Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Tytuł pozycji:

Establishment and characterization of 38 novel patient-derived primary cancer cell lines using multi-region sampling revealing intra-tumor heterogeneity of gallbladder carcinoma.

Tytuł:
Establishment and characterization of 38 novel patient-derived primary cancer cell lines using multi-region sampling revealing intra-tumor heterogeneity of gallbladder carcinoma.
Autorzy:
Feng F; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Cheng Q; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Li B; 3D Medicines Inc., Shanghai, 201114, China.
Liu C; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Wang H; 3D Medicines Inc., Shanghai, 201114, China.
Li B; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Xu X; 3D Medicines Inc., Shanghai, 201114, China.
Yu Y; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Chen Z; 3D Medicines Inc., Shanghai, 201114, China.
Wu X; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Dong H; 3D Medicines Inc., Shanghai, 201114, China.
Chu K; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Xie Z; 3D Medicines Inc., Shanghai, 201114, China.
Gao Q; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Xiong L; 3D Medicines Inc., Shanghai, 201114, China.
Li F; 3D Medicines Inc., Shanghai, 201114, China.
Yi B; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China.
Zhang D; 3D Medicines Inc., Shanghai, 201114, China. .
Jiang X; Department of Biliary I, Shanghai Eastern Hepatobiliary Surgery Hospital, Navy Military Medical University, Shanghai, 200438, China. xqjiang_.
Źródło:
Human cell [Hum Cell] 2021 May; Vol. 34 (3), pp. 918-931. Date of Electronic Publication: 2021 Apr 04.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: 2011- : Tokyo : Springer
Original Publication: Tōkyō-to : Hito Saibō Kenkyūkai : Kanishobo, Shōwa 63-nen [1988]-
MeSH Terms:
Genetic Heterogeneity*
Carcinoma/*genetics
Carcinoma/*pathology
Gallbladder Neoplasms/*genetics
Gallbladder Neoplasms/*pathology
Carcinogenesis/genetics ; Cell Line, Tumor ; Cyclin-Dependent Kinase Inhibitor p16/genetics ; DNA-Binding Proteins/genetics ; Disease Progression ; Gene Expression Regulation, Neoplastic/genetics ; Genes, MHC Class I ; Genes, MHC Class II ; Humans ; Mutation ; Nuclear Proteins/physiology ; Trans-Activators/physiology ; Transcription Factors/genetics ; Tumor Suppressor Protein p53/genetics
References:
Ghidini M, Pizzo C, Botticelli A, Hahne JC, Passalacqua R, Tomasello G, et al. Biliary tract cancer: current challenges and future prospects. Cancer Manag Res. 2019;11:379–88. https://doi.org/10.2147/CMAR.S157156 . (PMID: 10.2147/CMAR.S15715630643463)
Baiu I, Visser B. Gallbladder cancer. JAMA. 2018;320(12):1294. https://doi.org/10.1001/jama.2018.11815 . (PMID: 10.1001/jama.2018.1181530264121)
Hezel AF, Zhu AX. Systemic therapy for biliary tract cancers. Oncologist. 2008;13(4):415–23. https://doi.org/10.1634/theoncologist.2007-0252 . (PMID: 10.1634/theoncologist.2007-025218448556)
Mohammad YZ, Ghassan KA, Cecilia GE, Shailesh VS, Mahesh G, Bruno N, John P, et al. Evaluation and management of incidental gallbladder cancer. Chin Clin Oncol. 2019;8(4):37. https://doi.org/10.21037/cco.2019.07.01 . (PMID: 10.21037/cco.2019.07.01)
Marcano-Bonilla L, Mohamed EA, Mounajjed T, Roberts LR. Biliary tract cancers: epidemiology, molecular pathogenesis and genetic risk associations. Chin Clin Oncol. 2016;5(5):61. https://doi.org/10.21037/cco.2016.10.09 . (PMID: 10.21037/cco.2016.10.0927829275)
