| Literature DB >> 31884964 |
Han Fan1,2, Utkan Demirci3, Pu Chen4,5.
Abstract
Cancer heterogeneity is regarded as the main reason for the failure of conventional cancer therapy. The ability to reconstruct intra- and interpatient heterogeneity in cancer models is crucial for understanding cancer biology as well as for developing personalized anti-cancer therapy. Cancer organoids represent an emerging approach for creating patient-derived in vitro cancer models that closely recapitulate the pathophysiological features of natural tumorigenesis and metastasis. Meanwhile, cancer organoids have recently been utilized in the discovery of personalized anti-cancer therapy and prognostic biomarkers. Further, the synergistic combination of cancer organoids with organ-on-a-chip and 3D bioprinting presents a new avenue in the development of more sophisticated and optimized model systems to recapitulate complex cancer-stroma or multiorgan metastasis. Here, we summarize the recent advances in cancer organoids from a perspective of the in vitro emulation of natural cancer evolution and the applications in personalized cancer theranostics. We also discuss the challenges and trends in reconstructing more comprehensive cancer models for basic and clinical cancer research.Entities:
Keywords: 3D Bioprinting; Cancer heterogeneity; Cancer organoids; In vitro model system; Organ-on-a-chip; Patient-derived tumor organoids; Personalized anti-cancer therapy
Mesh:
Year: 2019 PMID: 31884964 PMCID: PMC6936115 DOI: 10.1186/s13045-019-0832-4
Source DB: PubMed Journal: J Hematol Oncol ISSN: 1756-8722 Impact factor: 17.388
Advantages and disadvantages of using PTDX models and cancer organoids for cancer research
| Feature | PDTX models | Cancer organoids |
|---|---|---|
| Generation efficiency | 10%–70% [ | 70%–100% |
| Tumor tissue source | Surgically resected specimens | Surgically resected or biopsy needle specimens |
| Retention of heterogeneity | Retention | Retention |
| Generation time | 4–8 months | 4–12 weeks [ |
| Passage efficiency | Low | High |
| Genetic manipulation | Not amenable | Amenable |
| High-throughput screening for drug discovery | No | Yes |
| Immune components | Without | Retention [ |
| Cost | High | Low |
Cancer organoid models: published reports
| Tumor organoid model | Cell derived | Research means | Achievement | Refs |
|---|---|---|---|---|
| Breast cancer organoids | Patient | Quantitative optical imaging | Predict the therapeutic response of anti-tumor drug in individual patients | [ |
| Mice | Organoid culture and xenotransplantation | Identify an early dissemination and metastasis mechanism for Her2+ breast cancer | [ | |
| Liver cancer organoids | Patient | Organoid culture and xenotransplantation | Establishment of hepatocellular carcinoma organoids from needle biopsies, and cancer organoids maintain the genomic features of the original tumors for up to 32 weeks | [ |
| Gastric cancer organoids | Patient | Whole-genome sequencing | Identify mutated driver genes of promoting escape from anoikis in organoid culture | [ |
| Murine | Gene editing | First reveal the potential metastatic role of TGFBR2 loss-of-function in diffuse gastric cancer | [ | |
| Colorectal cancer organoids | Human stem cell | CRISPR-Cas9 | Verify the deficient of key DNA repair gene MLH1 role in drives tumorigenesis | [ |
| Human stem cell | CRISPR-Cas9 and orthotopic transplantation | Visualize the different steps of the in vivo CRC metastatic cascade | [ | |
| Prostate cancer organoids | Patient, Mouse | Organoid culture and xenotransplantation | Show the role of nucleoporins in the progression of pancreatic cancer | [ |
| Patient | Organoid culture and xenotransplantation | Maintain prostate cancer-specific mutations and are suitable for in vitro and in vivo drug testing | [ | |
| Pancreatic cancer organoids | Patient | Organoid culture | The treatment profiles are parallel to the patient’s outcomes and the chemo-sensitivity of patient can be assessed | [ |
| Patient | Tumor organoids co-culture with stromal cells | Evaluate cancer-stroma cell interactions | [ | |
| Glioblastoma organoids | Patient | Organoid culture and xenotransplantation | Patient-derived organoids display histological features and recapitulate the hypoxic gradients in vivo | [ |
Fig. 1Cancer organoids can be derived from patients with diverse cancer grades and subtypes. Patient-derived organoids can possess patient-specific genetic and epigenetic contexts for preclinical cancer research and theranostics. Meanwhile, normal organoids can be used to model cancer evolution after the introduction of oncogenic mutations. By using the time-lapse microscopic imaging, tumor cell behaviors can be monitored in real-time. Similar to cell lines, cancer organoid lines can be expanded and cryopreserved to establish a living organoid biobank
Fig. 2Patient-derived cancer organoids can be derived from surgically resected/biopsied tissues and circulating tumor cells. Additionally, using the gene-editing technique, normal organoids can be mutated into tumor organoids
Cancer organoid biobanks from various patients
| Cancer types | Cancer organoid types in biobank | Success rate of establishment | Source | Passages | Institution | Refs |
|---|---|---|---|---|---|---|
| Metastatic gastrointestinal cancers | ~78 metastatic cancer organoids from 71 patients | 71% | Biopsies | Support | The Institute of Cancer Research, UK | [ |
| CRC | 22 cancer organoids from 27 tumor samples | ~90% | Surgically resected | Support | Royal Netherlands Academy of Arts and Sciences, Holland | [ |
| CRC | 55 cancer organoids from 43 patients | 100% | Biopsies, surgically resected | Support | Keio University, Japan | [ |
| Breast cancers | > 100 cancer organoids from 155 tumors | >80% | Surgically resected | > 20 passages | Royal Netherlands Academy of Arts and Sciences, Holland | [ |
| Pancreatic ductal adenocarcinoma | 114 cancer organoids from 101 patients | 75% | Biopsies, surgically resected, rapid autopsies | ≥ 5 passages | Cold Spring Harbor Laboratory, America | [ |
Fig. 3a A vascularized organ-on-a-chip model was utilized to analyze BC cell invasion and metastasis through a microvascular network. b A multi-organ-on-a-chip system was composed of a “primary site” and three “main sites of metastatic”. This microfluidic system was used to model lung cancer metastasis to distant organs, which provided an experimental platform to analyze cell-microenvironment interactions in organ-specific metastasis. c Schematic diagram of the 3D bioprinting technology for organ-on-a-chip models. d An extrusion-based bioprinting platform that interrogates the paracrine loop between BC cells and macrophages in different geometric arrangement. An extrusion-based 3D bioprinting technique for constructing breast cancer metastasis model. e Fabrication of the 3D HeLa/hydrogel spheroids by 3D printing