Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University Hospital, University of Leeds, Leeds, United Kingdom.
NHS Bowel Cancer Screening Programme - Southern Hub, Surrey Research Park, Guildford, United Kingdom.
Clin Cancer Res. 2021 Apr 15;27(8):2246-2254. doi: 10.1158/1078-0432.CCR-20-3807. Epub 2021 Mar 3.
There is potential for fecal microbiome profiling to improve colorectal cancer screening. This has been demonstrated by research studies, but it has not been quantified at scale using samples collected and processed routinely by a national screening program.
Between 2016 and 2019, the largest of the NHS Bowel Cancer Screening Programme hubs prospectively collected processed guaiac fecal occult blood test (gFOBT) samples with subsequent colonoscopy outcomes: blood-negative [ = 491 (22%)]; colorectal cancer [ = 430 (19%)]; adenoma [ = 665 (30%)]; colonoscopy-normal [ = 300 (13%)]; nonneoplastic [ = 366 (16%)]. Samples were transported and stored at room temperature. DNA underwent 16S rRNA gene V4 amplicon sequencing. Taxonomic profiling was performed to provide features for classification via random forests (RF).
Samples provided 16S amplicon-based microbial profiles, which confirmed previously described colorectal cancer-microbiome associations. Microbiome-based RF models showed potential as a first-tier screen, distinguishing colorectal cancer or neoplasm (colorectal cancer or adenoma) from blood-negative with AUC 0.86 (0.82-0.89) and AUC 0.78 (0.74-0.82), respectively. Microbiome-based models also showed potential as a second-tier screen, distinguishing from among gFOBT blood-positive samples, colorectal cancer or neoplasm from colonoscopy-normal with AUC 0.79 (0.74-0.83) and AUC 0.73 (0.68-0.77), respectively. Models remained robust when restricted to 15 taxa, and performed similarly during external validation with metagenomic datasets.
Microbiome features can be assessed using gFOBT samples collected and processed routinely by a national colorectal cancer screening program to improve accuracy as a first- or second-tier screen. The models required as few as 15 taxa, raising the potential of an inexpensive qPCR test. This could reduce the number of colonoscopies in countries that use fecal occult blood test screening.
粪便微生物组分析有可能改善结直肠癌的筛查效果。这已通过研究证实，但尚未通过使用全国性筛查计划常规采集和处理的样本进行大规模量化。
在 2016 年至 2019 年期间，NHS 肠癌筛查计划的最大中心前瞻性地收集了经处理的愈创木脂粪便潜血试验（gFOBT）样本，并随后进行了结肠镜检查：血阴性[=491（22%）]；结直肠癌[=430（19%）]；腺瘤[=665（30%）]；结肠镜检查正常[=300（13%）]；非肿瘤[=366（16%）]。样本在室温下运输和储存。DNA 经过 16S rRNA 基因 V4 扩增子测序。分类分析提供了通过随机森林（RF）分类的特征。
样本提供了基于 16S 扩增子的微生物特征，证实了先前描述的结直肠癌与微生物组的关联。基于微生物组的 RF 模型具有作为一线筛查的潜力，能够区分结直肠癌或肿瘤（结直肠癌或腺瘤）与血阴性，其 AUC 分别为 0.86（0.82-0.89）和 0.78（0.74-0.82）。基于微生物组的模型也具有作为二线筛查的潜力，能够区分 gFOBT 血阳性样本中的结直肠癌或肿瘤与结肠镜检查正常，其 AUC 分别为 0.79（0.74-0.83）和 0.73（0.68-0.77）。当限制在 15 个分类单元时，模型仍然稳健，并且在使用宏基因组数据集进行外部验证时表现相似。
可以使用全国结直肠癌筛查计划常规采集和处理的 gFOBT 样本评估微生物组特征，以提高作为一线或二线筛查的准确性。该模型所需的分类单元很少，可能需要进行一个廉价的 qPCR 检测。这可能会减少使用粪便潜血试验筛查的国家的结肠镜检查数量。
