Mass spectrometry to decode PTM patterns and enhance the Biomarker utility of ER

质谱法解码 PTM 模式并增强 ER 的生物标志物效用

• 批准号: 8134941
• 负责人: Christopher Benz
• 金额: $ 34.37万
• 依托单位: BUCK INSTITUTE FOR RESEARCH ON AGING
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-08-23 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8134941
• 关键词: Acer; Acetylation; Adjuvant; Amino Acids; Aromatase Inhibitors; Biological Assay; Biological Markers; Breast Cancer Cell; Cancer cell line; Cell Line; Chemicals; Clinical; Code; DNA Binding Domain; Endocrine; Estrogen Antagonists; Estrogen Receptor Modulators; Estrogen Receptors; Estrogens; Evaluation; Funding; Gene Expression; Growth Factor; Human; Individual; Ligand Binding Domain; Ligands; Link; Malignant Neoplasms; Mammary Neoplasms; Mass Spectrum Analysis; Measures; Medical; Methylation; Modification; Molecular; Molecular Conformation; Molecular Profiling; Monitor; Mutate; Outcome; Oxidants; Oxidative Stress; Oxidative Stress Induction; Pattern; Phenotype; Phosphorylation; Phosphorylation Site; Post-Translational Protein Processing; Predictive Value; Prevalence; Procedures; Protein Isoforms; Proteins; Protocols documentation; Relapse; Research Personnel; Resistance; Sampling; Signal Transduction; Specificity; Structure; Tamoxifen; Testing; Ubiquitination; Wit; analytical tool; anticancer research; base; cancer therapy; clinical decision-making; clinically relevant; cohort; design; estrophilin; hormone therapy; human ESR1 protein; improved; insight; interest; malignant breast neoplasm; multiple reaction monitoring; novel; overexpression; oxidation; prevent; prognostic; public health relevance; response; tandem mass spectrometry; tool; tumor

DESCRIPTION (provided by applicant): Estrogen receptor (ER, alpha isoform) was the first biomarker to be clinically validated as a predictor of cancer therapy response, and still stands as one of the few tumor biomarkers with sufficient medical evidence to justify its routine use in clinical decision making. While low or absent tumor ER expression (ER-) accurately predicts lack of responsiveness to endocrine therapy, tumor overexpression of ER (ER+) is a poor predictor of response with an accuracy averaging only 50%. Hence, improving the predictive accuracy of current ER assays that measure only tumor ER content is one of the most important unresolved issues in cancer research. Since the constellation of posttranslational modifications (PTMs) on any given protein is known to be a molecular code dictating conformation, localization, and intracellular function, we assembled an interdisciplinary team of translational investigators and protein chemists who developed mass spectrometry (MS) approaches, employing multiple reaction monitoring (MRM) capable of detecting and quantitating diverse PTMs, including Ser/Thr/Tyr phosphorylations, Lys modifications (acetylation/methylation/ubiquitination), and Cys oxidation across the six domains of endogenously expressed ER protein. Two study aims are proposed based on the premise that decoding ER PTMs is essential for improving ER biomarker specificity and the clinical subtyping of ER+ breast cancers. Aim 1 studies will fully optimize MRM/MS procedures to quantitate ligand-dependent (estrogen) and ligand-independent (growth factor, oxidative stress) induction of ER PTMs across a panel of ER+ human breast cancer cell lines selected for their range of antiestrogen sensitivities. Special emphasis will be given to the ER hinge and DNA-binding domains where specific PTM patterns are known to alter ER functionality and determine antiestrogen sensitivity. The functional impact of novel ER PTMs will also be assessed by introducing mutated ER PTM constructs and evaluating their intracellular impact on endogenous ER dependent gene expression. Among other objectives, Aim 1 efforts will generate a candidate PTM profile predictive of cell line antiestrogen resistance for further evaluation in Aim 2 tumor samples. Aim 2 studies will employ fully optimized MRM/MS protocols from Aim 1 to evaluate the prevalence and spectrum of tumor ER PTMs using two different clinically annotated cohorts of ER+ primary breast cancers. The two tumor cohorts available for MRM/MS analysis are powered to: i) validate our Aim 1 derived ER PTM profile associating with cell line tamoxifen responsiveness, and ii) independently derive and validate a tumor ER PTM profile associating with clinical resistance to adjuvant tamoxifen and other aggressive tumor features linked to early clinical relapse. On completion of these study aims, quantitative MRM/MS assays will have defined the spectrum and prevalence of all breast cancer PTMs, and a PTM pattern associated with more aggressive and antiestrogen resistant breast cancers will have been identified and validated. PUBLIC HEALTH RELEVANCE: The estrogen receptor protein represents one of the most important tumor biomarkers in routine clinical use, and is employed to identify breast cancers that overexpress ER (designated ER+), signifying that they MAY respond favorably to endocrine therapy with tamoxifen or aromatase inhibitors. Although low ER expressing tumors (ER-) are almost invariably unresponsive to such therapies, the corollary that ER+ tumors will always respond is not true. Using a sensitive and sophisticated mass spectrometry-based approach that we have pioneered, we will test the hypothesis that decoding the chemical modifications known or suspected to occur on various ER amino acids (known as post-translational modifications or PTMs) will enable more accurate prediction of ER+ breast tumors responsive to endocrine therapy, and provide new insight into ER+ breast cancer mechanisms associated with endocrine resistance.

