used in alleviating low knowledge and screening practices in urban poor communities.
在包括尼日利亚在内的撒哈拉以南非洲,宫颈癌症的患病率仍然很高。文献记录了癌症知识在促进采用包括筛查在内的预防策略方面的重要性,但大多数研究都集中在妇女和卫生组织环境中。这项研究评估了尼日利亚奥约州伊巴丹市城市贫困社区男性和女性成年人对宫颈癌症的知识和筛查实践。在伊巴丹的两个城市贫困社区环境中进行了一项横断面研究。数据是从两个社区的250名随机选择的同意受访者中收集的(N=500)。使用电子数据采集工具(开放数据包)数据库,使用电子设备收集数据。描述性统计使用分类变量的频率和百分比进行总结,平均值和标准差用于连续变量。知识分为0至39分(0至18分,低知识;19至23分,一般知识;24至39分,高知识)。使用χ2检验变量之间的相关性。受访者的平均年龄为35.36岁(±12.24)。大多数受访者为女性(70.6%),超过一半(52.6%)已完成中学教育。大多数人从未听说过帕帕尼考试验(93.6%)或癌症宫颈筛查(91.2%),只有10%听说过预防癌症的人乳头瘤病毒疫苗。大多数患者对宫颈癌症的了解程度较低(77.2%);知识包括宫颈癌症的检测、症状和危险因素。只有7.4%的女性听说过帕尼检查,很少有女性(4%)使用帕尼检查筛查过癌症。只有一名妇女(0.2%)通过醋酸目视检查进行了宫颈癌症筛查,四名妇女(0.8%)接种了人乳头瘤病毒疫苗以预防宫颈癌症。癌症知识与被调查者的就业状况之间存在显著关联(X~2=1.19;P<.05)。应使用健康促进干预措施和提高对癌症和筛查实践的认识的策略来缓解城市贫困社区的低知识和筛查实践。
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引用次数: 0
Tyrosine aminoacyl-tRNA synthetase sensitizes breast cancer to chemotherapy through a necroptosis-mediated mechanism. 酪氨酸氨基酰基-tRNA合成酶通过坏死介导的机制使癌症对化疗敏感。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.40
H. Ryu
40 Background: A complete response to chemotherapy for most cancer patients is, and there are many complications caused by this toxic therapy. Therefore, we sought to determine chemotherapy responses in breast cancer at the proteome level. Methods: Candidate proteins were filtered out by the proteomic-based multiple machine-learning algorithms. Results: The MS analysis of FFPE set yielded 6,069 protein groups. The filtered dataset resulted in 539 proteins with differential abundances. We searched for biological process in the Gene Ontology (GO) enrichment analysis in each proteomic cluster. Several immune responses process, apoptotic process, DNA replication process and aminoacylation for protein translation process primarily were represented in group with complete remission. On the other hand, cell adhesion process, cytoskeleton organization process, vesicle organization process and Golgi organization process represented in breast cancer which showed poor responses to the therapy. The machine learning approaches demonstrated the highest AUC value, 0.978 (sensitivity 1.0 and specificity 0.714) with a combination of 11 proteins. Among them the finally selected tyrosine aminoacyl-tRNA synthetase (YARS) showed AUC (AUC = 0.749) in the subsequent steps of verification using immunohistochemistry in 123 patient cohorts. We identified the predictive relevance of YARS. YARS induced tumor necroptosis was greatly enhanced when it was combined synergistically with a combination of SMAC mimetics and a BCL2 inhibitor. Conclusions: This suggested that YARS expression could serve as a new therapeutic target for improving the clinical benefits of chemotherapy.
