Andrew Carson, Michael Wang, Bryan Leatham, Kristin Fathe, Eun-Hae Cho, Tae-Rim Lee, Junnam Lee, J. Ahn, Dasom Kim, Byung In Lee
{"title":"Abstract PO1-07-10: Blood Based Early Cancer Detection Assay","authors":"Andrew Carson, Michael Wang, Bryan Leatham, Kristin Fathe, Eun-Hae Cho, Tae-Rim Lee, Junnam Lee, J. Ahn, Dasom Kim, Byung In Lee","doi":"10.1158/1538-7445.sabcs23-po1-07-10","DOIUrl":null,"url":null,"abstract":"\n Background: Breast cancer screening programs utilizing mammography have been shown to be highly effective in identifying breast cancer in women over the age of 40. High breast density is an independent risk factor for breast cancer and makes mammograms more difficult to interpret, decreasing their sensitivity. In the spring of 2023, the FDA, who certifies all mammography facilities under the Mammography Quality Standards Act, updated its regulations to require that breast density status be reported to all individuals receiving a mammogram. The new guidelines now require individuals with dense breast tissue be notified of this status. The guidelines also recommend these women discuss additional screening options with their healthcare providers1. These additional screening options may include breast tomosynthesis, breast MRI, breast ultrasound, and/or molecular breast imaging. Many of these options require additional exposure to radiation, are expensive, and are not equitably available across the country. In addition, they all require a follow-up appointment. Compliance can be challenging given the top barriers to mammography cited include the need for transportation, child-care, and the ability to take time off from work2. Genece Health is developing a simpler and less expensive screening solution that identifies the presence of early to late-stage breast cancer using cfDNA from a single blood draw. The Genece Health assay utilizes an algorithm that leverages Artificial Intelligence and Machine Learning to analyze fragment size and end motif patterns in cfDNA as well as regional mutational density to detect presence of ctDNA originating from breast cancer. This algorithm provides highly sensitive and specific results in a preliminary data set. Methods: The preliminary data set, presented herein, is a cohort of over 50 retrospective breast cancer plasma samples and over 100 presumed normal samples. The breast cancer samples were collected at all stages of progression, from stage 0, or ductal carcinoma in situ (DCIS), through stage IV. The majority ( >50%) were from stage I breast cancer. 400 µL of double spun plasma, collected in Streck BCT devices, was processed to purify and isolate cfDNA. cfDNA was used to create WGS libraries that were sequenced on a NovaSeq 6000. Sequence data were analyzed using a bioinformatics pipeline that yields an ensemble probability that correlates to the presence or absence of ctDNA from breast cancer. Results: The Genece Health assay and algorithm performed with a specificity greater than 85%. With this specificity, the assay had a sensitivity greater than 85% in samples from stages II to IV and a slightly lower sensitivity in stage 0 and I samples. Follow-up analyses were conducted to stratify performance based on breast cancer type (e.g. invasive ductal carcinoma vs invasive lobular carcinoma) and HR, PR, and HER2 status (e.g. HER2-negatives vs HER2-positives). Conclusions: The presented preliminary data indicate that the Genece Health technology can be leveraged as a complement to mammography in indications, such as dense breast tissue, where there is an unmet need for an easy and cost-effective way to monitor for breast cancer. The ability to have a blood-based test to complement mammography could reduce the access barriers most cited by females in the United States. Follow-up studies with greater numbers of samples and additional training and optimizations of the algorithm will yield performance improvements that allow the assay to detect all types and stages of breast cancer. References: 1. FDA News Release 09 March 2023. FDA Updates Mammography Regulations to Require Reporting of Breast Density Information and Enhance Facility Oversight. 2. Henderson LM et al. The Role of Social Determinants of Health in Self-Reported Access to Health Care Among Women Undergoing Screening Mammography. J Womens Health. 2020 Nov;29(11):1437-1446.