Advanced Stage NSCLC Patients Research Articles

EGFR-mutant NSCLC may remodel TME from non-inflamed to inflamed through acquiring resistance to EGFR-TKI treatment

BackgroundEGFR-TKI represent the standard first-line therapy for advanced NSCLC harboring EGFR mutations. However, resistance to EGFR-TKI inevitably develops in nearly all patients. Previous clinical study have demonstrated that, some patients that failed EGFR-TKI therapy show a benefit outcome from immunotherapy. Our objective is to explore the immune microenviroment remodeling induced by EGFR-TKI treatment in EGFR mutant lung cancer patients and to investigate the immune cell types and potential molecular signatures involved. MethodsA cohort of 37 EGFR mutant advanced-stage NSCLC patients, who are resistant to at least one type of TKI treatment, was retrospectively established. Both pre-treatment and TKI resistance tumor FFPE samples of each pairs were collected. Transcriptional profiling and bioinformatics analysis were employed to evaluate the change of immune associated hallmarks before and after EGFR-TKI therapy. ResultsTumor samples after EGFR-TKI treatment displayed enrichment of proinflammatory signaling like interferon-γ, allograft rejection and inflammatory response. Of note, cytotoxic factor granzyme A as well as PD-L1 were found to be more expressed in EGFR-TKI resistance samples. Approximately 33.3 % (11/33) of EGFR-TKI treated samples were classified as “hot” tumor, especially for EGFR L858R mutated NSCLC patients (46.7 %,7/15). Effector cells were significantly overexpressed in ‘hot’ tumors feature following TKI resistance. In addition, we found that four effector genes (CD8A, CDB8, GZMB, GZMK) showed higher expression in ‘hot’ tumors post-TKI resistance, and its 4-gene effector cell signature was found to have a good correlation with survival benefit in external immunotherapy database. ConclusionsTKI treatment may initiate immune activation in EGFR mutant NSCLC, leading to changes in immune cell infiltration following TKI resistance. We mechanistically explored that this might be due to an increased immune response caused by the rise in effector cells post-TKI resistance.

Beyond clinical trials: real-world impact of immunotherapy on NSCLC in Jordan.

This study aims to evaluate real-world (rw) outcomes of immunotherapy (IO) for advanced stage NSCLC at King Hussein Cancer Center (KHCC) in Jordan. Advanced stage NSCLC patients who received IO at KHCC between 2017 and 2022 were included. The data were retrospectively collected. PFS and OS were estimated for patients with ECOG performance status (ECOG PS) 0-1. Cox regression analyzed predictors of OS in first-line (1L) IO, regardless of performance status. The total number of patients included was 244. Out of those, 160 (65%), 67 (28%), and 17 (7%) patients received IO as 1L, second-line (2L), or third-line or beyond (3L or beyond), respectively. The median age for all patients was 59 years. Male were 88%, and 77% were smokers. The median follow-up time was 12.5 months. The median PFS and OS for 1L IO were 7 [95% CI 5.8 - 10.3] and 11.8 [95% CI 8.8 - 14.4], months, respectively. In the first 3 months after starting 1L IO, 34/160 (21%) patients had died. For those who survived beyond 3 months after starting 1L IO, the median PFS and OS were 11.3 [95% CI 8.3 - 16.5] and 15.4 [95% CI 13.2 - 21] months, respectively. In the Cox regression model of 1L IO patients with any performance status, ECOG PS 2 was predictive of worse OS compared to ECOG PS 0-1 (p= 0.005). This real-world study of advanced-stage NSCLC patients treated with immunotherapy at KHCC reveals outcomes that fall short of those anticipated from clinical trials. The inclusion of Middle Eastern patients in lung cancer trials is essential to ensure adequate representation of various ethnicities in clinical research.

Abstract 2526: Exploratory study of predicting systemic therapy response by IGRA in advanced stage NSCLC patients

