571:从靶标和非靶标测序数据中检测体细胞拷贝数变化

Catalin C. Barbacioru, Han-Yu Chuang, R. Nagy, Darya I. Chudova, Amirali Talasaz
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Methods: Using sequencing data from a large database of more than 100k clinical cell-free DNA (cfDNA) patient samples (Guardant Health, CA), we developed a probabilistic model to simultaneously normalize molecular coverage, segment the genome, predict copy number alterations, and estimate the tumor content in cfDNA samples, while accounting for mixtures of cell populations. The model is using off-target and on-target coverage. Copy number status, including loss of heterozygosity (LoH), is inferred in order to predict gene level somatic CNAs or genome wide instability/LoH. Results: We demonstrated the improvement from the off-target incorporation in three aspects. First, to estimate sensitivity improvement in detections of CNAs, we simulated deletions and amplifications of regions exceeding 40 Mb, using coverage and MAF variability observed in existing data. Combining coverage of on-target and off-target regions is expected to improve the LoD for detection of CNAs by 20%, when compared to CNA detection from on-target coverage. Next, we obtained samples from 15,618 cancer patients of different cancer types processed on GuardantOMNI® RUO and determined human leukocyte antigen (HLA) allele-specific copy number using this off-target assisted method. We observed a high prevalence (more than 15%) of LoH in HLA in bladder cancer, prostate cancer, NSCLC and HNSC, consistent with previous studies that HLA LOH is a common feature of several cancer types and diminishes immunotherapy efficacy. Finally, tumor fraction (TF) estimate was validated by comparing the TF against the maximum variant allele fraction of known oncogenic driver mutations in 6,000 cancer cases of various types. High concordance was observed in CRC samples (R2=0.75), gastric cancer (R2=0.63) and bladder cancer (R2=0.6), which suggest the use of this metric to better estimate tumor shedding levels in cfDNA in cases when driver mutations are not represented on a targeting panel. Conclusion: Our results show that probabilistic modeling of coverage data generated from both on-target and off-target cfDNA sequencing can detect gene specific or whole genome level somatic copy number alterations and LoH. This method may enable improvements in CNA detection accuracy, sensitivity, and specificity in plasma and provides more precise interrogation of LoH status and tumor fraction. Citation Format: Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz. Detection of somatic copy number alterations from on-target and off-target sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. 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引用次数: 0

摘要

背景:已经开发了几种计算方法来识别导致或与癌症发展相关的拷贝数改变(CNA),并在最近的研究中显示其早于癌症诊断多年。目前涉及无细胞DNA (cfDNA)靶向测序数据的方法是基于靶区或非靶区覆盖的深度,而结合种系SNP信息推断拷贝数改变和肿瘤分数的计算方法仍然不发达。方法:利用来自超过10万临床无细胞DNA (cfDNA)患者样本的大型数据库(Guardant Health, CA)的测序数据,我们开发了一个概率模型,同时标准化分子覆盖率,基因组片段,预测拷贝数改变,并估计cfDNA样本中的肿瘤含量,同时考虑细胞群的混合。该模型使用了非目标和目标覆盖。拷贝数状态,包括杂合性损失(LoH),是为了预测基因水平的体细胞CNAs或全基因组不稳定性/LoH而推断的。结果:我们从三个方面论证了脱靶合并的改进。首先,为了估计CNAs检测灵敏度的提高,我们利用现有数据中观察到的覆盖率和MAF变异性,模拟了超过40 Mb的区域的缺失和扩增。与从靶区检测CNA相比,结合靶区和非靶区覆盖率有望将检测CNA的LoD提高20%。接下来,我们从15618名不同癌症类型的癌症患者中获得GuardantOMNI®RUO处理的样本,并使用这种脱靶辅助方法测定人类白细胞抗原(HLA)等位基因特异性拷贝数。我们观察到膀胱癌、前列腺癌、NSCLC和HNSC中HLA中LoH的高患病率(超过15%),这与之前的研究一致,即HLA LoH是几种癌症类型的共同特征,并降低免疫治疗效果。最后,通过比较6000例不同类型癌症病例的肿瘤分数(TF)与已知致癌驱动突变的最大变异等位基因分数,验证了肿瘤分数(TF)的估计。在结直肠癌样本(R2=0.75)、胃癌样本(R2=0.63)和膀胱癌样本(R2=0.6)中观察到高度一致性,这表明在驱动突变未在靶向面板上代表的情况下,使用该指标可以更好地估计cfDNA中的肿瘤脱落水平。结论:我们的研究结果表明,对靶上和脱靶cfDNA测序产生的覆盖数据进行概率建模可以检测基因特异性或全基因组水平的体细胞拷贝数改变和LoH。该方法可以提高血浆中CNA检测的准确性、灵敏度和特异性,并提供更精确的LoH状态和肿瘤分数的查询。引文格式:Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz。从靶上和脱靶上测序数据检测体细胞拷贝数变化[摘要]。见:美国癌症研究协会2021年年会论文集;2021年4月10日至15日和5月17日至21日。费城(PA): AACR;癌症杂志,2021;81(13 -增刊):571。
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Abstract 571: Detection of somatic copy number alterations from on-target and off-target sequencing data
Background: Several computational methods have been developed to identify copy number alterations (CNA) leading to or associated with cancer development and shown in recent studies to precede cancer diagnosis by many years. Current methods involving cell-free DNA (cfDNA) targeted sequencing data are based on the depth of coverage of on-target or off-target regions, whereas computational methods incorporating germline SNP information for making inferences on copy number alterations and tumor fraction remain underdeveloped. Methods: Using sequencing data from a large database of more than 100k clinical cell-free DNA (cfDNA) patient samples (Guardant Health, CA), we developed a probabilistic model to simultaneously normalize molecular coverage, segment the genome, predict copy number alterations, and estimate the tumor content in cfDNA samples, while accounting for mixtures of cell populations. The model is using off-target and on-target coverage. Copy number status, including loss of heterozygosity (LoH), is inferred in order to predict gene level somatic CNAs or genome wide instability/LoH. Results: We demonstrated the improvement from the off-target incorporation in three aspects. First, to estimate sensitivity improvement in detections of CNAs, we simulated deletions and amplifications of regions exceeding 40 Mb, using coverage and MAF variability observed in existing data. Combining coverage of on-target and off-target regions is expected to improve the LoD for detection of CNAs by 20%, when compared to CNA detection from on-target coverage. Next, we obtained samples from 15,618 cancer patients of different cancer types processed on GuardantOMNI® RUO and determined human leukocyte antigen (HLA) allele-specific copy number using this off-target assisted method. We observed a high prevalence (more than 15%) of LoH in HLA in bladder cancer, prostate cancer, NSCLC and HNSC, consistent with previous studies that HLA LOH is a common feature of several cancer types and diminishes immunotherapy efficacy. Finally, tumor fraction (TF) estimate was validated by comparing the TF against the maximum variant allele fraction of known oncogenic driver mutations in 6,000 cancer cases of various types. High concordance was observed in CRC samples (R2=0.75), gastric cancer (R2=0.63) and bladder cancer (R2=0.6), which suggest the use of this metric to better estimate tumor shedding levels in cfDNA in cases when driver mutations are not represented on a targeting panel. Conclusion: Our results show that probabilistic modeling of coverage data generated from both on-target and off-target cfDNA sequencing can detect gene specific or whole genome level somatic copy number alterations and LoH. This method may enable improvements in CNA detection accuracy, sensitivity, and specificity in plasma and provides more precise interrogation of LoH status and tumor fraction. Citation Format: Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz. Detection of somatic copy number alterations from on-target and off-target sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 571.
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