1. Di Sabatino A, Moschetta A, Conte D, Tiribelli C, Caprioli FA, et al. Translational Committee of the Italian Society of Gastroenterology. The impact of translational research on gastroenterology. Dig Liver Dis. 2014; 46(4):293–294. PMID:
24508099.
2. Zerhouni EA. Translational and clinical science--time for a new vision. N Engl J Med. 2005; 353(15):1621–1623. PMID:
16221788.
3. Woolf SH. The meaning of translational research and why it matters. JAMA. 2008; 299(2):211–213. PMID:
18182604.
4. Choi Y, Choi HS, Jeon WK, Kim BI, Park DI, Cho YK, et al. Optimal number of endoscopic biopsies in diagnosis of advanced gastric and colorectal cancer. J Korean Med Sci. 2012; 27(1):36–39. PMID:
22219611.
5. Ahn S, Ahn S, Van Vrancken M, Lee M, Ha SY, Lee H, et al. Ideal number of biopsy tumor fragments for predicting HER2 status in gastric carcinoma resection specimens. Oncotarget. 2015; 6(35):38372–38380. PMID:
26460823.
6. Xu C, Liu Y, Ge X, Jiang D, Zhang Y, Ji Y, et al. Tumor containing fragment number influences immunohistochemistry positive rate of HER2 in biopsy specimens of gastric cancer. Diagn Pathol. 2017; 12(1):41. PMID:
28549444.
7. Dreskin BW, Luu K, Dong TS, Benhammou J, Lagishetty V, Vu J, et al. Specimen collection and analysis of the duodenal microbiome. J Vis Exp. 2021; 167(167):61900.
8. O’Hara AM, Shanahan F. The gut flora as a forgotten organ. EMBO Rep. 2006; 7(7):688–693. PMID:
16819463.
9. Shanahan ER, Zhong L, Talley NJ, Morrison M, Holtmann G. Characterisation of the gastrointestinal mucosa-associated microbiota: a novel technique to prevent cross-contamination during endoscopic procedures. Aliment Pharmacol Ther. 2016; 43(11):1186–1196. PMID:
27086880.
10. Lim Y, Totsika M, Morrison M, Punyadeera C. The saliva microbiome profiles are minimally affected by collection method or DNA extraction protocols. Sci Rep. 2017; 7(1):8523. PMID:
28819242.
11. Ji Y, Liang X, Lu H. Analysis of by high-throughput sequencing: Helicobacter pylori infection and salivary microbiome. BMC Oral Health. 2020; 20(1):84. PMID:
32197614.
12. Luo T, Srinivasan U, Ramadugu K, Shedden KA, Neiswanger K, Trumble E, et al. Effects of specimen collection methodologies and storage conditions on the short-term stability of oral microbiome taxonomy. Appl Environ Microbiol. 2016; 82(18):5519–5529. PMID:
27371581.
13. Liu AQ, Vogtmann E, Shao DT, Abnet CC, Dou HY, Qin Y, et al. A comparison of biopsy and mucosal swab specimens for examining the microbiota of upper gastrointestinal carcinoma. Cancer Epidemiol Biomarkers Prev. 2019; 28(12):2030–2037. PMID:
31519703.
14. Glassing A, Dowd SE, Galandiuk S, Davis B, Chiodini RJ. Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples. Gut Pathog. 2016; 8(1):24. PMID:
27239228.
15. Peters RP, Mohammadi T, Vandenbroucke-Grauls CM, Danner SA, van Agtmael MA, Savelkoul PH. Detection of bacterial DNA in blood samples from febrile patients: underestimated infection or emerging contamination? FEMS Immunol Med Microbiol. 2004; 42(2):249–253. PMID:
15364111.
16. Lauder AP, Roche AM, Sherrill-Mix S, Bailey A, Laughlin AL, Bittinger K, et al. Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota. Microbiome. 2016; 4(1):29. PMID:
27338728.
17. Stinson LF, Keelan JA, Payne MS. Comparison of meconium DNA extraction methods for use in microbiome studies. Front Microbiol. 2018; 9:270. PMID:
29515550.
18. Drengenes C, Wiker HG, Kalananthan T, Nordeide E, Eagan TM, Nielsen R. Laboratory contamination in airway microbiome studies. BMC Microbiol. 2019; 19(1):187. PMID:
31412780.