描述（由申请人提供）：雌激素受体（ER，α亚型）是第一个经过临床验证的癌症治疗反应预测生物标志物，并且仍然是少数具有足够医学证据证明其在临床决策中常规使用合理的肿瘤生物标志物之一。虽然肿瘤 ER 表达 (ER-) 低或缺失可准确预测对内分泌治疗缺乏反应，但肿瘤 ER (ER+) 过度表达是反应的不良预测因子，平均准确度仅为 50%。因此，提高当前仅测量肿瘤 ER 含量的 ER 检测的预测准确性是癌症研究中尚未解决的最重要问题之一。由于已知任何给定蛋白质上的翻译后修饰 (PTM) 群都是决定构象、定位和细胞内功能的分子密码，因此我们组建了一个由翻译研究人员和蛋白质化学家组成的跨学科团队，他们开发了质谱 (MS) 方法，采用能够检测和定量不同 PTM（包括 Ser/Thr/Tyr）的多反应监测 (MRM) 内源表达 ER 蛋白的六个结构域的磷酸化、Lys 修饰（乙酰化/甲基化/泛素化）和 Cys 氧化。基于解码 ER PTM 对于提高 ER 生物标志物特异性和 ER+ 乳腺癌临床亚型至关重要的前提，提出了两个研究目标。目标 1 研究将全面优化 MRM/MS 程序，以定量根据抗雌激素敏感性范围选择的一组 ER+ 人乳腺癌细胞系中配体依赖性（雌激素）和配体非依赖性（生长因子、氧化应激）诱导 ER PTM。我们将特别强调 ER 铰链和 DNA 结合域，其中已知特定的 PTM 模式可以改变 ER 功能并确定抗雌激素敏感性。新型 ER PTM 的功能影响也将通过引入突变的 ER PTM 构建体并评估其对内源 ER 依赖性基因表达的细胞内影响来评估。除其他目标外，Aim 1 的工作将生成预测细胞系抗雌激素耐药性的候选 PTM 谱，以便在 Aim 2 肿瘤样本中进行进一步评估。目标 2 研究将采用目标 1 中完全优化的 MRM/MS 方案，使用两个不同临床注释的 ER+ 原发性乳腺癌队列来评估肿瘤 ER PTM 的患病率和谱。可用于 MRM/MS 分析的两个肿瘤队列能够：i) 验证我们的 Aim 1 衍生的 ER PTM 谱与细胞系他莫昔芬反应性的相关性，以及 ii) 独立导出并验证与辅助他莫昔芬的临床耐药性以及与早期临床复发相关的其他侵袭性肿瘤特征相关的肿瘤 ER PTM 谱。完成这些研究目标后，定量 MRM/MS 测定将定义所有乳腺癌 PTM 的谱系和患病率，并且将识别和验证与更具侵袭性和抗雌激素耐药性乳腺癌相关的 PTM 模式。 公共健康相关性：雌激素受体蛋白是常规临床使用中最重要的肿瘤生物标志物之一，用于识别过度表达 ER（称为 ER+）的乳腺癌，这表明它们可能对他莫昔芬或芳香酶抑制剂的内分泌治疗有良好的反应。尽管低 ER 表达肿瘤 (ER-) 几乎总是对此类疗法没有反应，但 ER+ 肿瘤总是有反应的推论并不正确。使用我们首创的灵敏且复杂的基于质谱的方法，我们将测试以下假设：解码已知或怀疑在各种 ER 氨基酸上发生的化学修饰（称为翻译后修饰或 PTM）将能够更准确地预测 ER+ 乳腺肿瘤对内分泌治疗的反应，并为与内分泌抵抗相关的 ER+ 乳腺癌机制提供新的见解。