A novel faecal Lachnoclostridium marker for the non-invasive diagnosis of colorectal adenoma and cancer

Jessie Qiaoyi Liang, Tong Li, Geicho Nakatsu, Ying-Xuan Chen, Tung On Yau, Eagle Chu, Sunny Wong, Chun Ho Szeto, Siew C Ng, Francis K L Chan, Jing-Yuan Fang, Joseph J Y Sung, Jun Yu, Jessie Qiaoyi Liang, Tong Li, Geicho Nakatsu, Ying-Xuan Chen, Tung On Yau, Eagle Chu, Sunny Wong, Chun Ho Szeto, Siew C Ng, Francis K L Chan, Jing-Yuan Fang, Joseph J Y Sung, Jun Yu

Abstract

Objective: There is a need for early detection of colorectal cancer (CRC) at precancerous-stage adenoma. Here, we identified novel faecal bacterial markers for diagnosing adenoma.

Design: This study included 1012 subjects (274 CRC, 353 adenoma and 385 controls) from two independent Asian groups. Candidate markers were identified by metagenomics and validated by targeted quantitative PCR.

Results: Metagenomic analysis identified 'm3' from a Lachnoclostridium sp., Fusobacterium nucleatum (Fn) and Clostridium hathewayi (Ch) to be significantly enriched in adenoma. Faecal m3 and Fn were significantly increased from normal to adenoma to CRC (p<0.0001, linear trend by one-way ANOVA) in group I (n=698), which was further confirmed in group II (n=313; p<0.0001). Faecal m3 may perform better than Fn in distinguishing adenoma from controls (areas under the receiver operating characteristic curve (AUROCs) m3=0.675 vs Fn=0.620, p=0.09), while Fn performed better in diagnosing CRC (AUROCs Fn=0.862 vs m3=0.741, p<0.0001). At 78.5% specificity, m3 and Fn showed sensitivities of 48.3% and 33.8% for adenoma, and 62.1% and 77.8% for CRC, respectively. In a subgroup tested with faecal immunochemical test (FIT; n=642), m3 performed better than FIT in detecting adenoma (sensitivities for non-advanced and advanced adenomas of 44.2% and 50.8% by m3 (specificity=79.6%) vs 0% and 16.1% by FIT (specificity=98.5%)). Combining with FIT improved sensitivity of m3 for advanced adenoma to 56.8%. The combination of m3 with Fn, Ch, Bacteroides clarus and FIT performed best for diagnosing CRC (specificity=81.2% and sensitivity=93.8%).

Conclusion: This study identifies a novel bacterial marker m3 for the non-invasive diagnosis of colorectal adenoma.

Keywords: colonic bacteria; colorectal adenomas; colorectal cancer screening.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Identification and characterisation of m3. (A) Metagenome sequencing identified m3, as well as Fusobacterium nucleatum (Fn) and Clostridium hathewayi (Ch), to be significantly increased in faecal samples of patients with adenoma. (B) DNA sequence of m3 showed high similarity to Lachnoclostridium sp. YL32. (C) m3 encodes a putative reverse transcriptase (RTase) that maps to a group II intron RTase, lacking the first 60 amino acids but retaining the RTase conserved domain. A, adenoma; CRC, colorectal cancer; N, normal control.
Figure 2
Figure 2
Quantitative detection of faecal m3 in the diagnosis of patients with colorectal cancer (CRC) and adenoma. (A) Relative abundance of m3 in faecal samples differed significantly between healthy control subjects (N, n=288), patients with adenoma (A, n=207) and patients with CRC (n=203). ***p<0.0001 as compared with N; ##p<0.001 as compared with A. (B) No significant difference in faecal abundance of m3 was observed between non-advanced and advanced adenomas. (C) No difference in faecal abundance of m3 was observed among patients with CRC of different tumour-node-metastasis (TNM) stages. (D) Occurrence rates of m3 was significantly higher in patients with adenoma compared with control subjects, and highest in patients with CRC. (E) Receiver operating characteristic (ROC) curves and diagnostic performance of m3 in discriminating patients with CRC and adenoma from control subjects, respectively. AUROC, area under ROC.
Figure 3
Figure 3
Comparison and combination of bacterial markers for non-invasive diagnosis of colorectal cancer (CRC) and adenoma. (A) Relative abundances of Fusobacterium nucleatum (Fn), Clostridium hathewayi (Ch) in faecal samples of control subjects, patients with adenoma and patients with CRC. N, normal control; A, adenoma; ***p<0.0001 as compared with N; ###p<0.0001 as compared with A. (B) ROC curve analyses showed Fn could discriminate adenoma and CRC from controls, while Ch could discriminate CRC but not adenoma from controls. (C) Comparison of ROC curves of Fn, m3 and their combination. (D) Diagnostic performances of Fn, m3 and their combination. Fn performed better than m3 in diagnosing CRC, and m3 was superior to Fn in diagnosing adenoma. Combination with Fn improved the diagnostic performance of m3 for CRC but not for adenoma.
Figure 4
Figure 4
Combination of four markers for olorectal cancer (CRC) and m3 alone for adenoma. (A) Receiver operating characteristic (ROC) curve analysis of combination of the five bacterial markers of interest showed that combination of Fn, m3, Ch and Bc by a logistic regression (LR) model worked best for CRC diagnosis. Shown p values are by comparison ROC curves. (B) Level of the combination of Fn, m3, Ch and Bc (LR4) in faecal samples and comparison of its diagnostic performance with m3. N, normal control; A, adenoma; ***p<0.0001 as compared with N; ###p<0.0001 as compared with A. (C) Proposed strategy for the application of Fn, m3, Ch and Bc in the diagnosis of CRC and adenoma.
Figure 5
Figure 5
Validation of bacterial markers in diagnosing colorectal cancer (CRC) and adenoma in a second independent group of faecal samples. (A) Relative faecal abundances of Fn and m3 and level of the combination of Fn, m3, Ch and Bc (LR4) in patients with CRC and adenoma compared with control subjects of the second group. N, normal control; A, adenoma; *p<0.05 and ***p<0.0001 as compared with N; #p<0.05 and ##p<0.001 as compared with A. (B) Comparison of ROC curves and diagnostic performances of Fn, m3 and LR4.
Figure 6
Figure 6
Comparison and combination of bacterial markers with faecal immunochemical test (FIT). (A) Comparison of sensitivity and specificity of FIT, m3, combination of four makers (Fn, m3, Ch and Bc; LR4) and combination of bacterial markers with FIT in a subgroup of Hong Kong samples. LR4 combined with FIT performed best for colorectal cancer (CRC) detection, while m3 combined with FIT performed best for detecting adenoma. (B) Comparison of the sensitivities of FIT, LR4 and their combination in detecting CRC according to tumour-node-metastasis (TNM) stage subsets. (C) Comparison of the sensitivities of FIT, m3 and their combination in detecting non-advanced and advanced adenomas. All comparison of sensitivities was conducted by χ2 tests. A, non-advanced adenoma; AA, advanced adenoma.