Abstract Purpose: In this study, we aim to prospectively evaluate how patients’ pretreatment PSIG correlated with chemotherapy, immune checkpoint inhibitors (ICI) and epidermal growth factor receptor (EGFR) Tyrosine Kinasae Inhibior (TKI). Also, to assess the change of PSIG during anti-cancer treatment and the relation with clinical condition. Materials and Methods: Newly diagnosed advanced stage non-small cell lung cancer patients were enrolled. The inclusion criteria included pathology or cytology-proved stage IV and non-operable stage III non-small cell lung cancer, treatment-naïve, and planned to receive chemotherapy, EGFR-TKI therapy. Or, planned to receive any line of singe agent immunotherapy. We planned to enroll 30 patients in each treatment group (chemotherapy, immunotherapy, EGFR TKI therapy) with and additional control group of stage I NSCLC.Blood sample from each enrolled patient was obtained for INF-γ release assay (IGRA) within 3 days before the initiation of systemic therapy and 8-12 weeks after treatment. The IGRA was performed with QuantiFERON-TB In-Tube (QFT-GIT; Qiagen, Germany) according to the manufacture’s instruction. The amount of INF-γ produced in response to PHA is determined by the INF-γ level in the PHA-coated tube minus saline-coated tube, and is termed PHA-stimulated INF-γ (PSIG) level. Patients with PSIG level above 7.06IU were defined had high PSIG level according to our previous study. we also performed our in house INF-γ level by ELISA. Tumor response was assessed mainly by chest CT and brain MRI (if available) according to Response Evaluation Criteria in Solid Tumors (RECST). Results: Total 116 patients were enrolled. Demographic distribution was summarized in Table 1. Thirty-five of 116 (30.2%) patients had latent TB infection, while 12 patients (10.3%) had indeterminate OFT test, all due to low mitogen-stimulated INF-γ level. 84 patients had been obtained post-treatment blood test, and the box-plot of in-house INF-γ level were shown in Figure1. For stage I control group, INF-γ level seemed higher after surgery; for chemotherapy and immunotherapy, the INF-γ level also seemed increase among responders (who achieved disease control after treatment). There were no statistically difference of disease control rate between patients with high PSIG level and low PSIG level. Overall survival also showed no statistically difference between 2 PSIV level patient group among advanced stage NSCLC patients. Conclusions:There were no statistically different of disease control rate in PSIG high and low group. The increased trend of INF-γ level after surgery, immunotherapy and chemotherapy may suggested improving immune function after treatment even in the very early disease stage. Citation Format: Hsu Ching Huang, Chi-Lu Chiang, Yung-Hung Luo, Yuh-Min Chen, Chao-Hua Chiu. Exploratory study of predicting systemic therapy response by IGRA in advanced stage NSCLC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2526.

TCR-β Repertoire as a Source of Biomarkers for anti-PD1 Treatment Alone or in Combination With Chemotherapy in Advanced-stage NSCLC Patients

TCR-β Repertoire as a Source of Biomarkers for anti-PD1 Treatment Alone or in Combination With Chemotherapy in Advanced-stage NSCLC Patients

Cell-Free Methylated PTGER4 and SHOX2 Plasma DNA as a Biomarker for Therapy Monitoring and Prognosis in Advanced Stage NSCLC Patients

Notwithstanding some improvement in the earlier detection of patients with lung cancer, most of them still present with a late-stage disease at the time of diagnosis. Next to the most frequently utilized factors affecting the prognosis of lung cancer patients (stage, performance, and age), the recent application of biomarkers obtained by liquid profiling has gained more acceptance. In our study, we aimed to answer these questions: (i) Is the quantification of free-circulating methylated PTGER4 and SHOX2 plasma DNA a useful method for therapy monitoring, and is this also possible for patients treated with different therapy regimens? (ii) Is this approach possible when blood-drawing tubes, which allow for a delayed processing of blood samples, are utilized? Baseline values for mPTGER4 and mSHOX2 do not allow for clear discrimination between different response groups. In contrast, the combination of the methylation values for both genes shows a clear difference between responders vs. non-responders at the time of re-staging. Furthermore, blood drawing into tubes stabilizing the sample allows researchers more flexibility.

Abstract 2159: A pretreatment blood-based proteomic biomarker for enhanced decision-making in non-small cell lung cancer