19. Dahlberg J, Sun L, Persson Waller K, Östensson K, McGuire M, Agenäs S, et al. Microbiota data from low biomass milk samples is markedly affected by laboratory and reagent contamination. PLoS One. 2019; 14(6):e0218257. PMID:
31194836.
20. Kitchin PA, Szotyori Z, Fromholc C, Almond N. Avoidance of PCR false positives. Nature. 1990; 344(6263):201. PMID:
2156164.
21. Meadow JF, Altrichter AE, Bateman AC, Stenson J, Brown GZ, Green JL, et al. Humans differ in their personal microbial cloud. PeerJ. 2015; 3:e1258. PMID:
26417541.
22. Adams RI, Bateman AC, Bik HM, Meadow JF. Microbiota of the indoor environment: a meta-analysis. Microbiome. 2015; 3(1):49. PMID:
26459172.
23. Bittinger K, Charlson ES, Loy E, Shirley DJ, Haas AR, Laughlin A, et al. Improved characterization of medically relevant fungi in the human respiratory tract using next-generation sequencing. Genome Biol. 2014; 15(10):487. PMID:
25344286.
24. Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, et al. Bayesian community-wide culture-independent microbial source tracking. Nat Methods. 2011; 8(9):761–763. PMID:
21765408.
25. Jousselin E, Clamens AL, Galan M, Bernard M, Maman S, Gschloessl B, et al. Assessment of a 16S rRNA amplicon Illumina sequencing procedure for studying the microbiome of a symbiont-rich aphid genus. Mol Ecol Resour. 2016; 16(3):628–640. PMID:
26458227.
26. Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 2014; 12(1):87. PMID:
25387460.
27. Corless CE, Guiver M, Borrow R, Edwards-Jones V, Kaczmarski EB, Fox AJ. Contamination and sensitivity issues with a real-time universal 16S rRNA PCR. J Clin Microbiol. 2000; 38(5):1747–1752. PMID:
10790092.
28. Sharma JK, Gopalkrishna V, Das BC. A simple method for elimination of unspecific amplifications in polymerase chain reaction. Nucleic Acids Res. 1992; 20(22):6117–6118. PMID:
1334263.
29. Carroll NM, Adamson P, Okhravi N. Elimination of bacterial DNA from Taq DNA polymerases by restriction endonuclease digestion. J Clin Microbiol. 1999; 37(10):3402–3404. PMID:
10488219.
30. Hilali F, Saulnier P, Chachaty E, Andremont A. Decontamination of polymerase chain reaction reagents for detection of low concentrations of 16S rRNA genes. Mol Biotechnol. 1997; 7(3):207–216. PMID:
9219235.
31. Wages JM Jr, Cai D, Fowler AK. Removal of contaminating DNA from PCR reagents by ultrafiltration. Biotechniques. 1994; 16(6):1014–1017. PMID:
8074862.
32. Hein I, Schneeweiss W, Stanek C, Wagner M. Ethidium monoazide and propidium monoazide for elimination of unspecific DNA background in quantitative universal real-time PCR. J Microbiol Methods. 2007; 71(3):336–339. PMID:
17936386.
33. Flores GE, Henley JB, Fierer N. A direct PCR approach to accelerate analyses of human-associated microbial communities. PLoS One. 2012; 7(9):e44563. PMID:
22962617.
34. Willner D, Daly J, Whiley D, Grimwood K, Wainwright CE, Hugenholtz P. Comparison of DNA extraction methods for microbial community profiling with an application to pediatric bronchoalveolar lavage samples. PLoS One. 2012; 7(4):e34605. PMID:
22514642.
35. Lazarevic V, Gaïa N, Girard M, Schrenzel J. Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR. BMC Microbiol. 2016; 16(1):73. PMID:
27107811.
36. Nejman D, Livyatan I, Fuks G, Gavert N, Zwang Y, Geller LT, et al. The human tumor microbiome is composed of tumor type-specific intracellular bacteria. Science. 2020; 368(6494):973–980. PMID:
32467386.
37. Callahan BJ, DiGiulio DB, Goltsman DS, Sun CL, Costello EK, Jeganathan P, et al. Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women. Proc Natl Acad Sci U S A. 2017; 114(37):9966–9971. PMID:
28847941.