40背景:大多数癌症患者对化疗的完全反应是无效的,并且这种毒性治疗引起了许多并发症。因此,我们试图在蛋白质组水平上确定乳腺癌的化疗反应。方法:采用基于蛋白质组学的多机器学习算法筛选候选蛋白。结果:对FFPE组进行质谱分析,共得到6069个蛋白组。过滤后的数据集产生了539种不同丰度的蛋白质。我们在每个蛋白质组学簇的基因本体(GO)富集分析中寻找生物过程。完全缓解组主要表现为免疫应答过程、细胞凋亡过程、DNA复制过程和蛋白质翻译过程中的氨基酰化过程。另一方面,以乳腺癌为代表的细胞粘附过程、细胞骨架组织过程、囊泡组织过程和高尔基体组织过程对治疗反应较差。机器学习方法在11种蛋白质的组合中显示出最高的AUC值,为0.978(灵敏度1.0,特异性0.714)。其中最终选择的酪氨酸氨基酰基- trna合成酶(YARS)在123个患者队列的后续免疫组化验证步骤中显示AUC (AUC = 0.749)。我们确定了YARS的预测相关性。当YARS与SMAC模拟物和BCL2抑制剂联合使用时,YARS诱导的肿瘤坏死坏死显著增强。结论:提示YARS表达可作为提高化疗临床疗效的新靶点。
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引用次数: 0
A novel computational OMICS and non-OMICS approach for identifying true pathogenic risk variants for Asian prostate cancer. 一种新的计算组学和非组学方法用于识别亚洲前列腺癌的真正致病风险变异。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.47
Anusha Chimmiri, Haitao Wang, E. Yeo, K. Low, A. Tan, Wai Yee Woo, E. Ong, T. Tan, W. S. Looi, W. Nei, J. Tuan, Michael L C Wang, J. S. Tan, L. Lee, K. Tay, R. Kanesvaran, L. Khor, J. Yeong, Chien Sheng Tan, M. Chua
47 Background: Large-scale genome-wide association studies have established germline polygenic risk loci that underpin the susceptibility to prostate cancer (PCa). However, most trials conducted are in men of European ancestry with data missing for Asian male PCa. Here, we report on an in-house multidimensional bioinformatics pipeline that integrates OMICS and non-OMICS approaches in identifying true germline risk-variants for PCa in Asian men. Methods: We utilized a prospective cohort study of Asian men who were newly diagnosed with PCa. Whole exome sequencing (Illumina Hiseq, CA) of blood (100X) was performed. The OMICS-based approach entailed a stepwise screen for hallmarks of cancer-specific pathways. A genome-proteome network was then developed to filter for known pathogenic variants; this was followed by comparison against a large artificial database of aggregated germline variants (N = 95,000) with reported linkage to PCa susceptibility. Finally, mutations were filtered through a non-OMICS pipeline that entailed data synchronization with population-level statistics and clinical outcomes (recurrence and survival). Results: Preliminary analyses were based on 277 PCa cases; of which 50 were M1 cases. Screening using a non-combined unbiased approach yielded 36,157 germline variants. This contrast against our OMICS-based approach, which reduced the variant calls to 6,144 significantly associated mutations. Next, by focusing on pathway-specific genes related to hormonal regulation and known cancer hotspot mutations, we could further tighten our variant calls to 3,562 hormone-related variants (rs9269958 on HLA-DRB1) and 2,125 variants in known cancer genes, notably (rs8176320 on BRCA1/2, rs2555691 on LILRA2, rs8036934 on TP53BP1). Conclusions: Here, we show that application of an OMICS approach that combines pathway-driven analyses and an artificial dataset, along with population-level statistics and clinical relevance resulted in more robust annotation of germline variants that were associated with PCa.
47背景:大规模全基因组关联研究已经建立了种系多基因风险基因座,这些基因座支持了对前列腺癌症(PCa)的易感性。然而,大多数试验都是在欧洲血统的男性中进行的,亚洲男性前列腺癌的数据缺失。在这里,我们报道了一个内部多维生物信息学管道,该管道整合了OMICS和非OMICS方法,用于识别亚洲男性前列腺癌的真正种系风险变体。方法:我们对新诊断为前列腺癌的亚洲男性进行了前瞻性队列研究。对血液(100X)进行全外显子组测序(Illumina Hiseq,CA)。基于OMICS的方法需要逐步筛选癌症特异性途径的特征。然后开发了一个基因组蛋白质组网络来过滤已知的致病性变体;随后与已报道与PCa易感性相关的聚集种系变异(N=95000)的大型人工数据库进行比较。最后,通过非OMICS管道过滤突变,该管道需要与人群水平的统计数据和临床结果(复发和存活率)进行数据同步。结果:对277例前列腺癌进行了初步分析;其中M1型50例。使用非组合无偏方法进行筛选产生36157个种系变异。这与我们基于OMICS的方法形成了对比,后者将变体调用减少到6144个显著相关的突变。接下来,通过关注与激素调节和已知癌症热点突变相关的路径特异性基因,我们可以进一步加强对3562种激素相关变体(HLA-DRB1上的rs9269958)和已知癌症基因中2125种变体的变体调用,特别是(BRCA1/2上的rs8176320、LILRA2上的rs2555691、TP53BP1上的rs8036934)。结论:在这里,我们表明,OMICS方法的应用结合了路径驱动的分析和人工数据集,以及人群水平的统计和临床相关性,对与前列腺癌相关的种系变异进行了更有力的注释。
{"title":"A novel computational OMICS and non-OMICS approach for identifying true pathogenic risk variants for Asian prostate cancer.","authors":"Anusha Chimmiri, Haitao Wang, E. Yeo, K. Low, A. Tan, Wai Yee Woo, E. Ong, T. Tan, W. S. Looi, W. Nei, J. Tuan, Michael L C Wang, J. S. Tan, L. Lee, K. Tay, R. Kanesvaran, L. Khor, J. Yeong, Chien Sheng Tan, M. Chua","doi":"10.1200/jgo.2019.5.suppl.47","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.47","url":null,"abstract":"47 Background: Large-scale genome-wide association studies have established germline polygenic risk loci that underpin the susceptibility to prostate cancer (PCa). However, most trials conducted are in men of European ancestry with data missing for Asian male PCa. Here, we report on an in-house