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Meta-Analysis
Copyright: ©Author(s) 2027.
World J Gastroenterol. Jan 7, 2027; 33(1): 124236
Published online Jan 7, 2027. doi: 10.3748/wjg.124236
Table 1 Quality evaluation using AMSTAR 2 (a measurement tool to assess systematic reviews)
Ref.
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Q9
Q10
Q11
Q12
Q13
Q14
Q15
Q16
Jiang et al[21]YYYYPYPYYYYYYPYPYPYYY
Jin et al[18]YYYYPYPYYYYYYPYYYYY
Thomas et al[10]YYYPYNNYYYYYPYYYYY
Liu et al[11]YYYNNNYYYYYPYYYYY
Kharofa et al[13]YYYPYPYPYYYYYYPYYYYY
Li et al[12]YYYPYPYPYYYYYYPYYYYY
Lin et al[19]YYYYPYPYYYYYYPYYYYY
Wirbel et al[20]YYYYPYPYYYYYYPYYYYY
Piccinno et al[15]YYPYPYPYPYYYYYYPYPYYYY
Zhu et al[17]YYPYPYPYPYYYYYYPYPYYYY
Chen et al[16]YYPYPYPYPYYYYYYPYPYYYY
Table 2 Characteristics of the included studies (n = 11)
Ref.
First author
Journal and year
k meta
CRC cases (n)
Controls (n)
Country
Objective of study
Outcome
Liu et al[11]Ning-Ning LiuNature Microbiology, 20225491494Austria, France, Germany, China, Japan, Italy, and United StatesTo analyze multi-kingdom gut microbiome alterations in CRC and identify reproducible diagnostic biomarkersCRC showed multi-kingdom dysbiosis, with 16 validated biomarkers and altered D-amino acid and butanoate metabolism
Li et al[12]Tian-Hui LiGastroenterology, 202511738896China, Austria, United States, Italy, Japan, Germany, and FranceTo characterize CRC-associated gut archaea and assess their interactions with bacterial communitiesCRC showed reduced archaeal diversity, altered methanogenesis-related taxa, and improved diagnostic performance in combined archaea-bacteria models
Jiang et al[21]Pu-Zi JiangmSystems, 20217354357Japan, China, United States, Germany, France, Australia, and ItalyTo identify shared and disease-specific microbial signatures across CD (Crohn’s disease), UC (ulcerative colitis), and CRCSpecies- and pathway-level biomarkers were identified, with UC and CRC showing greater microbial similarity and strong diagnostic potential
Jin et al[18]Dong-Min JinmSystems, 20243 (CRC only)141141Germany, Austria, and FranceTo develop an interpretable meta-analysis workflow for comparing microbiome features across diseasesDisease pairs showed varying microbiome similarities, reflecting both pathogen enrichment and depletion of beneficial microbes
Lin et al[19]Yu-Feng LinGastroenterology, 20228454525Canada, United States, Germany, France, Italy, China, Japan, and AustraliaTo investigate CRC-associated gut mycobiota and evaluate fungal biomarkers for diagnosisCRC showed fungal dysbiosis, and fungal-bacterial biomarkers improved diagnostic performance over bacterial markers alone
Wirbel et al[20]Jakob WirbelNature Medicine, 20198386392France, Austria, China, United States, Germany, Italy, and JapanTo identify robust taxonomic and functional microbial signatures of CRC across heterogeneous cohortsCRC was associated with 29 core enriched species, increased protein and mucin degradation, and elevated secondary bile acid production
Kharofa et al[13]Jordan KharofaCancer Medicine, 202311692609Austria, Canada, China, Germany, France, India, Italy, Japan, and United StatesTo compare microbial features between early-onset and late-onset CRC, including virulence factorsEarly-onset CRC showed distinct microbial and virulence profiles, including associations with colibactin, Fusobacterium adhesin A, and Fusobacterium nucleatum
Thomas et al[10]Andrew Maltez ThomasNature Medicine, 20197313308Austria, France, Germany, Italy, Denmark, United States, China, and JapanTo identify reproducible CRC-associated biomarkers and explore related functional mechanismsCRC showed increased microbial richness, reproducible markers such as Fusobacterium nucleatum, and altered amino acid, gluconeogenesis, and choline metabolism
Piccinno et al[15]Gianmarco PiccinnoNature Medicine, 20251814711568Austria, China, Czech Republic, France, Germany, India, Italy, Japan, Spain, Turkey, and United StatesTo examine gut microbiome changes across adenoma-carcinoma progression, CRC stage, and tumor locationCRC microbiomes were enriched with oral taxa, and cross-cohort classifiers showed strong predictive performance with reproducible species- and strain-level markers
Zhu et al[17]Xin-Yue ZhuCommunications Biology, 20248485496Austria, China, France, Germany, Italy, and United StatesTo compare multi-kingdom microbial signatures between excess body weight CRC (EBW-CRC) and lean CRCEBW-CRC and lean-CRC showed distinct microbial and functional patterns, with the EBW-CRC classifier achieving strong validation performance
Chen et al[16]Fang ChenJournal of Advanced Research, 20239554546France, China, Austria, United States, Canada, Italy, Germany, and JapanTo identify reproducible gut virome signatures in CRC and adenoma and assess their diagnostic potentialCRC and adenoma showed altered viral profiles, and viral biomarkers demonstrated diagnostic potential across cohorts
Table 3 Characteristics of the included studies (n = 6)
Ref.