38. Larsson AJ, Stanley G, Sinha R, Weissman IL, Sandberg R. Computational correction of index switching in multiplexed sequencing libraries. Nat Methods. 2018; 15(5):305–307. PMID:
29702636.
39. Minich JJ, Sanders JG, Amir A, Humphrey G, Gilbert JA, Knight R. Quantifying and understanding well-to-well contamination in microbiome research. mSystems. 2019; 4(4):e00186-19.
40. Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome. 2018; 6(1):226. PMID:
30558668.
41. Claassen-Weitz S, Gardner-Lubbe S, Mwaikono KS, du Toit E, Zar HJ, Nicol MP. Optimizing 16S rRNA gene profile analysis from low biomass nasopharyngeal and induced sputum specimens. BMC Microbiol. 2020; 20(1):113. PMID:
32397992.
42. Yang HJ, Kim SG, Lim JH, Choi JM, Kim WH, Jung HC.
Helicobacter pylori-induced modulation of the promoter methylation of Wnt antagonist genes in gastric carcinogenesis. Gastric Cancer. 2018; 21(2):237–248. PMID:
28643146.
43. Maekita T, Nakazawa K, Mihara M, Nakajima T, Yanaoka K, Iguchi M, et al. High levels of aberrant DNA methylation in
Helicobacter pylori-infected gastric mucosae and its possible association with gastric cancer risk. Clin Cancer Res. 2006; 12(3 Pt 1):989–995. PMID:
16467114.
44. Nanjo S, Asada K, Yamashita S, Nakajima T, Nakazawa K, Maekita T, et al. Identification of gastric cancer risk markers that are informative in individuals with past H. pylori infection. Gastric Cancer. 2012; 15(4):382–388. PMID:
22237657.
45. Ando T, Yoshida T, Enomoto S, Asada K, Tatematsu M, Ichinose M, et al. DNA methylation of microRNA genes in gastric mucosae of gastric cancer patients: its possible involvement in the formation of epigenetic field defect. Int J Cancer. 2009; 124(10):2367–2374. PMID:
19165869.
46. Kim HJ, Kim N, Kim HW, Park JH, Shin CM, Lee DH. Promising aberrant DNA methylation marker to predict gastric cancer development in individuals with family history and long-term effects of
H. pylori eradication on DNA methylation. Gastric Cancer. 2021; 24(2):302–313. PMID:
32915372.
47. Asada K, Nakajima T, Shimazu T, Yamamichi N, Maekita T, Yokoi C, et al. Demonstration of the usefulness of epigenetic cancer risk prediction by a multicentre prospective cohort study. Gut. 2015; 64(3):388–396. PMID:
25379950.
48. Shin CM, Kim N, Lee HS, Park JH, Ahn S, Kang GH, et al. Changes in aberrant DNA methylation after Helicobacter pylori eradication: a long-term follow-up study. Int J Cancer. 2013; 133(9):2034–2042. PMID:
23595635.
49. Shin CM, Kim N, Jung Y, Park JH, Kang GH, Park WY, et al. Genome-wide DNA methylation profiles in noncancerous gastric mucosae with regard to Helicobacter pylori infection and the presence of gastric cancer. Helicobacter. 2011; 16(3):179–188. PMID:
21585603.
50. Shin CM, Kim N, Jung Y, Park JH, Kang GH, Kim JS, et al. Role of Helicobacter pylori infection in aberrant DNA methylation along multistep gastric carcinogenesis. Cancer Sci. 2010; 101(6):1337–1346. PMID:
20345486.
51. Zhu Q, Hu Q, Shepherd L, Wang J, Wei L, Morrison CD, et al. The impact of DNA input amount and DNA source on the performance of whole-exome sequencing in cancer epidemiology. Cancer Epidemiol Biomarkers Prev. 2015; 24(8):1207–1213. PMID:
25990554.
52. Wex T, Treiber G, Lendeckel U, Malfertheiner P. A two-step method for the extraction of high-quality RNA from endoscopic biopsies. Clin Chem Lab Med. 2003; 41(8):1033–1037. PMID:
12964810.
53. Cui G, Olsen T, Christiansen I, Vonen B, Florholmen J, Goll R. Improvement of real-time polymerase chain reaction for quantifying TNF-alpha mRNA expression in inflamed colorectal mucosa: an approach to optimize procedures for clinical use. Scand J Clin Lab Invest. 2006; 66(3):249–259. PMID:
16714253.
