Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing

使用多区域测序对基底样乳腺癌进行预后分析和进展建模

• 批准号: 10586445
• 负责人: Steve Goodison
• 金额: $ 66.81万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-09 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586445
• 关键词: Address; American Society of Clinical Oncology; Area; Automobile Driving; Bioinformatics; Biological Process; Cancer Patient; Cancer Prognosis; Cause of Death; Classification; Clinic; Clinical; Clinical Management; Clinical Research; Complex; Computational Technique; Computing Methodologies; DNA Sequence Alteration; DNA sequencing; Data; Data Set; Derivation procedure; Development; Disease; Disease-Free Survival; ERBB2 gene; Estrogen Receptors; Evaluation; Event; Evolution; Experimental Designs; Future; Genes; Genetic; Genetic Determinism; Genomic Instability; Guidelines; Institution; Interdisciplinary Study; Learning; Life; Machine Learning; Malignant - descriptor; Malignant Neoplasms; Mammary Neoplasms; Methods; Modeling; Molecular; Molecular Profiling; Multiomic Data; Neoplasm Metastasis; Outcome; Pathology; Pathway interactions; Patients; Pattern; Prevalence; Primary Neoplasm; Process; Progesterone Receptors; Recurrence; Resolution; Role; Sampling; Series; Specimen; Structure; System; Technology; Therapeutic; Tissue Banks; Treatment Protocols; Tumor Biology; Tumor Tissue; Visualization; Woman; Work; anticancer research; chemotherapy; genetic association; high risk; indexing; insight; malignant breast neoplasm; molecular subtypes; multidisciplinary; next generation sequencing; novel; prognostic; prognostic assays; prognostic model; prognostication; prospective; targeted treatment; theories; therapeutic target; tissue mapping; transcriptome sequencing; tumor; tumor progression; tumorigenesis

Project Summary/Abstract Breast cancer is the most common cancer in women worldwide, and the fifth most common cause of death from cancer overall. As with many other cancers, breast cancer presents in a variety of forms and can be broadly divided into four molecular subtypes, including luminal A, luminal B, HER2+ and basal. Among them, basal cancer represents ~20% of primary breast tumors and is one of the most aggressive and deadly subtypes. While significant efforts have been made, the biological process of how basal cancer progresses to a malignant, life-threatening disease is not well understood, and the prognostication and treatment of basal cancer remain major challenges. Specifically, there are currently no prognostic tests available that can assist clinical management, and nearly all basal cancer patients are classified as having a high risk of recurrence. Moreover, as the majority of basal tumors lack expression of estrogen receptor (ER), progesterone receptor (PR) and HER2, there are presently no effective targeted treatment regimens available, and harsh, indiscriminate chemotherapy is the only treatment option. Consequently, a significant number of basal cancer patients are under- or over-treated. Built logically on our previous work, we propose a large-scale interdisciplinary research plan, in which we will use multi-region sequencing and advanced computational techniques to address some pressing issues and the aforementioned unmet clinical needs of basal breast cancer. Specifically, we will perform molecular profiling of 300 primary basal tumors and 50 matched metastatic tumors that we have identified from Mayo Clinic tissue banks. By using the obtained multi-region sequencing tumor tissue data, we will derive a prognostic evaluation system for basal cancer through multiple instance learning, and construct and validate a high-resolution progression model of basal cancer. We will also perform a large-scale analysis on a range of molecular data to systematically search for genetic determinants of basal cancer progression at both gene and pathway levels, which will provide a wealth of insights into molecular mechanisms of tumorigenesis and enable us to identify potential therapeutic targets for basal cancer. If successfully implemented, this work will significantly advance the basal cancer research, and pave the way for applying similar strategies to study other deadly cancers.

项目总结/文摘