Cell Line Derived 5-FU and Irinotecan Drug-Sensitivity Profiles Evaluated in Adjuvant Colon Cancer Trial Data

A novel drug specific mRNA biomarker predictor for selection of patients responding to dovitinib treatment of advanced renal cell carcinoma and other solid tumors

PURPOSE

Dovitinib is a receptor tyrosine kinase inhibitor of VEGFR1-3, PDGFR, FGFR1/3, c-KIT, FLT3 and topoisomerase 1 and 2. The drug response predictor (DRP) biomarker algorithm or DRP-Dovitinib is being developed as a companion diagnostic to dovitinib and was applied retrospectively.

PATIENTS AND METHODS

Archival tumor samples were obtained from consenting patients in a phase 3 trial comparing dovitinib to sorafenib in renal cell carcinoma patients and the DRP-Dovitinib was applied. The biomarker algorithm combines the expression of 58 messenger RNAs relevant to the in vitro sensitivity or resistance to dovitinib, including genes associated with FGFR, PDGF, VEGF, PI3K/Akt/mTOR and topoisomerase pathways as well as ABC drug transport, and provides a likelihood score between 0-100%.

RESULTS

The DRP-Dovitinib divided the dovitinib treated RCC patients into two groups, sensitive (n = 49, DRP score >50%) or resistant (n = 86, DRP score ≤ 50%) to dovitinib. The DRP sensitive population was compared to the unselected sorafenib arm (n = 286). Median progression-free survival (PFS) was 3.8 months in the DRP sensitive dovitinib arm and 3.6 months in the sorafenib arm (hazard ratio 0.71, 95% CI 0.51-1.01). Median overall survival (OS) was 15.0 months in the DRP sensitive dovitinib arm and 11.2 months in the sorafenib arm (hazard ratio 0.69, 95% CI 0.48-0.99). The observed clinical benefit increased with increasing DRP score. At a cutoff of 67% the median OS was 20.6 months and the median PFS was 5.7 months in the dovitinib arm. The results were confirmed in five smaller phase II trials of dovitinib which showed a similar trend.

CONCLUSION

The DRP-Dovitinib shows promise as a potential biomarker for identifying advanced RCC patients most likely to experience clinical benefit from dovitinib treatment, subject to confirmation in an independent prospective trial of dovitinib in RCC patients.

Molecular Biomarker of Drug Resistance Developed From Patient-Derived Organoids Predicts Survival of Colorectal Cancer Patients

The drug 5-fluorouracil (5-Fu) is the critical composition of colorectal cancer (CRC) treatments. Prognostic and predictive molecular biomarkers for CRC patients (CRCpts) treated with 5-Fu-based chemotherapy can provide assistance for tailoring treatment approach. Here, we established a molecular biomarker of 5-Fu resistance derived from colorectal cancer organoids (CRCOs) for predicting the survival of CRCpts. Forty-one CRCO cultures were generated from 50 CRC tumor tissues after surgery (82%). The following experiments revealed a great diversity in drug sensitivity for 10 μM 5-Fu treatment tested by using organoid size change. Fourteen cases (34.1%) were 5-Fu sensitive and the other 27 (65.9%) were resistant. Then, differentially expressed genes (DEGs) associated with 5-Fu resistance were outputted by transcriptome sequencing. In particular, DEGs were generated in two comparison groups: 1) 5-Fu sensitive and resistant untreated CRCOs; 2) CRCOs before 5-Fu treatment and surviving CRCOs after 5-Fu treatment. Some molecules and most of the pathways that have been reported to be involved in 5-Fu resistance were identified in the current research. By using DEGs correlated with 5-Fu resistance and survival of CRCpts, the gene signature and drug-resistant score model (DRSM) containing five molecules were established in The Cancer Genome Atlas (TCGA)-CRC cohort by least absolute shrinkage and selection operator (LASSO) regression analysis and 5-fold cross-validation. Multivariate analysis revealed that drug-resistant score (DRS) was an independent prognostic factor for overall survival (OS) in CRCpts in TCGA-CRC cohort (P < 0.001). Further validation results from four Gene Expression Omnibus (GEO) cohorts elucidated that the DRSM based on five genes related to 5-Fu chemosensitivity and developed from patient-derived organoids can predict survival of CRCpts. Meanwhile, our model could predict the survival of CRCpts in different subgroups. Besides, the difference of molecular pathways, tumor mutational burden (TMB), immune response-related pathways, immune score, stromal score, and immune cell proportion were dissected between DRS-high and DRS-low patients in TCGA-CRC cohort.

Prediction of fulvestrant efficacy in patients with advanced breast cancer: retrospective-prospective evaluation of the predictive potential of a multigene expression assay

BACKGROUND

Fulvestrant is a selective oestrogen receptor (ER) degrader used as monotherapy and combination therapy for ER positive HER2 negative advanced breast cancer (ABC) in postmenopausal women. The drug response predictor (DRP), is a mathematical algorithm based on the expression of multiple genes in the tumour. The fulvestrant DRP algorithm has previously shown effect in BC. In this study, we investigated the DRP's potential in predicting fulvestrant benefit.

METHOD

Among 695 patients with ABC prospectively included in a Danish Breast Cancer Cooperative Group (DBCG) cohort we retrospectively included 226 patients who received fulvestrant as monotherapy. The DRP result was based on mRNA extracted from tumour biopsies and analysed using Affymetrix array. Primary endpoint was time to progression (TTP).

RESULTS

For patients who received fulvestrant in line one to four and were previously unexposed to adjuvant endocrine therapy, we identified a hazard ratio (HR) of 0.44 (90% confidence interval (90% CI) upper limit of 1.08, one sided p = 0.066) for a predicted positive vs negative outcome. A weaker association was seen when including patients exposed to adjuvant endocrine treatment or received fulvestrant in fifth or later lines. Exploratory analyses showed that the DRP was efficient when using recent biopsies for DRP estimate and among recently treated patients.

CONCLUSION

The DRP showed a potential in predicting fulvestrant treatment but was not significant in the overall analysis. Use of older biopsies, long-term endocrine treatment and multiple therapies between biopsy used for analysis and fulvestrant treatment, probably affect the predictive accuracy.

Predicting efficacy of epirubicin by a multigene assay in advanced breast cancer within a Danish Breast Cancer Cooperative Group (DBCG) cohort: a retrospective-prospective blinded study

Purpose

Anthracyclines remain a cornerstone in the treatment of primary and advanced breast cancer (BC). This study has evaluated the predictive value of a multigene mRNA-based drug response predictor (DRP) in the treatment of advanced BC with epirubicin. The DRP is a mathematical method combining in vitro sensitivity and gene expression with clinical genetic information from > 3000 clinical tumor samples.

Methods

From a DBCG cohort, 140 consecutive patients were treated with epirubicin between May 1997 and November 2016. After patient informed consent, mRNA was isolated from archival formalin-fixed paraffin-embedded primary breast tumor tissue and analyzed using Affymetrix arrays. Using time to progression (TTP) as primary endpoint, the efficacy of epirubicin was analyzed according to DRP combined with clinicopathological data collected retrospectively from patients’ medical records. Statistical analysis was done using Cox proportional hazards model stratified by treatment line.

Results

Median TTP was 9.3 months. The DRP was significantly associated to TTP (P = 0.03). The hazard ratio for DRP scores differing by 50 percentage points was 0.55 (95% CI –0.93, one-sided). A 75% DRP was associated with a median TTP of 13 months compared to 7 months following a 25% DRP. Multivariate analysis showed that DRP was independent of age and number of metastases.

Conclusion

The current study prospectively validates the predictive capability of DRP regarding epirubicin previously shown retrospectively allowing the patients predicted to be poor responders to choose more effective alternatives. Randomized prospective studies are needed to demonstrate if such an approach will lead to increased overall survival.

Molecular prediction of adjuvant cisplatin efficacy in Non-Small Cell Lung Cancer (NSCLC)-validation in two independent cohorts

INTRODUCTION

Effective predictive biomarkers for selection of patients benefiting from adjuvant platinum-based chemotherapy in non-small cell lung cancer (NSCLC) are needed. Based on a previously validated methodology, molecular profiles of predicted sensitivity in two patient cohorts are presented.

METHODS

The profiles are correlations between in vitro sensitivity to cisplatin and vinorelbine and baseline mRNA expression of the 60 cell lines in the National Cancer Institute panel. An applied clinical samples filter focused the profiles to clinically relevant genes. The profiles were tested on 1) snap-frozen tumors from 133 patients with completely resected stage 1B-2 NSCLC randomized to adjuvant cisplatin and vinorelbine (ACV, n = 71) or no adjuvant treatment (OBS, n = 62) and 2) formalin-fixed paraffin-embedded (FFPE) tumors from 95 patients with completely resected stage 1A-3B NSCLC receiving adjuvant cisplatin and vinorelbine.

RESULTS

The combined cisplatin and vinorelbine profiles showed: 1) univariate Hazard Ratio (HR) for sensitive versus resistant of 0.265 (95% CI:0.079-0.889, p = 0.032) in the ACV cohort and a HR of 0.28 in a multivariate model (95% CI:0.08-1.04, p = 0.0573); 2) significant prediction at 3 year survival from surgery in univariate (HR = 0.138 (95% CI:0.035-0.537), p = 0.004) and multivariate analysis (HR = 0.14 (95% CI:0.030-0.6), p = 0.0081). No discrimination was found in the OBS cohort (HR = 1.328, p = 0.60). The cisplatin predictor alone had similar figures with 1) univariate HR of 0.37 (95% CI:0.12-1.15, p = 0.09) in the ACV cohort and 2) univariate HR of 0.14 (95% CI:0.03-0.59, p = 0.0076) to three years. Functional analysis on the cisplatin profile revealed a group of upregulated genes related to RNA splicing as a part of DNA damage repair and apoptosis.

CONCLUSIONS

Profiles derived from snap-frozen and FFPE NSCLC tissue were prognostic and predictive in the patients that received cisplatin and vinorelbine but not in the cohort that did not receive adjuvant treatment.

Optimization of a Neural Stem-Cell-Mediated Carboxylesterase/Irinotecan Gene Therapy for Metastatic Neuroblastoma

Despite improved survival for children with newly diagnosed neuroblastoma (NB), recurrent disease is a significant problem, with treatment options limited by anti-tumor efficacy, patient drug tolerance, and cumulative toxicity. We previously demonstrated that neural stem cells (NSCs) expressing a modified rabbit carboxylesterase (rCE) can distribute to metastatic NB tumor foci in multiple organs in mice and convert the prodrug irinotecan (CPT-11) to the 1,000-fold more toxic topoisomerase-1 inhibitor SN-38, resulting in significant therapeutic efficacy. We sought to extend these studies by using a clinically relevant NSC line expressing a modified human CE (hCE1m6-NSCs) to establish proof of concept and identify an intravenous dose and treatment schedule that gave maximal efficacy. Human-derived NB cell lines were significantly more sensitive to treatment with hCE1m6-NSCs and irinotecan as compared with drug alone. This was supported by pharmacokinetic studies in subcutaneous NB mouse models demonstrating tumor-specific conversion of irinotecan to SN-38. Furthermore, NB-bearing mice that received repeat treatment with intravenous hCE1m6-NSCs and irinotecan showed significantly lower tumor burden (1.4-fold, p = 0.0093) and increased long-term survival compared with mice treated with drug alone. These studies support the continued development of NSC-mediated gene therapy for improved clinical outcome in NB patients.