Clinically relevant molecular subtypes in leiomyosarcoma

平滑肌肉瘤的临床相关分子亚型

基本信息

批准号：
8617808
负责人：
Jan Matt van de Rijn
金额：
$ 32.86万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-08-29 至 2016-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8617808
关键词：
Archives Behavior Chemotherapy-Oncologic Procedure Classification Clinical Comparative Genomic Analysis Development Diagnosis Diagnostic Disease Drug usage Event Formalin Freezing Funding Gastrointestinal Stromal Tumors Gene Expression Profile Gene Expression Profiling Genetic Genomics Goals Grant Individual Lead Malignant Neoplasms Messenger RNA Molecular Molecular Profiling Mutation Neoplasm Metastasis Nucleotides Oncogenic Outcome Paper Paraffin Embedding Pathway interactions Patients Peer Review Pharmaceutical Preparations Process Prognostic Marker Progress Reports Recording of previous events Sampling Series Staging Surgical Pathology System Systemic Therapy Techniques Tissue Sample Tissues Transcript Treatment Protocols Undifferentiated Variant Work base cancer therapy chemotherapy clinically relevant clinically significant deep sequencing effective therapy follow-up improved leiomyosarcoma malignant breast neoplasm molecular recognition new therapeutic target next generation sequencing novel novel diagnostics novel strategies prognostic public health relevance response sarcoma therapeutic target tool transcriptome sequencing tumor tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): The current treatment of leiomyosarcoma (LMS), the most common form of sarcoma, involves ineffective systemic therapy that is based on a trial and error approach and on the assumption that tumors called "LMS" form a homogenous group. Recent advances in other forms of cancer therapy have relied on recognizing targetable pathways that are active in subsets of cases and the use of drugs on those cases only. Currently, no such appreciation exists for LMS, and we propose that an effective treatment for LMS should be based on a rational, molecular sub-classification of these tumors. In a continuation of previous work, we will focus efforts our efforts on the study of the molecular subtypes in LMS that we recently discovered. In the first Aim we will establish molecular signatures for large numbers of LMS cases with detailed clinical follow-up from surgical pathology archives. To this end, we will use a novel technique (3SEQ) that we developed to allow gene expression profiling on mRNA isolated from formalin-fixed paraffin-embedded tissue (FFPET) through next generation sequencing. Using this approach, we will confirm and extend our initial molecular characterization of LMS subtypes. Furthermore we will determine the prognostic significance of the molecular subtypes, and identify subtype-specific oncogenic pathways. We aim at discovering predictors for the response to commonly used chemotherapeutic drugs, and will identify molecular prognosticators for the development of metastases. 3SEQ will also be used to analyze undifferentiated pleomorphic sarcoma (UPS, aka MFH) to determine to which extent the molecular subtypes now recognized in LMS can be identified in this tumor. In Aim 2 we will identify the genetic events that are unique to each subtype and that could represent potential therapeutic targets and additional diagnostic markers. To achieve this, we will perform paired-end whole transcriptome sequencing (RNA-Seq) on a representative set of LMS cases to identify the single nucleotide variants and fusion transcripts that are unique to each LMS subtype. These studies will lead to a better understanding of the molecular events that drive LMS oncogenesis, and will improve the ability of clinicians to better diagnose LMS. As an ultimate goal, this work will prognosticate LMS behavior in individual patients and could lead to a more rational choice of treatment options for this disease.

描述（由申请人提供）：最常见的肉瘤形式的平滑肌肉瘤（LMS）治疗涉及基于试验和错误方法的无效的全身治疗，并且假设称为“ LMS”的肿瘤形成了同质群体。其他形式的癌症疗法的最新进展依赖于识别在病例亚群中活跃的有针对性途径，并且仅在这些病例中使用药物。目前，对LMS尚无这种欣赏，我们建议对LMS进行有效的治疗方法基于这些肿瘤的合理分子亚分类。在以前的工作的延续中，我们将把精力集中在我们最近发现的LMS分子亚型的研究上。在第一个目标中，我们将为大量LMS病例建立分子特征，并具有手术病理档案的详细临床随访。为此，我们将使用一种新型技术（3SEQ），以通过下一代测序从福尔马林固定石蜡包含的组织（FFPET）中分离出的mRNA上进行基因表达分析。使用这种方法，我们将确认并扩展我们对LMS亚型的初始分子表征。此外，我们将确定分子亚型的预后意义，并确定亚型特异性致癌途径。我们旨在发现对常用化学治疗药物反应的预测因子，并将确定分子预后剂以开发转移。 3Seq还将用于分析未分化的多形性肉瘤（UPS，又名MFH），以确定在该肿瘤中可以鉴定出LMS中现在在LMS中识别的分子亚型的程度。在AIM 2中，我们将确定每个亚型独有的遗传事件，并可以代表潜在的治疗靶标和其他诊断标记。为了实现这一目标，我们将对代表性的LMS案例进行配对的整个转录组测序（RNA-Seq），以识别每个LMS亚型独特的单核苷酸变体和融合转录本。这些研究将使人们更好地了解驱动LMS肿瘤发生的分子事件，并提高临床医生更好地诊断LMS的能力。作为一个最终目标，这项工作将预测个别患者的LMS行为，并可能导致该疾病的治疗选择更合理。

项目成果

期刊论文数量（16）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Use of a KIT-specific monoclonal antibody to bypass imatinib resistance in gastrointestinal stromal tumors.

DOI：
10.4161/onci.24452
发表时间：
2013-06-01
期刊：
Oncoimmunology
影响因子：
7.2
作者：
Edris B;Willingham S;Weiskopf K;Volkmer AK;Volkmer JP;Mühlenberg T;Weissman IL;van de Rijn M
通讯作者：
van de Rijn M

Molecular subtyping of leiomyosarcoma with 3' end RNA sequencing.

DOI：
10.1016/j.gdata.2015.06.029
发表时间：
2015-09-01
期刊：
Genomics data
影响因子：
0
作者：
Guo X;Forgó E;van de Rijn M
通讯作者：
van de Rijn M

Flipping the script on macrophages in leiomyosarcoma.

DOI：
10.4161/onci.20799
发表时间：
2012-10-01
期刊：
Oncoimmunology
影响因子：
7.2
作者：
Edris B;Weiskopf K;Weissman IL;van de Rijn M
通讯作者：
van de Rijn M

Discovery of molecular subtypes in leiomyosarcoma through integrative molecular profiling.

DOI：
10.1038/onc.2009.381
发表时间：
2010-02-11
期刊：
ONCOGENE
影响因子：
8
作者：
Beck, A. H.;Lee, C-H;Witten, D. M.;Gleason, B. C.;Edris, B.;Espinosa, I.;Zhu, S.;Li, R.;Montgomery, K. D.;Marinelli, R. J.;Tibshirani, R.;Hastie, T.;Jablons, D. M.;Rubin, B. P.;Fletcher, C. D.;West, R. B.;van de Rijn, M.
通讯作者：
van de Rijn, M.

Clinically Relevant Molecular Subtypes in Leiomyosarcoma.

DOI：
10.1158/1078-0432.ccr-14-3141
发表时间：
2015-08-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
0
作者：
Guo X;Jo VY;Mills AM;Zhu SX;Lee CH;Espinosa I;Nucci MR;Varma S;Forgó E;Hastie T;Anderson S;Ganjoo K;Beck AH;West RB;Fletcher CD;van de Rijn M
通讯作者：
van de Rijn M