HPV genomic structure in cervical cancer radiation response and recurrence detection
HPV基因组结构在宫颈癌放射反应和复发检测中的作用
基本信息
- 批准号:10634999
- 负责人:
- 金额:$ 50.02万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-05-01 至 2028-04-30
- 项目状态:未结题
- 来源:
- 关键词:AddressAdenocarcinomaAdjuvantAdjuvant ChemotherapyAffectAftercareAlternative SplicingBiological AssayBiological MarkersCancer PatientCancer Personalized Profiling by Deep SequencingCervix NeoplasmsCessation of lifeCisplatinClinicClinicalClinical TrialsClonal EvolutionDNADNA sequencingDataDetectionDiagnosisDiseaseEarly DiagnosisEarly InterventionEpisomeEvolutionExonsFailureGene ExpressionGene Expression ProfileGene FrequencyGene FusionGenesGenomeGenomicsGenotypeGoalsHPV-High RiskHumanHuman ChromosomesHuman PapillomavirusHuman papilloma virus infectionHysterectomyImageImmunotherapyKeratinLocal TherapyMachine LearningMalignant NeoplasmsMalignant neoplasm of cervix uteriMalignant neoplasm of prostateManualsMeasuresMesenchymalMetabolicMetastatic/RecurrentMolecularMonitorNeoplasm MetastasisNewly DiagnosedNucleic Acid Regulatory SequencesOncogenesOutcomePatient-Focused OutcomesPatientsPatternPlasmaPopulationPrediction of Response to TherapyPublicationsRNARadiation therapyRadiosensitizationRandomized, Controlled TrialsRecurrenceRecurrent Malignant NeoplasmRecurrent diseaseReportingResearchResistanceRiskRisk AssessmentSamplingSeriesSingle Nucleotide PolymorphismStagingStaging SystemStratificationStructureSubgroupSurvival RateTargeted RadiotherapyTechnologyTestingThe Cancer Genome AtlasTimeTreatment FailureTreatment ProtocolsTumor BankValidationVariantVisualizationWomanX-Ray Computed Tomographyalternative treatmentannotation systemcancer diagnosiscancer genomicscancer recurrencecancer survivalcervical cancer preventionchemoradiationchemotherapychronic infectionclinical biomarkersclinical sequencingclinically actionablecohortexperienceflexibilityfluorodeoxyglucose positron emission tomographygenetic variantgenomic datahigh riskhuman papilloma virus oncogeneimprovedimproved outcomemalignant breast neoplasmneoantigensnoveloutcome predictionpalliativeprognostic valueprogrammed cell death ligand 1radiation responseresearch clinical testingresponserisk stratificationstandard of caretargeted sequencingtherapy resistanttooltranscriptome sequencingtreatment responsetumortumor DNAvaccine acceptance
项目摘要
PROJECT SUMMARY/ABSTRACT
Cervical cancer is one of the most common cancer diagnoses among women, and treatment failure of standard
of care (SOC) chemoradiation therapy (CRT) for locally advanced cervical cancer (LACC) is as high as 30-50%.
Since recurrent and metastatic diseases are not curable or detected too late to be treatable, there is a pressing
need for pre-treatment biomarkers to identify patients at risk of CRT treatment failure and post-treatment
biomarkers to detect LACC recurrence and metastasis early. TCGA’s effort to establish pre-treatment biomarkers
for cervical cancer by molecular stratification using human genes failed to associate to patient outcomes. On the
other hand, we recently demonstrated that HPV genotypes and HPV alternative splicing affect LACC recurrence
and survival after CRT. In our preliminary data, we additionally identified a diversity of HPV genomic structures
(HPV-GS), including HPV-human gene fusions involving alternative spliced HPV exons, that affect human
oncogene expression. We hypothesize that the variance of HPV genomic structural features among LACC
patients may represent a valuable clinical sequencing application to develop LACC SOC CRT biomarkers. For
post-treatment markers, we currently use F-fluorodeoxyglucose PET/CT (FDG-PET) images at 3–6 months to
define metabolic response, which was shown in our previous publications to predict patterns of failure after
radiotherapy for cervical cancer. We hypothesize that HPV genomic features can serve as post-treatment
biomarkers for LACC recurrence and metastasis detection that are both more accurate and detectable at earlier
timepoints. To achieve these goals, we will first test whether variance in HPV-GS can be utilized to develop a
clinical pre-treatment biomarker by developing a series of novel HPV-GS analysis tools based on our expertise
in both HPV genomics and human structural variants. HPV features will be extracted from matched DNA and
RNA sequencing data, and their prognostic values will be tested using samples from our cervical tumor bank of
LACC patients uniformly treated with curative-intent CRT. Second, we will examine whether CRT-induced LACC
clonal evolution can be used to identify treatment-resistant HPV-GS as on-treatment biomarkers. A novel deep
targeted sequencing approach will be used on single-nucleotide variants (SNV) and HPV-GS to identify LACC
subclones and fit HPV-GS in the context of clonal evolution. We will also examine the mechanisms of HPV-
human gene fusions using clonogenic survival assays and other standard assays. Last, we will use our proven
highly-sensitive and flexible CAPP-Seq technology to evaluate whether circulating tumor DNA (ctDNA) can be
used to develop HPV-GS tests for early diagnosis and post-CRT recurrence detection. We expect combining
both SNVs and HPV-GS will result in an optimized application superior to using single types of features alone.