Bridgewater J, Lopes A, Wasan H, Malka D, Jensen L, Okusaka T, et al. Prognostic factors for progression-free and overall survival in advanced biliary tract cancer. Ann Oncol. 2016;27(1):134–40. https://doi.org/10.1093/annonc/mdv483 . (PMID: 10.1093/annonc/mdv48326483051)
Li M, Zhang Z, Li X, Ye J, Wu X, Tan Z, et al. Whole-exome and targeted gene sequencing of gallbladder carcinoma identifies recurrent mutations in the ErbB pathway. Nat Genet. 2014;46(8):872–6. https://doi.org/10.1038/ng.3030 . (PMID: 10.1038/ng.303024997986)
Nakamura H, Arai Y, Totoki Y, Shirota T, Elzawahry A, Kato M, et al. Genomic spectra of biliary tract cancer. Nat Genet. 2015;47(9):1003–10. https://doi.org/10.1038/ng.3375 . (PMID: 10.1038/ng.337526258846)
Marks EI, Yee NS. Molecular genetics and targeted therapeutics in biliary tract carcinoma. World J Gastroenterol. 2016;22(4):1335–47. https://doi.org/10.3748/wjg.v22.i4.1335 . (PMID: 10.3748/wjg.v22.i4.1335268195034721969)
Christopher PW, Masashi F, Toru Y, Michele S, Matteo F, Rosa K, et al. Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations. J Hepatol. 2018;68(5):959–69. https://doi.org/10.1016/j.jhep.2018.01.009 . (PMID: 10.1016/j.jhep.2018.01.009)
Benjamin AW, Joanne X, Michael RL, Anthony FS, Jimmy JH, Kelsey P, et al. Molecular profiling of biliary cancers reveals distinct molecular alterations and potential therapeutic targets. J Gastrointest Oncol. 2019;10(4):652–62. https://doi.org/10.21037/jgo.2018.08.18 . (PMID: 10.21037/jgo.2018.08.18)
Akhilesh P, Eric WS, Steffen D, Harsha G, Leonard DG, Mustafa AB, et al. Integrated genomic analysis reveals mutated ELF3 as a potential gallbladder cancer vaccine candidate. Nat Commun. 2020;11(1):4225. https://doi.org/10.1038/s41467-020-17880-4 . (PMID: 10.1038/s41467-020-17880-4)
Mengdan L, Lihong C, Yiping Q, Fang S, Qi Y, Meiju J, et al. Identification of MAP kinase pathways as therapeutic targets in gallbladder carcinoma using targeted parallel sequencing. Oncotarget. 2017;8(22):36319–30. https://doi.org/10.18632/oncotarget.16751 . (PMID: 10.18632/oncotarget.16751)
Dong LQ, Shi Y, Ma LJ, Yang LX, Wang XY, Zhang S, et al. Spatial and temporal clonal evolution of intrahepatic cholangiocarcinoma. J Hepatol. 2018;69(1):89–98. https://doi.org/10.1016/j.jhep.2018.02.029 . (PMID: 10.1016/j.jhep.2018.02.02929551704)
Pribluda A, de la Cruz CC, Jackson EL. Intratumoral heterogeneity: from diversity comes resistance. Clin Cancer Res. 2015;21(13):2916–23. https://doi.org/10.1158/1078-0432.CCR-14-1213 . (PMID: 10.1158/1078-0432.CCR-14-121325838394)
Gerlinger M, Rowan AJ, Horswell S, Math M, Larkin J, Endesfelder D, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883–92. https://doi.org/10.1056/NEJMoa1113205 . (PMID: 10.1056/NEJMoa1113205223976504878653)
Zhang J, Fujimoto J, Zhang J, Wedge DC, Song X, Zhang J, et al. Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing. Science. 2014;346(6206):256–9. https://doi.org/10.1126/science.1256930 . (PMID: 10.1126/science.1256930253016314354858)
Sottoriva A, Spiteri I, Piccirillo SG, Touloumis A, Collins VP, Marioni JC, et al. Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci U S A. 2013;110(10):4009–14. https://doi.org/10.1073/pnas.1219747110 . (PMID: 10.1073/pnas.1219747110234123373593922)
Gao Q, Wang ZC, Duan M, Lin YH, Zhou XY, Worthley DL, et al. Cell culture system for analysis of genetic heterogeneity within hepatocellular carcinomas and response to pharmacologic agents. Gastroenterology. 2017;152(1):232–424. https://doi.org/10.1053/j.gastro.2016.09.008 . (PMID: 10.1053/j.gastro.2016.09.00827639803)
Edge S, Byrd DR, Compton CC, et al. AJCC cancer staging manual. New York: Springer; 2009.
