Genomic characteristics and drug screening among organoids derived from non-small cell lung cancer patients

Abstract

Background: Patient-derived organoid (PDO) models are highly valuable and have potentially widespread clinical applications. However, limited information is available regarding organoid models of non-small cell lung cancer (NSCLC). This study aimed to characterize the consistency between primary tumors in NSCLC and PDOs and to explore the applications of PDOs as preclinical models to understand and predict treatment response during lung cancer.

Methods: Fresh tumor samples were harvested for organoid culture. Primary tumor samples and PDOs were analyzed via whole-exome sequencing. Paired samples were subjected to immunohistochemical analysis. There were 26 antineoplastic drugs tested in the PDOs. Cell viability was assessed using the Cell Titer Glo assay 7-10 days after drug treatment. A heatmap of log-transformed values of the half-maximal inhibitory concentrations was generated on the basis of drug responses of PDOs through nonlinear regression (curve fit). A total of 12 patients (stages I-III) were enrolled, and 7 paired surgical tumors and PDOs were analyzed.

Results: PDOs retained the histological and genetic characteristics of the primary tumors. The concordance between tumors and PDOs in mutations in the top 20 NSCLC-related genes was >80% in five patients. Sample purity was significantly and positively associated with variant allele frequency (Pearson r = 0.82, P = 0.0005) and chromosome stability. The in vitro response to drug screening with PDOs revealed high correlation with the mutation profiles in the primary tumors.

Conclusions: PDOs are highly credible models for detecting NSCLC and for prospective prediction of the treatment response for personalized precision medicine.

Key points: Lung cancer organoid models could save precious time of drug testing on patients, and accurately select anticancer drugs according to the drug sensitivity results, so as to provide a powerful supplement and verification for the gene sequencing.

Keywords: Consistency analysis; drug screening; non-small cell lung cancer; patient-derived organoid; whole exome sequencing.

Figure 1

Patient‐derived organoids (PDOs) of NSCLC recapitulate the parental tumor. (a) The PDO phenotype was observed with a bright field microscope, as shown by the black arrows, after one week of culture. Scale bar, 100 μm. (b) Morphological changes of PDOs after the stated number of days in culture. P4 is squamous cell carcinoma; all others are adenocarcinoma. Scale bar, 100 μm. (c) HE‐stained and IHC images of PDOs and their parental tumor tissues. ADC marker TTF‐1 and SCC marker p63 were expressed in tumor tissues and corresponding organoids, respectively. ADC, adenocarcinoma; HE, hematoxylin‐eosin staining; IHC, immunohistochemistry; NSCLC, non‐small cell lung cancer; PDO, patient‐derived organoid; SCC, squamous cell carcinoma; T, tumor; TTF‐1, thyroid transcription factor‐1.

Figure 2

Genotypic features of the paired samples. (a) Heat map of the germline mutations in the peripheral blood, organoids, and tumor tissues of each patient. (b) Mutations detected in paired tissues (tumor and organoid) on the basis of gene mutations in lung cancer (top 20 genes are shown) Patient () P1, () P4, () P5, () P6, () P7, () P9, and () P11; Mutation () Missense, () Nonsense, () Frame Shift, () Splicing, () In Frame Indel; Type () Tumor, and () Organoid. (c) Concordance of somatic mutations detected in the organoid and corresponding tumor tissue () Concordant, () Organoid only, and () Tumor only. (d) Mutation signature distributions of organoid lines and tumor tissues in each patient. Signature types are displayed in the right panel. C > A, C > G, and C > T were the most common point mutations in our paired samples Point mutation type () C>A, () C>G, () C>T, () T>A, () T>C, and () T>G.

Figure 3

The association between tumor cell purity and VAF. (a) Correlation between the purity of the organoids and corresponding tumor samples and the median VAF () Tumor, and () Organoid. (b) Comparison of VAF distributions of common mutations in organoids and tumor tissues of each patient () Tumor, and () Organoid. (c) Correlation analysis of total mutations with VAF in organoids and tumor tissues in each patient. (d) Circos analysis of paired samples in the chromosomal context of PDOs. The outer layer represents the chromosome location; inner rings, CNVs at different chromosome loci. Red and green colors represent gains and losses in DNA copy number, respectively. CNV, copy number variation; VAF, variant allele frequency.

Figure 4

Heat map of drug response in Pptient‐derived organoids (PDOs). (a) The sensitivity to EGFR‐TKIs was analyzed in P1, P6, and P11, which harbored EGFR mutations () EGFR L858R, and () EGFR EX20ins. (b) The chemotherapeutic sensitivity was analyzed in P1, P6, and P11 () EGFR L858R, and () EGFR EX20ins. (c) Drug sensitivity screening was performed in P9, which harbored a KRAS mutation, using EGFR‐TKIs () Afatinib, () Erlotinib, () Gefitinib, () Icotinib, () Neratinib, and () Osimertinib and chemotherapy drugs () Methotrexate, () Cytarabine, () Cisplatin, () Carboplatin, () Docetaxel, () Etoposide, () Gemcitabine, () Irinotecan, () Paclitaxel, () Pemetrexed, () Topotecan, () Vincristine, () Vinorelbine, and () Cephalomannine. EGFR‐TKI, epidermal growth factor receptor tyrosine kinase inhibitor; PDO, patient‐derived organoid.