B185:上皮癌细胞表达基因有助于临床相关的基于免疫的乳腺癌分类

J. Shepherd, C. Perou
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Methods: More than 130 published immune related gene signatures were evaluated in 1095 breast tumors and 97 normal mammary samples. Groups were identified by consensus based hierarchical clustering of the immune signatures, using the proportion of ambiguous clustering to select the optimal number of groups. An ElasticNet model trained on TCGA data was applied to two other breast tumor datasets to predict immune group classification. RNA-sequencing (RNAseq) data from 70 breast cancer cell lines and from human tumor xenografts passaged in immune-compromised mice and processed through a human specific sequencing pipeline provided in vitro and in vivo sources of epithelial cancer cell expression with limited stromal content that was used to filter TCGA bulk RNAseq data for epithelial expressed genes. Results: We identified three distinct immune groups present in breast cancer: immune-low, immune-normal, and immune-high. The immune-high group is characterized by high T-cell scores, including both cytotoxic and regulatory T-cell signatures, and increased B cell and macrophage signatures. The immune-normal set shows signs of normal epithelia and low proliferation. The immune-low group has very low immune cell signatures. Intrinsic breast cancer subtypes (Basal, luminal A, Luminal B, Her2 and Normal-like) are present in each of the immune groups; however, enrichment of basal tumors in immune-high, luminal tumors in the immune-low, and normal mammary, normal-like tumors and luminal A tumors in the immune-normal group demonstrate an interaction between intrinsic tumor type and immune involvement. Immune groups are prognostic in TCGA, with the immune-high group having improved recurrence-free survival. Two more breast tumor datasets confirmed improved survival for basal tumors in the immune-high group relative to the immune-low tumors. Total mutation burden, unique somatic mutations, and copy number alterations did not show significant changes between immune-low and –high groups, whereas RNA expression differs between groups. Selecting for genes with evidence of expression by epithelial breast cancer cells identified over 8,000 genes differentially expressed between the immune-low and –high groups, with CCL5, ACAP1, PVRIG, SLA2, LCK and CD8A being among the most significant. Conclusion: Breast cancer can be divided into three clinically relevant immune-related groups. Immune-high has high immune involvement, showing of markers for cytotoxicity and immune suppression and exhaustion. These patients have improved survival, but may still benefit from immune checkpoint inhibition. Immune-normal is reflective of a normal mammary immune state, suggesting a microenvironment that has not been strongly altered by the tumor. 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引用次数: 0