\n Citation Format: Andrew Carson, Michael Wang, Bryan Leatham, Kristin Fathe, Eun-Hae Cho, Tae-Rim Lee, Junnam Lee, Jin Mo Ahn, Dasom Kim, Byung In Lee. Blood Based Early Cancer Detection Assay [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-10.","PeriodicalId":12,"journal":{"name":"ACS Chemical Health & Safety","volume":"12 3","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Chemical Health & Safety","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/1538-7445.sabcs23-po1-07-10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Breast cancer screening programs utilizing mammography have been shown to be highly effective in identifying breast cancer in women over the age of 40. High breast density is an independent risk factor for breast cancer and makes mammograms more difficult to interpret, decreasing their sensitivity. In the spring of 2023, the FDA, who certifies all mammography facilities under the Mammography Quality Standards Act, updated its regulations to require that breast density status be reported to all individuals receiving a mammogram. The new guidelines now require individuals with dense breast tissue be notified of this status. The guidelines also recommend these women discuss additional screening options with their healthcare providers1. These additional screening options may include breast tomosynthesis, breast MRI, breast ultrasound, and/or molecular breast imaging. Many of these options require additional exposure to radiation, are expensive, and are not equitably available across the country. In addition, they all require a follow-up appointment. Compliance can be challenging given the top barriers to mammography cited include the need for transportation, child-care, and the ability to take time off from work2. Genece Health is developing a simpler and less expensive screening solution that identifies the presence of early to late-stage breast cancer using cfDNA from a single blood draw. The Genece Health assay utilizes an algorithm that leverages Artificial Intelligence and Machine Learning to analyze fragment size and end motif patterns in cfDNA as well as regional mutational density to detect presence of ctDNA originating from breast cancer. This algorithm provides highly sensitive and specific results in a preliminary data set. Methods: The preliminary data set, presented herein, is a cohort of over 50 retrospective breast cancer plasma samples and over 100 presumed normal samples. The breast cancer samples were collected at all stages of progression, from stage 0, or ductal carcinoma in situ (DCIS), through stage IV. The majority ( >50%) were from stage I breast cancer. 400 µL of double spun plasma, collected in Streck BCT devices, was processed to purify and isolate cfDNA. cfDNA was used to create WGS libraries that were sequenced on a NovaSeq 6000. Sequence data were analyzed using a bioinformatics pipeline that yields an ensemble probability that correlates to the presence or absence of ctDNA from breast cancer. Results: The Genece Health assay and algorithm performed with a specificity greater than 85%. With this specificity, the assay had a sensitivity greater than 85% in samples from stages II to IV and a slightly lower sensitivity in stage 0 and I samples. Follow-up analyses were conducted to stratify performance based on breast cancer type (e.g. invasive ductal carcinoma vs invasive lobular carcinoma) and HR, PR, and HER2 status (e.g. HER2-negatives vs HER2-positives). Conclusions: The presented preliminary data indicate that the Genece Health technology can be leveraged as a complement to mammography in indications, such as dense breast tissue, where there is an unmet need for an easy and cost-effective way to monitor for breast cancer. The ability to have a blood-based test to complement mammography could reduce the access barriers most cited by females in the United States. Follow-up studies with greater numbers of samples and additional training and optimizations of the algorithm will yield performance improvements that allow the assay to detect all types and stages of breast cancer. References: 1. FDA News Release 09 March 2023. FDA Updates Mammography Regulations to Require Reporting of Breast Density Information and Enhance Facility Oversight. 2. Henderson LM et al. The Role of Social Determinants of Health in Self-Reported Access to Health Care Among Women Undergoing Screening Mammography. J Womens Health. 2020 Nov;29(11):1437-1446.
Citation Format: Andrew Carson, Michael Wang, Bryan Leatham, Kristin Fathe, Eun-Hae Cho, Tae-Rim Lee, Junnam Lee, Jin Mo Ahn, Dasom Kim, Byung In Lee. Blood Based Early Cancer Detection Assay [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-10.
