Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples

. 2019 Sep 17 ; 4 (5) : . [epub] 20190917

Status PubMed-not-MEDLINE Jazyk angličtina Země Spojené státy americké Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid31530647

Dysbiotic configurations of the human gut microbiota have been linked to colorectal cancer (CRC). Human small noncoding RNAs are also implicated in CRC, and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis, but their role has been less extensively explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens from patients with CRC or with adenomas and from healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We observed considerable overlap and a correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. We identified a combined predictive signature composed of 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC samples separately from healthy and adenoma samples (area under the curve [AUC] = 0.87). In the present study, we report evidence that host-microbiome dysbiosis in CRC can also be observed by examination of altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more-accurate tools for diagnostic purposes.IMPORTANCE The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

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Yu J, Feng Q, Wong SH, Zhang D, Liang QY, Qin Y, Tang L, Zhao H, Stenvang J, Li Y, Wang X, Xu X, Chen N, Wu WKK, Al-Aama J, Nielsen HJ, Kiilerich P, Jensen BAH, Yau TO, Lan Z, Jia H, Li J, Xiao L, Lam TYT, Ng SC, Cheng A-L, Wong V-S, Chan FKL, Xu X, Yang H, Madsen L, Datz C, Tilg H, Wang J, Brünner N, Kristiansen K, Arumugam M, Sung JJ-Y, Wang J. 2017. Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut 66:70–78. doi:10.1136/gutjnl-2015-309800. PubMed DOI

Tilg H, Adolph TE, Gerner RR, Moschen AR. 2018. The intestinal microbiota in colorectal cancer. Cancer Cell 33:954–964. doi:10.1016/j.ccell.2018.03.004. PubMed DOI

Garrett WS. 2015. Cancer and the microbiota. Science 348:80–86. doi:10.1126/science.aaa4972. PubMed DOI PMC

Brennan CA, Garrett WS. 2016. Gut microbiota, inflammation, and colorectal cancer. Annu Rev Microbiol 70:395–411. doi:10.1146/annurev-micro-102215-095513. PubMed DOI PMC

Thomas AM, Manghi P, Asnicar F, Pasolli E, Armanini F, Zolfo M, Beghini F, Manara S, Karcher N, Pozzi C, Gandini S, Serrano D, Tarallo S, Francavilla A, Gallo G, Trompetto M, Ferrero G, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Wirbel J, Schrotz-King P, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G, Cordero F, Dias-Neto E, Setubal JC, Tett A, Pardini B, Rescigno M, Waldron L, Naccarati A, Segata N. 2019. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med 25:667–678. doi:10.1038/s41591-019-0405-7. PubMed DOI PMC

Wirbel J, Pyl PT, Kartal E, Zych K, Kashani A, Milanese A, Fleck JS, Voigt AY, Palleja A, Ponnudurai R, Sunagawa S, Coelho LP, Schrotz-King P, Vogtmann E, Habermann N, Niméus E, Thomas AM, Manghi P, Gandini S, Serrano D, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Waldron L, Naccarati A, Segata N, Sinha R, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G. 2019. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med 25:679–689. doi:10.1038/s41591-019-0406-6. PubMed DOI PMC

Feng Q, Liang S, Jia H, Stadlmayr A, Tang L, Lan Z, Zhang D, Xia H, Xu X, Jie Z, Su L, Li X, Li X, Li J, Xiao L, Huber-Schönauer U, Niederseer D, Xu X, Al-Aama JY, Yang H, Wang J, Kristiansen K, Arumugam M, Tilg H, Datz C, Wang J. 2015. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat Commun 6:6528. doi:10.1038/ncomms7528. PubMed DOI

Williams MR, Stedtfeld RD, Tiedje JM, Hashsham SA. 2017. MicroRNAs-based inter-domain communication between the host and members of the gut microbiome. Front Microbiol 8:1896. doi:10.3389/fmicb.2017.01896. PubMed DOI PMC

Liu S, da Cunha AP, Rezende RM, Cialic R, Wei Z, Bry L, Comstock LE, Gandhi R, Weiner HL. 2016. The host shapes the gut microbiota via fecal microRNA. Cell Host Microbe 19:32–43. doi:10.1016/j.chom.2015.12.005. PubMed DOI PMC

Zhou X, Li X, Wu M. 2018. miRNAs reshape immunity and inflammatory responses in bacterial infection. Signal Transduct Target Ther 3:14. doi:10.1038/s41392-018-0006-9. PubMed DOI PMC