Abstract Introduction: Treatment modality selection for metastatic NSCLC patients (immunotherapy alone vs. combination of immunotherapy with chemotherapy) relies mainly on determining the programmed cell death 1 (PD-L1) expression levels in the tumor. However, available assays are only moderately predictive. Here we set to develop PROphet®, a plasma proteomics-based predictive model for informing treatment decisions for NSCLC patients receiving immune checkpoint inhibitor (ICI)-based therapy. Methods: Pre-ICI plasma samples were collected in 12 centers in a clinical trial (NCT04056247) from 367 advanced-stage NSCLC patients. Clinical benefit (CB) was assessed at 12 months based on the occurrence of progression-free survival (PFS) until this time point. Deep proteomic profiling of the plasma samples was performed using aptamer-based technology. A novel machine learning model was developed to determine the CB probability for each patient, and the performance was successfully evaluated on an independent validation set, followed by training and prediction over the entire cohort using cross-validation. The resulting PROphet® score (positive or negative) was determined by setting the median CB rate probability as a threshold. The patients were divided into four subgroups based on their PD-L1 expression level combined with their PROphet® score prediction, and the overall survival (OS) was examined for each subgroup. Results: The PROphet® computational model was evaluated in a blinded manner on a subset of 85 patients and displayed strong predictive capability with area under the curve (AUC) of the receiver operating characteristics (ROC) plot of 0.78 (p-value = 5.00e-05), outperforming a PD-L1-based predictive model (AUC = 0.62; p-value 2.76e-01). When combining PROphet® score with PD-L1 expression levels, four different outcome patterns were identified: (i) Patients with PD-L1 ≥50% and PROphet® negative score, who displayed significantly longer OS when treated with ICI-chemotherapy combination therapy compared to ICI monotherapy and may consider combination therapy. (ii) Patients with PD-L1 ≥50% and PROphet® positive score, who benefit similarly from either treatment modalities, and may consider monotherapy to avoid the potential toxicity of the combination therapy. (iii) Patients with PD-L1<50% and PROphet® negative score, who do not benefit from either treatment modalities and may consider chemotherapy alone or treatment beyond standard of care. (iv) Patients with PD-L1<50% and PROphet® positive score who benefit from combination therapy. Conclusions: Altogether, the PROphet® model, when combined with PD-L1 test, stratifies the patients into four subgroups, providing additional resolution to the PD-L1 biomarker currently used to guide treatment selection. Furthermore, the model accurately predicts CB at 12 months based on proteomic analysis of a pre-treatment plasma sample. Citation Format: Michal Harel, Petros Christopoulos, Coren Lahav, Itamar Sela, Nili Dahan, Niels Reinmuth, Ina Koch, Alona Zer, Mor Moskovitz, Adva Levy-Barda, Michal Lotem, Hovav Nechushtan, Rivka Katzenelson, Abed Agbarya, Mahmoud Abu-Amna, Maya Gottfried, Ido Wolf, Ella Tepper, Yanyan Lou, Raya Leibowitz, Adam P. Dicker, David Gandara, David P. Carbone. A pretreatment blood-based proteomic biomarker for enhanced decision-making in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2159.

Plasma-Based microRNA Expression Analysis in Advanced Stage NSCLC Patients Treated with Nivolumab.

Simple SummaryNivolumab (anti-PD-1 inhibitor) is the first monoclonal antibody approved for the treatment of NSCLC, with research results showing that patients who had received previous lines of therapy had a better response to this treatment and better overall survival. Tissue-level analyses fail to capture the dynamic tumor-host relationship, in contrast to circulating biomarkers, which can reflect the systemic response of the tumor, allowing for repeated sampling and monitoring. In the context of liquid biopsy, microRNAs are studied as biomarkers of immunotherapy efficacy based on their role in regulating antitumor immunity. The present study suggests that miR-200c and miR-34a plasma expression levels have a prognostic role in patients with advanced NSCLC receiving Nivolumab. It further supports that the expression profile of circulating immunomodulatory microRNAs provides information on the survival of patients with advanced NSCLC receiving Nivolumab and could represent promising circulating biomarkers that may provide information about patients’ responses to immunotherapy.Since circulating microRNAs (miRNAs) are involved in the modulation of the immune response, they are tested as liquid biopsy-based biomarkers in patients with NSCLC treated with immunotherapy. We analyzed the expression levels and examined the clinical significance of immunoregulatory miRNAs involved in immune checkpoint regulation (miR-34a, miR-200b, miR-200c), T-cell activity (miR-155), and the function of myeloid-derived suppressive cells (MDSCs) (miR-223) or regulatory T lymphocytes (Tregs) (miR-146a), in patients with advanced NSCLC (N = 69) treated with anti-PD-1 (Nivolumab) immunotherapy as 2nd or 3rd line of treatment therapy. Plasma levels of circulating miRNAs were analyzed by RT-qPCR before the initiation of immunotherapy. Expression of miR-34a, miR-146a, mir-200c, and miR-223 was found to be associated with response to immunotherapy. High miR-200c expression emerged as an independent prognostic factor for inferior overall survival in all patients with NSCLC (OS, HR: 2.243, 95% CI: 1.208–4.163; p = 0.010) and in patients with non-Squamous (non-SqCC) subtype (N = 38) (HR: 2.809, 95% CI: 1.116–7.074; p = 0.028). Low miR-34a expression independently predicted for shorter OS (HR: 3.189, 95% CI: 1.193–8.527; p = 0.021) in the non-SqCC subgroup. Our findings suggest that alterations in circulating miR-200c and miR-34a expression levels are associated with the response and outcome in patients with advanced NSCLC treated with anti-PD1 immunotherapy.