multidimensional bioinformatics pipeline that integrates OMICS and non-OMICS approaches in identifying true germline risk-variants for PCa in Asian men. Methods: We utilized a prospective cohort study of Asian men who were newly diagnosed with PCa. Whole exome sequencing (Illumina Hiseq, CA) of blood (100X) was performed. The OMICS-based approach entailed a stepwise screen for hallmarks of cancer-specific pathways. A genome-proteome network was then developed to filter for known pathogenic variants; this was followed by comparison against a large artificial database of aggregated germline variants (N = 95,000) with reported linkage to PCa susceptibility. Finally, mutations were filtered through a non-OMICS pipeline that entailed data synchronization with population-level statistics and clinical outcomes (recurrence and survival). Results: Preliminary analyses were based on 277 PCa cases; of which 50 were M1 cases. Screening using a non-combined unbiased approach yielded 36,157 germline variants. This contrast against our OMICS-based approach, which reduced the variant calls to 6,144 significantly associated mutations. Next, by focusing on pathway-specific genes related to hormonal regulation and known cancer hotspot mutations, we could further tighten our variant calls to 3,562 hormone-related variants (rs9269958 on HLA-DRB1) and 2,125 variants in known cancer genes, notably (rs8176320 on BRCA1/2, rs2555691 on LILRA2, rs8036934 on TP53BP1). Conclusions: Here, we show that application of an OMICS approach that combines pathway-driven analyses and an artificial dataset, along with population-level statistics and clinical relevance resulted in more robust annotation of germline variants that were associated with PCa.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45614986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
XenoSarc: A comprehensive platform of patient-derived xenograft (PDX) models of soft tissue sarcoma (STS) for early drug testing. XenoSarc:用于早期药物测试的患者来源的软组织肉瘤(STS)异种移植(PDX)模型的综合平台。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.37
P. Schöffski, Britt Van Renterghem, J. Cornillie, Yanni Wang, Y. Gebreyohannes, Che-Jui Lee, J. Wellens, U. Vanleeuw, Madita Nysen, D. Hompes, M. Stas, F. Sinnaeve, H. Wafa, B. Topal, T. Verbelen, M. Debiec-Rychter, R. Sciot, A. Wozniak
37 Background: STS is a family of rare, heterogeneous tumors with > 70 subtypes. There is an urgent need for reliable preclinical models, especially for orphan subtypes of STS, given the limited treatment options. Methods: A panel of PDX models was established by s.c. implantation of fresh tumor specimens in athymic NMRI mice. Growing pieces of tumor were re-transplanted to next generations of mice. At each passage fragments were collected for histological/molecular characterization. A model was considered “established” after observing stable features for at least 2 passages. Ex-mouse tissue samples were stored, characterized by immunohistochemistry/flow cytometry and used for in vitro drug testing. Results: Between 2011-2019, 329 samples from 301 consenting patients were transplanted; 56 models are established, 16 additional models are in early passaging. Clinical information about donor and tumor (including sensitivity to standard and experimental agents) is available. The platform includes models of dedifferentiated lipo- (10 models), myxofibro- (8), leiomyo- (7), synovial (2), intimal (2), CIC-positive round cell (1), mesenchymal chondro- (1), extraskeletal osteo- (1), myxoid lipo- (1), myxoinflammatory fibroblastic (1), rhabdomyo- (2) and high-grade undifferentiated pleomorphic sarcoma (7), as well as GIST (8), MPNST (4) and epithelioid hemangioendothelioma (1). Models are well-characterized, with molecular information on copy number changes (low-coverage whole genome sequencing) and gene expression profile (RNA-Seq) available. We also constructed tissue microarrays from the xenografts which are used for target identification and model selection for preclinical studies. Xenografts are available for in vivo testing of novel agents, and results already served as a rationale for a number of prospective clinical trials. Conclusions: XenoSarc offers opportunities for studying the biology of a variety of sarcoma subtypes including ultra-rare entities and is a valuable tool for early drug screening in preparation of clinical STS trials. The platform is well maintained and continuously expanded, and available to collaborators from academia and industry.