Dalmasso G, Nguyen HTT, Yan Y, Laroui H, Charania MA, Ayyadurai S, Sitaraman SV, Merlin D. 2011. Microbiota modulate host gene expression via microRNAs. PLoS One 6:e19293. doi:10.1371/journal.pone.0019293. PubMed DOI PMC

Yuan C, Burns MB, Subramanian S, Blekhman R. 2018. Interaction between host microRNAs and the gut microbiota in colorectal cancer. mSystems 3:e00205-17. doi:10.1128/mSystems.00205-17. PubMed DOI PMC

Proença MA, Biselli JM, Succi M, Severino FE, Berardinelli GN, Caetano A, Reis RM, Hughes DJ, Silva AE. 2018. Relationship between Fusobacterium nucleatum, inflammatory mediators and microRNAs in colorectal carcinogenesis. World J Gastroenterol 24:5351–5365. doi:10.3748/wjg.v24.i47.5351. PubMed DOI PMC

Yang Y, Weng W, Peng J, Hong L, Yang L, Toiyama Y, Gao R, Liu M, Yin M, Pan C, Li H, Guo B, Zhu Q, Wei Q, Moyer M-P, Wang P, Cai S, Goel A, Qin H, Ma Y. 2017. Fusobacterium nucleatum increases proliferation of colorectal cancer cells and tumor development in mice by activating Toll-like receptor 4 signaling to nuclear factor-κB, and up-regulating expression of microRNA-21. Gastroenterology 152:851–866.e24. doi:10.1053/j.gastro.2016.11.018. PubMed DOI PMC

Mjelle R, Sjursen W, Thommesen L, Sætrom P, Hofsli E. 2019. Small RNA expression from viruses, bacteria and human miRNAs in colon cancer tissue and its association with microsatellite instability and tumor location. BMC Cancer 19:161. doi:10.1186/s12885-019-5330-0. PubMed DOI PMC

Dutcher HA, Raghavan R. 2018. Origin, evolution, and loss of bacterial small RNAs. Microbiol Spectr 6(2). doi:10.1128/microbiolspec.RWR-0004-2017. PubMed DOI PMC

Ahmed W, Hafeez MA, Mahmood S. 2018. Identification and functional characterization of bacterial small non-coding RNAs and their target: a review. Gene Rep 10:167–176. doi:10.1016/j.genrep.2018.01.001. DOI

Nitzan M, Rehani R, Margalit H. 2017. Integration of bacterial small RNAs in regulatory networks. Annu Rev Biophys 46:131–148. doi:10.1146/annurev-biophys-070816-034058. PubMed DOI

Strong MJ, Xu G, Morici L, Splinter Bon-Durant S, Baddoo M, Lin Z, Fewell C, Taylor CM, Flemington EK. 2014. Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples. PLoS Pathog 10:e1004437. doi:10.1371/journal.ppat.1004437. PubMed DOI PMC

Mangul S, Yang HT, Strauli N, Gruhl F, Porath HT, Hsieh K, Chen L, Daley T, Christenson S, Wesolowska-Andersen A, Spreafico R, Rios C, Eng C, Smith AD, Hernandez RD, Ophoff RA, Santana JR, Levanon EY, Woodruff PG, Burchard E, Seibold MA, Shifman S, Eskin E, Zaitlen N. 2018. ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues. Genome Biol 19:36. doi:10.1186/s13059-018-1403-7. PubMed DOI PMC

Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. 2017. Shotgun metagenomics, from sampling to analysis. Nat Biotechnol 35:833–844. doi:10.1038/nbt.3935. PubMed DOI

Ferrero G, Cordero F, Tarallo S, Arigoni M, Riccardo F, Gallo G, Ronco G, Allasia M, Kulkarni N, Matullo G, Vineis P, Calogero RA, Pardini B, Naccarati A. 2018. Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species. Oncotarget 9:3097–3111. doi:10.18632/oncotarget.23203. PubMed DOI PMC

Kulkarni N, Alessandrì L, Panero R, Arigoni M, Olivero M, Ferrero G, Cordero F, Beccuti M, Calogero RA. 2018. Reproducible bioinformatics project: a community for reproducible bioinformatics analysis pipelines. BMC Bioinformatics 19:349. doi:10.1186/s12859-018-2296-x. PubMed DOI PMC

Katz L, Burge CB. 2003. Widespread selection for local RNA secondary structure in coding regions of bacterial genes. Genome Res 13:2042–2051. doi:10.1101/gr.1257503. PubMed DOI PMC

