Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

5230 - CANscript™ as a Patient-Derived Predictive Platform for individualizing Treatment in Lung Cancer

Date

20 Oct 2018

Session

Poster display session: Biomarkers, Gynaecological cancers, Haematological malignancies, Immunotherapy of cancer, New diagnostic tools, NSCLC - early stage, locally advanced & metastatic, SCLC, Thoracic malignancies, Translational research

Presenters

Govind Babu

Citation

Annals of Oncology (2018) 29 (suppl_8): viii649-viii669. 10.1093/annonc/mdy303

Authors

G. Babu1, K. Deepak2, B. Balakrishnan3, M. Biswas4, A. Prasath3, P. Radhakrishnan5, A. Chatterjee3, S. Thiyagarajan3, P. Chaudhuri3, P.K. Majumder5

Author affiliations

  • 1 Kidwai Memorial Institute Of Oncology, HCG Curie Centre of Oncology, 560029 - Bangalore/IN
  • 2 Medical Oncology, Kidwai Memorial Institute of Oncology, 560029 - Bangalore/IN
  • 3 Cancer biology, Mitra Biotech, 560099 - Bangalore/IN
  • 4 Molecular Pathology, Mitra Biotech, 560029 - Bangalore/IN
  • 5 Cancer biology, Mitra Biotech, 01801 - Woburn/US
More

Resources

Abstract 5230

Background

Lung cancer causes nearly 1.69 million deaths globally and 5-year survival rate is less than 20%. Several biomarkers have improved treatment selection and overall prognosis in lung cancer to some extent (JNCCN; 2017;15:504). However, clinical relevance of these biomarkers is limited to only a small percentage of patients. Hence, there is a need for an individulized tool that can accurately predict an individual’s response to a therapy, especially in scenarios where there is a choice of equivalent treatment regimens and no specific biomarkers.

Methods

CANscript™ effectively recreates a patient’s tumor microenvironment ex vivo by preserving the native contexture. The platform provides phenotypic assessment of response to the drug(s) tested for a given tumor and generates clinically relevant predictions for real-time treatment selection (Nat. Commun. 2014, 6:6169 ). We used this platform to assese phenotypic response of lung tumors.

Results

Twenty-one lung cancer patient tumors were treated with one or more FDA approved regimens including targeted therapy and chemotherapy in CANscript platform. We did not observe any advantage of targeted therapy (EGFR, PD1 inhibitors) over chemotherapy. Six tumors, which were non-responders to gefitinib, were predicted responders to carboplatin/pemetrexed and/or carboplatin/docetaxel. Further, out of 4 gefitinib responders, 3 were predicted to respond to chemotherapies carboplatin/pemetrexed or carboplatin/docetaxel. Highest efficacy was observed in carboplatin/pemetrexed and carboplatin/docetaxel (47% and 46% respectively). 25% tumors treated with anti-PD1 responded to the therapy, matching the reported clinical response rate of anti-PD-1 therapy.

Conclusions

CANscript™ is used as an ex-vivo, personalized platform that can predict an individual’s response to various classes of anticancer drugs. The platform has been validated over a large number of clinical samples and the current study indicates that CANscript is a preferred platform for selecting individualized drug responses for treatment of lung cancer.udy indicates that CANscript is a preferred platform for selecting individualized drug responses for treatment of lung cancer.

Clinical trial identification

Legal entity responsible for the study

Mitra Biotech and Kidwai Memorial Institute of Oncology.

Funding

Has not received any funding.

Editorial Acknowledgement

Disclosure

G. Babu: Consultant: HCG Hospital, Mitra Biotech. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.