37背景:STS是一个罕见的异质性肿瘤家族,有70多种亚型。鉴于治疗选择有限,迫切需要可靠的临床前模型,尤其是STS的孤儿亚型。方法:通过皮下植入无胸腺NMRI小鼠的新鲜肿瘤标本建立PDX模型。生长中的肿瘤块被重新移植到下一代小鼠身上。在每个传代时收集片段用于组织学/分子表征。在观察到至少2个传代的稳定特征后,认为模型已经“建立”。储存离体小鼠组织样本,通过免疫组织化学/流式细胞术进行表征,并用于体外药物测试。结果:2011-2019年间,来自301名自愿患者的329份样本被移植;建立了56个模型,另外16个模型处于早期通过阶段。关于供体和肿瘤的临床信息(包括对标准和实验药物的敏感性)是可用的。该平台包括去分化脂肪模型(10个模型)、粘纤维模型(8个)、平滑肌模型(7个)、滑膜模型(2个)、内膜模型(2)、CIC阳性圆细胞模型(1个)、间充质软骨模型(1)、骨外骨模型(1种)、粘液样脂肪模型(1份)、粘炎性成纤维细胞模型(一份)、横纹肌模型(2份)和高级未分化多形性肉瘤模型(7份),以及GIST模型(8份),MPNST(4)和上皮样血管内皮瘤(1)。模型具有良好的特征,可以获得关于拷贝数变化(低覆盖率全基因组测序)和基因表达谱(RNA-Seq)的分子信息。我们还从异种移植物中构建了组织微阵列,用于临床前研究的靶点识别和模型选择。异种移植物可用于新型药物的体内测试,其结果已成为许多前瞻性临床试验的基本原理。结论:XenoArc为研究包括超罕见实体在内的多种肉瘤亚型的生物学提供了机会,是临床STS试验准备中早期药物筛选的宝贵工具。该平台维护良好,并不断扩展,可供学术界和工业界的合作者使用。
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引用次数: 1
Immune dysregulation underpins radioresistance in nasopharyngeal carcinoma (NPC). 免疫失调是鼻咽癌放射耐药的基础。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.52
Haitao Wang, E. Yeo, J. Hwang, G. S. Tan, E. Ong, K. Low, Anusha Chimmiri, Wai Yee Woo, W. Nei, K. Lim, M. Tan, J. H. Loh, Constance Teo, H. Heah, G. Tay, J. Wee, N. Iyer, Ying Sun, J. Bei, M. Chua
52 Background: Radiotherapy (RT) is a primary modality in the treatment of NPC. However, 30% of patients present with disease recurrence following RT of this radiosensitive tumor. Here, we investigated the molecular and immune profiles associated with radioresistant (RR) NPC. Additionally, we investigated for aberrant molecular pathways in paired recurrences of patients to uncover new drivers underpinning radioresistance. Methods: We prospectively recruited a cohort of 100 NPC patients who completed definitive RT/chemoRT; including 30 cases who were recruited at recurrence. Whole exome sequencing (WES) at 200x was performed to identify low frequencies ( < 1%) of true somatic nucleotide variants (SNVs) and copy number alterations (CNAs). Transcriptomic profiles from RNAseq were interrogated using supervised and unsupervised statistical approaches to determine aberrant pathways that were significantly associated with RR. Results: Genomic instabilityas characterized by percentage genome alteration (PGA) was comparable in our cohort. Additionally, we did not observe any common or exclusive CNAs between RR- and nr-NPC cases. Based on a constellation of immune-related signatures, we observed an “immune-cold” profile that is associated with RR-NPC compared to nr-NPC controls, which is characterized by low expression of CD8+ T cell infiltration and interferon-γ response. Expectedly, pathways relating to angiogenesis, hypoxia and NOTCH signaling were upregulated in the RR-NPC cohort. Interestingly, we observed a reversal of the immune phenotype from “cold” to an enrichment of effector T cell infiltration in the paired recurrences. Conclusions: Here, we present a comprehensive mutational landscape of RR-NPC, which revealed the potential role of the immune environment in modulating RR. The longitudinal immune dysregulation of the tumor microenvironment between the de novo tumors and recurrences could be a driver or passenger event during the onset of recurrence.