HALP score and GNRI: Simple and easily accessible indexes for predicting prognosis in advanced stage NSCLC patients. The İzmir oncology group (IZOG) study.

ObjectiveThe Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and the Geriatric Nutrition Risk Index (GNRI) are used as prognostic factors in different types of cancers. In this study we analyzed the prognostic value of the HALP Score and the GNRI calculated prior to first-line treatment in patients diagnosed with de novo metastatic non-small cell lung cancer (mNSCLC).Materials and methodsDe novo mNSCLC patients were retrospectively evaluated from January 2016 to December 2019. Patients with Driver’s mutation, severe comorbidities, active infection, or insufficient organ function, and those receiving anti-inflammatory treatment were excluded from the study. Optimal cut-off points for the HALP score and the GNRI were calculated with the receiver operating characteristic (ROC) curve analysis. Predictive factors for overall survival (OS) were assessed with univariate and multivariate Cox proportional hazard analyses, and OS was studied with the Kaplan–Meier analysis.ResultsThe study included 401 patients in total. In the ROC curve analysis, the cut-off points were found 23.24 (AUC = 0.928; 95% CI: 0.901–0.955, p < 0.001) for HALP, and 53.60 (AUC = 0.932; 95% CI: 0.908–0.955, p < 0.001) for GNRI. Groups with lower HALP scores and lower GNRI had significantly shorter OS compared to those with higher HALP scores and GNRIs. Univariate analysis showed that male gender, smoking, high ECOG score, low HALP score and low GNRI were associated with worse survival rates. Multivariate analysis showed that low HALP score (HR = 2.988, 95% CI: 2.065–4.324, p < 0.001); low GNRI score (HR = 2.901, 95% CI: 2.045–4.114, p < 0.001) and smoking history (HR = 1.447, 95% CI: 1.046–2.001, p = 0.025) were independent factors associated with worse OS rates.ConclusionOur study showed the HALP score and the GNRI to be of prognostic value as simple, cost-effective, and useful markers that predict OS in de novo mNSCLC patients.

Prognostic value of integrating circulating tumour cells and cell-free DNA in non-small cell lung cancer

BackgroundNon-small cell lung cancer (NSCLC) often presents at an incurable stage, and majority of patients will be considered for palliative treatment at some point in their disease. Despite recent advances, the prognosis remains poor, with a median overall survival of 12–18 months. Liquid biopsy-based biomarkers have emerged as potential candidates for predicting prognosis and response to therapy in NSCLC patients. This pilot study evaluated whether combining circulating tumour cells and clusters (CTCs) and cell-free DNA (cfDNA) can predict progression-free survival (PFS) in NSCLC patients. MethodsCTC and cfDNA/ctDNA from advanced stage NSCLC patients were measured at study entry (T0) and 3-months post-treatment (T1). CTCs were enriched using a spiral microfluidic chip and characterised by immunofluorescence. ctDNA was assessed using an UltraSEEK® Lung Panel. Kaplan-Meier plots were generated to investigate the contribution of the presence of CTC/CTC clusters and cfDNA for PFS. Cox proportional hazards analysis compared time to progression versus CTC/CTC cluster counts and cfDNA levels. ResultsSingle CTCs were found in 14 out of 25 patients, while CTC clusters were found in 8 out of the 25 patients at T0. At T1, CTCs were found in 7 out of 18 patients, and CTC clusters in 1 out of the 18 patients. At T0, CTC presence and the combination of CTC cluster counts with cfDNA levels were associated with shorter PFS, p = 0.0261, p = 0.0022, respectively. ConclusionsCombining CTC cluster counts and cfDNA levels could improve PFS assessment in NSCLC patients. Our results encourage further investigation on the combined effect of CTC/cfDNA as a prognostic biomarker in a large cohort of advanced stage NSCLC patients.

Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict PET Image Quality of Three Generations EGFR TKI in Advanced-Stage NSCLC Patients.

