Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients.
Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients.
复制标题
DOI：
10.1186/s13073-021-00898-8
复制
发表时间：
2021-05-31
期刊：
影响因子：
12.3
通讯作者：
Solit DB
中科院分区：
文献类型：
--
作者：
Tsui DWY;Cheng ML;Shady M;Yang JL;Stephens D;Won H;Srinivasan P;Huberman K;Meng F;Jing X;Patel J;Hasan M;Johnson I;Gedvilaite E;Houck-Loomis B;Socci ND;Selcuklu SD;Seshan VE;Zhang H;Chakravarty D;Zehir A;Benayed R;Arcila M;Ladanyi M;Funt SA;Feldman DR;Li BT;Razavi P;Rosenberg J;Bajorin D;Iyer G;Abida W;Scher HI;Rathkopf D;Viale A;Berger MF;Solit DB
无细胞DNA（cfDNA）分析越来越多地用于指导癌症护理，但突变并不总是被识别出来。检测血浆中体细胞突变的能力取决于测定灵敏度和血浆中肿瘤来源的循环DNA的分数（即，cfDNA肿瘤部分）。我们假设cfDNA肿瘤分数可以为阴性cfDNA结果的解释提供信息，并指导更大基因组宽度或深度的后续测定的选择。从118名转移性癌症患者中收集的血浆样本用cf-IMPACT进行了分析，cf-IMPACT是FDA授权的MSK-IMPACT肿瘤检测的修改版本，可以检测410个癌症相关基因的基因组改变。还在相同样品中进行浅全基因组测序（sWGS），以使用z分数统计基于全基因组拷贝数改变来估计cfDNA肿瘤分数。基于sWGS估计的肿瘤分数，对通过cf-IMPACT检测到的没有体细胞改变的血浆样品进行分类，以使用不太全面但更灵敏的测定（MSK-ACCESS）或更广泛的全外显子组测序（WES）进行分析。使用cf-IMPACT进行的cfDNA分析在55/76（72%）具有MSK-IMPACT肿瘤分析数据的患者中发现了体细胞突变。对于具有高肿瘤分数（z评分≥ 5）的血浆样本，在血浆和肿瘤分析之间观察到突变谱和肿瘤突变负荷（TMB）的一致性显著较高。在42例肿瘤数据不可用的患者中，cf-IMPACT在16/42例（38%）中发现了突变。总的来说，cf-IMPACT血浆分析显示71/118（60%）例患者发生突变，30（25%）例患者发生临床可操作的变化，包括FDA批准药物的治疗靶点。在47个没有检测到改变和低肿瘤分数（z分数<5）的样品中，29个具有足够的材料以使用不太全面但更灵敏的测定MSK-ACCESS进行重新分析，其揭示了14/29（48%）的体细胞突变。相反，通过WES分析了5例cf-IMPACT未检测到变化且肿瘤分数较高（z评分≥ 5）的患者，确定了cf-IMPACT组未涵盖的潜在致癌驱动因子的突变特征和变化。总体而言，我们使用三种互补的血浆分析方法在整个队列中的90/118（76%）例患者中鉴定了突变。cfDNA肿瘤分数可以为阴性cfDNA结果的解释提供信息，并指导最有可能鉴定临床相关基因组改变的后续测序平台的选择。在线版本包含补充材料，可通过10.1186/s13073 - 021 - 00898 - 8获得。
Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES). cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches. cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations. The online version contains supplementary material available at 10.1186/s13073-021-00898-8.
登录
查看更多内容
影响因子：
64.8
作者：
Abbosh C;Birkbak NJ;Wilson GA;Jamal-Hanjani M;Constantin T;Salari R;Le Quesne J;Moore DA;Veeriah S;Rosenthal R;Marafioti T;Kirkizlar E;Watkins TBK;McGranahan N;Ward S;Martinson L;Riley J;Fraioli F;Al Bakir M;Grönroos E;Zambrana F;Endozo R;Bi WL;Fennessy FM;Sponer N;Johnson D;Laycock J;Shafi S;Czyzewska-Khan J;Rowan A;Chambers T;Matthews N;Turajlic S;Hiley C;Lee SM;Forster MD;Ahmad T;Falzon M;Borg E;Lawrence D;Hayward M;Kolvekar S;Panagiotopoulos N;Janes SM;Thakrar R;Ahmed A;Blackhall F;Summers Y;Hafez D;Naik A;Ganguly A;Kareht S;Shah R;Joseph L;Marie Quinn A;Crosbie PA;Naidu B;Middleton G;Langman G;Trotter S;Nicolson M;Remmen H;Kerr K;Chetty M;Gomersall L;Fennell DA;Nakas A;Rathinam S;Anand G;Khan S;Russell P;Ezhil V;Ismail B;Irvin-Sellers M;Prakash V;Lester JF;Kornaszewska M;Attanoos R;Adams H;Davies H;Oukrif D;Akarca AU;Hartley JA;Lowe HL;Lock S;Iles N;Bell H;Ngai Y;Elgar G;Szallasi Z;Schwarz RF;Herrero J;Stewart A;Quezada SA;Peggs KS;Van Loo P;Dive C;Lin CJ;Rabinowitz M;Aerts HJWL;Hackshaw A;Shaw JA;Zimmermann BG;TRACERx consortium;PEACE consortium;Swanton C
通讯作者：
Swanton C
通过碎片尺寸分析增强了循环肿瘤DNA的检测。
影响因子：
17.1
作者：
Mouliere F;Chandrananda D;Piskorz AM;Moore EK;Morris J;Ahlborn LB;Mair R;Goranova T;Marass F;Heider K;Wan JCM;Supernat A;Hudecova I;Gounaris I;Ros S;Jimenez-Linan M;Garcia-Corbacho J;Patel K;Østrup O;Murphy S;Eldridge MD;Gale D;Stewart GD;Burge J;Cooper WN;van der Heijden MS;Massie CE;Watts C;Corrie P;Pacey S;Brindle KM;Baird RD;Mau-Sørensen M;Parkinson CA;Smith CG;Brenton JD;Rosenfeld N
通讯作者：
Rosenfeld N
影响因子：
3.7
作者：
Koeppel F;Blanchard S;Jovelet C;Genin B;Marcaillou C;Martin E;Rouleau E;Solary E;Soria JC;André F;Lacroix L
通讯作者：
Lacroix L
影响因子：
12.3
作者：
Heitzer E;Ulz P;Belic J;Gutschi S;Quehenberger F;Fischereder K;Benezeder T;Auer M;Pischler C;Mannweiler S;Pichler M;Eisner F;Haeusler M;Riethdorf S;Pantel K;Samonigg H;Hoefler G;Augustin H;Geigl JB;Speicher MR
通讯作者：
Speicher MR
影响因子：
46.9
作者：
通讯作者：
--