Li L, Huang D, Cheung MK, Nong W, Huang Q, Kwan HS. 2013. BSRD: a repository for bacterial small regulatory RNA. Nucleic Acids Res 41:D233–D238. doi:10.1093/nar/gks1264. PubMed DOI PMC

Backes C, Kehl T, Stöckel D, Fehlmann T, Schneider L, Meese E, Lenhof H-P, Keller A. 2017. miRPathDB: a new dictionary on microRNAs and target pathways. Nucleic Acids Res 45:D90–D96. doi:10.1093/nar/gkw926. PubMed DOI PMC

Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ, von Mering C. 2019. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 47:D607–D613. doi:10.1093/nar/gky1131. PubMed DOI PMC

Santoru ML, Piras C, Murgia A, Palmas V, Camboni T, Liggi S, Ibba I, Lai MA, Orrù S, Blois S, Loizedda AL, Griffin JL, Usai P, Caboni P, Atzori L, Manzin A. 2017. Cross sectional evaluation of the gut-microbiome metabolome axis in an Italian cohort of IBD patients. Sci Rep 7:9523. doi:10.1038/s41598-017-10034-5. PubMed DOI PMC

Zeller G, Tap J, Voigt AY, Sunagawa S, Kultima JR, Costea PI, Amiot A, Böhm J, Brunetti F, Habermann N, Hercog R, Koch M, Luciani A, Mende DR, Schneider MA, Schrotz-King P, Tournigand C, Tran Van Nhieu J, Yamada T, Zimmermann J, Benes V, Kloor M, Ulrich CM, von Knebel Doeberitz M, Sobhani I, Bork P. 2014. Potential of fecal microbiota for early-stage detection of colorectal cancer. Mol Syst Biol 10:766. doi:10.15252/msb.20145645. PubMed DOI PMC

Dai Z, Coker OO, Nakatsu G, Wu WKK, Zhao L, Chen Z, Chan FKL, Kristiansen K, Sung JJY, Wong SH, Yu J. 2018. Multi-cohort analysis of colorectal cancer metagenome identified altered bacteria across populations and universal bacterial markers. Microbiome 6:70. doi:10.1186/s40168-018-0451-2. PubMed DOI PMC

Wassenaar TM. 2018. E. coli and colorectal cancer: a complex relationship that deserves a critical mindset. Crit Rev Microbiol 44:619–632. doi:10.1080/1040841X.2018.1481013. PubMed DOI

Sears CL, Garrett WS. 2014. Microbes, microbiota, and colon cancer. Cell Host Microbe 15:317–328. doi:10.1016/j.chom.2014.02.007. PubMed DOI PMC

Ambrosi C, Sarshar M, Aprea MR, Pompilio A, Di Bonaventura G, Strati F, Pronio A, Nicoletti M, Zagaglia C, Palamara AT, Scribano D. 2019. Colonic adenoma-associated Escherichia coli express specific phenotypes. Microbes Infect 2019:S1286-4579(19)30008-5. doi:10.1016/j.micinf.2019.02.001. PubMed DOI

Vogtmann E, Hua X, Zeller G, Sunagawa S, Voigt AY, Hercog R, Goedert JJ, Shi J, Bork P, Sinha R. 2016. Colorectal cancer and the human gut microbiome: reproducibility with whole-genome shotgun sequencing. PLoS One 11:e0155362. doi:10.1371/journal.pone.0155362. PubMed DOI PMC

Cavanagh AT, Wassarman KM. 2014. 6S RNA, a global regulator of transcription in Escherichia coli, Bacillus subtilis, and beyond. Annu Rev Microbiol 68:45–60. doi:10.1146/annurev-micro-092611-150135. PubMed DOI

Bak G, Lee J, Suk S, Kim D, Young Lee J, Kim K-S, Choi B-S, Lee Y. 2015. Identification of novel sRNAs involved in biofilm formation, motility, and fimbriae formation in Escherichia coli. Sci Rep 5:15287. doi:10.1038/srep15287. PubMed DOI PMC

Luirink J, Dobberstein B. 1994. Mammalian and Escherichia coli signal recognition particles. Mol Microbiol 11:9–13. doi:10.1111/j.1365-2958.1994.tb00284.x. PubMed DOI

Boysen A, Møller-Jensen J, Kallipolitis B, Valentin-Hansen P, Overgaard M. 2010. Translational regulation of gene expression by an anaerobically induced small non-coding RNA in Escherichia coli. J Biol Chem 285:10690–10702. doi:10.1074/jbc.M109.089755. PubMed DOI PMC

