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A prognostic mRNA immune signature for resected stage II-III melanoma

切除的 II-III 期黑色素瘤的预后 mRNA 免疫特征

基本信息

批准号：
10609514
负责人：
Yvonne Margaret Saenger
金额：
$ 33.28万
依托单位：
ALBERT EINSTEIN COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-06-13 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10609514
关键词：
Adjuvant Adjuvant Study Adjuvant Therapy Algorithmic Analysis Binding Biological Assay Biological Markers Biopsy Biotechnology British Columbia CD8B1 gene CLIA certified Cd68 Cessation of life Clinical Clinical Trials Collaborations Comprehensive Cancer Center Data Data Set Diagnosis Eastern Cooperative Oncology Group Ensure Environment Excision Exposure to Face Formalin Future Genes Goals Herbert Irving Comprehensive Cancer Center Immune Immune checkpoint inhibitor Immunofluorescence Immunologic Immunologic Markers Immunology procedure Immunotherapy Impairment Infiltration Interferons Interobserver Variability Investments Laboratories Manuals Messenger RNA Methodology Methods Migration Assay Morphology New York Operative Surgical Procedures Outcome Paraffin Embedding Pathologic Patient Selection Patients Phase Pilot Projects Placebos Polymerase Chain Reaction Population Procedures Process Prognosis Prognostic Marker Program Evaluation Publishing RNA Randomized Recurrence Recurrent tumor Regulator Genes Reporter Reproducibility Research Resected Retrospective Studies Risk Risk Assessment Roswell Park Cancer Institute Sampling Specificity Specimen Staging System Technology Testing Time Tissue Embedding Tissues Training Tumor-Infiltrating Lymphocytes Universities Validation autoimmune toxicity biomarker development biomarker signature clinical application clinical diagnostics clinical practice clinical prognostic cohort density experimental study follow-up genetic signature health care settings high risk immune activation immunotherapy clinical trials improved indexing instrumentation melanoma mortality nano-string patient biomarkers patient population patient stratification predicting response prevent prognostic prognostic value prospective relapse prevention sample fixation tool transcriptome sequencing trial design tumor tumor-immune system interactions

项目摘要

We propose to develop a prognostic mRNA immune signature for resected stage II-III melanoma, in order to stratify these patients, who have a recurrence risk of ~50%. There is an urgent need to define accurate prognostic markers for stage II-III melanoma patients because adjuvant immunotherapy to prevent recurrence is both toxic and expensive. Unfortunately, conventional staging does not allow for accurate assessment of risk and many “low risk” patients in fact progress. Further, while the immune tumor micro- environment is a key determinant of outcomes, standard pathologic assessment of tumor infiltrating lymphocytes (TILs) is subjective and not applicable to general clinical practice. In order to better stratify patients for adjuvant immunotherapy, we seek to validate a previously defined 53-gene signature. This signature employs NanoString, a probe based technology well suited to the analysis of the partially degraded RNA typically recovered from clinical grade FFPE tissue sections. We initially defined this signature in a training set and then validated these findings in an independent test set [Sivendran, et al. (2014) J. Invest. Dermatol. 134:2202-11]. As both training and test sets populations are retrospective, the next step to develop a clinically applicable assay is to test the signature on prospectively gathered samples. Given the fact that melanomas can recur years after resection in these early stage patients, prospective validation would be lengthy, and thus we opted to use the prospective retrospective analysis [PRA] approach whereby samples are collected and annotated prospectively but analyzed retrospectively. For this purpose we use samples from the Eastern Cooperative Group (ECOG) E1697 study of adjuvant interferon randomized vs placebo in stage II-III resected melanoma. Patients in this study have been maintained on study follow-up since they were randomized between 1998 and 2010. This project is collaboration between the Herbert Irving Comprehensive Cancer Center (HICCC) at Columbia University, the Roswell Park Comprehensive Cancer Center (RPCCC), the University of British Columbia and Omniseq, a commercial biotech spin-off that is majority owned by RPCCC. In Aim 1 (UH2 phase), we perform the analytical validation of the assay including validation of gene reference controls, RNA extraction quality, and reporter binding density. The milestone for moving to the UH3 phase (Aim 2) will be submission to the NYS Clinical Laboratory Evaluation Program. In the UH3 clinical validation phase, we first evaluate two additional retrospective sample populations (from HICCC and RPCCC). As part of this study we will also correlate the 53-gene signature with state of the art immune indices including quantitative multiplex immunofluorescence (qmIF) to assess CD8 to CD68 ratio, a metric recently defined (by our group) to correlate with survival. We then perform the definitive PRA analysis using the E1697 samples.

我们建议为切除的II-III期黑色素瘤开发一种预后mRNA免疫标记，对这些复发风险约为50%的患者进行分层。迫切需要准确界定 II-III期黑色素瘤患者的预后标志物，因为辅助免疫治疗可以预防复发是有害的，而且代价高昂。不幸的是，传统的分期不允许准确的风险评估和许多“低风险”患者实际上进展。此外，虽然免疫肿瘤微- 环境是结果的关键决定因素，肿瘤浸润的标准病理评估淋巴细胞（TIL）的检测是主观的，不适用于一般临床实践。为了更好地分层对于辅助免疫治疗的患者，我们试图验证先前定义的53个基因签名。这签名采用NanoString，这是一种基于探针的技术，非常适合于分析部分降解的RNA通常从临床级FFPE组织切片中回收。我们最初定义了签名，然后在独立的测试集中验证这些发现[Sivendran，et al. （2014）J. Invest. Dermatol. 134：2202-11]。由于训练集和测试集都是回顾性的，开发临床适用测定法的下一步是测试前瞻性收集的特征样品考虑到这些早期患者的黑色素瘤可能在切除后数年复发，前瞻性验证将是漫长的，因此我们选择使用前瞻性回顾性分析 [PRA]收集样本并进行前瞻性注释但进行分析的方法回顾性为此目的，我们使用来自东部协作组（ECOG）E1697的样品。 II-III期切除黑色素瘤中辅助干扰素随机化与安慰剂对比研究例患者自1998年至2010年随机化以来，研究一直保持研究随访。该项目是赫伯特欧文综合癌症中心（CDC）与哥伦比亚大学、罗斯韦尔公园综合癌症中心（RPCCC）、英国大学哥伦比亚和Omniseq，这是一家商业生物技术分拆公司，由RPCCC拥有多数股权。在目标1（UH 2 阶段），我们进行了试验的分析验证，包括基因参考对照的验证， RNA提取质量和报告分子结合密度。迈向UH 3阶段的里程碑（目标2）将提交给纽约州临床实验室评价项目。在UH 3临床确认中在第一阶段，我们首先评估了两个额外的回顾性样本人群（来自RPCCC和RPCCC）。作为在这项研究的一部分，我们还将53个基因的签名与最先进的免疫指标相关联包括定量多重免疫荧光（qmIF），以评估CD 8与CD 68的比率，最近被我们的小组定义为与生存相关。然后，我们进行确定性PRA分析，使用E1697样本。