Introduction: Epidermal growth factor receptor (EGFR) mutated NSCLC is best treated using an EGFR tyrosine kinase inhibitor (TKI). The presence and accessibility of EGFR overexpression and mutation in NSCLC can be determined using radiolabeled EGFR TKI PET/CT. However, recent research has shown a significant difference between image qualities (i.e., tumor-to-lung contrast) in three generation EGFR TKIs: 11C-erlotinib, 18F-afatinib and 11C-osimertinib. In this research we aim to develop a physiological pharmacokinetic (PBPK)-model to predict tumor-to-lung contrast and as a secondary outcome the uptake of healthy tissue of the three tracers. Methods: Relevant physicochemical and drug specific properties (e.g., pKa, lipophilicity, target binding) for each TKI were collected and applied in established base PBPK models. Key hallmarks of NSCLC include: immune tumor deprivation, unaltered tumor perfusion and an acidic tumor environment. Model accuracy was demonstrated by calculating the prediction error (PE) between predicted tissue-to-blood ratios (TBR) and measured PET-image-derived TBR. Sensitivity analysis was performed by excluding each key component and comparing the PE with the final mechanistical PBPK model predictions. Results: The developed PBPK models were able to predict tumor-to-lung contrast for all EGFR-TKIs within threefold of observed PET image ratios (PE tumor-to-lung ratio of −90%, +44% and −6.3% for erlotinib, afatinib and osimertinib, respectively). Furthermore, the models depicted agreeable whole-body distribution, showing high tissue distribution for osimertinib and afatinib and low tissue distribution at high blood concentrations for erlotinib (mean PE, of −10.5%, range −158%–+190%, for all tissues). Conclusion: The developed PBPK models adequately predicted the image quality of afatinib and osimertinib and erlotinib. Some deviations in predicted whole-body TBR lead to new hypotheses, such as increased affinity for mutated EGFR and active influx transport (erlotinib into excreting tissues) or active efflux (afatinib from brain), which is currently unaccounted for. In the future, PBPK models may be used to predict the image quality of new tracers.

Association of a novel 27-gene immuno-oncology assay with efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer

BackgroundImmune checkpoint inhibitor (ICI) therapies represent a major advance in treating a variety of advanced-stage malignancies. Nevertheless, only a subset of patients benefit, even when selected based on approved biomarkers such as PD-L1 and tumor mutational burden. New biomarkers are needed to maximize the therapeutic ratio of these therapies.MethodsIn this retrospective cohort, we assessed a 27-gene RT-qPCR immuno-oncology (IO) gene expression assay of the tumor immune microenvironment and determined its association with the efficacy of ICI therapy in 67 advanced-stage NSCLC patients. The 27-gene IO test score (IO score), programmed cell death ligand 1 immunohistochemistry tumor proportion score (PD-L1 TPS), and tumor mutational burden (TMB) were analyzed as continuous variables for response and as binary variables for one-year progression free survival. The threshold for the IO score was prospectively set based upon a previously described training cohort. Prognostic implications of the IO score were evaluated in a separate cohort of 104 advanced-stage NSCLC patients from The Cancer Genome Atlas (TCGA) who received non-ICI therapy.ResultsThe IO score was significantly different between responders or non-responders (p = 0.007) and associated with progression-free survival (p = 0.001). Bivariate analysis established that the IO score was independent of PD-L1 TPS and TMB in identifying patients benefiting from ICI therapy. In a separate cohort of late-stage NSCLC patients from TCGA, the IO score was not prognostic of outcome from non-ICI-treated patients.ConclusionsThis study is the first application of this 27-gene IO RT-qPCR assay in a clinical cohort with outcome data. IO scores were significantly associated with response to ICI therapy and prolonged progression-free survival. Together, these data suggest the IO score should be further studied to define its role in informing clinical decision-making for ICI treatment in NSCLC.

Rapid Arc-SBRT: Non-Invasive Immune Adjuvant for Advanced Stage Non-Small Cell Lung Carcinoma.

In conjunction with radio-chemotherapy, pulmonary resection is recommended for early-stage nonsmall- cell lung carcinoma but not for advanced-stage NSCLC patients having high-grade metastatic lesions. In these cases, the rapid Arc-Stereotactic body radiotherapy (Ra-SBRT) technique offers a therapeutic advantage by delivering focal irradiation to metastatic lung lesions and reduces the bystander toxicity to normal tissues. We have previously demonstrated that Ra-SBRT ablates metastatic lesions and induces tumor immune rejection of metastatic tumors by promoting in situ programming of M2 TAM towards M1-TAM and infiltration of Siglec-8+ Eosinophils. Most interestingly, Ra SBRT has very low abscopal impact and spares normal tissues, which are the significant limitations with conventional radiotherapy. In view of this and the immune adjuvant potential of Ra SBRT, it promotes normalization of aberrant vasculature and inhibits the metastatic potential of NSCLC lesions. In view of this, we here propose that Ra-SBRT indeed represents an immunogenic approach for the effective management of advanced-stage NSCLC.

