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: 7983917
• 负责人: Christopher Benz
• 金额: $ 15.75万
• 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/7983917
• 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）是第一个在临床上被验证为癌症治疗反应预测因子的生物标志物，并且仍然是少数几个具有足够医学证据证明其在临床决策中常规使用的肿瘤生物标志物之一。虽然低或缺乏肿瘤ER表达（ER-）准确地预测缺乏对内分泌治疗的反应性，但ER（ER+）的肿瘤过表达是反应的不良预测因子，准确性平均仅为50%。因此，提高目前仅测量肿瘤ER含量的ER测定的预测准确性是癌症研究中最重要的未解决的问题之一。由于已知任何给定蛋白质上的翻译后修饰（PTM）的星座是决定构象、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者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的多反应监测（MRM），包括Ser/Thr/Tyr磷酸化，赖氨酸修饰（乙酰化/甲基化/泛素化）和Cys氧化跨内源性表达的ER蛋白的六个结构域。基于解码ER PTM对于改善ER生物标志物特异性和ER+乳腺癌的临床亚型至关重要的前提，提出了两个研究目的。目标1研究将充分优化MRM/MS程序，以定量在一组ER+人乳腺癌细胞系中ER PTM的配体依赖性（雌激素）和配体非依赖性（生长因子，氧化应激）诱导，这些细胞系是根据其抗雌激素敏感性范围选择的。特别强调的是ER铰链和DNA结合域，其中特定的PTM模式是已知的改变ER功能和确定抗雌激素敏感性。还将通过引入突变的ER PTM构建体并评估其对内源性ER依赖性基因表达的细胞内影响来评估新型ER PTM的功能影响。在其他目标中，目标1的努力将产生预测细胞系抗雌激素抗性的候选PTM谱，用于在目标2肿瘤样品中进一步评价。目标2研究将采用目标1的完全优化的MRM/MS方案，使用两个不同的临床注释的ER+原发性乳腺癌队列评价肿瘤ER PTM的患病率和谱。可用于MRM/MS分析的两个肿瘤组群有能力：i）验证我们的Aim 1衍生的与细胞系他莫昔芬反应性相关的ER PTM谱，和ii）独立地衍生和验证与对佐剂他莫昔芬的临床抗性和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。在完成这些研究目标后，定量MRM/MS测定将确定所有乳腺癌PTM的谱和患病率，并将确定和验证与更具侵袭性和抗雌激素耐药乳腺癌相关的PTM模式。 公共卫生相关性：雌激素受体蛋白代表了常规临床使用中最重要的肿瘤生物标志物之一，并用于鉴定过表达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无反应，但ER+肿瘤总是有反应的推论是不正确的。使用我们开创的灵敏和复杂的基于质谱的方法，我们将测试以下假设，即解码已知或怀疑发生在各种ER氨基酸上的化学修饰（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ER+乳腺癌与内分泌抵抗相关的机制提供新的见解。