Taken together, we expect our genomic and mechanistic research on HPV-GS biomarkers in the context of CRT-
induced LACC evolution will create a series of optimized pre-treatment and recurrence biomarkers that can be
applied in the clinic for personalized alternative treatment regimens.
项目总结/摘要
宫颈癌是女性最常见的癌症诊断之一,标准治疗失败
局部晚期宫颈癌(LACC)的护理(SOC)放化疗(CRT)高达30- 50%。
由于复发性和转移性疾病是不可治愈的,或者发现得太晚而无法治疗,
需要治疗前生物标志物来识别有CRT治疗失败风险的患者和治疗后
早期检测LACC复发和转移的生物标志物。TCGA建立治疗前生物标志物的努力
使用人类基因进行分子分层的宫颈癌患者的预后与患者预后无关。上
另一方面,我们最近证实HPV基因型和HPV选择性剪接影响LACC复发
CRT后的生存率。在我们的初步数据中,我们还发现了HPV基因组结构的多样性,
(HPV-GS),包括涉及可变剪接的HPV外显子的HPV-人基因融合,其影响人类免疫系统。
癌基因表达我们假设LACC中HPV基因组结构特征的差异
患者可以代表开发LACC SOC CRT生物标志物的有价值的临床测序应用。为
治疗后标记物,我们目前使用氟脱氧葡萄糖PET/CT(FDG-PET)图像在3-6个月,
定义代谢反应,这在我们以前的出版物中显示,可以预测失败后的模式。
宫颈癌的治疗方法我们假设HPV基因组特征可以作为治疗后的
用于LACC复发和转移检测的生物标志物在早期更准确和可检测。
时间点。为了实现这些目标,我们将首先测试是否可以利用HPV-GS的差异来开发一种新的方法。
通过基于我们的专业知识开发一系列新型HPV-GS分析工具,
在HPV基因组学和人类结构变异中。HPV特征将从匹配的DNA中提取,
RNA测序数据及其预后价值将使用来自我们的宫颈肿瘤库的样本进行测试。
LACC患者统一接受治愈性CRT治疗。其次,我们将研究CRT诱导的LACC是否
克隆进化可用于鉴定治疗抗性HPV-GS作为治疗中生物标志物。一部小说,
靶向测序方法将用于单核苷酸变异(SNV)和HPV-GS,以鉴定LACC
亚克隆和适合HPV-GS在克隆进化的背景下。我们还将研究HPV的机制-
使用克隆存活测定和其它标准测定的人基因融合。最后,我们将使用我们经过验证的
高灵敏度和灵活的CAPP-Seq技术,以评估循环肿瘤DNA(ctDNA)是否可以
用于开发HPV-GS测试,用于早期诊断和CRT后复发检测。我们希望结合
SNV和HPV-GS都将导致优于单独使用单一类型特征的优化应用上级。
综上所述,我们期待我们在CRT背景下对HPV-GS生物标志物的基因组和机制研究-
诱导的LACC演变将产生一系列优化的治疗前和复发生物标志物,
在临床上用于个性化的替代治疗方案。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jin Zhang其他文献
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{{ truncateString('Jin Zhang', 18)}}的其他基金
Integrating multi-omics, imaging, and longitudinal data to predict radiation response in cervical cancer
整合多组学、成像和纵向数据来预测宫颈癌的放射反应
- 批准号:
10734702 - 财政年份:2023
- 资助金额:
$ 50.02万 - 项目类别:
Deep learning in cervical cancer radiogenomics
宫颈癌放射基因组学中的深度学习
- 批准号:
10643978 - 财政年份:2022
- 资助金额:
$ 50.02万 - 项目类别:
Deep learning in cervical cancer radiogenomics
宫颈癌放射基因组学中的深度学习
- 批准号:
10424854 - 财政年份:2022
- 资助金额:
$ 50.02万 - 项目类别:
HPV alternative splicing in cervical cancer radiation response
HPV选择性剪接在宫颈癌放射反应中的作用
- 批准号:
10308435 - 财政年份:2020
- 资助金额:
$ 50.02万 - 项目类别:
HPV alternative splicing in cervical cancer radiation response
HPV选择性剪接在宫颈癌放射反应中的作用
- 批准号:
9891761 - 财政年份:2020
- 资助金额:
$ 50.02万 - 项目类别:
HPV alternative splicing in cervical cancer radiation response
HPV选择性剪接在宫颈癌放射反应中的作用
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10523104 - 财政年份:2020
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