Integration of Pan-omics Technologies and Three-dimensional in Vitro Tumor Models: an Approach Toward Drug Discovery and Precision Medicine

Overview

Journal Mol Cancer

Publisher Biomed Central

Specialties Molecular Biology
Oncology

Date 2024 Mar 9

PMID 38461268

Authors

Anmi Jose

Pallavi Kulkarni

Jaya Thilakan

Murali Munisamy

Anvita Gupta Malhotra

Jitendra Singh

Ashok Kumar

Vivek M Rangnekar

Neha Arya

Mahadev Rao

Affiliations

Soon will be listed here.

Abstract

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

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References

Wang C, Sun M, Shao C, Schlicker L, Zhuo Y, Harim Y . A multidimensional atlas of human glioblastoma-like organoids reveals highly coordinated molecular networks and effective drugs. NPJ Precis Oncol. 2024; 8(1):19. PMC: 10811239. DOI: 10.1038/s41698-024-00500-5. View

Xie P, Liang X, Song Y, Cai Z . Mass Spectrometry Imaging Combined with Metabolomics Revealing the Proliferative Effect of Environmental Pollutants on Multicellular Tumor Spheroids. Anal Chem. 2020; 92(16):11341-11348. DOI: 10.1021/acs.analchem.0c02025. View

De Vita A, Vanni S, Fausti V, Cocchi C, Recine F, Miserocchi G . Deciphering the Genomic Landscape and Pharmacological Profile of Uncommon Entities of Adult Rhabdomyosarcomas. Int J Mol Sci. 2021; 22(21). PMC: 8584142. DOI: 10.3390/ijms222111564. View

Tung K, Chen K, Negrete M, Chen T, Safi A, Aljamal A . Integrated chromatin and transcriptomic profiling of patient-derived colon cancer organoids identifies personalized drug targets to overcome oxaliplatin resistance. Genes Dis. 2021; 8(2):203-214. PMC: 8099686. DOI: 10.1016/j.gendis.2019.10.012. View

Boretto M, Maenhoudt N, Luo X, Hennes A, Boeckx B, Bui B . Patient-derived organoids from endometrial disease capture clinical heterogeneity and are amenable to drug screening. Nat Cell Biol. 2019; 21(8):1041-1051. DOI: 10.1038/s41556-019-0360-z. View

Ries A, Flehberger D, Slany A, Pirker C, Mader J, Mohr T . Mesothelioma-associated fibroblasts enhance proliferation and migration of pleural mesothelioma cells via c-Met/PI3K and WNT signaling but do not protect against cisplatin. J Exp Clin Cancer Res. 2023; 42(1):27. PMC: 9869633. DOI: 10.1186/s13046-022-02582-0. View

Pieters V, Co I, Wu N, McGuigan A . Applications of Omics Technologies for Three-Dimensional Disease Models. Tissue Eng Part C Methods. 2021; 27(3):183-199. DOI: 10.1089/ten.TEC.2020.0300. View

Gao D, Vela I, Sboner A, Iaquinta P, Karthaus W, Gopalan A . Organoid cultures derived from patients with advanced prostate cancer. Cell. 2014; 159(1):176-187. PMC: 4237931. DOI: 10.1016/j.cell.2014.08.016. View

Kwon Y, Jo H, Bae S, Seo Y, Song P, Song M . Application of Proteomics in Cancer: Recent Trends and Approaches for Biomarkers Discovery. Front Med (Lausanne). 2021; 8:747333. PMC: 8492935. DOI: 10.3389/fmed.2021.747333. View

10.

Dijkstra J, Neikes H, Rezaeifard S, Ma X, Voest E, Tauriello D . Multiomics of Colorectal Cancer Organoids Reveals Putative Mediators of Cancer Progression Resulting from SMAD4 Inactivation. J Proteome Res. 2022; 22(1):138-151. PMC: 9830641. DOI: 10.1021/acs.jproteome.2c00551. View

11.

Kapalczynska M, Kolenda T, Przybyla W, Zajaczkowska M, Teresiak A, Filas V . 2D and 3D cell cultures - a comparison of different types of cancer cell cultures. Arch Med Sci. 2018; 14(4):910-919. PMC: 6040128. DOI: 10.5114/aoms.2016.63743. View

12.

Levin V, Panchabhai S, Shen L, Baggerly K . Protein and phosphoprotein levels in glioma and adenocarcinoma cell lines grown in normoxia and hypoxia in monolayer and three-dimensional cultures. Proteome Sci. 2012; 10(1):5. PMC: 3317865. DOI: 10.1186/1477-5956-10-5. View

13.

Maru Y, Tanaka N, Itami M, Hippo Y . Efficient use of patient-derived organoids as a preclinical model for gynecologic tumors. Gynecol Oncol. 2019; 154(1):189-198. DOI: 10.1016/j.ygyno.2019.05.005. View

14.

Sharick J, Walsh C, Sprackling C, Pasch C, Pham D, Esbona K . Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment. Front Oncol. 2020; 10:553. PMC: 7242740. DOI: 10.3389/fonc.2020.00553. View

15.

Vidavsky N, Kunitake J, Diaz-Rubio M, Chiou A, Loh H, Zhang S . Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression. ACS Cent Sci. 2019; 5(5):768-780. PMC: 6535773. DOI: 10.1021/acscentsci.8b00932. View

16.

Tang-Schomer M, Chandok H, Wu W, Lau C, Bookland M, George J . 3D patient-derived tumor models to recapitulate pediatric brain tumors In Vitro. Transl Oncol. 2022; 20:101407. PMC: 8980497. DOI: 10.1016/j.tranon.2022.101407. View

17.

Lundberg E, Borner G . Spatial proteomics: a powerful discovery tool for cell biology. Nat Rev Mol Cell Biol. 2019; 20(5):285-302. DOI: 10.1038/s41580-018-0094-y. View

18.

Driehuis E, Van Hoeck A, Moore K, Kolders S, Francies H, Gulersonmez M . Pancreatic cancer organoids recapitulate disease and allow personalized drug screening. Proc Natl Acad Sci U S A. 2019; 116(52):26580-26590. PMC: 6936689. DOI: 10.1073/pnas.1911273116. View

19.

Kang Y, Yoon J, Long N, Koo G, Noh H, Oh S . Spheroid-Induced Epithelial-Mesenchymal Transition Provokes Global Alterations of Breast Cancer Lipidome: A Multi-Layered Omics Analysis. Front Oncol. 2019; 9:145. PMC: 6437068. DOI: 10.3389/fonc.2019.00145. View

20.

Macosko E, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M . Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell. 2015; 161(5):1202-1214. PMC: 4481139. DOI: 10.1016/j.cell.2015.05.002. View