背景:放疗(RT)是鼻咽癌治疗的主要方式。然而,30%的患者在放疗后出现疾病复发。在这里,我们研究了与放射耐药(RR)鼻咽癌相关的分子和免疫谱。此外,我们研究了配对复发患者的异常分子途径,以发现支持放射耐药的新驱动因素。方法:我们前瞻性地招募了100名鼻咽癌患者,他们完成了最终的放疗/化疗;包括30例复发患者。采用200x全外显子组测序(WES)鉴定低频率(< 1%)的真体细胞核苷酸变异(snv)和拷贝数改变(CNAs)。使用监督和非监督统计方法对RNAseq的转录组谱进行查询,以确定与RR显著相关的异常通路。结果:以基因组改变百分比(PGA)为特征的基因组不稳定性在我们的队列中具有可比性。此外,我们没有观察到RR-和nr-NPC病例之间有任何共同或排他性的中枢神经系统病变。基于一系列免疫相关的特征,我们观察到与nr-NPC对照相比,RR-NPC具有“免疫冷”特征,其特征是CD8+ T细胞浸润和干扰素-γ反应的低表达。意料之中的是,与血管生成、缺氧和NOTCH信号通路相关的通路在RR-NPC队列中上调。有趣的是,我们观察到成对复发的免疫表型从“冷”逆转为效应T细胞浸润的富集。结论:在这里,我们展示了RR- npc的全面突变景观,揭示了免疫环境在调节RR中的潜在作用。肿瘤微环境在新生肿瘤和复发之间的纵向免疫失调可能是复发开始时的驱动或乘客事件。
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引用次数: 1
AI oncology algorithm and dynamic real-world learning health care system for precision oncology. AI肿瘤学算法和用于精确肿瘤学的动态真实世界学习医疗保健系统。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.35
I. Peták, C. Hegedűs, D. Tihanyi, R. Dóczi, P. Filotás, Attila Mate, M. Bacskai, R. Schwáb, I. Vályi-Nagy
35 Background: Most tumours harbor multiple driver genetic alterations and many driver alterations are linked to multiple targeted therapies with various level of evidence. In addition, a specific treatment can be linked to multiple genetic alterations in the same tumor. Several public and private databases and software solutions are available to link driver alterations to treatments options, but in clinical practice of precision oncology we need a solution to select the right treatment for our patients based on the highest level of evidence also in case of complex molecular profiles. Methods: We have developed an AI oncology algorithm and rule-engine to prioritise treatment options for every cancer patient based on the individual molecular of their tumor. This IT solution can now prioritise 1200 compounds in clinical use or clinical development based on the computing of 24,000 evidence-based associations (“rules”) between drivers, targets and compounds. The software calculates a numeric score, the “aggregated evidence level” for each driver alterations and compounds. We have linked this decision support software to a dynamic patient case management system, which records responds to therapy to create learning system to provide dynamic decision support through several lines of therapies of each patient and to use real-life evidence to further improve the algorithm. Results: Our first results indicate that system allows individualised decision of diagnostic option between single gene tests to comprehensive 600 gene NGS panels and identification of actionable alterations in 83% of cancer cases. Conclusions: This system can be a first working solution to standardise clinical decisions precision oncology, which also helps the real-life evaluation of novel multigene molecular diagnostic tests and therapies to find their best indications and accelerate their reimbursement by insurance companies and national health funds.