摘要

导论:随着乳腺癌免疫疗法的发展,需要可靠的方法来评估肿瘤中存在的免疫受累的程度和类型,并研究其对患者预后和治疗的影响。确定影响免疫受累的肿瘤特异性特征将是了解肿瘤免疫受累的关键。因此,我们评估了TCGA乳腺癌数据中免疫相关mRNA特征的表达,以识别不同的免疫相关肿瘤亚群和相关的预后价值。我们还评估了免疫细胞特征,包括B细胞和t细胞受体的丰富度和多样性,以及上皮肿瘤细胞特异性特征,包括体细胞突变、拷贝数改变和鉴定组之间的差异RNA表达。方法:对1095例乳腺肿瘤和97例正常乳腺样本的130多个已发表的免疫相关基因特征进行评价。采用基于共识的免疫特征分层聚类方法,利用模糊聚类比例选择最优组数。在TCGA数据上训练的ElasticNet模型应用于另外两个乳腺肿瘤数据集来预测免疫群分类。来自70种乳腺癌细胞系和人类肿瘤异种移植物的rna测序(RNAseq)数据在免疫受损小鼠中传代,并通过人类特异性测序管道进行处理,该管道提供了体外和体内上皮癌细胞表达来源,基质含量有限,用于过滤TCGA大量上皮表达基因的RNAseq数据。结果:我们确定了乳腺癌中存在的三种不同的免疫组:免疫低、免疫正常和免疫高。免疫高组的特点是t细胞评分高,包括细胞毒性和调节性t细胞特征,以及B细胞和巨噬细胞特征增加。免疫正常组显示正常上皮和低增殖的迹象。免疫低下组的免疫细胞特征非常低。内在乳腺癌亚型(基底、腔内A型、腔内B型、Her2型和正常样)存在于每个免疫组中;然而,免疫高组的基底肿瘤、免疫低组的管腔肿瘤以及免疫正常组的正常乳腺、正常样肿瘤和管腔A肿瘤的富集表明,内在肿瘤类型与免疫受累之间存在相互作用。免疫组是TCGA的预后,免疫高组的无复发生存率更高。另外两个乳腺肿瘤数据集证实,相对于免疫低下的肿瘤,免疫高组的基础肿瘤存活率有所提高。总突变负担、独特体细胞突变和拷贝数改变在免疫低组和免疫高组之间没有显着变化,而RNA表达在组间存在差异。选择上皮性乳腺癌细胞有表达证据的基因,在免疫低组和免疫高组之间发现了8000多个基因的差异表达,其中CCL5、ACAP1、PVRIG、SLA2、LCK和CD8A是最显著的。结论:乳腺癌可分为三个临床相关免疫相关组。免疫高具有高度的免疫参与,表现出细胞毒性和免疫抑制和衰竭的标记。这些患者的生存率有所提高,但可能仍然受益于免疫检查点抑制。免疫正常反映了正常的乳腺免疫状态,表明微环境没有被肿瘤强烈改变。免疫低下似乎表明免疫细胞从肿瘤中被排斥,即使肿瘤中含有预测的新抗原。这些患者生存率较差,需要开发新的治疗策略来激活免疫参与。上皮癌细胞表达许多免疫相关基因,包括CCL5、LCK和CD8A,这些基因可能是免疫细胞吸引的关键决定因素。引用格式:Jonathan Shepherd, Charles Perou。上皮癌细胞表达的基因有助于乳腺癌临床相关的免疫分类[摘要]。第四届CRI-CIMT-EATI-AACR国际癌症免疫治疗会议:将科学转化为生存;2018年9月30日至10月3日;纽约,纽约。费城(PA): AACR;癌症免疫学杂志2019;7(2增刊):摘要nr B185。
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Abstract B185: Epithelial cancer cell-expressed genes contribute to clinically relevant immune-based classifications of breast cancer
Introduction: With the development of immunotherapies for breast cancer therapy, reliable methods to evaluate the extent and type of immune involvement present in tumors and investigation of its effect on patient prognosis and treatment are needed. Identifying tumor-specific features that affect immune involvement will be a key to understand tumor-immune involvement. Therefore, we evaluated expression of immune-related mRNA signatures in TCGA breast cancer data to identify distinct immune-related tumor subsets and asociated prognostic values. We also evaluated immune cell features, including B cell and T-cell receptor richness and diversity, as well as epithelial tumor cell-specific features, including somatic mutations, copy number alterations and differential RNA expression between identified groups. Methods: More than 130 published immune related gene signatures were evaluated in 1095 breast tumors and 97 normal mammary samples. Groups were identified by consensus based hierarchical clustering of the immune signatures, using the proportion of ambiguous clustering to select the optimal number of groups. An ElasticNet model trained on TCGA data was applied to two other breast tumor datasets to predict immune group classification. RNA-sequencing (RNAseq) data from 70 breast cancer cell lines and from human tumor xenografts passaged in immune-compromised mice and processed through a human specific sequencing pipeline provided in vitro and in vivo sources of epithelial cancer cell expression with limited stromal content that was used to filter TCGA bulk RNAseq data for epithelial expressed genes. Results: We identified three distinct immune groups present in breast cancer: immune-low, immune-normal, and immune-high. The immune-high group is characterized by high T-cell scores, including both cytotoxic and regulatory T-cell signatures, and increased B cell and macrophage signatures. The immune-normal set shows signs of normal epithelia and low proliferation. The immune-low group has very low immune cell signatures. Intrinsic breast cancer subtypes (Basal, luminal A, Luminal B, Her2 and Normal-like) are present in each of the immune groups; however, enrichment of basal tumors in immune-high, luminal tumors in the immune-low, and normal mammary, normal-like tumors and luminal A tumors in the immune-normal group demonstrate an interaction between intrinsic tumor type and immune involvement. Immune groups are prognostic in TCGA, with the immune-high group having improved recurrence-free survival. Two more breast tumor datasets confirmed improved survival for basal tumors in the immune-high group relative to the immune-low tumors. Total mutation burden, unique somatic mutations, and copy number alterations did not show significant changes between immune-low and –high groups, whereas RNA expression differs between groups. Selecting for genes with evidence of expression by epithelial breast cancer cells identified over 8,000 genes differentially expressed between the immune-low and –high groups, with CCL5, ACAP1, PVRIG, SLA2, LCK and CD8A being among the most significant. Conclusion: Breast cancer can be divided into three clinically relevant immune-related groups. Immune-high has high immune involvement, showing of markers for cytotoxicity and immune suppression and exhaustion. These patients have improved survival, but may still benefit from immune checkpoint inhibition. Immune-normal is reflective of a normal mammary immune state, suggesting a microenvironment that has not been strongly altered by the tumor. Immune-low appears to demonstrate exclusion of immune cells from the tumor, even though tumors contain predicted neoantigens. These patients have poor survival and novel therapeutic strategies to activate immune involvement need to be developed. Epithelial cancer cell expressed many immune-related genes, including CCL5, LCK and CD8A, which may be critical determinants of immune cell attraction. Citation Format: Jonathan Shepherd, Charles Perou. Epithelial cancer cell-expressed genes contribute to clinically relevant immune-based classifications of breast cancer [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B185.
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