Virtual Library
Start Your Search
M. Cabanero
Author of
-
+
P2.03b - Poster Session with Presenters Present (ID 465)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Advanced NSCLC
- Presentations: 2
- Moderators:
- Coordinates: 12/06/2016, 14:30 - 15:45, Hall B (Poster Area)
-
+
P2.03b-077 - EGFR/ALK+ Patient-Derived Xenografts from Advanced NSCLC for TKI Drug Selection & Resistance Development: The REAL-PDX Study (ID 6081)
14:30 - 14:30 | Author(s): M. Cabanero
- Abstract
Background:
Lung cancer patient-derived xenografts (PDX) have shown to be representative models for individual patient tumors. Theoretically, such models could inform the choice of subsequent lines of therapy, since PDX development, TKI resistance induction, and subsequent drug-screening can be completed before TKI resistance develops in the patient. The goal of Resistance modeling in EGFR and ALK Lung cancer (REAL)-PDX is to develop PDX models for real-time treatment selection of subsequent lines of therapy in advanced-stage NSCLC patients.
Methods:
Since August 2015, Princess Margaret Cancer Centre patients with EGFR/ALK+, as well as lifetime never-smoking lung cancer patients with unknown mutation status, were consented to have additional tumor sampling for PDX development during routine- or trial-related biopsies. Tumor sufficiency was confirmed prior to implantation into non-obese severe combined immunodeficient (NOD-SCID) mice, with successful engraftment defined as propagation beyond first passage; unsuccessful implantations had no palpable tumor after 6 months.
Results:
72/82 (88%) approached patients consented; 49/72 (68%) had adequate tumor tissue for implantation (71% stage III/IV): 46 adenocarcinomas, 2 squamous cell carcinoma, 1 LCNEC. 36/49 (73%) were lifetime never smokers. Patients received adjuvant chemotherapy (3), TKI therapy (15), both (5), or no treatment (26) prior to sampling. Tumor samples were taken from surgically resected lung (18), metastatic adrenal (1) and brain (2), CT-guided lung biopsies (5), endoscopic ultrasound-guided (EBUS) biopsies (6), and thoracentesis pleural fluid (17) specimens. Twenty-eight implanted tumors were EGFR+ (12 exon19 deletions, 2 exon19 deletion/T790M, 1 exon19 del/exon18 mutation, 12 L858R, and 1 L858R/T790M); 7 had ALK-rearrangements, and 1 had ROS1-rearrangement. Engraftment rates of 31 assessable implanted tumors were as follows: lung resections 12/12 (100%), metastatic resections 2/3 (67%), CT- or EBUS-guided biopsies 1/5 (20%), and pleural fluid 2/11 (18%); Engraftment rate was associated with no prior treatment (14/17 no treatment vs 3/14 any treatment, p=0.001). Of 17 assessable tumors with EGFR activating mutations, 9 engrafted (53%). Of 3 assessable tumors with ALK-rearrangement, 1 was successful (33%).
Conclusion:
PDX development of EGFR/ALK+ models for testing with novel therapeutics from various tumor biopsy sites is feasible and will provide valuable real-time information for subsequent treatment decisions in advanced NSCLC patients. Updated engraftment and drug screening data will be presented.
-
+
P2.03b-089 - CD1C in Lung Adenocarcinoma: Prognosis and Cellular Origin (ID 4809)
14:30 - 14:30 | Author(s): M. Cabanero
- Abstract
Background:
Adaptive immune response is critical for cancer surveillance and elimination. Dendritic cells (DC) arise from a hematopoietic lineage distinct from other leukocytes which play a central role in adaptive immunity. CD1C is expressed in DC, presenting exogenous lipid antigens to T cell receptor to activate “unconventional” T cells. This study aims to evaluate the cellular expression and prognostic value of CD1C.
Methods:
The study used 5 gene expression datasets: UHN181 [lung adenocarcinoma (ADC, n=128), squamous cell carcinoma (SqCC, n=43)], GSE30219 (ADC n=81, non-ADC n=138)], and 3 integrated cohorts [non-SqCC NSCLC (n=1106), PRECOG (39 types of cancer, n=~18,000), and TCGA (33 types of cancer, n=11,000)]. Cancer Cell Line Encyclopedia (CCLE) data were used to determine if CD1C was expressed by cancer cell lines. CIBERSORT algorithm was used to estimate immune cell fraction and Cox proportional model was used to evaluate the association of CD1C expression with survival. Immunohistochemistry (IHC) was used to measure protein expression of CD1C.
Results:
Except for hematopoietic and lymphoid cancer cell lines, all CCLE cell lines lack CD1C expression. CIBERSORT analysis together with Pearson correlation analyses on the ADC cases in UHN181, the integrated cohort, and GSE30219 showed that CD1C was expressed by DC. IHC showed staining with a dendritic cell shape pattern. However, the staining of CD1C did not overlapped with CD11c staining, suggesting a specific DC subtype. Cox proportional regression revealed that CD1C was significantly prognostic in the UHN181 ADC cohort (HR=0.75, p=0.05) as the training set. When CD1C expression was categorized into 3 equal groups, the risk of death was reduced in high compared to low CD1C expression group (HR=0.55, 95%CI 0.28-1.07, p=0.07). CD1C is protective only in PD-L1 low expression group (n=108, HR=0.37, 95%CI 0.15-0.89, p=0.026). The favorable prognosis associated with CD1C expression was validated in the integrated cohort of non-SqCC NSCLC (HR=0.55, 95% CI 0.43-0.72, p<0.0001), and in GSE30219 ADC cohort (HR=0.30, 95% CI 0.11-0.84, p=0.02). In PRECOG and TCGA datasets, high CD1C expression is significantly good prognostic in all cancer types (p<1×10[-7] and p<0.001, respectively), suggesting a universal protective role of CD1C expression in cancers. CD1C IHC score was highly correlated with CD1C mRNA expression in ADC patients of UHN181 and was prognostic (HR=0.46, 95%CI 0.22-0.96, p=0.039).
Conclusion:
CD1C preferentially is expressed on a subset of DCs and higher expression of CD1C is significant protective factor in all cancer types, especially in lung adenocarcinoma