Validation of in-house knowledge-based planning model for predicting change in target coverage during VMAT radiotherapy to in-operable advanced-stage NSCLC patients

Objectives. anatomical changes are inevitable during the course of radiotherapy treatments and, if significant, can severely alter expected dose distributions and affect treatment outcome. Adaptive radiotherapy (ART) is employed to maintain the planned distribution and minimise detriment to predicted treatment outcome. Typically, patients who may benefit from adaptive planning are identified via a re-planning process, i.e., re-simulation, re-contouring, re-planning and treatment plan quality assurance (QA). This time-intensive process significantly increases workload, can introduce delays and increases unnecessary stress to those patients who will not actually gain benefit. We consider it crucial to develop efficient models to predict changes to target coverage and trigger ART, without the need for re-planning. Methods. knowledge-based planning (KBP) models were developed using data for 20 patients’ (400 fractions) to predict changes in PTV V95 coverage Initially, this change in coverage was calculated on the synthetic computerised tomography (sCT) images produced using the Velocity adaptive radiotherapy software. Models were developed using patient (cell death bio-marker) and treatment fraction (PTV characteristic) specific parameters to predict and verified using five patients (100 fractions) data. Results. three models were developed using combinations of patient and fraction specific terms. The prediction accuracy of the model developed using biomarker (PD-L1 expression) and the difference in ‘planning’ and ‘fraction’ PTV centre of the mass (characterised by mean square difference, MSD) had the higher prediction accuracy, predicting the within ± 1.0% for 77% of the total fractions; with 59% for the model developed using, PTV size, PD-L1 and MSD and 48% PTV size and MSD respectively. Conclusion. the KBP models can predict very effectively and efficiently for advanced-stage NSCLC patients treated using volumetric modulated arc therapy and to identify patients who may benefit from adaption for a specific fraction.

Abstract SY05-03: Radiomics of immune therapy in NSCLC

Abstract Checkpoint blockade immunotherapy provides improved long-term survival in a subset of advanced stage NSCLC patients. Currently, predictive biomarkers of immunotherapy response are an unmet clinical need. CT and PET/CT images are routinely obtained during workup of NSCLC patients, and we hypothesize that quantitative analysis of these images (radiomics) can fill this need. In a study of CT radiomics, 332 NSCLC patients treated with checkpoint blockade were curated into independent training (N = 180), validation (N = 90) and test cohorts (N = 62) for radiomic analyses. The most informative clinical and radiomic features were subjected to Classification and Regression Tree (CART) analysis which identified novel cut-points to stratified patients into four different survival risk-groups. The identified very-high risk group was associated with extremely poor OS in both test ([HR] = 5.35, 95% CI= 2.14 - 13.36) and validation (HR = 13.81 95% CI: 2.58 - 73.93) cohorts when compared to the low-risk group (HRs = 1.00). Similar findings were observed for 3-year PFS (0% HR = 1.00 vs. 29.8% HR = 3.95). The most predictive radiomic feature was the GLCM inverse difference, which was representative of a set of nine features that were related to tumor heterogeneity. For further validation, this feature was then tested against four additional independent NSCLC data sets (total N = 446) who were treated with surgery, radio- or chemo-therapies, showing that it was significantly associated with OS suggesting a pan-marker. The biological underpinnings of the GLCM inverse difference were investigated using gene expression data and was associated with the hypoxia-related carbonic anhydrase, CA-IX, and confirmed by immunohistochemistry. In a separate study of PET/CT radiomics, we curated data sets from 837 NSCLC patients from four international institutions. Two residual-convolutional-network (ResCNN) models were generated to predict EGFR mutation and PDL1 positive status in training (N=429) and validation (N=187) cohorts and were subsequently tested on external cohorts to predict EGFR mutation status (N=65) and PDL1 expression status (N=85). The EGFR and PDL1 scores demonstrated high accuracy to predict EGFR mutation status with AUCs of 0.86, 0.83, and 0.81, and in prediction of PDL1 positive status with AUCs of 0.89, 0.84, and 0.82 for training, validation, and external test cohorts, respectively. The generated EGFR and PDL1 deep learning scores were subsequently used to predict PFS in patients treated with EGFR TKI (N=67) and chekpoint blockade (N=149). For patients with high EGFR score, EGFR-TKI treatment was significantly associated with longer PFS in patients with a low PDL1 score (p=0.013); for patients with a high PDL1 score, checkpoint blockade was significantly associated with longer PFS (p&amp;lt;0.001) in particular those patients with a low EGFR score. Therefore, the combination of EGFR and PDL1 scores, generated from the same PET-CT scan can be used as a non-invasive Decision Support Tool for NSCLC. Citation Format: Wei Mu, Ilke Tunali, Matthew B. Schabath, Robert J. Gillies. Radiomics of immune therapy in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr SY05-03.

