Table 1 Brief description of studies done using various omics techniques and 3-D in vitro tumor models
Sl. No | Type of omics used | Method adopted | Type of cancer studied | Purpose of the study | References |
|---|---|---|---|---|---|
1. | Genomics | WGS | Breast cancer | Validation of PDO model using patient data | [125] |
2. | WGS | Gastrointestinal cancer | Validation of PDO model using patient data | [126] | |
3. | WGS | Colorectal cancer | Validation of PDO model using patient data | [127] | |
4. | WGS | Esophageal cancer | Validation of PDO model using patient data | [128] | |
5. | WGS | Gastric cancer | Human and mouse gastric cancer organoids to check different drug targets | [129] | |
6. | NGS | Ovarian tumor & endometrial tumor | Validation of PDO model using patient data | [130] | |
7. | WGS | Gastroenteropancreatic (GEP) neuroendocrine neoplasm | Validation of PDO model for identification of new therapeutic targets | [37] | |
8. | WGS | Pancreatic cancer | Validation of 3-D models for identification of genomic markers contributing towards drug sensitivity | [39] | |
9. | WGS | Kidney cancer | Validation of PDO model based on pediatric kidney cancer patients | [38] | |
10. | WGS | Colon cancer, Breast cancer | PDO based model for studying the changes in mutational landscape of tumor when exposed to fluoropyrimidines | [131] | |
11. | WGS | Ovarian cancer | PDO based models to understand the inter- and intra-patient heterogeneity to drug response | [132] | |
12. | WES | Prostate cancer | PDO model to understand association of EZH2 driven molecular changes with cancer progression | [122] | |
13. | WES | Prostate cancer | Recapitulation of molecular diversity of the various subtypes of prostate cancer and validation of PDO Model | [36] | |
14. | WES | Gastric cancer | Establishment of primary gastric cancer organoid biobank & molecular profiling | [133] | |
15. | WES | Colorectal cancer | Biobank establishment, gene-drug association, validation using PDO model and 3-D model | ||
16. | WES | Brain cancer | PDO models of pediatric high-grade gliomas to understand the role of hypoxia in cancer progression | [135] | |
17. | CRISPR-Cas9 screening with NGS | Colon cancer | PDO model to screen patient-specific functional genomics | [41] | |
18. | Transcriptomics | Microarray | Breast cancer | Studied the gene expression profile affecting the drug response in 3-D compared to 2-D model | |
19. | RNA-Seq | Colorectal cancer | Transcriptomic and chromatin profiling for personalized drug targets to overcome chemoresistance | [49] | |
20. | RNA-Seq | Endometrial cancer | PDO based Biobank development which recapitulated the lesions from all clinical stages and can be used for drug screening purposes | [50] | |
21. | RNA-Seq | Breast cancer | PDO model validation using patient data | [125] | |
22. | RNA-Seq | Pancreatic cancer | PDO & PDX derived organoid model for understanding genomic and histopathological changes along with drug testing | [136] | |
23. | RNA-Seq | Colorectal cancer | Colonic organoids from induced pluripotent stem cells used in disease modelling and drug discovery for colorectal disease | [137] | |
24. | RNA-Seq | Bladder cancer | Validation of PDO model using patient data | ||
25. | RNA-Seq | Liver cancer | Micro-scaffold-based model to enumerate relationship between EMT status and hepatic functions | [139] | |
26. | RNA-Seq | Brain cancer | PDOs developed via CRISPR-Cas9-mediated mutagenesis for drug testing | [140] | |
27. | RNA-Seq | Colorectal cancer | Patient-derived organotypic tumor spheroids in 3-D microfluidic culture to screen the response of immune check point blockade therapy | [93] | |
28. | RNA-Seq | Colorectal cancer | Model validation of 2-D patient derived cancer cells, 3-D air-liquid interface based organoid culture and xenograft for identification of potential drug targets | [141] | |
29. | RNA-Seq | Colorectal cancer | PDOs for therapeutic drug screening | [54] | |
30. | RNA-Seq | Lung cancer | Development of PDO models to recapitulate the tumor heterogeneity and to identify the targets against Wnt signalling | [60] | |
31. | RNA-Seq | Pancreatic cancer | PDO based models to identify transcriptomic groups involved in invasion | [64] | |
32. | RNA-Seq | Brain tumor | Pediatric patients derived 3-D culture model to study the microenvironment induced gene expression changes | [142] | |
33. | GeneChip™ Human Transcriptome Array | Metastatic colorectal cancer | Pharmacogenomic profiling for PDO models to check the drug sensitivity | [59] | |
34. | Single‐cell RNA-Seq | Metastatic colorectal cancer | PDO formed to recapitulate the tumor heterogeneity and further used to study the drug response | [52] | |
35. | Single‐cell RNA-Seq | Metastatic renal cell carcinoma | 3-D model for combinatorial drug therapy | [61] | |
36. | Single‐cell RNA-Seq | Glioblastoma | Laboratory engineered glioblastoma organoid models to recapitulate genetic heterogeneity and identification of various drug targets | [65] | |
37. | Single‐cell RNA-Seq | Multi organ tumors | PDO based models to recapitulate tumor immune microenvironment for personalized therapeutic applications | [143] | |
38. | miRNA Microarrays | Colorectal adenoma and colorectal cancer | PDO utilised to understand the miRNA signature patterns in colorectal adenoma and colorectal cancer | [75] | |
39. | Proteomics | Mass spectrometry | Pancreatic cancer | Extracellular vesicle protein profiling to investigate tumorigenesis | [81] |
