Lung cancer organoids rapidly predict patient drug responses

rapid no-chip test to predict patient responses with lung cancer

Date: 12th May 2021

Despite the increasing availability of therapeutic drugs and advances in next generation immunotherapies, lung cancer is the leading cause of cancer mortality worldwide, responsible for ~1.8 million deaths in 2020. This is, in part, due to a lack of accurate predictions of patient outcomes, causing a hinderance in the selection process of appropriate and prompt treatment regimes. Now, researchers have developed a one-week drug test using patient-derived lung cancer organoids (LCOs) that predict patient therapeutic responses with 100% accuracy and specificity.

Organoid-based systems are emerging and recognised in the biomedical field as a robust and reliable developing technology broadening the scope for developmental biology, disease modelling and drug screening.  They are becoming an important tool to complement, and hopefully provide an alternative to, animal experiments.

There is a growing body of evidence that has demonstrated that the phenotypic and genotypic concordance between the original patient tumour tissue and generated tumour organoid is high, and that they can deliver a high success rate of prognosing clinical responses of individual patients to therapies.

However, despite having promising potential, translation to the clinic of PDO-based drug tests (patient-derived organoids) has been hindered as time-to-results can be several weeks, even months, due to limited numbers of PDOs deriving from patient samples which then results in the requirement for prolonged in vitro expansions. In addition, the current success rate of establishing PDOs with steady expansion rates for tumours is either undetermined or low.

Now, researchers led by Peng Lui at Tsinghua University, Jun Wang at Peking University, and Xiaofang Chen at Beihang University, China, have generated LCOs from surgically resected and biopsy tumour tissues, and by employing an integrated superhydrophobic microwell array chip, InSMAR-chip, show that the hundreds of LCOs generated at passage 0 are sufficient to produce clinically meaningful drug responses within a week.

To overcome the technical challenges of establishing suitable large numbers of LCOs from patient samples the team developed a set of methodologies and exploited microfabricated array devices, that reduced reaction volumes of the PDO-based drug tests in order to avoid prolonged expansions cultures.

To start, a mechanical sample processing method was developed to generate sufficient numbers of LCOs from patient tumour tissues in ~3 days, and produced higher numbers of organoids than conventional enzyme digestions. These LCOs retained the histological and genetic features of the original tumour tissue.

The LCOs were then cultured on a nanoliter scale, on an integrated superhydrophobic microwell array chip, InSMAR-chip, on which the responses to drugs could be measured. A 6-day drug sensitivity test on the InSMAR-chip to evaluate the responses of the LCOs to multiple anticancer drugs demonstrated that the drug–response curve measured on the chip perfectly overlapped with conventional methods (96-well plate).

With the assay set up, and the reliability of the on-chip system to measure cell viability verified, the team wanted to test the system using clinically relevant samples. Here, they used 21 patient samples and examined the effects of commonly used anti-lung cancer drugs on the resulting LCOs, obtaining the results within a week of surgery.  The tests of patient samples demonstrated that the drug responses of the LCOs correlated highly with genetic mutations and the reported clinic outcomes.  Furthermore, the chip assay was also able to represent the chemotherapy response to tumour heterogeneity.

Overall, of the 21 patient samples, 10 LCOs – where the respective patient data and drug evaluations had been administered – tested on the InSMAR-chip corresponded to the clinical data, showing 100% accuracy and specificity.  Of the other 11 LCOs the clinical patient data was not directly comparably with the chip data, for example treatment regimes were different, or treatment had not been received at all.

Conclusions and future applications

The team here have successfully demonstrated that the one week InSAR-chip drug test using patient-derived lung cancer organoids can provide a 100% consistency with known clinical outcomes and genetic mutations.  The on-chip test could mirror acquired resistance of the patient, and was sensitive to the response heterogeneity of tumours to chemotherapies.

The LCO model coupled with the microwell device provides a technically feasible means for predicting the responses of in vivo  tumours to anticancer reagents, and for screening the most effective drugs and regimes in personalised cancer treatments in a clinical setting.  The team will be exploring the clinical translation further, focusing on a well-designed pilot study to assess the sensitivity and specificity of the assay.

Currently, one of the limiting features of the LCOs is that whilst the tumour can be recapitulated through the organoid, the microenvironment is not.  The team are hoping to introduce a coculture system in the near future to reflect this microenvironment.  This will broaden the applications for this chip assay, opening the doors to research immunotherapies.

The key to success for this technology has been the nanoscaling of reactions.  Other organoid research has also benefited from the fabrication of microcavity arrays aimed at advancing the industrialisation of organoids.  Furthermore, scientists have also developed nanoscale production of new active drugs, combining chemical synthesis, with analysis and biological testing on a single chip.  It was be interesting to see whether drugs developed in such a way could be also be screened on PDOs using the InSAR-chip assays.

It is also likely that the upstream process could also be refined.  For example, there is a newly emerging plethora of artificial intelligence models that can accelerate drug discovery, such as anti-senescence drug discovery platforms and the ability to predict cancer killing drug combinations. These types of algorithms could be leveraged as an initial tool to narrow down test-sets of highly effective drugs which can then be tested on the InSAR-chip, providing a more streamlined and rapid drug discovery workflow.

From a broader perspective it is probable that the InSAR-chip system will have far reaching applications beyond that of lung cancer.  Organoids can be used for various types of cancers, and can be models for many diseases.  As such, it is likely the platform will adapted and optimised with this in mind, and it will provide a rapid screen for testing many different drugs and therapies, accelerating personalised medicine and drug discovery.


Hu, Y., Sui, X., Song, F., Li, Y., Li, K., Chen, Z., Yang, F., Chen, X., Zhang, Y., Wang, X., et al. (2021). Lung cancer organoids analyzed on microwell arrays predict drug responses of patients within a week. Nature Communications 12, 2581.