College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Fujian Key Laboratory for Translational Research, Institute of Translational Medicine, Fujian Medical University, Fuzhou, 350001, China.
BMC Genomics. 2019 Nov 21;20(1):881. doi: 10.1186/s12864-019-6086-2.
BACKGROUND: Targeted therapy for non-small cell lung cancer is histology dependent. However, histological classification by routine pathological assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. Additionally, the effectiveness of immunomarkers is limited by technical inconsistencies of immunostaining and lack of standardization for staining interpretation. RESULTS: Using gene expression profiles of pathologically-determined lung adenocarcinomas and squamous cell carcinomas, denoted as pADC and pSCC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to distinguish ADC from SCC. The signature consists of two genes, KRT5 and AGR2, which has the stable REO pattern of KRT5 > AGR2 in pSCC and KRT5 < AGR2 in pADC. In the two test datasets with relative unambiguous NSCLC types, the apparent accuracy of the signature were 94.44 and 98.41%, respectively. In the other integrated dataset for frozen tissues, the signature reclassified 4.22% of the 805 pADC patients as SCC and 12% of the 125 pSCC patients as ADC. Similar results were observed in the clinical challenging cases, including FFPE specimens, mixed tumors, small biopsy specimens and poorly differentiated specimens. The survival analyses showed that the pADC patients reclassified as SCC had significantly shorter overall survival than the signature-confirmed pADC patients (log-rank p = 0.0123, HR = 1.89), consisting with the knowledge that SCC patients suffer poor prognoses than ADC patients. The proliferative activity, subtype-specific marker genes and consensus clustering analyses also supported the correctness of our signature. CONCLUSIONS: The non-subjective qualitative REOs signature could effectively distinguish ADC from SCC, which would be an auxiliary test for the pathological assessment of the ambiguous cases.
背景:非小细胞肺癌的靶向治疗依赖于组织学。然而,通过常规病理评估,包括对低分化肿瘤(尤其是小活检样本)进行苏木精-伊红染色和免疫组化染色,组织学分类仍然具有挑战性。此外,免疫标志物的有效性受到免疫组化技术差异和染色解释标准化不足的限制。
结果:我们使用经病理确定的肺腺癌和肺鳞癌的基因表达谱,分别表示为 pADC 和 pSCC,开发了一种基于基因对样本内相对基因表达顺序(REO)的定性转录特征,用于区分 ADC 和 SCC。该特征由两个基因 KRT5 和 AGR2 组成,在 pSCC 中具有 KRT5>AGR2 的稳定 REO 模式,而在 pADC 中则具有 KRT5<AGR2 的模式。在两个具有相对明确 NSCLC 类型的测试数据集中,该特征的明显准确率分别为 94.44%和 98.41%。在另一个用于冷冻组织的综合数据集,该特征重新将 805 例 pADC 患者中的 4.22%分类为 SCC,将 125 例 pSCC 患者中的 12%分类为 ADC。在包括 FFPE 标本、混合肿瘤、小活检标本和低分化标本在内的临床挑战性病例中,也观察到了类似的结果。生存分析表明,重新分类为 SCC 的 pADC 患者的总生存期明显短于经特征确认的 pADC 患者(对数秩检验 p=0.0123,HR=1.89),这与 SCC 患者的预后比 ADC 患者差的认识一致。增殖活性、亚型特异性标记基因和共识聚类分析也支持我们特征的正确性。
结论:非主观定性 REO 特征可有效区分 ADC 和 SCC,这将是对不明确病例进行病理评估的辅助测试。
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