Country
Design
Population
N, P/C
Intervention
Dose
Duration/sampling
Age, P/C
Sex, M/F, P/C
BMI, P/C
Rafter et al[22]IrelandRCT, double-blind, placebo-controlled; single-centerPostoperative colon cancer patients within 5 years of resection37, 19/18Bifidobacterium lactis Bb12 + Lactobacillus rhamnosus GG + inulinSynbiotic 1 12 g/day; 1010 CFU/day12 weeks; baseline, weeks 6, weeks 1261.1 ± 5.55/57.0 ± 9.75Reported values need checkingNR/NR
Park et al[26]South KoreaRCT, double-blind, placebo-controlled; multicenterColon cancer patients undergoing anterior resection; perioperative intervention60, 29/31Bifidobacterium animalis subsp. lactis HY8002 + Lactiplantibacillus casei HY2782 + Lactiplantibacillus plantarum HY77122 g bid; 2 × 108 CFU/day total4 weeks + 1-week follow-up; baseline, pre-op, 3 weeks post-op, 4 weeks post-op60.10 ± 10.37/61.03 ± 7.0213/18, 13/18, check P group24.42 ± 2.90/24.04 ± 3.53
Wang et al[27]ChinaRetrospective cohort; single-centerAdvanced CRC with malnutrition; receiving chemotherapy or radiotherapy ± targeted therapy80, 40/40Streptococcus thermophilus acidophilus NCFM + Bifidobacterium lactis Bi-07 + Streptococcus thermophilus St-21 + mixed fiber2 × 109 CFU/day + fiber 20 g/day12 weeks; baseline, weeks 1264.75 ± 6.22/63.94 ± 5.6319/21, 23/1717.56 ± 1.04/17.47 ± 1.16
Hibberd et al[25]SwedenProspective randomized pilot study; single-centerStage I-III colon cancer patients; intervention after colonoscopy and before surgery15, 8/7Bifidobacterium lactis Bl-04 + Lactiplantibacillus acidophilus NCFM + inulin2 tablets/day; 2.1 × 1010 CFU/day total + inulin 0.63 gMean 31 ± 28 days; post-colonoscopy, pre-op77 ± 5.2/63 ± 13.3Reported values need checking24.1 ± 1.7/NR
Gianotti et al[23]ItalyRCT, double-blind, placebo-controlled, 3-arm; multicenterColon cancer patients undergoing elective colorectal resection; perioperative intervention31, 11 low-dose/10 high-dose/10 controlLactiplantibacillus johnsonii La1 + Bifidobacterium longum BB536Low: 2 × 107 CFU/day; high: 2 × 109 CFU/day; bid6 days; day - 4, day 0, day + 564.7 ± 4.8 low/62.7 ± 7.8 high/63.3 ± 10.2 controlReported values need checking26.5 ± 4.1 low/24.4 ± 3.7 high/25.6 ± 2.6 control
Liu et al[24]ChinaRCT, double-blind, placebo-controlled; single-centerCRC patients undergoing elective radical colorectomy; perioperative intervention100, 50/50Lactiplantibacillus plantarum CGMCC No.1258 + Lactiplantibacillus acidophilus LA-11 + Bifidobacterium longum BL-882 g/day; 2.6 × 1014 CFU/day total16 days; pre-trial, pre-op, post-op day 3, post-op day 1065.7 ± 9.9/65.3 ± 11.028/22, 31/1922.8 ± 1.8/22.6 ± 2.0
Table 4 17 microbial genera were significantly associated with colorectal cancer risk according to second-order meta-analysis (P ≤ 0.05, k ≥ 5)
Taxon
Outcome
k meta
Effects (n)
Pooled effect
CI low
CI high
P value
I2 value
τ2 value
QE test P value
ParvimonasCRC/control991.2270.092.3650.03499.9992.970
FusobacteriumCRC/control880.9170.1391.6960.02199.9991.1290
HungatellaCRC/control550.8850.4251.3461.62 × 10-491.9390.2482.76 × 10-10
AnaerococcusCRC/control550.7560.221.2920.00698.8160.3498.30 × 10-6
GemellaCRC/control880.6160.2870.9452.39 × 10-499.9980.220
ClostridiumCRC/control990.5080.1290.8880.0091000.3270
PrevotellaCRC/control10100.4290.1610.6970.00299.9990.1730
AnaerotruncusCRC/control770.4230.0460.80.02899.9970.250
ParabacteroidesCRC/control770.420.0410.7990.0399.9950.2570
DialisterCRC/control550.4010.0510.7510.02599.9960.1530
PeptostreptococcusCRC/control660.3980.270.5269.96 × 10-1081.6620.0147.06 × 10-4
MethanobrevibacterCRC/control550.3980.0420.7530.02896.7410.130
SlackiaCRC/control550.3930.0760.7090.01598.3020.1250
BilophilaCRC/control660.3840.0680.70.01797.3990.1470
BacteroidesCRC/control10100.3550.0920.6190.00899.9990.1760
AlistipesCRC/control990.3530.0490.6570.02399.9940.2060
StreptococcusCRC/control990.2960.0470.5450.0299.9970.1340


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