54. Moen AE, Tannæs TM, Vatn S, Ricanek P, Vatn MH, Jahnsen J, et al. Simultaneous purification of DNA and RNA from microbiota in a single colonic mucosal biopsy. BMC Res Notes. 2016; 9(1):328. PMID:
27352784.
55. Stiekema J, Cats A, Boot H, Langers AM, Balague Ponz O, van Velthuysen ML, et al. Biobanking of fresh-frozen endoscopic biopsy specimens from esophageal adenocarcinoma. Dis Esophagus. 2016; 29(8):1100–1106. PMID:
26541751.
56. Chao HP, Chen Y, Takata Y, Tomida MW, Lin K, Kirk JS, et al. Systematic evaluation of RNA-Seq preparation protocol performance. BMC Genomics. 2019; 20(1):571. PMID:
31296163.
57. Schuierer S, Carbone W, Knehr J, Petitjean V, Fernandez A, Sultan M, et al. A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples. BMC Genomics. 2017; 18(1):442. PMID:
28583074.
58. Liu X, Xu Y, Meng Q, Zheng Q, Wu J, Wang C, et al. Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling. Biochem Biophys Res Commun. 2016; 476(4):286–292. PMID:
27230957.
59. Saleem S, Tariq S, Aleem I, Sadr-Ul Shaheed , Tahseen M, Atiq A, et al. Proteomics analysis of colon cancer progression. Clin Proteomics. 2019; 16(1):44. PMID:
31889941.
60. Abe Y, Hirano H, Shoji H, Tada A, Isoyama J, Kakudo A, et al. Comprehensive characterization of the phosphoproteome of gastric cancer from endoscopic biopsy specimens. Theranostics. 2020; 10(5):2115–2129. PMID:
32089736.
61. Wang M, Ji X, Wang B, Li Q, Zhou J. Simultaneous evaluation of the preservative effect of RNAlater on different tissues by biomolecular and histological analysis. Biopreserv Biobank. 2018; 16(6):426–433. PMID:
30484701.
62. Bennike TB, Kastaniegaard K, Padurariu S, Gaihede M, Birkelund S, Andersen V, et al. Comparing the proteome of snap frozen, RNAlater preserved, and formalin-fixed paraffin-embedded human tissue samples. EuPA Open Proteom. 2015; 10:9–18. PMID:
29900094.
63. Auer H, Mobley JA, Ayers LW, Bowen J, Chuaqui RF, Johnson LA, et al. The effects of frozen tissue storage conditions on the integrity of RNA and protein. Biotech Histochem. 2014; 89(7):518–528. PMID:
24799092.
64. Kelly R, Albert M, de Ladurantaye M, Moore M, Dokun O, Bartlett JM. RNA and DNA Integrity remain stable in frozen tissue after long-term storage at cryogenic temperatures: a report from the Ontario Tumour Bank. Biopreserv Biobank. 2019; 17(4):282–287. PMID:
30762427.
65. Zhang X, Han QY, Zhao ZS, Zhang JG, Zhou WJ, Lin A. Biobanking of fresh-frozen gastric cancer tissues: impact of long-term storage and clinicopathological variables on RNA quality. Biopreserv Biobank. 2019; 17(1):58–63. PMID:
30457887.
66. Babel M, Mamilos A, Seitz S, Niedermair T, Weber F, Anzeneder T, et al. Compared DNA and RNA quality of breast cancer biobanking samples after long-term storage protocols in - 80 °C and liquid nitrogen. Sci Rep. 2020; 10(1):14404. PMID:
32873858.
67. Sathe A, Grimes SM, Lau BT, Chen J, Suarez C, Huang RJ, et al. Single-cell genomic characterization reveals the cellular reprogramming of the gastric tumor microenvironment. Clin Cancer Res. 2020; 26(11):2640–2653. PMID:
32060101.
68. Zhang P, Yang M, Zhang Y, Xiao S, Lai X, Tan A, et al. Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer. Cell Reports. 2019; 27(6):1934–1947.e5. PMID:
31067475.
69. Zhang M, Hu S, Min M, Ni Y, Lu Z, Sun X, et al. Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing. Gut. 2021; 70(3):464–475. PMID:
32532891.