40. | Mass spectrometry | Colorectal cancer | Organoid based model to show the effect of SMAD4 inactivation on metastasis | [83] | |
41. | Mass spectrometry | Pancreatic cancer | Murine and human derived organoids to investigate the pancreatic cancer pathogenesis | [144] | |
42. | Mass spectrometry | Colorectal cancer | Organoids from healthy donor and cancer patients subjected to proteomic analysis to understand the patient-specific protein signatures | [145] | |
43. | DigiWest multiplex protein profiling | Colorectal cancer | PDO based model for studying tumor heterogeneity and prediction of therapy response | [146] | |
44. | Single-cell mass cytometry (CyTOF®) | Breast cancer | Primary breast organoids to preserve complex epithelial lineage | [147] | |
45. | LC-MS/MS analysis | Brain cancer | Drug screening platform using patient derived neurospheres/3-D culture | ||
46. | LC–MS/MS -SWATH | Colorectal cancer | PDO based model to integrate the drug sensitivity with proteomics for prediction of better therapeutic response | [84] | |
47. | LC-MS/MS analysis | Colon cancer | Quantitative proteomic and phosphoproteomic analysis of 3-D spheroids | [90] | |
48. | Reverse phase protein microarray | Colon cancer | PDO based model to study altered molecular pathway involved in tumorigenesis | [33] | |
49. | Reverse phase protein microarray | Multiple Cancers | Compared 121 different phosphorylated and non-phosphorylated proteins between 2-D and 3-D cell cultured models under the influence of hypoxia | [89] | |
50. | Protein Array | Colorectal cancer | PDO based models to identify the role of MIR21 dysregulation, JAM-A silencing and signalling pathways involved in tumorigenesis | [149] | |
51. | Milliplex® MAP Human Cytokine/Chemokine Panel | Pancreatic cancer | To study the effect of tumor cells and fibroblast on monocytes in a 3-D co-culture model | [92] | |
52. | Metabolomics and lipidomics | 1H-NMR Spectroscopy | Brain cancer | To validate patient-derived model in hypoxic microenvironment | [135] |
53. | Mass spectrometry and Raman chemical imaging | Breast cancer | Cell line-based spheroid model to map lipid distribution during disease progression | [115] | |
54. | Mass spectrometry | Breast cancer | Spheroid based model to study the effect of bisphenol- S on tumor progression | [98] | |
55. | Mass spectrometry | Prostate and breast cancer | Spheroid models to evaluate the alterations in intracellular lipid concentrations when treated with metabolic enzyme inhibitors | [113] | |
56. | LC-QTOF-MS | Colorectal cancer | PDO based models used for metabolomic and lipidomic profiling when treated with 5-fluorouracil | [108] | |
57. | Optical metabolic Imaging | Breast cancer and pancreatic cancer | PDO based models to analyse the optical metabolic imaging of cellular heterogeneity as a predictor of clinical treatment response | [150] | |
58. | LCMS | Breast cancer | PDO based model to describe the metabolomic landscape of TNBC patients | [107] | |
59. | HPLC-MS/MS | Colorectal cancer | Understanding the mechanism of curcumin in PDO based model | [151] | |
60. | Organ on chip platform with electrochemical microsensors | Breast cancer | Patient derived breast cancer stem cell based organoid model for in situ metabolite monitoring and drug screening | [152] | |
61. | Mass spectrometry | Ovarian cancer | PDO based model for drug testing and to evaluate the role of lipid metabolic activities in cancer progression | [112] | |
62. | UHPLC | Colorectal cancer | PDO based models to identify the role of drug sensitizing activity of spirulina polysaccharides in 5 fluorouracil resistant CRC organoids | [153] | |
63. | UPLC-MS | Multiple tumor cells | Chip based 3-D co-culture model to evaluate metabolism induced anticancer activity | [96] | |
64. | MALDI Mass Spectrometry Imaging | Colorectal cancer | PDO based model to examine drug and its metabolite distribution | [102] | |
65. | GCxGC-MS Analysis | Ovarian cancer | To evaluate the difference in intracellular and extracellular metabolite profile amongst ovarian cancer cell and spheroid derived ovarian cancer stem cells | [105] | |
66. | LCMS | Breast cancer | To understand the changes in lipidome during breast cancer metastasis | [116] | |
67. | Epigenomics | DNA methylation profiling | Kidney cancer | Validation of PDO model based on pediatric kidney cancer patients | [38] |
68. | Enhanced reduced representation bisulfite sequencing | Prostate cancer | PDO based models used to understand the role of epigenetic modifier EZH2 in cancer progression | [122] | |
69. | ATAC Seq | Pancreatic cancer | PDO based model to study chromatin accessibility associated with drug sensitivity | [154] | |
70. | Whole-genome bisulfite sequencing | Colorectal cancer | PDO based model used to evaluate the transcriptomic and epigenetic landscape with respect to the culture conditions | [155] | |
71. | Methylation epic bead ChIP microarrays | Colorectal cancer | PDO based model used to prove the anti-metastatic activity of ginseng by inhibiting the expression of DNA methyltransferases | [156] | |
72. | ChIP Seq | Prostate cancer | PDX/PDO models to understand the lineage plasticity and epigenetic reprogramming induced by N-Myc | [120] | |
73. | Methylation array analysis | Osteosarcoma | Comparing 3-D bio-printed model with other tumor models for changes in cell cycle, metabolomics and epigenetic regulation | [121] | |
74. | m6A methylated RNA immunoprecipitation sequencing | Colorectal cancer | The tumorigenic effect of YTHDF1-m6A-ARHGEF2 axis on disease progression studied on organoids and mice models | [123] |