Curated Papers > High-impact authoritative literature on "organoids"

Organoid Models of Human Liver Cancers Derived from Tumor Needle Biopsies.

Literature Information

DOI	10.1016/j.celrep.2018.07.001
PMID	30067989
Journal	Cell reports
Impact Factor	6.9
JCR Quartile	Q1
Publication Year	2018
Times Cited	253
Keywords	Biobank, cholangiocellular carcinoma, drug response, genetic heterogeneity, hepatocellular carcinoma
Literature Type	Journal Article, Research Support, Non-U.S. Gov't
Pages	1363-1376
Issue	24(5)
Authors	Sandro Nuciforo, Isabel Fofana, Matthias S Matter, Tanja Blumer, Diego Calabrese, Tujana Boldanova, Salvatore Piscuoglio, Stefan Wieland, Femke Ringnalda, Gerald Schwank, Luigi M Terracciano, Charlotte K Y Ng, Markus H Heim

TL;DR

This study addresses the limitations of current in vitro models for hepatocellular carcinoma (HCC) by generating long-term organoid cultures from tumor biopsies, which maintain the tumor's morphology, genetic heterogeneity, and marker expression. These organoids not only offer a relevant model for studying HCC but also serve as a platform for testing drug sensitivity, potentially aiding in the development of personalized therapies for patients.

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Biobank · cholangiocellular carcinoma · drug response · genetic heterogeneity · hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the second most frequent cause of cancer-related mortality worldwide. The multikinase inhibitor sorafenib is the only treatment option for advanced HCC. Due to tumor heterogeneity, its efficacy greatly varies between patients and is limited due to adverse effects and drug resistance. Current in vitro models fail to recapitulate key features of HCCs. We report the generation of long-term organoid cultures from tumor needle biopsies of HCC patients with various etiologies and tumor stages. HCC organoids retain the morphology as well as the expression pattern of HCC tumor markers and preserve the genetic heterogeneity of the originating tumors. In a proof-of-principle study, we show that liver cancer organoids can be used to test sensitivity to sorafenib. In conclusion, organoid models can be derived from needle biopsies of liver cancers and provide a tool for developing tailored therapies.

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Primary Questions Addressed

1. What are the potential advantages of using organoid models over traditional in vitro models for studying hepatocellular carcinoma?
2. How might the genetic heterogeneity preserved in organoid cultures influence the development of personalized therapies for HCC?
3. What specific tumor markers were retained in the organoid cultures, and how do they correlate with patient outcomes?
4. In what ways could organoid models contribute to understanding the mechanisms of drug resistance in HCC?
5. How do the findings from organoid studies compare with clinical outcomes in patients treated with sorafenib for advanced HCC?

Key Findings

Research Background and Objectives

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer and a leading cause of cancer-related mortality globally. The current treatment options, primarily the multikinase inhibitor sorafenib, are limited in efficacy due to tumor heterogeneity, leading to variable patient responses and the development of drug resistance. This study aims to establish long-term organoid cultures from tumor needle biopsies of HCC patients to better model the disease and evaluate therapeutic responses.

Main Methods/Materials/Experimental Design

The study utilized a coaxial needle biopsy technique to obtain tumor samples from patients with varying stages and etiologies of HCC. The organoid cultures were established from these biopsies and characterized through histopathological analysis, immunohistochemistry, and genomic sequencing.

• Biopsy Procedure: Ultrasound-guided coaxial needle biopsies were performed to collect multiple samples from the same tumor location.
• Organoid Generation: Tumor tissue was minimally digested and cultured in a specialized medium to establish organoid lines.
• Characterization: Organoids were analyzed for histological features, marker expression, and genetic profiles, maintaining characteristics of the original tumors.

Key Results and Findings

1. Organoid Establishment: The study successfully established 10 organoid lines from 8 patients, with a 26% success rate based on biopsy attempts.
2. Histological Recapitulation: Organoids preserved the morphological features and differentiation grade of the original tumors, showing similar growth patterns and expression of tumor markers like alpha-fetoprotein (AFP).
3. Genetic Fidelity: Whole-exome sequencing revealed that organoids retained the somatic mutations and genetic alterations of the originating tumors, maintaining significant intratumoral heterogeneity.
4. Drug Response: Organoids exhibited variable sensitivity to sorafenib treatment, with IC50 values ranging from 2.0 to 5.0 μM, indicating potential for personalized therapy testing.

