Department of Translational and Precision Medicine, University La Sapienza, 00161, Rome, Italy.
Institute for Systems Analysis and Computer Science Antonio Ruberti, National Research Council, 00185, Rome, Italy.
Biol Direct. 2022 May 9;17(1):10. doi: 10.1186/s13062-022-00324-y.
Historically, the molecular classification of colorectal cancer (CRC) was based on the global genomic status, which identified microsatellite instability in mismatch repair (MMR) deficient CRC, and chromosomal instability in MMR proficient CRC. With the introduction of immune checkpoint inhibitors, the microsatellite and chromosomal instability classification regained momentum as the microsatellite instability condition predicted sensitivity to immune checkpoint inhibitors, possibly due to both high tumor mutation burden (TMB) and high levels of infiltrating lymphocytes. Conversely, proficient MMR CRC are mostly resistant to immunotherapy. To better understand the relationship between the microsatellite and chromosomal instability classification, and eventually discover additional CRC subgroups relevant for therapeutic decisions, we developed a computational pipeline that include molecular integrative analysis of genomic, epigenomic and transcriptomic data.
The first step of the pipeline was based on unsupervised hierarchical clustering analysis of copy number variations (CNVs) versus hypermutation status that identified a first CRC cluster with few CNVs enriched in Hypermutated and microsatellite instability samples, a second CRC cluster with a high number of CNVs mostly including non-HM and microsatellite stable samples, and a third cluster (7.8% of the entire dataset) with low CNVs and low TMB, which shared clinical-pathological features with Hypermutated CRCs and thus defined Hypermutated-like CRCs. The mutational features, DNA methylation profile and base substitution fingerprints of these tumors revealed that Hypermutated-like patients are molecularly distinct from Hypermutated and non-Hypermutated tumors and are likely to develop and progress through different genetic events. Transcriptomic analysis highlighted further differences amongst the three groups and revealed an inflamed tumor microenvironment and modulation Immune Checkpoint Genes in Hypermutated-like CRCs.
Therefore, our work highlights Hypermutated-like tumors as a distinct and previously unidentified CRC subgroup possibly responsive to immune checkpoint inhibitors. If further validated, these findings can lead to expanding the fraction of patients eligible to immunotherapy.
从历史上看,结直肠癌(CRC)的分子分类基于整体基因组状态,其将错配修复(MMR)缺陷型 CRC 中的微卫星不稳定和 MMR 功能完整型 CRC 中的染色体不稳定性区分开来。随着免疫检查点抑制剂的引入,微卫星和染色体不稳定性分类再次受到重视,因为微卫星不稳定状态预示着对免疫检查点抑制剂的敏感性,这可能是由于高肿瘤突变负担(TMB)和高水平浸润淋巴细胞的双重作用。相反,MMR 功能完整型 CRC 大多对免疫治疗有抗性。为了更好地理解微卫星和染色体不稳定性分类之间的关系,并最终发现与治疗决策相关的其他 CRC 亚组,我们开发了一种计算分析管道,包括对基因组、表观基因组和转录组数据的分子综合分析。
该管道的第一步基于拷贝数变异(CNVs)与超突变状态的无监督层次聚类分析,该分析确定了第一个 CRC 聚类,该聚类中 CNVs 数量较少,富含超突变和微卫星不稳定的样本;第二个 CRC 聚类中 CNVs 数量较多,主要包括非 HM 和微卫星稳定的样本;第三个聚类(占整个数据集的 7.8%)中 CNVs 和 TMB 均较低,与超突变型 CRC 具有相同的临床病理特征,因此将其定义为超突变样 CRC。这些肿瘤的突变特征、DNA 甲基化谱和碱基替换指纹揭示了超突变样患者在分子上与超突变和非超突变肿瘤不同,并且可能通过不同的遗传事件发展和进展。转录组分析进一步突出了这三个组之间的差异,并揭示了超突变样 CRC 中炎症肿瘤微环境和免疫检查点基因的调节。
因此,我们的工作强调了超突变样肿瘤作为一个独特的、以前未被识别的 CRC 亚组,可能对免疫检查点抑制剂有反应。如果进一步验证,这些发现可能会扩大免疫治疗合格患者的比例。