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Francesca Veneziano
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P1.04 - Immuno-oncology (ID 164)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Immuno-oncology
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.04-45 - Immune-Oncology Gene Expression Profiles Allow Lung Cancer Patients’ Stratification and Identification of Responders to Immunotherapy (ID 2339)
09:45 - 18:00 | Author(s): Francesca Veneziano
- Abstract
Background
Immune-checkpoint inhibitors (ICI) represent a new standard of care for Non-Small Cell Lung Cancer (NSCLC) patients. Beyond tumor PD-L1 protein expression, other biological parameters are emerging as potential predictive biomarkers. We evaluated high-throughput immune-related Gene Expression Profiles (GEP) in tumor tissue from ICI-treated patients, correlating immune activation data with clinical response to immunotherapy.
Method
RNA was isolated from tumor tissues of 44 metastatic NSCLC patients treated with Nivolumab (as 2nd or 3rd line therapy) and collected from different Italian centers. The nCounter® PanCancer IO360™ Panel was applied on NanoString platform to analyze 770 genes involved in key immuno-oncology pathways. Clinical-pathological data, as well as best response to ICI treatment, have been collected.
Result
Patients were dichotomized as responders (7 Partial Response and 19 Stable Disease) and non-responders (18 Progressive Disease). A pre-identified T-cell inflamed signature was evaluated at single gene level and the expression of CCL5, CD27, CD276, CMKLR1, CXCL9, CXCR6, LAG3, NKG7, PDCD1LG2, PSMB10, TIGIT was higher in the responder group, although not reaching statistical significance. Moreover, higher STING, CGAS and IRF3 genes expression level appeared to be more commonly associated with non-responder patients.
Considering the disease stage at the time of diagnosis, a different gene panel (CCL5, CD27, CD274, CD8A, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PSMB10, TIGIT) resulted to be more expressed in early and locally advanced (16 from stage I to IIIA) compared to metastatic (28 stage IV) tissue samples.
Conclusion
A trend in differential expression patterns was observed between responders and non-responders NSCLC patients treated with Nivolumab and additional analyses on this cohort could reveal specific pathways able to predict unresponsiveness to ICI treatment. Different disease stage seems also to influence immune-related GEPs.
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P2.09 - Pathology (ID 174)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Pathology
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.09-18 - Lymphocyte Infiltration Pattern and STING Expression Identify Different Prognostic Groups in Early Stage NSCLC (ID 2536)
10:15 - 18:15 | Author(s): Francesca Veneziano
- Abstract
Background
Lymphocyte infiltration has been described has a potential biomarker of lung cancer patients’ survival. Different studies de-convoluted immune cell compartment (i.e. stromal CD8 density) trying to identify clinically relevant immune patterns.
Method
A series of 178 early-stage (IB-IIIA) NSCLC has been retrospectively collected at Department of Oncology, San Luigi Hospital (Orbassano, Italy). From Formalin-Fixed and Paraffine-Embedeed (FFPE) tumor blocks, Tissue Microarrays (TMA) were constructed (4 cores were selected for each case). Lymphocyte infiltration pattern was determined by light-microscopy on Hemathoxylin-Eosin (HE) whole slides. Immunohistochemistry was performed as follow: CD8 (SP57) and STING (D2P2F) antibodies were tested with Ventana Benchmark and PD-L1 (22C3) with Dako Autostainer. Infiltration pattern has been clustered in 4 different categories: brisk-diffuse, non-brisk multifocal, non-brisk focal and none. CD8 was quantified as positivity percentage, PD-L1 through TPS (<1%, 1-49% and ≥50%) and STING taking advantage of H-score. Overall survival (OS) and Progression Free Survival (PFS) were estimated using the Kaplan-Meier method and compared using log-rank test.
Result
Most represented patients had following features: male (119-71%), current or previous smokers (145-82%), stage II (94-53%) and adenocarcinoma histology (119-67%). Distribution of lymphocyte infiltration pattern was: 110 cases with brisk-diffuse (62%), 56 with non-brisk (multi-focal and focal) (31%) and 12 with none pattern (7%). CD8 positivity was distributed in 3 categories: high (66 - 37%), intermediate (75 - 42%) and low (37 -21%) density. For PD-L1 TPS analyses 111 cases (62%) had <1%, 39 cases (22%) 1-49% and 28 cases (16%) >50%. STING high-expressors were 88 (49%) and low-expressors 90 cases (51%). Lastly, were identified 81 samples (45%) with STING positivity at high-density on immune cells (IC) and 97 samples (55%) with low-density. As expected, Brisk-infiltrated samples presented an higher CD8 density (p=0.015). At PFS analyses, STING IC resulted associated (p=0.05) with a worse PFS for high-density patients. At OS analyses, brisk lymphocyte infiltration pattern appeared to have a negative impact (p=0.05) and STING higher-expressors on tumor cells had a worse prognosis (p=0.04).
Conclusion
NSCLC with wider lymphocyte infiltration and expression of immune activation markers (as STING) appeared to be associated with a worse prognosis (PFS and OS). These date need further validation at multivariate analyses.
