Department of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.
Neuro Oncol. 2022 Jul 1;24(7):1090-1100. doi: 10.1093/neuonc/noac009.
The role of tumor genomic profiling is rapidly growing as it results in targeted, personalized, cancer therapy. Though routinely used in clinical practice, there are no data exploring the reliability of genomic data obtained from spine metastases samples often leading to multiple biopsies in clinical practice. This study compares the genomic tumor landscape between spinal metastases and the corresponding primary tumors as well as between spinal metastases and visceral metastases.
Spine tumor samples, obtained for routine clinical care from 2013 to 2019, were analyzed using MSK-IMPACT, a next-generation sequencing assay. These samples were matched to primary or metastatic tumors from the corresponding patients. A concordance rate for genomic alterations was calculated for matching sample pairs within patients for the primary and spinal metastatic tumor samples as well as for the matching sample pairs within patients for the spinal and visceral metastases. For a more robust and clinically relevant estimate of concordance, subgroup analyses of previously established driver mutations specific to the main primary tumor histologies were performed.
Eighty-four patients contributed next-generation sequencing data from a spinal metastasis and at least one other site of disease: 54 from the primary tumor, 39 had genomic tumor data from another, nonspinal metastasis, 12 patients participated in both subsets. For the cohort of matched primary tumors and spinal metastases (n = 54) comprised of mixed histologies, we found an average concordance rate of 96.97% for all genetic events, 97.17% for mutations, 100% for fusions, 89.81% for deletions, and 97.01% for amplifications across all matched samples. Notably, >25% of patients harbored at least one genetic variant between samples tested, though not specifically for known driver mutations. The average concordance rate of driver mutations was 96.99% for prostate cancer, 95.69% (P = .0004513) for lung cancer, and 96.43% for breast cancer. An average concordance of 99.02% was calculated for all genetic events between spine metastases and non-spinal metastases (n = 41) and, more specifically, a concordance rate of 98.91% was calculated between spine metastases and liver metastases (n = 12) which was the largest represented group of nonspine metastases.
Sequencing data performed on spine tumor samples demonstrate a high concordance rate for genetic alterations between the primary tumor and spinal metastasis as well as between spinal metastases and other, visceral metastases, particularly for driver mutations. Spine tumor samples may be reliably used for genomic-based decision making in cancer care, particularly for prostate, NSCLC, and breast cancer.
随着肿瘤基因组分析在靶向和个性化癌症治疗方面的作用迅速发展，其已得到广泛应用。尽管该方法已在临床实践中常规使用，但目前尚无数据探讨从脊柱转移瘤样本中获得的基因组数据的可靠性，这通常导致在临床实践中进行多次活检。本研究比较了脊柱转移瘤与其相应的原发性肿瘤以及脊柱转移瘤与内脏转移瘤之间的肿瘤基因组图谱。
从 2013 年至 2019 年，为常规临床治疗采集脊柱肿瘤样本，并使用 MSK-IMPACT（下一代测序检测）进行分析。这些样本与来自相应患者的原发性或转移性肿瘤相匹配。对于同一患者的原发性和脊柱转移瘤样本以及同一患者的脊柱和内脏转移瘤样本，计算配对样本中基因组改变的一致性率。为了更稳健和更具临床相关性的一致性估计，对主要原发性肿瘤组织学特有的先前确定的驱动突变进行了亚组分析。
84 名患者提供了来自脊柱转移瘤和至少一个其他部位疾病的下一代测序数据：54 名来自原发性肿瘤，39 名来自另一个非脊柱转移瘤，12 名患者参与了这两个亚组。对于包含混合组织学的 54 对匹配的原发性肿瘤和脊柱转移瘤（n=54）队列，我们发现所有遗传事件的平均一致性率为 96.97%，突变的一致性率为 97.17%，融合的一致性率为 100%，缺失的一致性率为 89.81%，扩增的一致性率为 97.01%，所有匹配样本均如此。值得注意的是，>25%的患者在测试的样本之间存在至少一种遗传变异，尽管并非专门针对已知的驱动突变。前列腺癌的平均驱动突变一致性率为 96.99%，肺癌为 95.69%（P=0.0004513），乳腺癌为 96.43%。脊柱转移瘤和非脊柱转移瘤（n=41）之间所有遗传事件的平均一致性率为 99.02%，更具体地说，脊柱转移瘤和肝转移瘤（n=12）之间的一致性率为 98.91%，肝转移瘤是最大的非脊柱转移瘤代表群体。
在脊柱肿瘤样本上进行的测序数据表明，原发性肿瘤与脊柱转移瘤以及脊柱转移瘤与其他内脏转移瘤之间的遗传改变具有很高的一致性率，特别是对于驱动突变。脊柱肿瘤样本可用于癌症治疗中的基于基因组的决策，特别是对于前列腺癌、非小细胞肺癌和乳腺癌。
