Gut microbiome in colorectal cancer, Shanghai, case-control
200 gut microbiome samples from Shanghai, China, comprising 100 colorectal cancer cases and 100 healthy controls, analyzed in a case-control study design. machine-written summary
200 samples · 200 runs · CN · Adult · 2021 · 10.47 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 1,400 sample values (collection date, country, health condition, health condition detail, latitude, location region, longitude) |
| ○ Abstract / description | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC10408458, PMC10436198, PMC11035630, PMC11402190, PMC11409688, PMC11508446, PMC11681701, PMC12090783, PMC13383993, PMC8604900 |
| ○ Supplementary tables | files read; no table could be matched to the samples |
| ✓ External resources | 200 sample values (antibiotic exposure) · from BugSigDB |
| – User contribution | nothing uploaded yet · share metadata |
| – Human verified | not yet checked by a person · I checked this project — verify it |
Genera, mean relative abundance over 188 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 0 | 0% | ||||
| country | 200 | 100% | 200 | |||
| health_condition | 200 | 100% | 200 | |||
| subject_id | 0 | 0% | ||||
| antibiotic_exposure | 200 | 100% | 200 | |||
| collection_date | 200 | 100% | 200 | |||
| detailed_location | 200 | 100% | ||||
| health_condition_detail | 200 | 100% | 200 | |||
| latitude | 200 | 100% | 200 | |||
| location_region | 200 | 100% | 200 | |||
| longitude | 200 | 100% | 200 |
- Dysbiosis of human gut microbiome in young-onset colorectal cancer. 2021 PMID 34799562 PMC8604900 own_data
- An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur. 2023 PMID 37560524 PMC10408458 own_data
- Consistent signatures in the human gut microbiome of old- and young-onset colorectal cancer. 2024 PMID 38649355 PMC11035630 own_data
- Improved diagnostic efficiency of CRC subgroups revealed using machine learning based on intestinal microbes. 2024 PMID 39289618 PMC11409688 own_data
- Inflammation, Gut Microbiota, and Metabolomic Shifts in Colorectal Cancer: Insights from Human and Mouse Models. 2024 PMID 39456970 PMC11508446 own_data
14 more
- Distinct microbes, metabolites, and the host genome define the multi-omics profiles in right-sided and left-sided colon cancer. 2024 PMID 39731152 PMC11681701
- Meta-analysis of fecal viromes demonstrates high diagnostic potential of the gut viral signatures for colorectal cancer and adenoma risk assessment. 2023 PMID 36198381 PMC10334131
- Metagenomic analysis reveals gut plasmids as diagnosis markers for colorectal cancer. 2023 PMID 37283932 PMC10239823
- Taxonomic and functional profiling of fecal metagenomes for the early detection of colorectal cancer. 2023 PMID 37601681 PMC10436198
- Machine learning approaches in microbiome research: challenges and best practices. 2023 PMID 37808286 PMC10556866
- Gut bacterial type III secretion systems aggravate colitis in mice and serve as biomarkers of Crohn's disease. 2024 PMID 39216231 PMC11402190
- The physical biogeography of <i>Fusobacterium nucleatum</i> in health and disease. 2025 PMID 40062772 PMC11980382
- Temporal network analysis of gut microbiota unveils aging trajectories associated with colon cancer. 2025 PMID 40298386 PMC12090783
- Pooled analysis of 3,741 stool metagenomes from 18 cohorts for cross-stage and strain-level reproducible microbial biomarkers of colorectal cancer. 2025 PMID 40461820 PMC12283368
- Distinct prophage infections in colorectal cancer-associated Bacteroides fragilis. 2026 PMID 41654659 PMC12992544
- CroCoDeEL: accurate control-free detection of cross-sample contamination in metagenomic data. 2026 PMID 42103726 PMC13377033
- Instance-based transfer learning enables cross-cohort early detection of colorectal cancer. 2026 PMID 42106361 PMC13381771
- Gut fungal signatures in colorectal cancer and their potential for supporting diagnosis: a multi-cohort metagenomic analysis. 2026 PMID 42271362 PMC13281578
- Metagenome analysis reveals multi-kingdom gut microbiota as diagnostic markers for colorectal cancer. 2026 PMID 42519695 PMC13383993
Archive description
Our study comprehensively characterizes the association between gut microbiome dysbiosis and CRC risks in young or elderly groups, and highlights the great potential of gut microbiota biomarkers as a promising non-invasive tool in accurate detection and distinction of CRC onset based on age.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult and elderly by deterministic_prior with confidence 0.90. Assay shotgun_dna.
- host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- body site study.title · “Dysbiosis of human gut microbiome in young-onset”
- body site study.description · “the association between gut microbiome dysbiosis and”
- life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- life stage study.description · “in young or elderly groups, and highlights”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN21877043 | antibiotic_exposure | no | R2 | 0.60 | external.bugsigdb source | Antibiotics exclusion: 1 month |
| SAMN21877043 | collection_date | 2018-01-01 | R1 | 0.90 | biosample.attribute:collection_date | 2018-01-01 |
| SAMN21877043 | country | CN | R1 | 0.90 | sample.attr.geo_loc_name | China:Shanghai |
| SAMN21877043 | health_condition | healthy_control | R1 | 0.70 | sample.name_rule:library_names | M_HO_01 |
| SAMN21877043 | health_condition_detail | Healthy, Old (elderly healthy control) | R1 | 0.70 | sample.name_rule:library_names | M_HO_01 |
| SAMN21877043 | latitude | 31.0000 | R1 | 0.90 | biosample.attribute:lat_lon | 31 N 121 E |
| SAMN21877043 | location_region | Shanghai | R1 | 0.85 | biosample.attribute:geo_loc_name | China:Shanghai |
| SAMN21877043 | longitude | 121.0000 | R1 | 0.90 | biosample.attribute:lat_lon | 31 N 121 E |
Sequencing
200 runs over 200 samples · mean 10.74 Gbp per run (median 10.47 Gbp, total 2,147.85 Gbp; 200 runs with a base count) · layout PAIRED 200 · platform ILLUMINA 200 · models Illumina NovaSeq 6000 (200) · 94% of runs with a Sandpiper profile · first public 2021-10-26 – 2021-10-27
Authors (65)
Liu G first · Su L · Kong C · Huang L · Zhu X · Zhang X · Ma Y · Wang J last · Chen Z first · Zhang Z · Nie BN · Huang W · Zhu Y · Zhang L · Xu M · Wang M · Yuan C · Liu N · Wang X · Tian J · Ba Q · Wang Z last · Damgaard F first · Jespersen MG · Møller JK · Coia JE · Dessau RB · Sydenham TV · Strube ML · Møller-Jensen J · Justesen US last · Huang S first · Chaudhari DS · Shukla R · Kanani P · Zeidan RS · Lin Y · Burrow W · Mankowski RT · Jain S · Yadav H last · Goulet L first · Plaza Oñate F · Famechon A · Quinquis B · Belda E · Prifti E · Le Chatelier E · Gautreau G last · Lu T · Dong B · Liu J · Zhang Y · Li S · Liu H · Li X · Guan T · Guo H · Yan Q · Lei Z · Yu X · Wang L · Kang J · Li L · Zhao D last
Help complete this project
2 of the 4 core fields are below 50% coverage: age_category, subject_id. Share metadata
Downloads
PRJNA763023.csv.gz (5.7 KB) · parquet (77.4 KB) — all 200 samples, every field with route and confidence · PRJNA763023_determinations.csv.gz (10.5 KB) — 1,600 evidence rows