References

    1. Allemani C, Matsuda T, Di Carlo V, et al. . Global surveillance of trends in cancer survival 2000–14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet 2018;391:1023–75. 10.1016/S0140-6736(17)33326-3
    1. The Lancet GLOBOCAN 2018: counting the toll of cancer. Lancet 2018;392:985 10.1016/S0140-6736(18)32252-9
    1. Irrazábal T, Belcheva A, Girardin SE, et al. . The multifaceted role of the intestinal microbiota in colon cancer. Mol Cell 2014;54:309–20. 10.1016/j.molcel.2014.03.039
    1. Yu J, Feng Q, Wong SH, et al. . Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut 2017;66:70–8. 10.1136/gutjnl-2015-309800
    1. Nakatsu G, Li X, Zhou H, et al. . Gut mucosal microbiome across stages of colorectal carcinogenesis. Nat Commun 2015;6:8727 10.1038/ncomms9727
    1. Dai Z, Coker OO, Nakatsu G, et al. . Multi-cohort analysis of colorectal cancer metagenome identified altered bacteria across populations and universal bacterial markers. Microbiome 2018;6 10.1186/s40168-018-0451-2
    1. Tilg H, Adolph TE, Gerner RR, et al. . The intestinal microbiota in colorectal cancer. Cancer Cell 2018;33:954–64. 10.1016/j.ccell.2018.03.004
    1. Wong SH, Zhao L, Zhang X, et al. . Gavage of fecal samples from patients with colorectal cancer promotes intestinal carcinogenesis in germ-free and conventional mice. Gastroenterology 2017;153:1621–33. 10.1053/j.gastro.2017.08.022
    1. Kostic AD, Chun E, Robertson L, et al. . Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 2013;14:207–15. 10.1016/j.chom.2013.07.007
    1. Rubinstein MR, Wang X, Liu W, et al. . Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/β-catenin signaling via its FadA adhesin. Cell Host Microbe 2013;14:195–206. 10.1016/j.chom.2013.07.012
    1. Yu T, Guo F, Yu Y, et al. . Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 2017;170:548–63. e16 10.1016/j.cell.2017.07.008
    1. Tsoi H, Chu ESH, Zhang X, et al. . Peptostreptococcus anaerobius induces intracellular cholesterol biosynthesis in colon cells to induce proliferation and causes dysplasia in mice. Gastroenterology 2017;152:1419–33. 10.1053/j.gastro.2017.01.009
    1. Liang Q, Chiu J, Chen Y, et al. . Fecal bacteria act as novel biomarkers for noninvasive diagnosis of colorectal cancer. Clin Cancer Res 2017;23:2061–70. 10.1158/1078-0432.CCR-16-1599
    1. Xie Y-H, Gao Q-Y, Cai G-X, et al. . Fecal Clostridium symbiosum for noninvasive detection of early and advanced colorectal cancer: test and validation studies. EBioMedicine 2017;25:32–40. 10.1016/j.ebiom.2017.10.005
    1. Shah MS, DeSantis TZ, Weinmaier T, et al. . Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer. Gut 2018;67:882–91. 10.1136/gutjnl-2016-313189
    1. Lee JK, Liles EG, Bent S, et al. . Accuracy of fecal immunochemical tests for colorectal cancer: systematic review and meta-analysis. Ann Intern Med 2014;160:171.
    1. Robertson DJ, Lee JK, Boland CR, et al. . Recommendations on fecal immunochemical testing to screen for colorectal neoplasia: a consensus statement by the US Multi-Society Task force on colorectal cancer. Gastroenterology 2017;152:1217–37. 10.1053/j.gastro.2016.08.053
    1. Yutin N, Galperin MY. A genomic update on clostridial phylogeny: gram-negative spore formers and other misplaced clostridia. Environ Microbiol 2013;140:2631–41. 10.1111/1462-2920.12173
    1. Traore SI, Azhar EI, Yasir M, et al. . Description of 'Blautia phocaeensis' sp. nov. and 'Lachnoclostridium edouardi' sp. nov., isolated from healthy fresh stools of Saudi Arabia Bedouins by culturomics. New Microbes New Infect 2017;19:129–31. 10.1016/j.nmni.2017.05.017
