Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Department of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL, USA.
Cancer Med. 2021 Aug;10(16):5712-5720. doi: 10.1002/cam4.4095. Epub 2021 Jun 29.
In silico deconvolution of invasive immune cell infiltration in bulk breast tumors helps characterize immunophenotype, expands treatment options, and influences survival endpoints. In this study, we identify the differential expression (DE) of the LM22 signature to classify immune-rich and -poor breast tumors and evaluate immune infiltration by receptor subtype and lymph node metastasis.
Using publicly available data, we applied the CIBERSORT algorithm to estimate immune cells infiltrating the tumor into immune-rich and immune-poor groups. We then tested the association of receptor subtype and nodal status with immune-rich/poor phenotype. We used DE to test individual signature genes and over-representation analysis for related pathways.
CCL19 and CXCL9 expression differed between rich/poor signature groups regardless of subtype. Overexpression of CHI3L2 and FES was observed in triple negative breast cancers (TNBCs) relative to other subtypes in immune-rich tumors. Non-signature genes, LYZ, C1QB, CORO1A, EVI2B, GBP1, PSMB9, and CD52 were consistently overexpressed in immune-rich tumors, and SCUBE2 and GRIA2 were associated with immune-poor tumors. Immune-rich tumors had significant upregulation of genes/pathways while none were identified in immune-poor tumors.
Overall, the proportion of immune-rich/poor tumors differed by subtype; however, a subset of 10 LM22 genes that marked immune-rich status remained the same across subtype. Non-LM22 genes differentially expressed between the phenotypes suggest that the biologic processes responsible for immune-poor phenotype are not yet well characterized.
在体解析批量乳腺肿瘤中浸润性免疫细胞有助于描绘免疫表型,扩大治疗选择,并影响生存终点。在这项研究中,我们确定了 LM22 特征的差异表达(DE),以将富含免疫和免疫贫乏的乳腺肿瘤进行分类,并评估受体亚型和淋巴结转移的免疫浸润。
使用公开可用的数据,我们应用 CIBERSORT 算法来估计肿瘤中浸润的免疫细胞分为富含免疫和免疫贫乏的组。然后,我们测试了受体亚型和淋巴结状态与免疫丰富/贫乏表型的关联。我们使用 DE 来测试个体特征基因,并进行相关通路的过度表达分析。
CCL19 和 CXCL9 的表达在丰富/贫乏特征组之间存在差异,而与亚型无关。在富含免疫的肿瘤中,与其他亚型相比,三阴性乳腺癌(TNBC)中 CHI3L2 和 FES 的表达上调。非特征基因 LYZ、C1QB、CORO1A、EVI2B、GBP1、PSMB9 和 CD52 在富含免疫的肿瘤中持续过表达,而 SCUBE2 和 GRIA2 与免疫贫乏的肿瘤相关。富含免疫的肿瘤中存在显著的基因/通路上调,而在免疫贫乏的肿瘤中则没有发现。
总体而言,富含免疫/贫乏的肿瘤比例因亚型而异;然而,一组 10 个标记免疫丰富状态的 LM22 基因在各亚型之间保持不变。表型之间差异表达的非 LM22 基因表明,负责免疫贫乏表型的生物学过程尚未得到很好的描述。