Combining Organoid Models with Next-Generation Sequencing to Reveal Tumor Heterogeneity and Predict Therapeutic Response in Breast Cancer

Abstract

Estrogen receptor-positive (ER+) breast cancer (BC) is a common subtype of BC with a relatively good prognosis. However, recurrence and death from ER+ BC occur because of tumor heterogeneity. This study aimed to explore tumor heterogeneity using next-generation sequencing (NGS) and tumor-organoid models to promote BC precise therapy. We collected needle biopsy, surgical excision, and cerebrospinal fluid (CSF) samples to establish tumor organoids. We found that the histological characteristics of organoids were consistent with original lesions and recapitulated their heterogenicity. In addition, the NGS results showed that PIK3CA and TP53 genes had detrimental mutations. BAP1, RET, AXIN2, and PPP2R2A genes had mutations with unknown function. The score for homologous recombination deficiency (HRD) of genome was 56, indicating that the tumor was likely sensitive to PARPi. The mutant-allele tumor heterogeneity (MATH) value of the tumor genome was 68.03, indicating high tumor heterogeneity. At last, we performed a drug screening on organoids. The toxicity of different drugs toward BC organoids originated from needle biopsy and surgical excision was tested, respectively. The IC50 values in the needle biopsy groups were paclitaxel 2.83 μM, carboplatin 61.47 μM, neratinib 0.8 μM, lapatinib >100 μM; in the surgical excision groups: trastuzumab >100 μM, docetaxel 0.036 μM, tamoxifen 20.54 μM, olaparib 5.478 μM, BYL719 < 0.1 μM. The toxicity data showed that the BC organoids could show dynamic characteristics of tumor progression and reflect the heterogeneity of BC. Our study demonstrates that the combined use of tumor organoids and NGS is a potential way to test tumor heterogeneity and predict drug response in ER + BC, which contributes to the development of personalized therapy.

Emerging roles of 3D-culture systems in tackling tumor drug resistance

“…Resveratrol treatment with subsequent hypoxia inhibition partially re-sensitized cells to doxorubicin treatment, highlighting the relevance of these 3D preclinical models in the study of resistance mechanisms. Conversely, data obtained in monolayers were not able to recapitulate in vivo conditions and efficacy was overestimated when tested in a 2D context [75] . To investigate recurrence mechanisms in ER+ BC, tumor organoids were generated from needle biopsy, surgical excision, and cerebrospinal fluid samples.…”

“…Next generation sequencing (NGS) analysis revealed detrimental mutations in PIK3CA and TP53 genes and mutations of unknown functions in BAP1, RET, AXIN2, and PPP2R2A. Drug screening in BC organoids allowed for the evaluation of drug toxicity and showed dynamic changes in tumor progression, reflecting the heterogeneity of BC and demonstrating their reliability as models for personalized medicine development [ 76 ] . In ER+ positive BC cells, the recurrent deletion of 16q12.2 affects AKTIP, which governs tumorigenesis, specifically in ER+ positive BC cells.…”

Flourishing tumor organoids: History, emerging technology, and application

“…It also allows drug screening and safety testing to determine which patients are most likely to benefit from it and to develop an appropriate treatment plan (Figure 6a-d). [199][200][201][202][203] A proven treatment regimen will help increase patient survival and improve quality of life. 204 Vlachogiannis et al 200 tional precision medicine research methods.…”

“…(d) Drug response prediction for PDOs and NGS and clinical response. (Reproduced with permission from Reference 202. Copyright 2022, Y. Liu et al).…”

Organoid Models and Next-Generation Sequencing for Bone Marrow and Related Disorders

“…Once the models can partially mimic the physiological conditions, NGS can be used to confirm the genetic landscape of the physiological conditions and explore and predict therapeutic responses. The combination of organoid and NGS technology has already been attempted to investigate breast cancer organoids [128] and retinal organoids [129]. As quoted by the creators of 'OrganoidDB', similar platforms could not only 'facilitate a better understanding of organoids' but additionally seek to improve current organoid culture protocols to model organoids that 'fully recapitulate the structure of the modelled organs' [96].…”