背景:大多数肿瘤含有多种驱动基因改变,许多驱动基因改变与多种靶向治疗有关,证据水平不一。此外,一种特定的治疗方法可能与同一肿瘤中的多种基因改变有关。有几个公共和私人数据库和软件解决方案可以将驱动因素的改变与治疗方案联系起来,但在精确肿瘤学的临床实践中,我们需要一个解决方案,在复杂分子谱的情况下,根据最高水平的证据为患者选择正确的治疗方案。方法:我们开发了一种人工智能肿瘤学算法和规则引擎,根据每个癌症患者的肿瘤个体分子来优先考虑治疗方案。该IT解决方案现在可以根据驱动因素、靶点和化合物之间24000种循证关联(“规则”)的计算,对1200种临床使用或临床开发的化合物进行优先排序。该软件计算出一个数字分数,即每个司机的改变和混合的“综合证据水平”。我们将该决策支持软件与动态患者病例管理系统联系起来,该系统记录对治疗的反应,创建学习系统,通过每个患者的几条治疗线提供动态决策支持,并使用现实证据进一步改进算法。结果:我们的第一个结果表明,该系统可以在单基因测试和综合600个基因NGS面板之间做出个性化的诊断选择,并在83%的癌症病例中识别出可操作的改变。结论:该系统可作为规范精准肿瘤学临床决策的首个工作解决方案,也有助于新型多基因分子诊断检测和治疗的现实评估,找到其最佳适应症,加快其被保险公司和国家卫生基金报销。
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引用次数: 0
Deep learning analysis for automatic lung nodule detection. 肺结节自动检测的深度学习分析。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.27
Xiaohua Liu
27 Background: The prevalence of lung cancer has been increased markedly in worldwide range with growing clinical significance, the quantitative and qualitative analysis on lung nodules has proven to be important for the early-detection of lung cancer as well as its treatment in clinical practice. However, lung lesion screening performed by radiologists can be very time-consuming and its accuracy varies depending on doctor’s individual experiences. In this study, we aim to build up a robust CAD system that automatically detects the lesion locations and quantitatively characterizes the detected lesions on CT images. Methods: Specifically, we employed the deep learning analysis for lesion detection in patients and performed image processing techniques to generate quantitative morphology features for assisting lesion diagnosis . The data collected includes 3956 lung CT series (slice thickness≤3mm) with multiple lung nodules from 15 Class-A hospitals in China , 1155 lung CT scan from Luna16 dataset as well as CT scans from Kaggle dataset (Data Science Bowl 2017). Lung nodule annotation was then performed by two experienced radiologists and further assessed by four senior associate chief physicians. The obtained CT images were randomly selected and split to construct training, validation and test dataset. After preprocessing, a pre-trained ResNet18 framework is transferred to develop a robust detection system to detect the possible lung lesion locations with corresponding probabilities. Results: The resulting detection system yields FROC of 0.4663, recall of 82.46%, precision of 36.06% for 5~30mm nodules. Each detected lesion was labeled by its bounding box and was then analyzed through image processing algorithm to generate diagnostic assisting features, including longest diameter, shortest diameter, volume, largest cross section area as well as its density type (calcify, solid, partial solid, and ground-glass opacity). Conclusions: The proposed CAD system offers a fast and convenient approach for assisting the diagnosis of lung nodule pathologies, and it is beneficial to relate our research to the current framework of lung cancer diagnosis.