70. Kim J, Park C, Kim KH, Kim EH, Kim H, Woo JK, et al. Single-cell analysis of gastric pre-cancerous and cancer lesions reveals cell lineage diversity and intratumoral heterogeneity. NPJ Precis Oncol. 2022; 6(1):9. PMID:
35087207.
71. Haque A, Engel J, Teichmann SA, Lönnberg T. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome Med. 2017; 9(1):75. PMID:
28821273.
72. Lafzi A, Moutinho C, Picelli S, Heyn H. Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies. Nat Protoc. 2018; 13(12):2742–2757. PMID:
30446749.
73. Slyper M, Porter CB, Ashenberg O, Waldman J, Drokhlyansky E, Wakiro I, et al. A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors. Nat Med. 2020; 26(5):792–802. PMID:
32405060.
74. Guillaumet-Adkins A, Rodríguez-Esteban G, Mereu E, Mendez-Lago M, Jaitin DA, Villanueva A, et al. Single-cell transcriptome conservation in cryopreserved cells and tissues. Genome Biol. 2017; 18(1):45. PMID:
28249587.
75. Alles J, Karaiskos N, Praktiknjo SD, Grosswendt S, Wahle P, Ruffault PL, et al. Cell fixation and preservation for droplet-based single-cell transcriptomics. BMC Biol. 2017; 15(1):44. PMID:
28526029.
76. Wang W, Penland L, Gokce O, Croote D, Quake SR. High fidelity hypothermic preservation of primary tissues in organ transplant preservative for single cell transcriptome analysis. BMC Genomics. 2018; 19(1):140. PMID:
29439658.
77. Kim J, Kwon J, Kim M, Do J, Lee D, Han H. Low-dielectric-constant polyimide aerogel composite films with low water uptake. Polym J. 2016; 48(7):829–834.
78. Krishnaswami SR, Grindberg RV, Novotny M, Venepally P, Lacar B, Bhutani K, et al. Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons. Nat Protoc. 2016; 11(3):499–524. PMID:
26890679.
79. Habib N, Li Y, Heidenreich M, Swiech L, Avraham-Davidi I, Trombetta JJ, et al. Div-Seq: single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. Science. 2016; 353(6302):925–928. PMID:
27471252.
80. Habib N, Avraham-Davidi I, Basu A, Burks T, Shekhar K, Hofree M, et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat Methods. 2017; 14(10):955–958. PMID:
28846088.
81. Gao M, Lin M, Rao M, Thompson H, Hirai K, Choi M, et al. Development of patient-derived gastric cancer organoids from endoscopic biopsies and surgical tissues. Ann Surg Oncol. 2018; 25(9):2767–2775. PMID:
30003451.
82. Li J, Chen Y, Zhang Y, Peng X, Wu M, Chen L, et al. Clinical value and influencing factors of establishing stomach cancer organoids by endoscopic biopsy. J Cancer Res Clin Oncol. 2023; 149(7):3803–3810. PMID:
35987927.
83. Song H, Park JY, Kim JH, Shin TS, Hong SA, Huda MN, et al. Establishment of patient-derived gastric cancer organoid model from tissue obtained by endoscopic biopsies. J Korean Med Sci. 2022; 37(28):e220. PMID:
35851862.
84. Bartfeld S, Bayram T, van de Wetering M, Huch M, Begthel H, Kujala P, et al. In vitro expansion of human gastric epithelial stem cells and their responses to bacterial infection. Gastroenterology. 2015; 148(1):126–136.e6. PMID:
25307862.
85. Lau HC, Kranenburg O, Xiao H, Yu J. Organoid models of gastrointestinal cancers in basic and translational research. Nat Rev Gastroenterol Hepatol. 2020; 17(4):203–222. PMID:
32099092.
86. Nanki K, Toshimitsu K, Takano A, Fujii M, Shimokawa M, Ohta Y, et al. Divergent routes toward Wnt and R-spondin niche independency during human gastric carcinogenesis. Cell. 2018; 174(4):856–869.e17. PMID:
30096312.
87. Seidlitz T, Merker SR, Rothe A, Zakrzewski F, von Neubeck C, Grützmann K, et al. Human gastric cancer modelling using organoids. Gut. 2019; 68(2):207–217. PMID:
29703791.
88. Zhang M, Liu Y, Chen YG. Generation of 3D human gastrointestinal organoids: principle and applications. Cell Regen (Lond). 2020; 9(1):6.