Identifying advanced stage NSCLC patients who benefit from afatinib therapy using 18F-afatinib PET/CT imaging

ObjectivesNon-small cell lung cancer (NSCLC) tumors harboring common (exon19del, L858R) and uncommon (e.g. G719X, L861Q) activating epidermal growth factor receptor (EGFR) mutations are best treated with EGFR tyrosine kinase inhibitors (TKI) such as the first-generation EGFR TKI erlotinib, second-generation afatinib or third-generation osimertinib. However, identifying these patients through biopsy is not always possible. Therefore, our aim was to evaluate whether 18F-afatinib PET/CT could identify patients with common and uncommon EGFR mutations. Furthermore, we evaluated the relation between tumor 18F-afatinib uptake and response to afatinib therapy. Materials and methods18F-afatinib PET/CT was performed in 12 patients: 6 EGFR wild type (WT), 3 EGFR common and 3 EGFR uncommon mutations. Tumor uptake of 18F-afatinib was quantified using TBR_WB60−90 (tumor-to-whole blood activity ratio 60−90 min post-injection) for each tumor. Response was quantified per lesion using percentage of change (PC): [(response measurement (RM)–baseline measurement (BM))/BM]×100. Statistical analyses were performed using t-tests, correlation plots and sensitivity/specificity analysis. ResultsTwenty-one tumors were identified. Injected dose was 348 ± 31 MBq. Group differences were significant between WT versus EGFR (common and uncommon) activating mutations (p = 0.03). There was no significant difference between EGFR common versus uncommon mutations (p = 0.94). A TBR_WB60−90 cut-off value of 6 showed the best relationship with response with a sensitivity of 70 %, a specificity of 100 % and a positive predictive value of 100 %. Conclusion18F-afatinib uptake was higher in tumors with EGFR mutations (common and uncommon) compared to WT. Furthermore, a TBR_WB60−90 cut-off of 6 was found to best predict response to therapy. 18F-afatinib PET/CT could provide a means to identify EGFR mutation positive patients who benefit from afatinib therapy.

OC-0199: Cardiac sparing in advanced stage NSCLC patients: at what cost?

OC-0199: Cardiac sparing in advanced stage NSCLC patients: at what cost?

495P - Serum EGFR1 and EGFR2 expression in non-small cell lung cancer patients

Background: Serum mRNA is promising prognostic tool for non-invasive malignant disease prognosis of disease, and to study serum mRNA may have important role in the prognosis of disease. Methods: Materials and Methods: Histopathologically confirmed 100 NSCLC cases and 100 healthy control subjects were included in study to evaluate the possible prognostic role of serum EGFR1 and 2 mRNA expressions in lung adenocarcinoma patients. Results: Quantification analysis showed 13.54 and 13.92 mean fold increase in serum EGFR1 &2 expression among NSCLC patients than healthy controls. Patients with larger tumor size had higher EGFR1 & 2 expression which was found to be significantly associated with tumor size (p = 0.02, 0.01). NSCLC patients who had distant metastases (M1) in organs like brain, adrenal, bone etc showed increased EGFR1 & 2 mRNA expression compared to patients without distant metastases (M0) showed significant difference in expression(p < 0.0001).With increasing TNM stage of NSCLC, increased serum EGFR1 & 2 mRNA expression was observed (p < 0.0001). It was found out that a significantly poor overall survival was associated with > 13 fold increase in EGFR1 mRNA expression (p < 0.0001). It was found that a significantly poor progression free survival was associated with patients with > 13 fold increase in EGFR1 mRNA expression (p = 0.001). It was found out that a significantly poor overall median survival was associated with patients with > 13 fold increase in EGFR2 expression (p = 0.02). It was found out that a significantly poor progression free survival was associated with patients with > 13 fold increase in EGFR2 expression (p = 0.001). ROC curves for EGFR1 & 2 were plotted between early and advanced stage NSCLC patients (AUC=0.95, p < 0.0001, AUC=0.81 p < 0.0001), presence/absence of distant metastases (AUC=0.81, p < 0.0001, AUC=0.73, p < 0.0001) and pleural effusion (AUC=0.81, p0.009, AUC= 0.67, p = 0.03) respectively. Conclusions: Increased circulating mRNAs expression in serum of EGFR1 and 2 genes was found to be associated with worse overall and progression free survival of NSCLC patients. ROC curve analysis showed circulating EGFR1 and EGFR2 mRNA expression in serum could be useful as important predictive indicators for prognosis of NSCLC patients. Legal entity responsible for the study: Mirza Masroor Ali Beg. Funding: Has not received any funding. Disclosure: The author has declared no conflicts of interest.