27背景:肺癌的患病率在世界范围内显著增加,临床意义日益重要,肺结节的定量和定性分析在临床实践中对肺癌的早期发现和治疗具有重要意义。然而,由放射科医生进行的肺病变筛查非常耗时,其准确性取决于医生的个人经验。在本研究中,我们的目标是建立一个强大的CAD系统,自动检测病变的位置,并定量表征检测到的病变在CT图像上。方法:具体而言,我们采用深度学习分析对患者进行病变检测,并使用图像处理技术生成定量形态学特征以辅助病变诊断。收集的数据包括来自中国15家甲级医院的3956个肺CT系列(切片厚度≤3mm),来自Luna16数据集的1155个肺CT扫描以及来自Kaggle数据集的CT扫描(2017年数据科学碗)。然后由两名经验丰富的放射科医生进行肺结节注释,并由四名高级副主任医师进一步评估。随机选取并分割得到的CT图像,构建训练、验证和测试数据集。预处理后,转移预训练的ResNet18框架,开发鲁棒检测系统,以相应概率检测可能的肺病变位置。结果:所建立的检测系统对5~30mm结节的检出率为0.4663,召回率为82.46%,精密度为36.06%。对检测到的病灶进行边界框标记,然后通过图像处理算法进行分析,生成诊断辅助特征,包括最长直径、最短直径、体积、最大横截面积及其密度类型(钙化、实性、部分实性、毛玻璃不透明)。结论:所建立的CAD系统为辅助肺结节病理诊断提供了一种快速便捷的方法,有利于将我们的研究与当前肺癌诊断框架联系起来。
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引用次数: 3
MAIA (Medical Artificial Intelligence Assistant) as interface for a new cancer healthcare integrative platform. MAIA (Medical Artificial Intelligence Assistant,医疗人工智能助手)作为癌症医疗一体化新平台的接口。
Pub Date : 2019-10-07 DOI: 10.1200/jgo.2019.5.suppl.25
L. Pino, Eduardo Large, J. Mejía, I. Triana
25 Background: Cancer healthcare systems are an example of inequity and waste in low and middle income countries. Access to high quality cancer pathways focused in early diagnosis, molecular biology, proper staging and evidence based treatments are scarce and the patient`s care experience is dramatic and difficult in a majority of cases. There are no integrative healthcare models based on new technologies that improve outcomes and make more comfortable and expeditious all the patient and physician´s journey in cancer. Methods: Our team developed and trained a talkbot called MAIA (Medical Artificial Intelligence Assistant) using an algorithmic translation of medical language focused in the state or art for non small cell lung cancer. Our clinical team developed decision trees in diagnosis, staging, medical and surgical treatment and molecular biology that were incorporated in a virtual platform and then integrated onto a narrow artificial intelligence bot brain using neural networks with the proposal of generate clinical support to the physician and create a standard text using the verbal information captured in the oncological consultation and integrated images (reports) through a image edition software and then create a unique medical record without using computers by the physician. MAIA also can create medical treatment choices in first line of treatment and create alerts and alarms through an own app (MAIA Hip). Results: Our proof of concept was released in video at this link https://drive.google.com/file/d/12YtiOkhfEmIsL2bFp9T3QyfHHWxBvvKU/view?ts=5ceec096 Due to our decision trees size we can´t upload them, but are available for presentation. Conclusions: A talkbot trained as a narrow artificial intelligence interface for an integrative cancer healthcare platform (HIP) is possible through the clinical and engineer integration of languages using a neural network method and other software tools. MAIA is for now a patient and physician experience improvement, but the real impact will be in the data standarization and acquisition for advanced analytics. The final scope of MAIA HIP will be a blockchain for cancer in low and middle income countries.
25背景:癌症卫生保健系统是低收入和中等收入国家不公平和浪费的一个例子。获得以早期诊断、分子生物学、适当分期和循证治疗为重点的高质量癌症途径是稀缺的,在大多数情况下,患者的护理经历是戏剧性的和困难的。目前还没有一种基于新技术的综合医疗模式,可以改善治疗效果,使患者和医生在癌症治疗过程中更舒适、更快捷。方法:我们的团队开发并训练了一个名为MAIA(医疗人工智能助手)的聊天机器人,使用一种算法翻译医学语言,专注于非小细胞肺癌的最新进展。我们的临床团队在诊断、分期、将医疗和外科治疗以及分子生物学整合到虚拟平台中,然后使用神经网络集成到狭窄的人工智能机器人大脑中,并建议为医生提供临床支持,并使用肿瘤咨询中捕获的口头信息创建标准文本,并通过图像编辑软件集成图像(报告),然后由医生创建独特的医疗记录,而无需使用计算机。MAIA还可以在一线治疗中创建医疗选择,并通过自己的应用程序(MAIA Hip)创建警报和警报。结果:我们的概念证明以视频形式发布在此链接https://drive.google.com/file/d/12YtiOkhfEmIsL2bFp9T3QyfHHWxBvvKU/view?ts=5ceec096由于我们的决策树的大小,我们无法上传它们,但可以用于演示。结论:通过使用神经网络方法和其他软件工具,通过临床和工程语言的集成,可以将聊天机器人训练成一个用于综合癌症医疗平台(HIP)的狭窄人工智能接口。目前,MAIA改善了患者和医生的体验,但真正的影响将是数据标准化和高级分析的获取。MAIA HIP的最终范围将是低收入和中等收入国家的癌症基金。
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引用次数: 3
期刊
Journal of global oncology
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