Caris Life Sciences and ECOG-ACRIN Partner to Enhance Breast Cancer Risk Stratification
核心洞察
Caris Life Sciences (搜索) and ECOG-ACRIN (搜索) are collaborating to analyze data from the TAILORx breast cancer (搜索) trial, aiming to improve risk stratification and recurrence prediction.
The project will utilize Caris's AI and machine learning algorithms with genomic, transcriptomic, and proteomic profiling on tumor tissues from nearly 10,000 patients.
The collaboration seeks to address racial disparities in breast cancer (搜索) mortality and identify more effective treatment options for women with early-stage disease.
Caris Life Sciences (搜索) and the ECOG-ACRIN (搜索) Cancer Research Group have announced a multi-year research collaboration to further investigate early-stage breast cancer (搜索). The partnership will leverage data and samples from the landmark TAILORx (Trial Assigning Individualized Options for Treatment) breast cancer clinical trial to improve risk stratification, predict recurrence, and understand drivers of racial disparities in outcomes.
The collaboration will pair Caris's advanced genomic, transcriptomic, and proteomic profiling capabilities with ECOG-ACRIN (搜索)'s research expertise. The initial project will involve comprehensive molecular characterization, including whole exome and transcriptome sequencing, on tumor tissue samples from nearly 10,000 patients with early-stage breast cancer (搜索) who participated in the TAILORx trial. These patients have been followed for at least 11 years, with plans for continued follow-up to 20 years.
Addressing Unmet Needs in Early-Stage Breast Cancer
Breast cancer (搜索) remains the most common cancer among women in the United States, with approximately 310,720 new cases diagnosed annually, and about 60% are early stage. While overall breast cancer mortality has declined by 42% over the past 30 years due to increased screening and improved treatments, a mortality gap persists between minority and white patients. Analysis published in JAMA Surgery showed that racial and ethnic differences in locoregional breast cancer recurrence patterns are prevalent even in a clinical trial population with similar access to care.
"I’m excited to build on the trial’s initial findings which prevented millions of women with early breast cancer (搜索) from having to endure toxic treatments, to continue discerning valuable insights related to long term recurrence risk and to identify even more women who may benefit from more efficient treatment options," said George W. Sledge, Jr., MD, EVP and Chief Medical Officer of Caris.
Leveraging AI and Machine Learning
Caris will apply its advanced artificial intelligence (AI) and machine learning algorithms to the molecular data generated from the TAILORx samples. The goal is to identify superior biomarkers for risk stratification, predict recurrence more accurately, and gain a better understanding of the factors contributing to racial disparities in breast cancer (搜索) outcomes. Data from the project will be made publicly available in an appropriate NCI database after a designated period following completion of the research.
ECOG-ACRIN Joins Caris Precision Oncology Alliance
In addition to the research collaboration, ECOG-ACRIN (搜索) has joined the Caris Precision Oncology Alliance™ (POA), a global network of leading cancer centers and research consortia. The POA aims to advance precision oncology and biomarker-driven research by establishing and optimizing standards of care for molecular testing and improving clinical outcomes for cancer patients.
"Our shared vision of improving the outcomes of all patients with cancer will nurture this collaborative effort with the ECOG-ACRIN (搜索) researchers. We aim to achieve common goals in advancing precision medicine and biomarker research in cancer, and to increase treatment options for cancer patients," said Sledge.