Tessoulin B, Moreau-Aubry A, Descamps G, Gomez-Bougie P, Maiga S, Gaignard A, et al. Whole-exon sequencing of human myeloma cell lines shows mutations related to myeloma patients at relapse with major hits in the DNA regulation and repair pathways. J Hematol Oncol. 2018;11(1):137. https://doi.org/10.1186/s13045-018-0679-0 . (PMID: 10.1186/s13045-018-0679-0305453976293660)
Kohli M, Ho Y, Hillman DW, Van Etten JL, Henzler C, Yang R, et al. Androgen receptor variant AR-V9 Is coexpressed with AR-V7 in prostate cancer metastases and predicts abiraterone resistance. Clin Cancer Res. 2017;23(16):4704–15. https://doi.org/10.1158/1078-0432.CCR-17-0017 . (PMID: 10.1158/1078-0432.CCR-17-0017284735355644285)
Li H, Durbin R. Fast and accurate long-read alignment with burrows-wheeler transform. Bioinformatics. 2010;26(5):589–95. https://doi.org/10.1093/bioinformatics/btp698 . (PMID: 10.1093/bioinformatics/btp69828281082828108)
Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 2013;31(3):213–9. https://doi.org/10.1038/nbt.2514 . (PMID: 10.1038/nbt.2514233960133833702)
Ye K, Schulz MH, Long Q, Apweiler R, Ning Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics. 2009;25(21):2865–71. https://doi.org/10.1093/bioinformatics/btp394 . (PMID: 10.1093/bioinformatics/btp394195610182781750)
Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38(16):e164. https://doi.org/10.1093/nar/gkq603 . (PMID: 10.1093/nar/gkq603206016852938201)
Genomes Project C, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422):56–65. https://doi.org/10.1038/nature11632 . (PMID: 10.1038/nature11632)
Fu W, O’Connor TD, Jun G, Kang HM, Abecasis G, Leal SM, et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature. 2013;493(7431):216–20. https://doi.org/10.1038/nature11690 . (PMID: 10.1038/nature1169023201682)
Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91. https://doi.org/10.1038/nature19057 . (PMID: 10.1038/nature19057275355335018207)
Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: somatic cancer genetics at high-resolution. Nucleic Acids Res. 2017;45(D1):D777–83. https://doi.org/10.1093/nar/gkw1121 . (PMID: 10.1093/nar/gkw112127899578)
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2. https://doi.org/10.1093/bioinformatics/btq033 . (PMID: 10.1093/bioinformatics/btq033201102782832824)
Ong CK, Subimerb C, Pairojkul C, Wongkham S, Cutcutache I, Yu W, et al. Exome sequencing of liver fluke-associated cholangiocarcinoma. Nat Genet. 2012;44(6):690–3. https://doi.org/10.1038/ng.2273 . (PMID: 10.1038/ng.227322561520)
Farshidfar F, Zheng S, Gingras MC, Newton Y, Shih J, Robertson AG, et al. Integrative genomic analysis of cholangiocarcinoma identifies distinct IDH-mutant molecular profiles. Cell Rep. 2017;18(11):2780–94. https://doi.org/10.1016/j.celrep.2017.02.033 . (PMID: 10.1016/j.celrep.2017.02.033282976795493145)
Jiao Y, Pawlik TM, Anders RA, Selaru FM, Streppel MM, Lucas DJ, et al. Exome sequencing identifies frequent inactivating mutations in BAP1, ARID1A and PBRM1 in intrahepatic cholangiocarcinomas. Nat Genet. 2013;45(12):1470–3. https://doi.org/10.1038/ng.2813 . (PMID: 10.1038/ng.2813241855094013720)
Rosenthal R, McGranahan N, Herrero J, Taylor BS, Swanton C. DeconstructSigs: delineating mutational processes in single tumors distinguishes DNA repair deficiencies and patterns of carcinoma evolution. Genome Biol. 2016;17:31. https://doi.org/10.1186/s13059-016-0893-4 . (PMID: 10.1186/s13059-016-0893-4268991704762164)
Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–21. https://doi.org/10.1038/nature12477 . (PMID: 10.1038/nature1247737763903776390)
Talevich E, Shain AH, Botton T, Bastian BC. CNVkit: genome-wide copy number detection and visualization from targeted DNA sequencing. PLoS Comput Biol. 2016;12(4):e1004873. https://doi.org/10.1371/journal.pcbi.1004873 . (PMID: 10.1371/journal.pcbi.1004873271007384839673)
Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0 Facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 2011;12(4):4. https://doi.org/10.1186/gb-2011-12-4-r41 . (PMID: 10.1186/gb-2011-12-4-r41)
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21. https://doi.org/10.1093/bioinformatics/bts635 . (PMID: 10.1093/bioinformatics/bts6352310488623104886)
Wang L, Wang S, Li W. RSeQC: quality control of RNA-seq experiments. Bioinformatics. 2012;28(16):2184–5. https://doi.org/10.1093/bioinformatics/bts356 . (PMID: 10.1093/bioinformatics/bts356)
Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30(7):923–30. https://doi.org/10.1093/bioinformatics/btt656 . (PMID: 10.1093/bioinformatics/btt65624227677)
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7. https://doi.org/10.1089/omi.2011.0118 . (PMID: 10.1089/omi.2011.01182245546322455463)
Crystal AS, Shaw AT, Sequist LV, Friboulet L, Niederst MJ, Lockerman EL, et al. Patient-derived models of acquired resistance can identify effective drug combinations for cancer. Science. 2014;346(6216):1480–6. https://doi.org/10.1126/science.1254721 . (PMID: 10.1126/science.1254721253947914388482)
Nishida T, Iwasaki H, Johzaki H, Tanaka S, Watanabe R, Kikuchi M. A human gall-bladder signet ring cell carcinoma cell line. Pathol Int. 1997;47(6):368–76. https://doi.org/10.1111/j.1440-1827.1997.tb04510.x . (PMID: 10.1111/j.1440-1827.1997.tb04510.x9211524)
Liu ZY, Xu GL, Tao HH, Yang YQ, Fan YZ, et al. Establishment and characterization of a novel highly aggressive gallbladder cancer cell line, TJ-GBC2. Cancer Cell Int. 2017;17:20. https://doi.org/10.1186/s12935-017-0388-8 . (PMID: 10.1186/s12935-017-0388-8281940915299695)
Zhou F, Zhang YH, Sun JH, Yang XM. Characteristics of a novel cell line ZJU-0430 established from human gallbladder carcinoma. Cancer Cell Int. 2019;19:190. https://doi.org/10.1186/s12935-019-0911-1 . (PMID: 10.1186/s12935-019-0911-1313671886647153)
Shinichi S, Yutaka S, Takuya N, Makoto M, Testuya O, Isaku Y, et al. Establishment and characterization of a new human gallbladder carcinoma cell line. Anticancer Res. 2012;32(8):3211–8.
Feng FL, Cheng QB, Yang L, Zhang DD, Ji SL, Zhang QZ, et al. Guidance to rational use of pharmaceuticals in gallbladder sarcomatoid carcinoma using patient-derived cancer cells and whole exome sequencing. Oncotarget. 2017;8(3):5349–60. https://doi.org/10.18632/oncotarget.14146 . (PMID: 10.18632/oncotarget.1414628029662)
Patricia G, Carolina B, Lorena R, Jaime AE, Helga W, Javier CI, et al. Functional and genomic characterization of three novel cell lines derived from a metastatic gallbladder cancer tumor. Biol Res. 2020;53(1):13. https://doi.org/10.1186/s40659-020-00282-7 . (PMID: 10.1186/s40659-020-00282-7)
Yamada A, Yu P, Lin W, Okugawa Y, Boland CR, Goel A. A RNA-Sequencing approach for the identification of novel long non-coding RNA biomarkers in colorectal cancer. Sci Rep. 2018;8(1):575. https://doi.org/10.1038/s41598-017-18407-6 . (PMID: 10.1038/s41598-017-18407-62933037029330370)
Reuben A, Gittelman R, Gao J, Zhang J, Yusko EC, Wu CJ, et al. TCR repertoire intratumor heterogeneity in localized lung adenocarcinomas: an association with predicted neoantigen heterogeneity and postsurgical recurrence. Cancer Discov. 2017;7(10):1088–97. https://doi.org/10.1158/2159-8290.CD-17-0256 . (PMID: 10.1158/2159-8290.CD-17-0256287334285628137)
Ting JP, Trowsdale J. Genetic control of MHC class II expression. Cell. 2002;109(Suppl):S21-33. (PMID: 10.1016/S0092-8674(02)00696-7)
Sconocchia G, Eppenberger-Castori S, Zlobec I, Karamitopoulou E, Arriga R, Coppola A, et al. HLA class II antigen expression in colorectal carcinoma tumors as a favorable prognostic marker. Neoplasia. 2014;16(1):31–42. (PMID: 10.1593/neo.131568)