Main Conclusions/Significance/Innovation

The successful generation of organoids from HCC biopsies demonstrates a novel approach to modeling liver cancer that retains critical biological features of the original tumors. These organoids can serve as a valuable tool for understanding tumor biology, exploring drug responses, and developing personalized treatment strategies for HCC patients.

Research Limitations and Future Directions

• Limited Success Rate: The overall success rate for organoid establishment was lower compared to other cancers, possibly due to the nature of hepatocytes.
• Subclonal Representation: The study found that organoids may not capture all subclonal mutations, which could affect therapeutic predictions.
• Need for Further Optimization: Future work should focus on refining culture conditions to improve the derivation efficiency of organoids from a broader range of HCC cases.
• Clinical Validation: Further studies are needed to correlate organoid drug response with patient outcomes to validate their utility in clinical settings.

In summary, this research establishes a foundational model for HCC that could enhance drug development and personalized medicine approaches, addressing a significant unmet need in liver cancer treatment.

References

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Literatures Citing This Work

1. Organoid technology and applications in cancer research. - Hanxiao Xu;Xiaodong Lyu;Ming Yi;Weiheng Zhao;Yongping Song;Kongming Wu - Journal of hematology & oncology (2018)
2. Platinum Resistance in Ovarian Cancer: Role of DNA Repair. - Giovanna Damia;Massimo Broggini - Cancers (2019)
3. Organoid models for translational pancreatic cancer research. - Hervé Tiriac;Dennis Plenker;Lindsey A Baker;David A Tuveson - Current opinion in genetics & development (2019)
4. Remodelling and Improvements in Organoid Technology to Study Liver Carcinogenesis in a Dish. - Umesh Tharehalli;Michael Svinarenko;André Lechel - Stem cells international (2019)
5. Application of Cancer Organoid Model for Drug Screening and Personalized Therapy. - Jumpei Kondo;Masahiro Inoue - Cells (2019)
6. Liver organoids: from basic research to therapeutic applications. - Nicole Prior;Patricia Inacio;Meritxell Huch - Gut (2019)
7. Hepatocellular Carcinoma Xenografts Established From Needle Biopsies Preserve the Characteristics of the Originating Tumors. - Tanja Blumer;Isabel Fofana;Matthias S Matter;Xueya Wang;Hesam Montazeri;Diego Calabrese;Mairene Coto-Llerena;Tujana Boldanova;Sandro Nuciforo;Venkatesh Kancherla;Luigi Tornillo;Salvatore Piscuoglio;Stefan Wieland;Luigi M Terracciano;Charlotte K Y Ng;Markus H Heim - Hepatology communications (2019)
8. Gene manipulation in liver ductal organoids by optimized recombinant adeno-associated virus vectors. - Jinsong Wei;Gai Ran;Xin Wang;Ning Jiang;Jianqing Liang;Xinhua Lin;Chen Ling;Bing Zhao - The Journal of biological chemistry (2019)
9. A Pharmacogenomic Landscape in Human Liver Cancers. - Zhixin Qiu;Hong Li;Zhengtao Zhang;Zhenfeng Zhu;Sheng He;Xujun Wang;Pengcheng Wang;Jianjie Qin;Liping Zhuang;Wei Wang;Fubo Xie;Ying Gu;Keke Zou;Chao Li;Chun Li;Chenhua Wang;Jin Cen;Xiaotao Chen;Yajing Shu;Zhao Zhang;Lulu Sun;Lihua Min;Yong Fu;Xiaowu Huang;Hui Lv;He Zhou;Yuan Ji;Zhigang Zhang;Zhiqiang Meng;Xiaolei Shi;Haibin Zhang;Yixue Li;Lijian Hui - Cancer cell (2019)
10. Disease modelling in human organoids. - Madeline A Lancaster;Meritxell Huch - Disease models & mechanisms (2019)

... (243 more literatures)

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