--- title: "Applications & Cases" lang: ko url: https://www.gereallife.com/ko/services/resources-cases.html canonical: https://www.gereallife.com/ko/services/resources-cases.html entity: Shanghai Gereallife Biotech Co., Ltd updated: 2026-11-02 --- ## 01Application Areas Multi-omics technologies are widely applied across the core fields of life-science and medical research Cancer Research metabolic reprogramming, tumor biomarkers, drug-resistance mechanisms Plant Science stress responses, metabolic pathways, quality improvement Microbiome gut microbiota, environmental microbes, host–microbiota interactions Clinical Medicine precision diagnosis, disease subtyping, drug-response prediction Drug R&D target discovery, efficacy evaluation, toxicity mechanisms ## 02Cancer-Research Case Studies Breakthrough applications of integrative multi-omics in tumor biology ### Metabolic Reprogramming in Liver Cancer Integrative proteomics and genomics revealed metabolic-reprogramming mechanisms in HBV-related hepatocellular carcinoma, identifying PYCR2 and ADH1A as potential prognostic biomarkers. Technical Approach paired tumor–adjacent tissues from 159 patients; integrated proteome + genome + transcriptome analysis Representative Publications Gao Q, Zhu H, Dong L, et al. (2019). Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma. Cell , 179(2): 561-577. DOI: 10.1016/j.cell.2019.08.052 ### Gut-Microbiome Biomarkers for Colorectal Cancer Fecal metagenomic sequencing identified non-invasive diagnostic biomarkers for colorectal cancer; the predictive model achieved an AUC of 0.84 , significantly outperforming conventional methods. Technical Approach multi-cohort fecal metagenomic discovery + independent qPCR validation Representative Publications Yu J, Feng Q, Wong SH, et al. (2017). Metagenomic analysis of faecal microbiome as a tool towards targeted non-invasive biomarkers for colorectal cancer. Gut , 66(1): 70-78. DOI: 10.1136/gutjnl-2015-309800 ## 03Plant-Science Case Studies Omics technologies advancing plant stress biology and metabolic-regulation research ### Salt Tolerance in Rice Transcriptomics salt tolerance comparative transcriptomics Comparative transcriptome analysis under salt stress revealed differential responses between salt-tolerant and salt-sensitive rice cultivars in proline accumulation, starch–sucrose metabolism and flavonoid biosynthesis, providing molecular targets for breeding salt-tolerant rice. Technical Approach salt-tolerant vs salt-sensitive cultivars, 4 time points (0/6/24/48 h), RNA-seq transcriptome analysis Representative Publications Fang X, Mo J, Zhou H, et al. (2023). Comparative transcriptome analysis of gene responses of salt-tolerant and salt-sensitive rice cultivars to salt stress. Scientific Reports , 13: 19089. DOI: 10.1038/s41598-023-46389-1 ### Active Ingredients in Medicinal Plants transcription factor artemisinin glandular-trichome development The AP2 transcription factor TAR1 was found to regulate glandular-trichome development and artemisinin biosynthesis in Artemisia annua by directly targeting the key enzyme genes ADS and CYP71AV1, providing targets for genetic engineering of high-yield artemisinin production. Research Significance key regulatory genes for artemisinin metabolic engineering and synthetic biology Representative Publications Tan H, Xiao L, Gao S, et al. (2015). TRICHOME AND ARTEMISININ REGULATOR 1 Is Required for Trichome Development and Artemisinin Biosynthesis in Artemisia annua. Molecular Plant , 8(9): 1396-1411. DOI: 10.1016/j.molp.2015.04.002 ## 04Microbiome Case Studies Combined metagenomics and metabolomics resolving microbial-community functions ### Gut Microbiota & Metabolic Health metagenomics gut microbiota probiotic intervention A metagenome-wide association study of gut microbiota in 345 Chinese subjects found significantly reduced butyrate-producing bacteria and increased opportunistic pathogens in type-2 diabetes patients, revealing the key role of gut dysbiosis in metabolic disease. Application Value precision probiotic formulation and personalized dietary intervention Representative Publications Qin J, Li Y, Cai Z, et