背景:利用乳房 X 射线照相术进行的乳腺癌筛查计划已被证明能非常有效地发现 40 岁以上妇女的乳腺癌。高乳腺密度是乳腺癌的一个独立风险因素,它使乳房 X 光检查更难以解读,从而降低了检查的灵敏度。2023 年春,根据《乳房 X 射线照相质量标准法案》对所有乳房 X 射线照相设施进行认证的美国食品及药物管理局更新了其规定,要求所有接受乳房 X 射线照相检查的人都必须报告乳房密度状况。新指南现在要求向乳腺组织致密的人告知这一状态。指南还建议这些妇女与其医疗保健提供者讨论其他筛查方案1。这些额外的筛查方案可能包括乳腺断层扫描、乳腺核磁共振成像、乳腺超声和/或分子乳腺成像。其中许多方法都需要额外暴露于辐射中,价格昂贵,而且无法在全国范围内公平提供。此外,它们都需要预约复诊。鉴于乳房 X 射线照相术的最大障碍包括交通需求、儿童保育以及能否请假2 ,因此遵守规定可能具有挑战性。Genece Health 正在开发一种更简单、成本更低的筛查解决方案,利用一次抽血中的 cfDNA 来确定是否存在早期至晚期乳腺癌。Genece Health 检测利用人工智能和机器学习算法来分析 cfDNA 中的片段大小和末端主题模式以及区域突变密度,以检测是否存在源自乳腺癌的 ctDNA。该算法可在初步数据集中提供高灵敏度和特异性的结果。方法:本文介绍的初步数据集是由 50 多份回顾性乳腺癌血浆样本和 100 多份假定正常样本组成的队列。乳腺癌样本收集于乳腺癌进展的各个阶段,从 0 期或导管原位癌(DCIS)到 IV 期。大部分样本(>50%)来自 I 期乳腺癌。在 Streck BCT 设备中收集的 400 µL 双旋血浆经过处理后纯化并分离出 cfDNA。cfDNA 用于创建 WGS 文库,并在 NovaSeq 6000 上进行测序。使用生物信息学管道分析序列数据,得出与乳腺癌中是否存在ctDNA相关的集合概率。结果Genece Health 检测方法和算法的特异性超过 85%。在这种特异性下,该检测方法对 II 期至 IV 期样本的灵敏度超过 85%,而对 0 期和 I 期样本的灵敏度略低。后续分析根据乳腺癌类型(如浸润性导管癌与浸润性小叶癌)、HR、PR 和 HER2 状态(如 HER2 阴性与 HER2 阳性)对检测结果进行了分层。结论所提供的初步数据表明,Genece Health 技术可作为乳腺 X 线照相术的补充,用于致密乳腺组织等适应症,因为这些适应症对简便、经济的乳腺癌监测方法的需求尚未得到满足。通过血液检测来补充乳腺 X 射线照相术的不足,可以减少美国女性最常提到的获取乳腺 X 射线照相术的障碍。使用更多样本进行后续研究,并对算法进行更多的培训和优化,将能提高性能,使该检测方法能检测出所有类型和阶段的乳腺癌。参考文献1.FDA 新闻稿 09 March 2023.FDA 更新乳腺 X 射线照相法规,要求报告乳腺密度信息并加强设施监督。2.Henderson LM et al. The Role of Social Determinants of Health in Self-Reported Access to Health Care Among Women Undergoing Screening Mammography. J Womens Health.J Womens Health.2020 Nov;29(11):1437-1446.引用格式:Andrew Carson, Michael Wang, Bryan Leatham, Kristin Fathe, Eun-Hae Cho, Tae-Rim Lee, Junnam Lee, Jin Mo Ahn, Dasom Kim, Byung In Lee.基于血液的早期癌症检测方法[摘要]。In:2023 年圣安东尼奥乳腺癌研讨会论文集;2023 年 12 月 5-9 日;德克萨斯州圣安东尼奥。费城(宾夕法尼亚州):AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-10.
期刊介绍:
The Journal of Chemical Health and Safety focuses on news, information, and ideas relating to issues and advances in chemical health and safety. The Journal of Chemical Health and Safety covers up-to-the minute, in-depth views of safety issues ranging from OSHA and EPA regulations to the safe handling of hazardous waste, from the latest innovations in effective chemical hygiene practices to the courts'' most recent rulings on safety-related lawsuits. The Journal of Chemical Health and Safety presents real-world information that health, safety and environmental professionals and others responsible for the safety of their workplaces can put to use right away, identifying potential and developing safety concerns before they do real harm.