Organ-on-Chip platforms to study tumor evolution and chemosensitivity

Venzil Lavie Dsouza, Raviprasad Kuthethur, Shama Prasada Kabekkodu, Sanjiban Chakrabarty

Research output: Contribution to journalReview articlepeer-review

10 Citations (Scopus)


Despite tremendous advancements in oncology research and therapeutics, cancer remains a primary cause of death worldwide. One of the significant factors in this critical challenge is a precise diagnosis and limited knowledge on how the tumor microenvironment (TME) behaves to the treatment and its role in chemo-resistance. Therefore, it is critical to understand the contribution of a heterogeneous TME in cancer drug response in individual patients for effective therapy management. Micro-physiological systems along with tissue engineering have facilitated the development of more physiologically relevant platforms, known as Organ-on-Chips (OoC). OoC platforms recapitulate the critical hallmarks of the TME in vitro and subsequently abet in sensitivity and efficacy testing of anti-cancer drugs before clinical trials. The OoC platforms incorporating conventional in vitro models enable researchers to control the cellular, molecular, chemical, and biophysical parameters of the TME in precise combinations while analyzing how they contribute to tumor progression and therapy response. This review discusses the application of OoC platforms integrated with conventional 2D cell lines, 3D organoids and spheroid models, and the organotypic tissue slices, including patient-derived and xenograft tumor slice cultures in cancer treatment responses. We summarize the relevance and drawbacks of conventional in vitro models in assessing cancer treatment response, challenges and limitations associated with OoC models, and future opportunities enabled by the OoC technologies towards developing personalized cancer diagnostics and therapeutics.

Original languageEnglish
Article number188717
JournalBiochimica et Biophysica Acta - Reviews on Cancer
Issue number3
Publication statusPublished - 05-2022

All Science Journal Classification (ASJC) codes

  • Oncology
  • Genetics
  • Cancer Research


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