Khiabanian Hossein, Hirshfield Kim M, Goldfinger Mendel, Bird Simon, Stein Mark, Aisner Joseph, Toppmeyer Deborah, Wong Serena, Chan Nancy, Dhar Kalyani, Gheeya Jinesh, Vig Hetal, Hadigol Mohammad, Pavlick Dean, Ansari Sepand, Ali Siraj, Xia Bing, Rodriguez-Rodriguez Lorna, Ganesan Shridar
Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA.
Center for Systems and Computational Biology, Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, USA.
JCO Precis Oncol. 2018;2018. doi: 10.1200/PO.17.00148. Epub 2018 Jan 19.
Inherited germline defects are implicated in up to 10% of human tumors, with particularly well-known roles in breast and ovarian cancers that harbor -mutated genes. There is also increasing evidence for the role of germline alterations in other malignancies such as colon and pancreatic cancers. Mutations in familial cancer genes can be detected by high throughput sequencing (HTS), when applied to formalin-fixed paraffin-embedded (FFPE) tumor specimens. However, due to often lack of patient-matched control normal DNA and/or low tumor purity, there is limited ability to determine the genomic status of these alterations (germline versus somatic) and to assess the presence of loss of heterozygosity (LOH). These analyses, especially when applied to genes such as , can have significant clinical implications for patient care.
LOHGIC (LOH-Germline Inference Calculator) is a statistical model selection method to determine somatic-versus-germline status and predict LOH for mutations identified via clinical grade, high-depth, hybrid-capture tumor-only sequencing. LOHGIC incorporates statistical uncertainties inherent to HTS as well as specimen biases in tumor purity estimates, which we use to assess mutations in 1,636 specimens sequenced at Rutgers Cancer Institute of New Jersey.
Evaluation of LOHGIC with available germline sequencing from testing, demonstrates 93% accuracy, 100% precision, and 96% recall. This analysis highlights a differential tumor spectrum associated with mutations.
LOHGIC can assess LOH status for both germline and somatic mutations. It also can be applied to any gene with candidate, inherited mutations. This approach demonstrates the clinical utility of targeted sequencing in both identifying patients with potential germline alterations in tumor suppressor genes as well as estimating LOH occurrence in cancer cells, which may confer therapeutic relevance.
遗传性种系缺陷在高达10%的人类肿瘤中起作用，在携带突变基因的乳腺癌和卵巢癌中作用尤为显著。种系改变在其他恶性肿瘤如结肠癌和胰腺癌中的作用也有越来越多的证据。当应用于福尔马林固定石蜡包埋（FFPE）肿瘤标本时，可通过高通量测序（HTS）检测家族性癌症基因中的突变。然而，由于常常缺乏患者匹配的对照正常DNA和/或肿瘤纯度低，确定这些改变的基因组状态（种系与体细胞）以及评估杂合性缺失（LOH）的存在的能力有限。这些分析，尤其是应用于诸如等基因时，可能对患者护理具有重要的临床意义。
LOHGIC（LOH-种系推断计算器）是一种统计模型选择方法，用于确定体细胞与种系状态，并预测通过临床级、高深度、仅肿瘤的杂交捕获测序鉴定的突变的LOH。LOHGIC纳入了HTS固有的统计不确定性以及肿瘤纯度估计中的样本偏差，我们用其评估新泽西州罗格斯癌症研究所测序的1636个标本中的突变。
用来自检测的可用种系测序对LOHGIC进行评估，显示准确率为93%，精确率为100%，召回率为96%。该分析突出了与突变相关的不同肿瘤谱。
LOHGIC可以评估种系和体细胞突变的LOH状态。它也可应用于任何有候选遗传性突变的基因。这种方法证明了靶向测序在识别肿瘤抑制基因中具有潜在种系改变的患者以及估计癌细胞中LOH发生率方面的临床实用性，这可能具有治疗相关性。