Clements A, Young JC, Constantinou N, Frankel G. 2012. Infection strategies of enteric pathogenic Escherichia coli. Gut Microbes 3:71–87. doi:10.4161/gmic.19182. PubMed DOI PMC

Prokhorenko I, Zubova S, Kabanov D, Voloshina E, Grachev S. 2012. Toll-like receptor 4 in phagocytosis of Escherichia coli by endotoxin-activated human neutrophils in whole blood. Crit Care 16:P80. doi:10.1186/cc11767. DOI

Agramonte-Hevia J, González-Arenas A, Barrera D, Velasco-Velázquez M. 2002. Gram-negative bacteria and phagocytic cell interaction mediated by complement receptor 3. FEMS Immunol Med Microbiol 34:255–266. doi:10.1111/j.1574-695X.2002.tb00640.x. PubMed DOI

Miller SI, Ernst RK, Bader MW. 2005. LPS, TLR4 and infectious disease diversity. Nat Rev Microbiol 3:36–46. doi:10.1038/nrmicro1068. PubMed DOI

Neal MD, Leaphart C, Levy R, Prince J, Billiar TR, Watkins S, Li J, Cetin S, Ford H, Schreiber A, Hackam DJ. 2006. Enterocyte TLR4 mediates phagocytosis and translocation of bacteria across the intestinal barrier. J Immunol 176:3070–3079. doi:10.4049/jimmunol.176.5.3070. PubMed DOI

Wu Z, Qin W, Wu S, Zhu G, Bao W, Wu S. 2016. Identification of microRNAs regulating Escherichia coli F18 infection in Meishan weaned piglets. Biol Direct 11:59. doi:10.1186/s13062-016-0160-3. PubMed DOI PMC

Luoreng Z-M, Wang X-P, Mei C-G, Zan L-S. 2018. Expression profiling of peripheral blood miRNA using RNAseq technology in dairy cows with Escherichia coli-induced mastitis. Sci Rep 8:12693. doi:10.1038/s41598-018-30518-2. PubMed DOI PMC

Nguyen HTT, Dalmasso G, Müller S, Carrière J, Seibold F, Darfeuille–Michaud A. 2014. Crohn’s disease-associated adherent invasive Escherichia coli modulate levels of microRNAs in intestinal epithelial cells to reduce autophagy. Gastroenterology 146:508–519. doi:10.1053/j.gastro.2013.10.021. PubMed DOI

Guo Z, Cai X, Guo X, Xu Y, Gong J, Li Y, Zhu W. 2018. Let-7b ameliorates Crohn’s disease-associated adherent-invasive E coli induced intestinal inflammation via modulating Toll-like receptor 4 expression in intestinal epithelial cells. Biochem Pharmacol 156:196–203. doi:10.1016/j.bcp.2018.08.029. PubMed DOI

Maudet C, Mano M, Eulalio A. 2014. MicroRNAs in the interaction between host and bacterial pathogens. FEBS Lett 588:4140–4147. doi:10.1016/j.febslet.2014.08.002. PubMed DOI

Hsieh C-H, Rau C-S, Jeng J, Chen Y-C, Lu T-H, Wu C-J, Wu Y-C, Tzeng S-L, Yang J. 2012. Whole blood-derived microRNA signatures in mice exposed to lipopolysaccharides. J Biomed Sci 19:69. doi:10.1186/1423-0127-19-69. PubMed DOI PMC

Gagnière J, Bonnin V, Jarrousse A-S, Cardamone E, Agus A, Uhrhammer N, Sauvanet P, Déchelotte P, Barnich N, Bonnet R, Pezet D, Bonnet M. 2017. Interactions between microsatellite instability and human gut colonization by Escherichia coli in colorectal cancer. Clin Sci (Lond) 131:471–485. doi:10.1042/CS20160876. PubMed DOI

Wilson MR, Jiang Y, Villalta PW, Stornetta A, Boudreau PD, Carrá A, Brennan CA, Chun E, Ngo L, Samson LD, Engelward BP, Garrett WS, Balbo S, Balskus EP. 2019. The human gut bacterial genotoxin colibactin alkylates DNA. Science 363:eaar7785. doi:10.1126/science.aar7785. PubMed DOI PMC

Faïs T, Delmas J, Barnich N, Bonnet R, Dalmasso G. 2018. Colibactin: more than a new bacterial toxin. Toxins 10:151. doi:10.3390/toxins10040151. PubMed DOI PMC