Bruna A, Rueda OM, Greenwood W, Batra AS, Callari M, Batra RN, et al. A biobank of breast cancer explants with preserved intra-tumor heterogeneity to screen anticancer compounds. Cell. 2016;167(1):260–7422. https://doi.org/10.1016/j.cell.2016.08.041 . (PMID: 10.1016/j.cell.2016.08.041276415045037319)
Qazi MA, Vora P, Venugopal C, Sidhu SS, Moffat J, Swanton C, et al. Intratumoral heterogeneity: pathways to treatment resistance and relapse in human glioblastoma. Ann Oncol. 2017;28(7):1448–56. https://doi.org/10.1093/annonc/mdx169 . (PMID: 10.1093/annonc/mdx16928407030)
Morris LG, Riaz N, Desrichard A, Senbabaoglu Y, Hakimi AA, Makarov V, et al. Pan-cancer analysis of intratumor heterogeneity as a prognostic determinant of survival. Oncotarget. 2016;7(9):10051–63. https://doi.org/10.18632/oncotarget.7067 . (PMID: 10.18632/oncotarget.7067268402674891103)
Hou Y, Nitta H, Wei L, Banks PM, Portier B, Parwani AV, et al. HER2 intratumoral heterogeneity is independently associated with incomplete response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma. Breast Cancer Res Treat. 2017;166(2):447–57. https://doi.org/10.1007/s10549-017-4453-8 . (PMID: 10.1007/s10549-017-4453-828799059)
Grant Information:
15411951900 Science and Technology Commission of Shanghai Municipality; 81472280 National Natural Science Foundation of China; 2017JZ11 Special Fund for the Application and Transformation of Precision Medicine at the Second Military Medical University
Contributed Indexing:
Keywords: Gallbladder carcinoma; Genomic profiling; Intra-tumor heterogeneity; Patient-derived primary cancer cell line; Transcriptome profiling
Substance Nomenclature:
0 (ARID1A protein, human)
0 (CDKN2A protein, human)
0 (Cyclin-Dependent Kinase Inhibitor p16)
0 (DNA-Binding Proteins)
0 (KMT2C protein, human)
0 (MHC class II transactivator protein)
0 (Nuclear Proteins)
0 (TP53 protein, human)
0 (Trans-Activators)
0 (Transcription Factors)
0 (Tumor Suppressor Protein p53)
Entry Date(s):
Date Created: 20210404 Date Completed: 20211004 Latest Revision: 20211004
Update Code:
20240105
PubMed Central ID:
PMC8057967
DOI:
10.1007/s13577-021-00492-5
PMID:
33813726
Czasopismo naukowe
Gallbladder carcinoma (GBC) is a lethal biliary tract malignant neoplasm. Patient-derived primary cancer cell lines (PDPCs) are appropriate models to explore biological characteristics and potential therapeutics; however, there is a lack of PDPCs in GBC. In this study, we aimed to establish and characterize the GBC PDPCs, and further investigated the intra-tumor heterogeneity (ITH). Multi-region sampling (3-9 regions) of the operable tumor tissue samples was used to establish PDPCs. Short tandem repeat genotyping for cell authentication and karyotyping was performed, followed by whole-exome sequencing and RNA sequencing to assess the ITH at the genetic and transcriptional levels, respectively. Thirty-eight PDPCs were successfully established from seven GBC patients and characterized. ITH was observed with a median of 38.3% mutations being heterogeneous (range, 26.6-59.4%) across all patients. Similar with other tumor types, TP53 mutations were always truncal. In addition, there were three genes, KMT2C, CDKN2A, and ARID1A, with truncal mutations in at least two patients. A median of 370 differentially expressed genes (DEGs) was identified per patient. Distinct expression patterns were observed between major histocompatibility complex (MHC) class I and II genes. We found the expression of MHC class II genes in the PDPC samples was closely regulated by CIITA, while that of MHC class I genes were not correlated with CIITA expression. The PDPCs established from GBC patients can serve as novel in vitro models to identify the ITH, which may pave a crucial molecular foundation for enhanced understanding of tumorigenesis and progression.

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies