Background

Baseline tumor size (BTS) is a known predictor of response to anti-PD(L)1 immune checkpoint inhibitors (ICI) in melanoma and NSCLC patients (pts), with lower BTS predicting better treatment outcome. However, no data are currently available on the role of BTS in other solid tumors as well as for next-generation immuno-oncology agents (NGIO).

Methods

We reviewed data of pts with any solid tumor consecutively treated at our institution from August 2014 to March 2019, receiving ≥1 dose of ICI and/or NGIO within phase 1 trials. Included drugs, alone or variously combined, were: monoclonal antibodies (mAb) targeting PD(L)1, CTLA4, LAG3, GITR, TIM3, NGK2A, CSF1R, anti-FAPα IL2v, bispecific anti-PD1/TGFß mAb, anti- IDO1 small molecule, intralesional oncolytic peptides or TLR7-agonist. BTS was calculated as ∑iRECIST 1.1 baseline target lesions. Pts were divided into two groups according to BTS (≤median, >median). Differences in terms of overall response rate (ORR), clinical benefit rate at 6 months (CBR6) and progression-free survival (PFS) were compared.

Results

150 pts were included in the analysis with: breast, ovarian, head & neck, colorectal, lung, mesothelioma, melanoma, pancreatic, uterine/cervical, transitional cell and other cancer types. 22 pts were pretreated with ICI. Median BTS was 79 mm (range 10-313); baseline LDH was more frequently elevated in pts with high BTS (68% vs 30%, p<0.001). Pts with low BTS achieved higher ORR (23% vs 4%, p<0.001), higher CBR6 (37% vs 14%, p<0.001) and longer median PFS (3.6 vs 1.9 months; p<0.001) compared with the high BTS group. By restricting the analysis to pts receiving a study regimen including an anti-PD1 agent (n=115), the benefit remained consistent, with higher ORR (31% vs 5%, p=0.002), numerically higher CBR6 (43% vs 17%, p=0.28) and longer median PFS (4.7 vs 2.1 months, p<0.001) in the low BTS group. The benefit was also significant in pts receiving NGIO for more immunogenic tumors (with at least 1 EMA approved ICI before March 2019) (n=55): higher ORR (45% vs 11.5%, p=0.006), numerically higher CBR (52% vs 23%, p=0.29) and longer median PFS (7 vs 2,3 months; p=0.003) in pts with low BTS.

Conclusion

Lower BTS is associated with better treatment outcome in pts with any solid tumor treated with NGIO.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

C. Criscitiello: Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self): Lilly; Honoraria (self): novartis; Honoraria (self), Advisory/Consultancy: Roche. G. Curigliano: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Seattle Genetics; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Lilly; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Ellipses Pharma; Honoraria (self): Foundation Medicine; Honoraria (self): Samsung. All other authors have declared no conflicts of interest.

Background

Cancer stem cells (CSC) are defined as cells with a tumor-initiating potential and are resistant to chemo-radiation therapy. Evasion of apoptosis is one of the hallmarks of human cancers attributed to CSCs. Human TRAIL/Apo-2L is a ligand of the TNF family that can trigger apoptotic cell death and has been demonstrated to induce apoptosis in a wide range of cancers. Interestingly, TRAIL receptor DR5 was found to be over-expressed in leukemic stem cells (LSCs). Inducing apoptosis in CSCs using TRAIL protein would be a novel and efficient strategy. We characterized and targeted the leukemic stem cells to induce self-death by TRAIL-based pathway. A fusion protein of IL2-TRAIL peptide was constructed to target leukemic cells over-expressing IL2 α receptor.

Methods

A chimeric recombinant construct was genetically engineered by fusing active peptide of human TRAIL with human IL2α gene. The LSCs were isolated from 13 leukemic patients using specific LSC markers by FACS sorting and was characterized using stem cell assays, flow cytometry and fluorescence microscopy. The cytotoxicity of isolated cells was evaluated with the recombinant TRAIL peptide in vitro by MTT assay.

Results

LSCs isolated from leukemic patients showed presence of stem cell markers like CD123, CD45/CD34, CD96 and CD90. Further the LSCs showed stem cell characteristics like quiescent nature, drug efflux and expression of stem cell marker genes like ABCG2, CLL-1, Wnt3A, TERT, Notch1, Nanog, Sox2, Oct4, BMI1 and βCat. Recombinant immunotoxin of 12 kDa had an IC50 of 700 nM in vitro in leukemic cell lines. The immunotoxin showed ∼80 % efficacy, inducing apoptosis in LSCs derived from 11 patients in vitro.

Conclusion

Specific targeting of cancer stem cells using novel recombinant molecules is an efficient strategy in cancer therapy and could be explored in other types of cancer also to avoid recurrence due to chemo-resistance or radio-resistance.

Legal entity responsible for the study

The authors.

Funding

Department of Science and Technology, Government of India.

Disclosure

All authors have declared no conflicts of interest.

Background

Melanoma is the most lethal malignancy of the skin. Immunotherapy has contributed to improved survival in melanoma patients, yet the mechanisms explaining differences in efficacy have not been elucidated. In previous studies our group found an immune signature that predicts response to antiPD1 immunotherapy. On the other hand, melanoma genomics have been extensively studied, but data regarding protein expression are still scarce. We have performed a genomics plus proteomics analysis of advanced melanoma samples aiming to find mechanisms of resistance to antiPD1.

Methods

53 formalin-fixed, paraffin-embedded (FFPE) melanoma samples were analyzed using a high-throughput proteomics approach based on mass-spectrometry. Using the same 53 FFPE samples we performed RNA-seq of 2000 preselected genes through SeqCap® RNA Choice Probes. Both proteomics and RNA-seq data will be analyzed using probabilistic graphical models (PGM) and sparse-k means plus consensus cluster algorithm, independently and joint together.

Results

53 advanced melanoma patients treated with anti-PD1 immunotherapy were recruited. Proteomics analyses allowed the identification and quantification of 1605 proteins passing quality criteria (two unique peptides and less than 50% of missing values). A PGM, including these 1605 proteins was built, and the resulting graph was processed to seek for functional structures. Successive sparse k-means and consensus cluster algorithm were performed to find the different informative layers. We found an informative layer composed of 102 proteins that divide patients in two groups; these two groups had prognostic value. On the other hand, a PGM including the 2000 genes will be also built (experiments already ongoing). Finally, results from both proteomics and genomics approach will be combined looking for anti-PD1 resistance mechanisms.

Conclusion

The integration of different omics will lead us to a better understanding of the resistance mechanisms to anti-PD1 immunotherapy in advanced melanoma.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

G. Prado Vázquez, L. Trilla Fuertes, A. Zapater Moros, E. López Camacho: Full/Part-time employment: biomedica Molecular Medicine. A. Gámez Pozo, J.A. Fresno Vara, E. Espinosa: Shareholder/Stockholder/Stock options: biomedica Molecular Medicine. All other authors have declared no conflicts of interest.

Background

Interleukin-24 (IL-24) is known to selectively induce apoptosis in cancer cells through endoplasmic reticulum (ER) stress when it is expressed inside the cells. However, IL-24 alone is unable to enter the cells and consequently unable to inhibit cell proliferation. In the present study, we developed a novel chimeric protein, P28-IL-24, containing IL-24 which is linked to P-28, a defined cancer specific cell penetrating peptide and a P53 stabilizer, to target IL-24 into breast cancer cells. Afterwards, specific and non-specific cytolethal effect of this fusion protein were evaluated in vitro and in vivo.

Methods

MTT assay was performed to evaluate cytotoxicity of the fusion protein on MCF-7 and MDA-MB-231 cancer cells. Next, in order to evaluate the mechanism of the induced cell death, Annexin/PI staining of MCF-7 cells treated with the fusion protein was performed and followed by flowcytometry. Finally, in vivo effect of the fusion protein was evaluated on syngenic breast tumors induced in inbred Balb/C mice.

Results

Our findings showed inhibitory effects on proliferation of MCF-7 and MDA-MB-231 cancer cells by the P28-IL-24 protein. In addition, Annexin/PI staining of the treated MCF-7 cells showed that apoptosis induction is the mechanism of cell death induced by the fusion protein. Treatment of inbred Balb/C mice bearing syngenic 4T1 tumor cells with the p28-IL-24 significantly reduced the tumor sizes up to half of the original size within the study period. Furthermore, Hematoxylin and eosin (H&E) staining and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay, revealed that this tumor growth suppression was associated with increase in necrotic and apoptotic cells.

Conclusion

Taken together, the findings of the current study suggest that the recombinant chimeric protein p28-IL-24 can serve as a potent candidate for development of a novel cancer therapeutics. Further in vitro and in vivo preclinical evaluations are undergoing.

Legal entity responsible for the study

Isfahan University of Medical Sciences and Health Services.

Funding

Isfahan University of Medical Sciences and Health Services.

Disclosure

All authors have declared no conflicts of interest.

Background

GSK609 an agonist IgG4 monoclonal antibody (mAb) against inducible co-stimulatory receptor (ICOS) exhibits T cell mediated immune stimulating and anti-tumor activity. INDUCE-1 is the first in human study investigating GSK609 alone and in combinations which include pembrolizumab in select tumor types including recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC).

Methods

Safety, PK, PD, and preliminary antitumor activity of GSK609 are being evaluated at doses from 0.001 to 10 mg/kg every 3 weeks (Q3W). Blood samples collected prior to dosing and on-study were evaluated for PK and PD effects on lymphocytes and ICOS receptor occupancy (RO). Tumor biopsies at screening and week 6 were evaluated for changes in tumor immune infiltrates (TIL) by a multiplexed immuno-fluorescence and gene expression platforms.

Results

The GSK609 PK disposition showed low clearance, limited central volume of distribution, and mean systemic half-life of 19 days, which is consistent with other humanized mAbs. Evidence of target engagement and tumor size reduction are observed in a R/M HNSCC expansion cohort (EC) at 0.3 mg/kg with 200 mg pembrolizumab. Dose and concentration-RO analyses suggest ≥0.1 mg/kg GSK609 maintains ≥ 70% RO on peripheral CD4+ and CD8+ T cells. Quantitative TIL evaluation of paired tumor biopsies demonstrates favorable immune microenvironment in the tumor at exposures observed in patients treated with 0.3mg/kg. TIL and tumor-based gene expression data demonstrated non-linear, dose-dependent changes in select immune activation markers. Exposure-response assessments revealed no difference in baseline-to-Week 9 target lesion change across exposures in the EC. Furthermore, cross-cohort pooled exposure-response analysis of ≥Grade 2 AEs demonstrated similar safety outcomes across the exposures/doses. Additionally, population PK modeling suggests comparable exposures can be maintained by fixed dosing as well.

Conclusion

The current data provide preliminary evidence of GSK609 target engagement and biological activity at clinically tolerable doses and support further exploration of the 0.3 mg/kg or 24mg fixed dose.

Clinical trial identification

NCT02723955.

Editorial acknowledgement

Chloe Stevenson of Fishawack Indicia Ltd, UK.

Legal entity responsible for the study

GlaxoSmithKline.

Funding

GlaxoSmithKline (GSK) in collaboration with Merck Sharp & Dohme Corp.

Disclosure

E. Angevin: Advisory/Consultancy, Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: MSD; Advisory/Consultancy, Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: GSK; Advisory/Consultancy: Celgene Research; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: MedImmune; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: AbbVie; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Aduro; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Agios; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Amgen; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Argen-x; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Astex; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: AstraZeneca; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: Roche; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: Sanofi; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: Pfizer; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: Innate Pharma; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: Celgene; Research grant/Funding (institution), Travel/Accommodation/Expenses, principal/sub-investigator of Clinical Trials: BMS; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Aveo pharmaceuticals; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Beigene; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Blueprint; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Boehringer Ingelheim; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Chugai; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Clovis; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Daiichi Sankyo; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Debiopharm; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Eisai; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials Eos; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Bayer; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Exelixis; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Forma; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Gamamabs; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Genentech; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Gortec; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: H3 Biomedicine; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Incyte; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Janssen; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Kura Oncology; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Kyowa; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Lilly; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Loxo; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Lysarc; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Lytix Biopharma; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Menarini; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Merus; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Nanobiotix; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Nektar Therapeutics; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Novartis; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Octimet; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Oncoethix; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Oncopeptides AB; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Orion; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Pharmamar; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Pierre Fabre; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Servier; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Sierra Oncology; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Taiho; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Takeda; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Tesoro; Research grant/Funding (institution), principal/sub-investigator of Clinical Trials: Xencor. T. Bauer: Advisory/Consultancy: Ignyta; Advisory/Consultancy: Guardant Health; Advisory/Consultancy, Speaker Bureau/Expert testimony: Loxo; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Moderna Therapeutics; Speaker Bureau/Expert testimony: Bayer; Speaker Bureau/Expert testimony: Daiichi Sankyo; Speaker Bureau/Expert testimony: Medpacto Inc; Speaker Bureau/Expert testimony: Incyte; Speaker Bureau/Expert testimony: Mirati Therapeutics; Speaker Bureau/Expert testimony: MedImmune; Speaker Bureau/Expert testimony: AbbVie; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: AstraZeneca; Speaker Bureau/Expert testimony: Leap Therapeutics; Speaker Bureau/Expert testimony: MabVax; Speaker Bureau/Expert testimony: Stemline Therapeutics; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Merck; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Lilly; Speaker Bureau/Expert testimony: GSK; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Novartis; Speaker Bureau/Expert testimony: Pfizer; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Genentech/Roche; Speaker Bureau/Expert testimony: Deciphera; Speaker Bureau/Expert testimony: Merrimack; Speaker Bureau/Expert testimony: Immunogen; Speaker Bureau/Expert testimony: Millennium; Speaker Bureau/Expert testimony: Ignyta; Speaker Bureau/Expert testimony: Calithera Biosciences; Speaker Bureau/Expert testimony: Peleton; Speaker Bureau/Expert testimony: Kolltan Pharmaceuticals; Speaker Bureau/Expert testimony: Principia Biopharma; Speaker Bureau/Expert testimony: Immunocore; Speaker Bureau/Expert testimony: Roche; Speaker Bureau/Expert testimony: Aileron Therapeutics; Speaker Bureau/Expert testimony: BMS; Speaker Bureau/Expert testimony: Amgen; Speaker Bureau/Expert testimony: Moderna Therapeutics; Speaker Bureau/Expert testimony: Sanofi; Speaker Bureau/Expert testimony: Boehringer Ingelheim; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Astellas Pharma; Speaker Bureau/Expert testimony: Five Prime Therapeutics; Speaker Bureau/Expert testimony: Jacobio; Speaker Bureau/Expert testimony: Top Alliance BioScience; Speaker Bureau/Expert testimony: Janssen; Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Clovis Oncology; Speaker Bureau/Expert testimony: Takeda; Speaker Bureau/Expert testimony: Karyopharm Therapeutics; Speaker Bureau/Expert testimony: Onyx; Speaker Bureau/Expert testimony: Phosplatin Therapeutics; Speaker Bureau/Expert testimony: Foundation Medicine; Speaker Bureau/Expert testimony: ARMO BioSciences; Travel/Accommodation/Expenses: Celgene; Travel/Accommodation/Expenses: EMD Serono; Travel/Accommodation/Expenses: Pharmacyclics; Travel/Accommodation/Expenses: Sysmex. D. Rischin: Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: MSD; Advisory/Consultancy, Research grant/Funding (institution): Regeneron; Advisory/Consultancy, Research grant/Funding (institution): GSK; Advisory/Consultancy, Research grant/Funding (institution): BMS; Research grant/Funding (institution): Roche. V. Moreno: Advisory/Consultancy: Merck; Advisory/Consultancy, Travel/Accommodation/Expenses: BMS; Travel/Accommodation/Expenses: Regeneron/Sanofi; Research grant/Funding (institution): Medscape/Bayer. J.M. Trigo: Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche; Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: AstraZeneca; Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Boehringer Ingelheim; Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: BMS; Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: MSD. M. Chisamore: Shareholder/Stockholder/Stock options, Full/Part-time employment: Merck. J. Shaik, F. Rigat, C. Ellis, H. Chen, R. Gagnon, S.J. Scherer, D. Turner, S. Yadavilli, A. Hoos: Shareholder/Stockholder/Stock options, Full/Part-time employment: GSK. M. Ballas: Shareholder/Stockholder/Stock options, Full/Part-time employment: GSK; Shareholder/Stockholder/Stock options: BMS; Shareholder/Stockholder/Stock options: Abbott; Shareholder/Stockholder/Stock options: Novartis. M. Maio: Advisory/Consultancy, Travel/Accommodation/Expenses: GSK; Advisory/Consultancy, Travel/Accommodation/Expenses: BMS; Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Advisory/Consultancy, Travel/Accommodation/Expenses: MSD; Advisory/Consultancy, Travel/Accommodation/Expenses: Incyte. All other authors have declared no conflicts of interest.

Background

During cancer development, IL-18 plays both positive and negative roles. IL-18 can promote tumor progression or metastasis, mainly through its effect on VCAM-1 and VEGF production. In contrast, IL-18 has been proven to enhance immunity against several kinds of tumors including melanoma and liver cancer. Due to its impact on IFN-γ production, IL-18 enhances anti-tumor activity by NK and Th1. We have previously shown that pulse stimulation with zoledronate and IL-2 or IL-15 greatly enhance the expansion, and anti-tumor activity of Vγ2Vδ2 T cells. Given the importance of IL-18 on the expansion, differentiation, and function of NK and Th1 cells, we hypothesized that expansion, memory and anti-immunity function of Vγ2Vδ2 T cells can be further optimized by using IL-18 in combination with IL-2 or IL-15 cytokines in prostate cancer settings.

Methods

We used fresh and frozen PBMCs obtained from random healthy donors. Ex vivo expansion for gamma delta T cells was done by pulsing with zoledronate in the presence of IL-2, IL-15, and/or IL-18. Multicolor Flow Cytometry LSR II was used to assess the cell functionality by measuring cytokines expression (IFN-γ, and TNF-a). Anti-cancer cytotoxicity was measured by CD107a expression after co-culturing with target cells. Human prostate cancer PC-3 cell line was used as target cells for activated Vγ2Vδ2 T cells. CD27 and CD28 were used to quantify the memory subsets of Vγ2Vδ2 T cells.

Results

Along with zoledronate pulse stimulation, adding IL-18 to IL-2 or IL-15 has significantly increased the absolute cell number of activated Vγ2Vδ2 T cells. Also, IFN-γ secretion has markedly increased when IL-18 added to the culture compare to IL-2 or 15 alone. Our findings showed different memory subset distribution based on the cytokines combination. IL-18 seems to maintain high central/early memory subsets with IL-2 and more late memory with IL-15. More importantly, IL-18 addition has increased the CD107a expression on activated Vγ2Vδ2 T cells when co-cultured with sensitized human prostate cancer cell line.

Conclusion

Our findings conclude that using IL-18 in combination with IL-2 or IL-15 results in increasing the yield, balancing out the memory subsets, and promoting the anti-cancer immunity of human Vγ2Vδ2 T cells.

Legal entity responsible for the study

Department of Internal Medicine, The University of Iowa Carver College of Medicine, USA.

Funding

Department of Veterans Affairs (Veterans Health Administration, Office of Research and Development, Biomedical Laboratory Research and Development Grant 2I01 BX000972-05) and the National Institutes of Health, National Cancer Institute, Grants CA097274 (University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence) and P30 CA086862 (Core Support) to C.T.M. C.T.M. is the Kelting Family Scholar in Rheumatology. M.H.N. was supported in part by the Higher Committee for Education Development in Iraq and National Institutes of Health Grant 5 T32 AI007485.

Disclosure

All authors have declared no conflicts of interest.

Background

Breast cancer (BC) comprises the most prevalent malignancy among females, whilst being the chief cause of cancer-related mortalities. The advent of immunotherapy has opened the gateway towards several therapeutic strategies that surpass the conventional approaches with regards to efficacy and specificity. The most prominent of said strategies is immune checkpoint inhibitors (ICI), which despite its promise has shown evidence of primary and secondary resistance. It has been suggested that the BC-induced immune suppressive tumor microenvironment (TME) can be a definite reason for ICI resistance. As such, we aim to investigate the possible mechanisms of resistance related to TME and probe the administration of a toxicologically safe anti-cancer natural compound known as quercetin-3′-methoxy-3-O-(4″-acetylrhamnoside)-7-O-α-rhamnoside isolated by our group from Cleome droserifolia to alleviate the immune suppressive nature of BC-TME.

Methods

Forty BC patients were recruited in this study. MDA-MB-231 and MCF-7 cells were cultured. IL-10 and TNF-α were measured using Elisa kits. Quercetin glycoside was isolated from C. droserifolia. Cell treatment was performed. RNA was extracted using Bizol. Expression profiles were determined via q-RT-PCR.

Results

BC patients and cell lines showed a marked increase in TNF-α level. Treatment of BC cells with quercetin derivative isolated from C. droserifolia showed resulted in a significant attenuation of the immune-suppressive TNF-α. Nonetheless, the quercetin compound resulted in a concurrent reduction in IL-10 as well. To understand the mechanism of their induced-repression, miR-155 was found to dually direct TNF-α and IL-10. Therefore, miR-155 expression level was probed in BC cells treated with quercetin-derivative where it resulted in a significant modulation of miR-155/IL-10/TNF-α and thus alleviating the immune suppressive TME in BC.

Conclusion

This study provides a potential combinational approach of ICI with a safe natural compound, quercetin-derivative, alleviating BC-induced immune-suppressive TME and thus decreasing the risk of resistance among BC patients.

Legal entity responsible for the study

German University in Cairo.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

Immunotherapy has changed clinical practise. Patient enrolment in immunotherapy phase I trials is still crucial. Therefore, new tests have been developed (GRIM score and LIPI score), challenging the classical ones designed for targeted therapy such as Royal Marsden Score (RMS). Although they include different variables, here we perform a comparison, aimed at identifying if there are differences in terms of their predictive power of survival.

Methods

Variables from patients treated in our institution (2012-2019) were collected retrospectively and used to calculate these different scores: RMS (number of metastasis, LDH, albumin), GRIM score (LDH, Albumin, NLR (Neutrophil/Lymphocyte ratio)>6) and LIPI score (LDH, NLR>3). Cox regression model was performed for predicting OS (time between the day of the first dose and date of death or lost to follow up). C-Harrell index and its confidence interval were calculated for each score for measuring the power of prediction. Differences between c-Harrell indexes were calculated. A p value < 0.05 was considered statistically significant. All calculations were performed with STATA v16.0.

Results

In terms of predicting overall survival we found that a higher punctuation in RMS (high vs low HR = 2.14 95% CI 1.47-3.10), in Grim score (high vs low HR = 2.14; 95% CI 1.51-3.02) and LIPI score (high vs low HR = 1.83; 95% CI 1.42-2.37) were all statistically significant. In terms of power of prediction we found that LIPI score presented a c-Harrel index slightly higher (0.63; 95% CI 0.59-0.68) than GRIM score (0.62; 95% CI 0.57-0.66) and RMS (0.62; 95% CI 0.59-0.66). Nevertheless, differences between c-index of each score were not statistically significant.

Conclusion

Selecting patients for participating in phase I immunotherapy trials is still critical. Although in this study we have seen a slightly higher predictive power for LIPI score in comparison to GRIM score or RMS, differences were not statistically significant. Nevertheless, and assuming the most parsimonious model, LIPI score seemed to be an easy and accurate model for predicting survival.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

L. Resano, A. Sánchez: Full/Part-time employment: Roche. All other authors have declared no conflicts of interest.

Background

Preclinical and clinical data suggest MEK-inhibition (MEKi) to be effective in NRAS-mutant (mt) and NRAS wild-type (wt) melanoma. However, MEKi causes considerable cutaneous treatment-related adverse events (TRAE) which are less present if MEKi is combined with BRAFi.

Methods

This open-label, dual-stratum, single-center phase 2 clinical trial investigated trametinib (T; 2 mg QD) in patients (pts) with advanced BRAF^V600 wt, NRAS^Q61R/K/L mt/wt melanoma who had progressed following or were ineligible for immune checkpoint inhibitors. In case of T-related cutaneous TRAE, low-dose dabrafenib (ld-D; 50 mg BID) was added to prevent further skin TRAE. The trial was amended in June 2019 to administer ld-D upfront with T. The primary endpoint was the confirmed objective response rate (ORR; per RECIST 1.1); secondary endpoints were progression-free and overall survival and safety.

Results

Between Jan and Dec 2019, 9 pts initiated T monotherapy and 8 pts initiated T + ld-D. TRAE were seen in 15 pts (29% G3-4; 29% SAE). One pt permanently interrupted T due to G3 pneumonitis. All 9 pts who initiated T monotherapy developed G1-2 acneiform rash which resolved (to G0: 6 pts; to G1: 3 pts) with temporary interruption of T, local metronidazole therapy and subsequent addition of ld-D to T. One pt had a G1 recurrence of acneiform rash that was managed with local therapy. Of 8 pts who initiated T + ld-D upfront, 1 developed G1 acneiform rash that resolved with local therapy only. Other TRAE are shown in the table. T dose was reduced in 4 pts for TRAE (1 pt with left ventricular ejection fraction decrease; 1 with central serous retinopathy; 1 with AST/ALT increase; 1 with hyponatremia and syncope). The unconfirmed ORR is 4/15 and the disease control rate is 7/15 evaluable pts. Table: 20P

TRAE in ≥2 pts

Conclusion

No unexpected toxicities were seen with T or T + ld-D. ld-D is able to prevent T-related skin toxicity. Thus, combining ld-D with T is a safe approach to increase tolerance of and optimize exposure to T.

Clinical trial identification

NCT04059224; EudraCT 2018-004003-39.

Legal entity responsible for the study

Universitair Ziekenhuis Brussel.

Funding

Novartis, Stichting tegen Kanker.

Disclosure

G. Awada: Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer; Travel/Accommodation/Expenses: Astellas; Travel/Accommodation/Expenses: Merck Sharp & Dohme; Advisory/Consultancy, Research grant/Funding (institution): Novartis. J.K. Schwarze: Travel/Accommodation/Expenses: Amgen; Travel/Accommodation/Expenses: Merck Sharp & Dohme. S. Aspeslagh: Advisory/Consultancy, Speaker Bureau/Expert testimony: Amgen; Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche; Advisory/Consultancy, Speaker Bureau/Expert testimony: AstraZeneca; Advisory/Consultancy, Speaker Bureau/Expert testimony: Bristol-Myers Squibb; Advisory/Consultancy, Speaker Bureau/Expert testimony: Merck Sharp & Dohme; Advisory/Consultancy, Speaker Bureau/Expert testimony: Sanofi; Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis. B. Neyns: Advisory/Consultancy, Speaker Bureau/Expert testimony, Research grant/Funding (institution): Roche; Advisory/Consultancy, Speaker Bureau/Expert testimony: Bristol-Myers Squibb; Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis; Advisory/Consultancy, Speaker Bureau/Expert testimony: Merck Sharp & Dohme; Advisory/Consultancy, Speaker Bureau/Expert testimony: AstraZeneca; Advisory/Consultancy, Speaker Bureau/Expert testimony: EtheRNA; Advisory/Consultancy, Speaker Bureau/Expert testimony: CryoStorage; Research grant/Funding (institution): Pfizer; Research grant/Funding (institution): Merck Serono. All other authors have declared no conflicts of interest.

Background

Onxeo has pioneered a radically new approach of anti-cancer treatment to tackle emergence of resistance: the decoy agonist mechanism of action (MoA). Drugs based on this unprecedented MoA hijack and hyper activate therapeutic targets (decoy effect) leading to exhaustion (agonist effect). This breakthrough MoA has already shown, using our lead compound AsiDNA, target engagement and excellent safety profile in humans and importantly lack of resistance in multiple preclinical studies. These exciting results led us to develop a proprietary platform of oligonucleotides (platON) with decoy agonist properties: the new generation product OX401 targeting PARP, a target already validated in oncology.

Methods

OX401-induced PARP activation, NAD⁺ consumption and tumor cytotoxicity was monitored 2, 7 and 12 days after tumor and non-tumor cell treatment. Inhibition of the homologous recombination repair pathway was monitored by analyzing Rad51 protein recruitment to damage sites. Accumulation of cytoplasmic DNA fragments was monitored after DNA staining and microscopy analysis. OX401 effects on the innate immune response was assessed by following STING expression and activation and T-cell mediated anti-tumor cytotoxicity.

Results

OX401 binds and hyper activates PARP diverting it away from its proper role in cancer cells. As a consequence, OX401 inhibits DNA repair due to PARP sequestration leading to accumulation of DNA breaks and cytoplasmic chromatin fragments which activate innate immunity through STING pathway. Moreover, OX401 increases the anti-tumor T-cell-dependent immune response. The sustained hyper-activation of PARP induced by OX401 leads to a rapid NAD⁺ consumption (below the viability threshold) and the nuclear translocation of mitochondrial apoptosis-inducing factor (AIF) (parthanatos). By these unprecedented properties on DNA repair and innate immunity in addition to major metabolic effects, OX401 displays a potent and selective tumor cytotoxicity without resistance emergence.

Conclusion

Our results provide a rationale for using OX401 as an immunomodulatory and “metabolic exhauster” agent, with a therapeutic interest in particular in appropriately selected tumors with metabolic deficiencies.

Legal entity responsible for the study

Onxeo.

Funding

Onxeo.

Disclosure

W. Jdey, V. Hayes, C. Zandanel, V. Trochon-Joseph, F. Bono: Employee: Onxeo.

Background

Breast cancer is the most common cancer in women. There is an urgent need for new drugs with novel modes of effect on tumors. It is very important to develop compounds with high activity against tumor cells and low toxicity on normal epithelium. The development of new anti-tumor drugs based on steroidal compounds is a promising approach for obtaining agents that combine antiestrogenic, cytostatic and proapoptotic effects. The aim of the work is to study the mechanism of anticancer action of new steroidal compound, 3,20 (R)-dihydroxy-19-norpregnatriene (Kuz7).

Methods

MCF-7 breast cancer cell line and MCF-10A human mammary epithelial cell line were obtained from the ATCC collection. Antiproliferative activity was measured by MTT. ERα activity was assessed by gene-reporter assay. Protein expression was measured by standard immunoblotting.

Results

We have developed a new type of anticancer steroids - a series of 3-hydroxyestra-1,3,5(10)-trienes of natural and epimeric 13α-configuration with 17th-side chain bearing the second hydroxy group and 16,17-fused three- or six-membered carbocycle (or without it). Most of these compounds exhibited cytotoxic and ERα inhibiting activities on MCF-7 cells and have low toxicity in the MCF-10A normal epithelial cells. 3,20(R)-dihydroxy-19-norpregnatriene (Kuz7) was selected as a leader molecule for in-depth study. At low doses, Kuz7 caused significant accumulation of p21 and inhibition of CDK2 and CDK4 in MCF-7 cells. Apoptosis provoked by Kuz7 was determined by fragmented PARP. Compound kuz7 is considered as an effective inhibitor of proliferation and ERα signaling in MCF-7 cells. kuz7 decreased cyclin D1 expression and caused cell arrest in G0 phase.

Conclusion

New series of highly active antitumor steroids has been developed. The lead compound, kuz7, blocks the growth of MCF-7 cells through induction of apoptosis and regulation of hormonal pathways and cell cycle. Further studies, in vitro and in vivo, are needed to confirm our findings in relation to luminal type A breast cancer. The work was supported by RFBR (project 19-03-00246).

Legal entity responsible for the study

The authors.

Funding

Russian Foundation for Basic Research (project 19-03-00246).

Disclosure

All authors have declared no conflicts of interest.

Background

Small-cell neuroendocrine prostate cancer (SCNPC) is an aggressive variant form of prostate cancer that is resistant to androgen receptor(AR)-directed targeted therapies. SCNPC has molecular and morphological features in common with other aggressive small-cell tumors such as small-cell lung cancer (SCLC) and Merkel cell carcinoma (MCC). We recently conducted a pan-cancer transcriptomic analysis to identify “druggable” targets that display conserved expression patterns across small-cell tumors. Using this method, we identified and subsequently determined that BCL2 inhibitors (BCL2i) are lethal in SCNPC cell lines and repress the growth of a subset of SCNPC patient-derived xenograft models (PDXs). In this study, we profile the expression of an additional candidate target identified by this method, L1CAM.

Methods

We compiled transcriptomic data from prostate cancer metastases (including SCNPC and AR-pathway driven tumors), SCLC and MCC metastases. We identified druggable targets similarly expressed amongst small-cell tumors using differential expression analysis. We then profiled RNA and protein expression of individual candidates in a panel of cell lines and prostate cancer PDX models.

Results

We identified 875 genes previously determined to contain druggable features as commonly expressed across SCNPC, SCLC, and MCC. L1CAM is amongst these genes and is highly expressed across all small-cell tumors profiled. L1CAM is also positively correlated with a 10-gene neuroendocrine signature across small-cell tumors and PDX models. L1CAM protein levels are elevated in small-cell tumor cell lines and SCNPC PDX models compared to non-neuroendocrine prostate models. L1CAM protein in small-cell cell lines and PDX models can be detected by the CE7 epitope. Initial co-culture experiments with prostate lines and the L1CAM-CE7R-BBζ chimeric antigen receptor (CAR) T cells demonstrate IFNˠ release in the presence of SCNPC cell lines.

Conclusion

We identify L1CAM as highly expressed in SCNPC patient metastases, cell lines, and PDX models. A CAR targeting L1CAM is currently under investigation for the treatment of another neuroendocrine tumor type, neuroblastoma. Here we provide evidence for the pre-clinical assessment of the L1CAM-CE7R CAR in SCNPC.

Legal entity responsible for the study

The authors.

Funding

PNW SPORE: CA097186, W81XWH-18-1-0347, PC170350P1, Prostate Cancer Foundation and Kelsey Dickson Challenge Award, Movember Foundation/Prostate Cancer Foundation Challenge Award, Department of Defense Prostate Cancer Research Program Physician Research Award PC160018, Ford Foundation Dissertation Fellowship, Chromosome Metabolism and Cancer Training Grant 2T32CA009657.

Disclosure

P.S. Nelson: Advisory/Consultancy, employee/paid consultant: Astellas; Advisory/Consultancy, employee/paid consultant: Janssen. All other authors have declared no conflicts of interest.

Background

Choline is an organic cation that plays a critical role in the structure and function of biological membranes. Intracellular choline accumulation through choline transporters is the rate-limiting step in phospholipid metabolism, and it is a prerequisite for cell proliferation. Choline PET/CT has been used to visualize various cancers, and high levels of choline accumulation have been observed in tumors. However, the uptake system for choline and the functional expression of choline transporters in pancreatic cancer are not completely understood. In this study, we examined the functional characterization of choline transporters in pancreatic cancer cells. Furthermore, we searched for compounds that inhibit choline uptake as well as cell proliferation in a plant-derived natural organic compound library.

Methods

We examined [³H]choline uptake in the pancreatic cancer cell line MIA PaCa-2. Cells were cultured in RPMI 1640 medium supplemented with 10 % fetal bovine serum and grown at 37 C in 5% CO₂. The CellTiter-Glo Luminescent Cell Viability Assay is a homogeneous method of determining the number of viable cells. The caspase-Glo 3/7 Assay System is a homogeneous luminescent method used to measure caspase-3 and -7 activities.

Results

Choline transporter-like protein 1 (CTL1) and CTL2 mRNA are highly expressed. CTL1 and CTL2 were located in the cell membrane and intracellular compartment, respectively. [³H]Choline uptake was mediated by a single Na⁺-independent, intermediate-affinity transport system. We found two hit compounds from 500 plant-derived natural organic compounds that inhibited choline uptake and cell viability. These hit compounds reduced cell survival and enhanced caspase-3/7 activity. One of the compounds inhibited tumor growth in MIA PaCa-2 cell xenograft model mice.

Conclusion

These results suggest that CTL1 is functionally expressed in pancreatic cancer cells and is also involved in abnormal proliferation. Identification of this CTL1-mediated choline transport system provides a potential new therapeutic target for the treatment of this disease.

Legal entity responsible for the study

Tokyo Medical University.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

Oncogenic virus infections contribute to approximately 15% of the total cancer burden, causing 1.6 million new malignancies annually. HPV, HBV, and EBV are the three most hazardous oncogenic DNA viruses. One common feature is the insertion of their DNA into the human genome to further promote tumorigenesis. However, the insertional patterns and mechanisms are still poorly understood.

Methods

To systematically interrogate the integration profiles of HPV, HBV and EBV, we conducted genome-wide virus capture sequencing on 6075 possible HPV-related samples and two EBV-positive cell lines. We then applied detection of integrated papillomavirus sequences by ligation-mediated PCR (DIPS-PCR) on 397 cervical cancer samples, and collected the datasets of 1483 HPV-related cancers, 1070 HBV-related carcinomas, and 556 EBV-related tumors from public database. Furthermore, we developed and performed a novel pipeline named Viral Integration Pathway Analysis (VIPA) for diverse viruses in our own data and the collected public data.

Results

We uncovered that the integration patterns of different HPV, HBV, and EBV genotypes were significantly distinct and non-randomly affected several key cancer-associated genes. This subtype-specific integration pattern for each virus supports the notion that different viral genotypes require differential treatment and should be treated as different viruses. Notably, 449 integration hotspots were shared by all three viruses, indicating the presence of pan-oncovirus integration hotspots. We further examined these integration hotspots and found that HPV, HBV, and EBV insertion events are predominately mediated by synthesis-dependent end joining, which is in contrast to the traditional view of classical non-homologous end-joining.

Conclusion

In summary, we report a genome-wide unbiased analysis of HPV, HBV and EBV insertional mutagenesis in our own data and the public data. We discovered HPV, HBV, and EBV share the same dominant SD-EJ integration mechanism during carcinogenesis. Our data provide a framework for patient stratification based on viral integration patterns and shed new light on novel therapeutic approaches to virus-induced cancers.

Legal entity responsible for the study

The First Affiliated Hospital, Sun Yat-sen University.

Funding

National Science and Technology Major Project of the Ministry of Science and Technology of China (No.2018ZX10301402).

Disclosure

All authors have declared no conflicts of interest.

Background

Recent studies have shown that the non-enzymatic function of CD73 plays a key role in tumor progression, but this function of CD73 in pancreatic cancer cells has not been studied. Furthermore, little is still known about the mechanisms involved in CD73 regulation in tumors.

Methods

Western blot and immunohistochemical assays were used to detect the expression of CD73 and other proteins in pancreatic ductal adenocarcinoma (PDAC). CCK-8 assay was used to investigate cell proliferation. Flow cytometry was used to detect cell cycle stage and apoptosis. Wound healing assay was used to investigate the migration ability. Xenograft mouse model was also used to investigate the interaction between miR-30a-5p and CD73.

Results

Here, we found that CD73 expression was upregulated in pancreatic ductal adenocarcinoma (PDAC) and that its expression correlated with poor prognosis. CD73 knockdown inhibited cell growth and induced G1 phase arrest via the AKT/ERK/cyclin D signaling pathway. We also found that tumor necrosis factor receptor (TNFR) 2 was involved in CD73-induced AKT and ERK signaling pathway activation in PDAC. Further, miR-30a-5p overexpression significantly increased the cytotoxic effect of gemcitabine in pancreatic cancer by directly targeting CD73 mRNA, suggesting that regulation of the miR-30a-5p/CD73 axis may play an important role in the development of gemcitabine resistance in pancreatic cancer.

Conclusion

In summary, this regulatory network of CD73 appears to represent a new molecular mechanism underlying PDAC progression, and the mechanistic interaction between miR-30a-5p, CD73 and TNFR2 may provide new insights into therapeutic strategies for pancreatic cancer.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

The development of FGFR inhibitors, Multi-Tyrosine Kinase Inhibitors (MTKI) and specific FGFR1-4 inhibitors (FGFRinh) has been focused in FGFR-amplified (FGFRamp) BC patients (pt). However, previous results suggested that clinical benefit with FGFRinh was limited to tumours with high FGFR copy number alterations (CNA), resulting in high FGFR expression. Here, we aimed to study whether FGFR1-4 mRNAh is a predictive biomarker for both MTKI and/or FGFRinh.

Methods

We generated an FGFR1amp BC PDXs’ collection within the FGFR 360° RESISTANCE project. We tested the efficacy of FGFRinh rogaratinib (FGFR1-4) in 17 models and the MTKI lucitanib (FGFR1/2, VEGFR1-3, PDGFRA/B) in 7 FGFR1amp BC PDXs. A cohort of BC pts (8/9 FGFR1amp) treated with MTKI was used to validate the findings. PDXs and pt tumour samples were analysed by nCounter® and by HTG EdgeSeq® platform with Oncology Biomarker Panel (OBP).

Results

FGFR1-4 mRNAh showed better correlation with efficacy to FGFRinh compared with FGFR CNA, being able to differentiate responders (R) from non-responders (NR) BC PDXs without FGFR mutations. Of note, some sensitive FGFR1amp PDXs expressed low FGFR1 mRNA levels whilst FGFR2-4 mRNAh. MTKI demonstrated higher antitumour activity than FGFRinh, specifically in PDXs with low FGFR1-4 mRNA levels. In agreement, FGFR1-4 mRNAh did not discriminate R (5) from NR (4) in pts treated with MTKI. Interestingly, we identified 3 pts who achieved prolonged responses (14-50 months), of which only one had FGFR1 mRNAh. Also, we noticed 2 pts that had previously received FGFRinh, who still presented clinical benefit with MTKI. When assessing mRNA expression levels of other angiogenic targets, such as VEGFR1-3 or PDGFRA/B and their ligands, none of them correlated with MTKI sensitivity, neither in PDXs nor in our BC pt cohort.

Conclusion

In this exploratory study, total FGFR1-4 mRNAh is a predictive biomarker for FGFRinh (e.g. rogaratinib) but not for MTKI such as lucitanib in BC PDXs. MTKI efficacy does not rely on mRNAh levels of its targets in BC. Future development of FGFR inhibitors should consider optimized enrolment strategies according to these results. Co-funded by ISCIII-FEDER (PI15/00360) and Grants4Targets Bayer (ID 2015-08-1441).

Legal entity responsible for the study

Vall d'Hebron Institute of Oncology (VHIO).

Funding

Vall d'Hebron Institute of Oncology (VHIO).

Disclosure

C. Hierro: Research grant/Funding (institution): Bayer; Speaker Bureau/Expert testimony: Ignyta; Speaker Bureau/Expert testimony: Lilly; Travel/Accommodation/Expenses: Roche; Travel/Accommodation/Expenses: Amgen; Travel/Accommodation/Expenses: Merck. E. Garralda: Research grant/Funding (institution): Novartis; Research grant/Funding (institution): Roche; Research grant/Funding (institution): ThermoFisher; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Agios Pharmaceuticals; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Amgen; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Bayer; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Beigene USA; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Blueprint Medicines; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Genmab B.V.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: GSK; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Glycotope Gmbh; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Incyte Biosciences; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Incyte Corporation; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: ICO; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Kura Oncology Inc; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Lilly S.A.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Loxo Oncology Inc; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Macrogenics Inc; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Menarini Ricerche Spa; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Merck, Sharp & Dohme de España S.A.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Nanobiotix S.A.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Novartis Farmacéutica S.A.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Pfizer SLU; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: PharmaMar S.A.U.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Pierre Fabre Medicament; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Principia Biopharma Inc; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Poises Therapeutics Ltd; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Sanofi; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Sierra Oncology Inc; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Sotio A.S.; Non-remunerated activity/ies, Clinical Investigator as PI or co-PI: Symphogen A/S; Advisory/Consultancy: Roche/Genentech; Advisory/Consultancy: F.Hoffmann/La Roche; Advisory/Consultancy: Ellipses Pharma; Advisory/Consultancy: Neomed Therapeutics1 Inc; Advisory/Consultancy: Boehringer Ingelheim; Advisory/Consultancy: Janssen Global Services; Advisory/Consultancy: SeaGen; Advisory/Consultancy: TFS; Advisory/Consultancy: Alkermes; Advisory/Consultancy: ThermoFisher; Advisory/Consultancy: Bristol-Mayers Squibb; Travel/Accommodation/Expenses: Bristol-Mayers Squibb; Travel/Accommodation/Expenses: Merck, Sharp & Dohme ; Travel/Accommodation/Expenses: Menarini; Travel/Accommodation/Expenses: Glycotope; Speaker Bureau/Expert testimony: Merck, Sharp & Dohme; Speaker Bureau/Expert testimony: Roche; Speaker Bureau/Expert testimony: ThermoFisher. J. Tabernero: Advisory/Consultancy: Array Biopharma; Advisory/Consultancy: AstraZeneca; Advisory/Consultancy: Bayer; Advisory/Consultancy: BeiGene; Advisory/Consultancy: Boehringer Ingelheim; Advisory/Consultancy: Chugai; Advisory/Consultancy: Genentech; Advisory/Consultancy: Inc.; Advisory/Consultancy: Genmab A/S; Advisory/Consultancy: Halozyme; Advisory/Consultancy: Imugene Limited; Advisory/Consultancy: Inflection Biosciences Limited; Advisory/Consultancy: Ipsen; Advisory/Consultancy: Kura Oncology; Advisory/Consultancy: Lilly; Advisory/Consultancy: MSD; Advisory/Consultancy: Menarini; Advisory/Consultancy: Merck Serono; Advisory/Consultancy: Merrimack; Advisory/Consultancy: Merus; Advisory/Consultancy: Molecular Partners; Advisory/Consultancy: Novartis; Advisory/Consultancy: Peptomyc; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Pharmacyclics; Advisory/Consultancy: ProteoDesign SL; Advisory/Consultancy: Rafael Pharmaceuticals; Advisory/Consultancy: Rafael Pharmaceuticals; Advisory/Consultancy: Sanofi; Advisory/Consultancy: SeaGen; Advisory/Consultancy: Seattle Genetics; Advisory/Consultancy: Servier; Advisory/Consultancy: Symphogen; Advisory/Consultancy: Taiho; Advisory/Consultancy: VCN Biosciences; Advisory/Consultancy: Biocartis; Advisory/Consultancy: Foundation Medicine; Advisory/Consultancy: HalioDX SAS ; Advisory/Consultancy: Roche Diagnostics. J. Rodon: Travel/Accommodation/Expenses: European Journal of Cancer; Travel/Accommodation/Expenses: Vall d'Hebron Institute of Oncology; Travel/Accommodation/Expenses: Chinese University of Hong Kong; Travel/Accommodation/Expenses: SOLTI; Travel/Accommodation/Expenses: Elsevier; Travel/Accommodation/Expenses: GlaxoSmithKline; Advisory/Consultancy: Novartis; Advisory/Consultancy: Eli Lilly; Advisory/Consultancy: Orion Pharmaceuticals; Advisory/Consultancy: Servier; Advisory/Consultancy: Peptomyc; Advisory/Consultancy: Merck Sharp & Dohme; Advisory/Consultancy: Kelun Pharmaceutical/Klus Pharma; Advisory/Consultancy: Spectrum Pharmaceuticals Inc; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Roche Pharmaceuticals; Advisory/Consultancy: Ellipses Pharma; Advisory/Consultancy: NovellusDx; Advisory/Consultancy: Ionctura; Advisory/Consultancy: Molecular Partners; Research grant/Funding (institution): Bayer; Research grant/Funding (institution): Blueprint Pharmaceuticals; Research grant/Funding (institution): Novartis; Travel/Accommodation/Expenses: ESMO; Travel/Accommodation/Expenses: US Department of Defense; Travel/Accommodation/Expenses: Louissiana State University; Travel/Accommodation/Expenses: Hunstman Cancer Institute; Travel/Accommodation/Expenses: Cancer Core Europe; Travel/Accommodation/Expenses: Karolinska Cancer Institute ; Travel/Accommodation/Expenses: King Abdullah International Medical Research Center (KAIMRC); Travel/Accommodation/Expenses: Molecular Partners; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Spectrum Pharmaceuticals; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Tocagen; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Symphogen; Non-remunerated activity/ies, Clinical Investigator in clinical trials: BioAtla; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Pfizer; Non-remunerated activity/ies, Clinical Investigator in clinical trials: GenMab; Non-remunerated activity/ies, Clinical Investigator in clinical trials: CytomX; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Kelun-Biotech; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Takeda-Millenium; Non-remunerated activity/ies, Clinical Investigator in clinical trials: GlaxoSmithKline; Non-remunerated activity/ies, Clinical Investigator in clinical trials: Ipsen. V. Serra: Research grant/Funding (institution): AstraZeneca; Research grant/Funding (institution): Genentech; Research grant/Funding (institution): Novartis. All other authors have declared no conflicts of interest.

Background

Amplification of RICTOR has been suggested to drive PI3K/mTOR pathway activation in squamous cell lung cancer (SQLC), representing a potential predictive biomarker of response to targeted therapy. Here, we sought to perform a thorough validation of RICTOR as predictive biomarker in SQLC preclinical models before advancing potential intervention strategies to the clinic.

Methods

Three SQLC cell lines (H-1869, H-1703, SK-Mes-1) and tissue samples (97 SQLC patients) were subjected to targeted DNA sequencing analysis, FISH, qRT-PCR, and immunoblotting. The activity of PI3K/mTOR pathway inhibitors was examined by cell viability assays, while RNA interference (RNAi) using inducible systems was applied to evaluate the impact of RICTOR knock-down on cell growth and response to drugs.

Results

RICTOR copy-number gain (CNG) was displayed in all cell lines (H-1869 harbored the highest CNG) and 28% of SQLC patients, as polysomy of the short arm of chromosome 5 as FISH (locus-specific, 5p-centromeric, and 5q-telomeric probes) revealed. Increasing levels of Rictor transcript/protein expression were detected in cell lines (H1869>SK-MES-1>H-1703). Therefore, we assessed causative link between RICTOR gene dosage and PI3K/mTOR pathway through genetic RNAi and pharmacological perturbation. We found that Rictor levels were not associated with increased activity of PI3K/mTOR axis or increased sensitivity to several pathway inhibitors (PF-05212384, AZD2014, MK-2206). Coherently, RICTOR silencing with inducible shRNA systems did not significantly affect cell growth and drug sensitivity of the three cell lines tested.

Conclusion

Here, we show that polysomy of 5p rather than amplification of RICTOR is evident in subset of SQLC patients and derived cell lines. While CNG of RICTOR corresponded to increased protein expression, no correlation was observed with PI3K/mTOR pathway activity and drug sensitivity in vitro. We complemented this with genetic perturbation analyses, whose results aligned with pharmacological findings and suggest that Rictor does not represent a predictive biomarker of response towards PI3K/mTOR directed therapy.

Legal entity responsible for the study

The authors.

Funding

Progetto AIRC (Fondazione AIRC per la Ricerca sul Cancro) IG 20583.

Disclosure

All authors have declared no conflicts of interest.

Background

Chronic myeloid leukemia (CML) is characterized by the production of BCR-ABL oncoprotein that has enhanced tyrosine kinase activity. The use of imatinib has redefined the survival of CML patients. Further understanding of disease pathogenesis has led to the identification of quiescent CML Leukemic Stem Cells (LSC) that are resistant to tyrosine kinase inhibitors (TKI) and lead to failure to achieve complete molecular response in many patients. The PPAR-γ agonists can purge them out of quiescence, thereby sensitizing them to imatinib. Hence, combining the two can act in synergy to deplete the leukemic cells. The objective of our study was to determine if the addition of PPAR-γ agonist, pioglitazone to imatinib could attain major molecular response (MMR) in patients who fail to achieve optimal response with imatinib.

Methods

Patients of CML-CP who failed to achieve MMR after at least 12-15 months of treatment with imatinib 400/600 mg and were IRMA negative were included in the study. They were continued on imatinib and received pioglitazone 30 mg once daily for 12 months with monitoring of BCR-ABL transcript levels at 6 and 12 months. Hereby we present the 6-month outcomes of these patients.

Results

A total of 31 patients were included of which 77.4% (n=24) had a decrease in BCR-ABL levels after 6 months with 16 patients (51.6%) showing more than 50% decrease and 7 patients (22.5%) achieving MMR. Two patients discontinued pioglitazone (after 5 and 6 months respectively) due to grade 1 pedal edema. No other patients had any significant increase in weight or a decrease in hemoglobin (p>0.05). There was no episode of hypoglycemia recorded. Patients with high BCR-ABL levels at the start of pioglitazone did not respond well, this could be due to other mechanisms of imatinib resistance.

Conclusion

Preliminary data show that the combination of PPAR-γ agonists with imatinib increases the response rates in CML patients by increasing the sensitivity to imatinib. This requires validation in randomized studies to identify the subgroup of patients who would derive clinical benefit with the addition of pioglitazone. It can be a good option in a low-resource setting where the availability of second-generation TKIs is still limited.

Legal entity responsible for the study

Department of Medical Oncology, Kidwai Memorial Institute of Oncology.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

Hypoxia is an extremely important condition for tumor metabolism. The cellular response to hypoxia is mainly mediated by the hypoxia-inducible factor (HIF) family of transcription factors, which regulate the expression of multiple genes engaged in different processes that lead to adaptation, progression and drug resistance of cancers. CA9 (CA IX) is a gene controlled by HIF-1α and is one of two tumor-associated carbonic anhydrase isoenzymes known. We aimed to obtain water-soluble derivatives of quinoxaline 1,4-dioxides targeting HIF-1α/CA9 path in breast cancer cells.

Methods

New 6(7)-amino derivatives were synthesized from corresponding 7- or/and 6-halogenoquinoxaline-2-carbonitrile 1,4-dioxides by the substitution of halogen atom by cyclic diamines. The antiproliferative activity of 6(7)-aminoquinoxaline-2-carbonitrile 1,4-dioxides was evaluated in normoxia and hypoxia. HIF-1α and CA9 expression was assessed by immunoblotting.

Results

All synthetized derivatives quinoxaline-2-carbonitrile 1,4-dioxides have higher cytotoxicity and hypoxia-selectivity against breast cancer cell lines (MCF-7, MDAMB-231) than reference drug tirapazamine. Furthermore, the cytotoxicity of obtained compounds highly increased under hypoxic conditions. The most hypoxia-selective derivatives were congeners bearing diamine in position 7 which had hypoxic cytotoxicity ratio (HCR) values ranges from 20 to 42. The most potent derivative LCTA-2647 in hypoxia had IC₅₀ value lower than 0.2 μM with HCR 37. Compounds LCTA-2424 and LCTA-2647 showed inhibitory effects on HIF-1α and CA9 expression in MCF-7 breast cancer cells.

Conclusion

Novel derivatives of 7-amino-quinoxaline-2-carbonitrile 1,4-dioxide showed high antiproliferative potency and hypoxia-selectivity. Lead compounds caused HIF-1α-CA9 inhibitory effects are considered as promising agents for tumors, including those with hypoxic areas.

Legal entity responsible for the study

Gause Institute of New Antibiotics.

Funding

The experiments were supported by Russian Foundation for Basic Research (RFBR) grants 18-53-34005 (chemistry) and 18-015-00422 (biology).

Disclosure

G.I. Buravchenko: Research grant/Funding (institution), Travel/Accommodation/Expenses: Gause Institute of New Antibiotics. All other authors have declared no conflicts of interest.

Background

Docetaxel therapy is approved for castration-resistant metastatic prostate cancer. However, it is unknown whether docetaxel should be added to the treatment regimen after patients become resistant to androgen deprivation therapy or only once they develop metastasis. Therefore, the aim of the study was to identify demographic, clinical and genetic predictors of docetaxel response which would help optimize both its use and timing for initiation.

Methods

A total of 209 prostate cancer patients were analyzed for factors predicting GRID (genome resource information database) gene expression scores for docetaxel response (score = 1-100) using linear regression. Factors included in the analysis were age, race, stress, comorbidity measured by TIBI-CaP (Total Illness Burden Index–Carcinoma Prostate), androgen receptor signaling and tumor proliferation signaling gene signatures, PSA (prostate specific antigen) levels, and Gleason grade.

Results

African American men had significantly lower docetaxel sensitivity compared to Whites based on GRID gene signatures. In a regression analysis, however, only comorbidity (β = -0.93, p=0.05), increasing androgen receptor signaling (β = 0.60, p <0.001) and tumor proliferation signaling gene signatures (β = 0.39, p <0.001) were significant predictors of genetics of docetaxel response independent of race. Additionally, TIBI-CaP was significantly correlated with tumor proliferation. The model explained 42% variance in the genetics of docetaxel response.

Conclusion

Optimization of docetaxel therapy use in prostate cancer should take into account patient’s comorbidity, androgen receptor signaling and tumor proliferation signaling gene signatures. Comorbidity may be exerting its effect on docetaxel response by increasing the chances of proliferation of the prostate tumor cells. The pharmacogenomics of docetaxel response could aid precision medicine initiatives by improving survival rates in prostate cancer patients.

Legal entity responsible for the study

The authors.

Funding

California Initiative to Advance Precision Medicine.

Disclosure

All authors have declared no conflicts of interest.

Background

Recently the texture analysis has been applied to help diagnose and predict the clinical outcome of various tumor types. To investigate the diagnostic ability of radiomics-based machine learning in differentiating atypical low-grade astrocytoma (LGA) from anaplastic astrocytoma (AA).

Methods

The present study included 106 patients diagnosed with LGA and AA at the department of neurosurgery, West China Hospital from January-2014 to December-2018. The radiomics features of tumor tissues were extracted from contrast-enhanced T1 weighted imaging (T1C) taken prior to treatment. Nine diagnostic models were established with three selection methods and three classification algorithms including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and random forest (RF). The sensitivity, specificity, accuracy, and area under curve (AUC) of each model were calculated, based on which the diagnostic ability of each model was evaluated.

Results

The algorithms-based models presented the most remarkable diagnostic performances. As for LDA-based models, the optimal one was the combination of LASSO+LDA with an AUC of 0.802. Furthermore, LASSO+SVM represented the optimal SVM-based model with an AUC of 0.799. As for RF-based models, LASSO+RF and GBDT+RF demonstrated feasible discriminative ability with AUC of 0.778.

Conclusion

The radiomic-based machine learning could potentially serve as differentiating tool for atypical low-grade astrocytoma and anaplastic astrocytoma. In view of the present study and previous reports, contrast-enhanced computed tomography-based radiomics can be recommended in the clinical practice.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

Phase I clinical trials are an essential step for the development of new anticancer treatments. Next-generation phase I trials investigating novel drugs led to consistent improvements in terms of response rates and survival of the enrolled pts. The aim of our study is to evaluate the outcomes of patients enrolled in phase I trials testing targeted therapies (TT), immunotherapy (IT), and combinations.

Methods

We retrospectively reviewed clinical characteristics and outcomes of all consecutive pts with advanced/metastatic cancers who were screened and/or treated at our Early Drug Development Unit between Dec 2014 and Nov 2018. Factors associated with ORR and CBR were tested with logistic regression in univariate and multivariate analyses. Primary objectives of the study were to determine overall response rate (ORR) and disease control rate (DCR), according to RECIST 1.1 or iRECIST criteria. Factors associated with ORR and CBR were tested with logistic regression in univariate and multivariate analyses. Statistical significance threshold was set to a two-tailed 0.05 value.

Results

723 pts were screened. Median age was 57 years (22-82). After study screening procedures, 481 pts (66.5%) resulted as not-eligible, mainly due to the absence of druggable molecular alteration(s) for biomarker-driven trials (56.1%), abnormal lab tests (12.7%), or poor performance status (11.4%). Conversely, the 242 (33.5%) eligible pts received IT (47.5%), TT (48.3%), or combinations (4.2%). Most common tumor types were breast, lung, gynecological, and gastrointestinal cancers (43.6%, 13.6%, 9.3%, 7.6%, respectively). ORR and CBR were 14.8% and 28.0%, respectively. Pts with less than 2 metastatic sites had a higher CBR (35% vs 17%; OR 2.67; 95% CI, 1.39-5.10; p=0.003), while pts who received less than 2 prior lines of systemic therapy presented higher ORR (18% vs 10%; OR 2.37; 95%, CI 1.03-5.44; p=0.004).

Conclusion

Our analysis confirms substantial improvements in terms of outcomes in next-generation phase I trials. Heavily pre-treated pts as well as those with higher burden of disease have worse outcomes, underlining that pts should be enrolled in earlier lines of therapy to maximize the clinical benefit.

Legal entity responsible for the study

Istituto Europeo di Oncologia IRCCS.

Funding

Has not received any funding.

Disclosure

G. Curigliano: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche, Pfizer, Novartis, Seattle Genetics, Lilly, Ellipses Pharma, Foundation Medicine and Samsung. All other authors have declared no conflicts of interest.

Background

CellMiner and CellMiner Cross Database (CDB) function to integrate datasets and allow comparison of genomic, molecular and pharmacological data within multiple cancerous cell line sets, including the i) National Cancer Institute's NCI-60, ii) Cancer Cell Line Encyclopedia (CCLE), iii) Genomics of Drug Sensitivity in Cancer (GDSC), iv) Cancer Therapeutics Response Portal (CTRP), v) NCI/DTP small cell lung cancer (SCLC), and vi) the NCI Almanac (with two-drug combinations).

Methods

CellMiner facilitates pharmacogenomics analyses for the NCI-60. It currently includes 24 downloadable data sets. CellMinerCDB facilitates pharmacogenomics analyses for the NCI-60, CCLE, GDSC, CTRP, NCI/DTP SCLC, and NCI Almanac cell line sets. It currently includes 26 downloadable data sets. Both provide multiple tools query functions, and supportive information and are described in detail in their respective urls.

Results

CellMiner contains data for the NCI-60, including the most extensive public set of cell line molecular and drug activity data. The drug data is generated by the NCI Developmental Therapeutics Program https://dtp.cancer.gov. These include 4.0×10⁹ gene alteration versus compound activity combinations. CellMinerCDB contains data for the CCLE, GDSC, and CTRP, which provide substantially increased cell line numbers and tissue of origin types. These include 7.2×10⁷ gene alteration versus compound activity combinations. Taken together, the two web-applications provide partially overlapping complimentary data and functionalities. The data types available for each cell line set varies, as well as the numbers of cell lines that overlap between cell line sets. There are 60 cell lines for the NCI-60, 67 for the NCI/DTP SCLC, 1,036 for the CCLE, 1,080 for the GDSC, and 823 for CTRP. Using the overlaps that exist between these cell line sets, one may fill in data gaps, extend analyses, and assess quality and reliability.

Conclusion

Exploration of pharmacological responses in cancers is facilitated by the rich and unmatched set of data and functionalities made available within these tools, and it serves as a base for translational analysis.

Legal entity responsible for the study

The National Cancer Institute, USA.

Funding

The National Cancer Institute, USA.

Disclosure

All authors have declared no conflicts of interest.

Background

Resistance to targeted therapy is one of the important problems in oncology. The main purpose of the work was to study the exosomes involvement in the progression of the resistance of breast cancer cells.

Methods

MCF-7 breast cancer cell line was obtained from the ATCC collection. The cells-derived exosomes were isolated by ultracentrifugation and thoroughly characterised. Protein expression was measured by immunoblotting. To measure AP1 activity gene-reporter assay was used.

Results

The rapamycin-resistant MCF-7 cells were developed under long-term treatment of the cells with the increasing doses of rapamycin. The selected cells named as MCF-7/Rap were characterized with the resistance to rapamycin, and at the same time - the partial resistance to antiestrogen tamoxifen. We have shown that the treatment of the parent MCF-7 cells with exosomes from the resistant MCF-7/Rap cells within 14 days lead to the cross resistance of the MCF-7 cells to rapamycin and tamoxifen. The MCF-7/Rap cells and the cells with the exosome-induced resistance were characterized with the increased expression of mTOR-interacting Raptor protein, activation of Akt and transcriptional factor AP-1.

Conclusion

The results obtained demonstrate the important role of Akt/mTOR signaling in the development of exosome-induced cancer cell resistance to growth signal-targeting anti-tumor drugs.

Legal entity responsible for the study

The authors.

Funding

RSF (19-15-00245, resistance studies) and RFBR (18-29-09017, exosome characterization).

Disclosure

All authors have declared no conflicts of interest.

Background

Patient-derived xenograft (PDX), a cancer stem cell (CSC)-derived in vivo model, is an accepted model of choice for preclinical and translational research due to its proven predictive power. Patient-derived cancer organoids (PDOs), also CSC-derived 3D culture of carcinoma with defined structures, harbor carcinoma’s multicellular components and mimics cancer lesion structures/heterogeneity, both genomicly and histopathologically. PDO was first described by Hans Clevers Lab and proven to be a predictive model for preclinical research, similar to PDX.

Methods

We have used the Hubrecht organoid technology (HUB approach to systematically create the worlds-first biobank of organoids derived from a well annotated PDX library (the world’s largest with >2,500, covering a variety of carcinomas, with extensive pathology, genomic and treatment information), referred to as PDXOs. We then systematically profiled these PDXOs by WES (whole exome sequencing)/RNAseq (transcriptome sequencing), histopathology and standard of care (SOC) treatment.

Results

At present, we have established > 150 PDXOs covering > 15 cancer types, including bladder, breast, colorectal, gastric, liver, lung, ovarian and pancreatic cancer, cholangiocarcinoma, etc. Histopathological analysis showed cellular/structural similarities (ductal, mucous or carcinoid) between PDXO and original PDX, suggesting that tissue specific structural features were maintained in the 3D organoids. A high throughput screening (HTS in 384 well) format was established using the PDXOs and SOC sensitivity testing was conducted. The preliminary results largely correlated to the SOC response seen in vivo for the corresponding PDXs.

Conclusion

In summary, we have successfully established a large biobank of the PDXOs that mirror the original PDXs, creating a unique library of matched in vitro/in vivo models with high translational power and enabling HTS, thus likely become an important tool for the future oncology drug discovery and development tools.

Legal entity responsible for the study

CrownBio.

Funding

CrownBio.

Disclosure

L. Bourre, X. Xu, L. Shang, L. Wang, C. Li, Y. Liu, P. Han, Z. Sun, Y. Qu, L. Zhang, B. Chen, D. Ouyang, Y. Huang, H. Li: Full/Part-time employment: CrownBio.