    1. Pham T-P-T, Cadoret F, Alou MT, et al. . 'Urmitella timonensis' gen. nov., sp. nov., 'Blautia marasmi' sp. nov., 'Lachnoclostridium pacaense' sp. nov., 'Bacillus marasmi' sp. nov. and 'Anaerotruncus rubiinfantis' sp. nov., isolated from stool samples of undernourished African children. New Microbes New Infect 2017;17:84–8. 10.1016/j.nmni.2017.02.004
    1. Tidjani Alou M, Khelaifia S, La Scola B, et al. . "Lachnoclostridium touaregense," a new bacterial species isolated from the human gut microbiota. New Microbes New Infect 2016;14:51–2. 10.1016/j.nmni.2016.07.007
    1. Zhang S, Cai S, Ma Y. Association between Fusobacterium nucleatum and colorectal cancer: progress and future directions. J Cancer 2018;9:1652–9. 10.7150/jca.24048
    1. Flanagan L, Schmid J, Ebert M, et al. . Fusobacterium nucleatum associates with stages of colorectal neoplasia development, colorectal cancer and disease outcome. Eur J Clin Microbiol Infect Dis 2014;33:1381–90. 10.1007/s10096-014-2081-3
    1. Amitay EL, Werner S, Vital M, et al. . Fusobacterium and colorectal cancer: causal factor or passenger? Results from a large colorectal cancer screening study. Carcinogenesis 2017;38:781–8. 10.1093/carcin/bgx053
    1. Watanabe Y, Nagai F, Morotomi M, et al. . Bacteroides clarus sp. nov., Bacteroides fluxus sp. nov. and Bacteroides oleiciplenus sp. nov., isolated from human faeces. Int J Syst Evol Microbiol 2010;60:1864–9. 10.1099/ijs.0.015107-0
    1. Steer T, Collins MD, Gibson GR, et al. . Clostridium hathewayi sp. nov., from human faeces. Syst Appl Microbiol 2001;24:353–7. 10.1078/0723-2020-00044
    1. Imperiale TF, Ransohoff DF, Itzkowitz SH, et al. . Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med 2014;370:1287–97. 10.1056/NEJMoa1311194
    1. Jalanka J, Salonen A, Salojärvi J, et al. . Effects of bowel cleansing on the intestinal microbiota. Gut 2015;64:1562–8. 10.1136/gutjnl-2014-307240
    1. Nakatsu G, Zhou H, Wu WKK, et al. . Alterations in enteric virome are associated with colorectal cancer and survival outcomes. Gastroenterology 2018;155:529–41. 10.1053/j.gastro.2018.04.018
    1. Coker OO, Nakatsu G, Dai RZ, et al. . Enteric fungal microbiota dysbiosis and ecological alterations in colorectal cancer. Gut 2019;68:654–62. 10.1136/gutjnl-2018-317178
    1. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754–60. 10.1093/bioinformatics/btp324
    1. Morgulis A, Gertz EM, Schäffer AA, et al. . A fast and symmetric dust implementation to mask low-complexity DNA sequences. J Comput Biol 2006;13:1028–40. 10.1089/cmb.2006.13.1028
    1. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010;26:841–2. 10.1093/bioinformatics/btq033
    1. Franzosa EA, McIver LJ, Rahnavard G, et al. . Species-level functional profiling of metagenomes and metatranscriptomes. Nat Methods 2018;15:962–8. 10.1038/s41592-018-0176-y
    1. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014;30:2068–9. 10.1093/bioinformatics/btu153
    1. Wong SH, Kwong TNY, Chow T-C, et al. . Quantitation of faecal Fusobacterium improves faecal immunochemical test in detecting advanced colorectal neoplasia. Gut 2017;66:1441–8. 10.1136/gutjnl-2016-312766
    1. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837–45. 10.2307/2531595
    1. Youden WJ. Index for rating diagnostic tests. Cancer 1950;3:32–5. 10.1002/1097-0142(1950)3:1&lt;32::AID-CNCR2820030106&gt;;2-3

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