Janssens Y, Nielandt J, Bronselaer A, Debunne N, Verbeke F, Wynendaele E, Van Immerseel F, Vandewynckel Y-P, De Tré G, De Spiegeleer B. 2018. Disbiome database: linking the microbiome to disease. BMC Microbiol 18:50. doi:10.1186/s12866-018-1197-5. PubMed DOI PMC

Sridhar J, Gunasekaran P. 2013. Computational small RNA prediction in bacteria. Bioinform Biol Insights 7:83–95. doi:10.4137/BBI.S11213. PubMed DOI PMC

Hör J, Gorski SA, Vogel J. 2018. Bacterial RNA biology on a genome scale. Mol Cell 70:785–799. doi:10.1016/j.molcel.2017.12.023. PubMed DOI

Guthrie L, Gupta S, Daily J, Kelly L. 2017. Human microbiome signatures of differential colorectal cancer drug metabolism. NPJ Biofilms Microbiomes 3:27. doi:10.1038/s41522-017-0034-1. PubMed DOI PMC

Zitvogel L, Ma Y, Raoult D, Kroemer G, Gajewski TF. 2018. The microbiome in cancer immunotherapy: diagnostic tools and therapeutic strategies. Science 359:1366–1370. doi:10.1126/science.aar6918. PubMed DOI

Martin M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10. doi:10.14806/ej.17.1.200. DOI

Kozomara A, Griffiths-Jones S. 2014. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73. doi:10.1093/nar/gkt1181. PubMed DOI PMC

Zhang P, Si X, Skogerbø G, Wang J, Cui D, Li Y, Sun X, Liu L, Sun B, Chen R, He S, Huang D-W. 2014. piRBase: a web resource assisting piRNA functional study. Database (Oxford) 2014:bau110. doi:10.1093/database/bau110. PubMed DOI PMC

Leung YY, Kuksa PP, Amlie-Wolf A, Valladares O, Ungar LH, Kannan S, Gregory BD, Wang L-S. 2016. DASHR: database of small human noncoding RNAs. Nucleic Acids Res 44:D216–D222. doi:10.1093/nar/gkv1188. PubMed DOI PMC

Li H, Durbin R. 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. doi:10.1093/bioinformatics/btp324. PubMed DOI PMC

Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550. doi:10.1186/s13059-014-0550-8. PubMed DOI PMC

Xie B, Ding Q, Han H, Wu D. 2013. miRCancer: a microRNA-cancer association database constructed by text mining on literature. Bioinformatics 29:638–644. doi:10.1093/bioinformatics/btt014. PubMed DOI

Wood DE, Salzberg SL. 2014. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 15:R46. doi:10.1186/gb-2014-15-3-r46. PubMed DOI PMC

The RNAcentral Consortium. 2019. RNAcentral: a hub of information for non-coding RNA sequences. Nucleic Acids Res 47:D1250–D1251. doi:10.1093/nar/gky1206. PubMed DOI PMC

Lorenz R, Bernhart SH, zu Siederdissen CH, Tafer H, Flamm C, Stadler PF, Hofacker IL. 2011. ViennaRNA package 2.0. Algorithms Mol Biol 6:26. doi:10.1186/1748-7188-6-26. PubMed DOI PMC

Bonnal RJP, Rossi RL, Carpi D, Ranzani V, Abrignani S, Pagani M. 2015. miRiadne: a web tool for consistent integration of miRNA nomenclature. Nucleic Acids Res 43:W487–W492. doi:10.1093/nar/gkv381. PubMed DOI PMC

Mjelle R, Sjursen W, Thommesen L, Sætrom P, Hofsli E. 2019. Small RNA expression from viruses, bacteria and human miRNAs in colon cancer tissue and its association with microsatellite instability and tumor location. BMC Cancer 19:161. doi:10.1186/s12885-019-5330-0. PubMed DOI PMC

Neerincx M, Sie DL, van de Wiel MA, van Grieken NC, Burggraaf JD, Dekker H, Eijk PP, Ylstra B, Verhoef C, Meijer GA, Buffart TE, Verheul HM. 2015. MiR expression profiles of paired primary colorectal cancer and metastases by next-generation sequencing. Oncogene 4:e170. doi:10.1038/oncsis.2015.29. PubMed DOI PMC

Sun G, Cheng YW, Lai L, Huang TC, Wang J, Wu X, Wang Y, Huang Y, Wang J, Zhang K, Hu S, Yang JR, Yen Y. 2016. Signature miRNAs in colorectal cancers were revealed using a bias reduction small RNA deep sequencing protocol. Oncotarget 7:3857–3872. doi:10.18632/oncotarget.6460. PubMed DOI PMC

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