Vogtmann Emily, Hua Xing, Zeller Georg, Sunagawa Shinichi, Voigt Anita Y, Hercog Rajna, Goedert James J, Shi Jianxin, Bork Peer, Sinha Rashmi
Division of Cancer Epidemiology & Genetics, National Cancer Institute, Bethesda, Maryland, United States of America.
Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, United States of America.
PLoS One. 2016 May 12;11(5):e0155362. doi: 10.1371/journal.pone.0155362. eCollection 2016.
Accumulating evidence indicates that the gut microbiota affects colorectal cancer development, but previous studies have varied in population, technical methods, and associations with cancer. Understanding these variations is needed for comparisons and for potential pooling across studies. Therefore, we performed whole-genome shotgun sequencing on fecal samples from 52 pre-treatment colorectal cancer cases and 52 matched controls from Washington, DC. We compared findings from a previously published 16S rRNA study to the metagenomics-derived taxonomy within the same population. In addition, metagenome-predicted genes, modules, and pathways in the Washington, DC cases and controls were compared to cases and controls recruited in France whose specimens were processed using the same platform. Associations between the presence of fecal Fusobacteria, Fusobacterium, and Porphyromonas with colorectal cancer detected by 16S rRNA were reproduced by metagenomics, whereas higher relative abundance of Clostridia in cancer cases based on 16S rRNA was merely borderline based on metagenomics. This demonstrated that within the same sample set, most, but not all taxonomic associations were seen with both methods. Considering significant cancer associations with the relative abundance of genes, modules, and pathways in a recently published French metagenomics dataset, statistically significant associations in the Washington, DC population were detected for four out of 10 genes, three out of nine modules, and seven out of 17 pathways. In total, colorectal cancer status in the Washington, DC study was associated with 39% of the metagenome-predicted genes, modules, and pathways identified in the French study. More within and between population comparisons are needed to identify sources of variation and disease associations that can be reproduced despite these variations. Future studies should have larger sample sizes or pool data across studies to have sufficient power to detect associations that are reproducible and significant after correction for multiple testing.
越来越多的证据表明,肠道微生物群会影响结直肠癌的发展,但以往的研究在研究人群、技术方法以及与癌症的关联方面存在差异。为了进行比较以及可能的跨研究汇总,需要了解这些差异。因此,我们对来自华盛顿特区的52例治疗前结直肠癌病例和52例匹配对照的粪便样本进行了全基因组鸟枪法测序。我们将先前发表的16S rRNA研究结果与同一人群中宏基因组学衍生的分类学结果进行了比较。此外,还将华盛顿特区病例和对照中宏基因组预测的基因、模块和通路与在法国招募的病例和对照进行了比较,法国的样本使用相同平台进行处理。16S rRNA检测到的粪便梭杆菌属、梭杆菌和卟啉单胞菌属与结直肠癌之间的关联通过宏基因组学得到了重现,而基于16S rRNA的癌症病例中梭菌属相对丰度较高,基于宏基因组学则仅处于临界水平。这表明在同一样本集中,两种方法能观察到大多数但并非所有的分类学关联。考虑到最近发表的法国宏基因组学数据集中癌症与基因、模块和通路相对丰度之间的显著关联,在华盛顿特区人群中,10个基因中有4个、9个模块中有3个、17条通路中有7条检测到具有统计学意义的关联。总体而言,华盛顿特区研究中的结直肠癌状态与法国研究中确定的39%的宏基因组预测基因、模块和通路相关。需要进行更多的人群内部和人群之间的比较,以确定尽管存在这些差异但仍可重现的变异来源和疾病关联。未来的研究应该有更大的样本量或跨研究汇总数据,以便有足够的能力检测在多重检验校正后可重现且显著的关联。