al. (2012). A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature , 490: 55-60. DOI: 10.1038/nature11450 ### Soil Microbial-Community Function metagenomics petroleum degradation environmental remediation Metagenomic analysis of petroleum-degradation functional genes in microbial communities across three oilfield soils identified Proteobacteria and Actinobacteria as the dominant degraders, revealed the impact of oil contamination on nitrogen-cycle genes, and provided key microbial resources for bioremediation strategies. Application Value development of microbial degrader agents for oil-contaminated soils and ecological restoration Representative Publications Liu Q, He W, Zhang W, et al. (2024). Metagenomic analysis reveals the microbial response to petroleum contamination in oilfield soils. Science of The Total Environment , 912: 168972. DOI: 10.1016/j.scitotenv.2023.168972 ## 05Clinical-Medicine Applications Multi-omics has demonstrated enormous clinical potential in precision medicine | Application | Omics strategy | Sample type | Clinical value | | --- | --- | --- | --- | | Early cancer screening | plasma metabolome + ctDNA methylation | plasma | non-invasive early detection | | Disease subtyping | transcriptome + proteome | tissue / blood | precise subtype classification | | Drug-response prediction | genome + metabolome | blood / tissue | personalized medication plans | | Prognosis assessment | multi-omics integrative scoring | tissue | recurrence-risk prediction | | Rare-disease diagnosis | whole genome + transcriptome | blood | definitive molecular etiology | ## 06Representative Publications in Clinical Medicine Multi-omics technologies are moving precision medicine from concept to clinic Early cancer screening Nakatsu G, et al. (2015). Gut mucosal microbiome across stages of colorectal carcinogenesis. Nature Communications , 6: 8727. DOI: 10.1038/ncomms9727 Disease subtyping TCGA (2012). Comprehensive molecular portraits of human breast tumours. Nature , 490: 61. DOI: 10.1038/nature11412 Drug-response prediction Haslam A, Prasad V. (2019). Estimation of the Percentage of US Patients With Cancer Who Are Eligible for and Respond to Checkpoint Inhibitor Immunotherapy Drugs. JAMA Network Open , 2(5): e192535. DOI: 10.1001/jamanetworkopen.2019.2535 Prognosis assessment Shen R, Mo Q, Schultz N, et al. (2012). Integrative subtype discovery in glioblastoma using iCluster. PLoS ONE , 7(4): e35236. DOI: 10.1371/journal.pone.0035236 Rare-disease diagnosis Wojcik MH, et al. (2024). Genome Sequencing for Diagnosing Rare Diseases. New England Journal of Medicine , 390(21): 1985-1997. DOI: 10.1056/NEJMoa2314761 ## Q&AFAQ Has multi-omics been used to find prognostic markers in liver cancer? Yes. In HBV-related hepatocellular carcinoma, integrated proteomics and genomics revealed metabolic-reprogramming mechanisms and identified PYCR2 and ADH1A as potential prognostic biomarkers. Could a stool test replace invasive screening for colorectal cancer? Fecal metagenomic sequencing identified non-invasive diagnostic biomarkers for colorectal cancer, and the predictive model reached an AUC of 0.84, significantly outperforming conventional methods. How would I design a salt-stress transcriptome study in rice? Compare salt-tolerant and salt-sensitive cultivars at 4 time points (0/6/24/48 h) using RNA-seq; the comparative analysis revealed differential responses in proline accumulation, starch–sucrose metabolism and flavonoid biosynthesis. What has gut-microbiome sequencing shown in people with type 2 diabetes? A metagenome-wide association study of 345 Chinese subjects found significantly reduced butyrate-producing bacteria and increased opportunistic pathogens in type-2 diabetes patients, revealing the key role of gut dysbiosis in metabolic disease. For early cancer screening, is a blood draw enough instead of a tissue sample? Yes. In early cancer screening the omics strategy is plasma metabolome plus ctDNA methylation, the sample type is plasma, and the clinical value is non-invasive early detection. Need study design? Free study design and sample assessment, response within 1 hour. Contact the team → Call us： 400-660-8826 Scan to chat on WeChat