P2.13-17 Non-Small Lung Cancer in the Very Young: More EGFR/ALK Mutation Rate Than the Elder.

Lung cancer was the leading cause of cancer in worldwise1. Although it remains a disease of older patients, there is a subset of patients who are diagnosed at younger age, such as blow 40 year old. Several studies had shown that the younger group had more females, more non-smokers, more advanced stages of disease, and better survive rate. However, most of these studies didn’t include tumor EGFR/ALK mutation data, especially for the younger group. We retrospectively studied the clinical difference between the younger and the older in patients, including pathologic type, treatment characteristics, and EGFR/ALK mutation status. We retrospective reviewed data of NSCLC patients diagnosed during Jun. 2007 to Dec. 2014, and whose age was less than 90 year-old. at Taipei Veterans General Hospital(TPEVGH). There were 5,051 cases of NSCLC, including 168 patients who were <40 years old (younger group) and 4,883 patients aged 40 years or older (older group). It was found younger group had significantly higher EGFR mutation rate than older group (22.6% VS 16.2%, p=0.026), and ALK mutation (4.2% VS 0.5%, p<0.001). Although the younger group had more stage IV patients (60.1% VS 49.6%, p=0.002), they had better (one year:73.7% VS 66.2%, five year:44.4% VS 33.7%) overall survival rate(OS) ( median survival time: 55 VS 26 months ,p=0.002). Regarding histologic subtype, younger group had less squamous cell carcinoma (4.2% VS 16.1% , p<0.001), while adenocarcinoma subtype was similar between two groups (76.8% VS 76.5%, p=0.924). Overall survival rate in younger NSCLC patients were better than the older ones. This survival benefit most likely due to higher EGFR mutation and ALK mutation rate and corresponding TKI treatment. Although more advanced-stage NSCLC patients were seen in the younger group at the same time.

P3.15-27 Initial Response to First Line Treatment is the Best Predictor of the Patient Survival in Advanced NSCLC

Although most of the NSCLC patients are treated according to the standart guidelines, the patients who present in routine clinical practice usually have inferior performance status, in comparison to the patients registered in the clinical trials. Also in comparison, the frequency and thoroughness of the tests and procedures the clinical trial patients subjected are more intense as well. The oncologist practising in community needs simpler ways and means to assess patients' disease course to make timely and reliable judgement on their management. We searched among 5130 patients treated in our clinic since 2006 to find 678 lung cancer patients of all stages and pathology. Of these, 171 advanced stage NSCLC patients that were treated primarily under our supervision are selected for the calculations. The other histologies and the patients seen once or twice for a second opinion are excluded. The common patients characteristics including age, gender, stage, date of diagnosis, the date of progression, the site and the number of metastasis etc. are all recorded. The median age of the patients were 62, 23% were female, the median overall survival was 18 months. The majority did not receive any targeted immunotherapy because either it did not exist back then or they had access problems in more recent times. We did then univariate/moltivariate analysis of survival according to the age, gender, site of metastasis, platin vs non-platin based treatment and response to first line of chemotherapy. Of these, only the response to first line of therapy appeared as a statitically significant variable, 23 vs 14 months with p=0.0001. In over 90% of the patients, the radiological findings were in line with clinical picture. Although more complex and costly measures exist to predict the overall survival of the NSCLC patients, in our experience the clinical responsiveness to first line of chemotherapy most precisely predicted the overall survival. This simple measure may help the healthcare profesionals to understand the disease course of the patients and manage their needs in more proper fashion.

P1.01-040 Clinical Utility of Plasma-Based NGS for Advanced-Stage NSCLC Patients with Insufficient or Unavailable Tumor Tissue

P1.01-040 Clinical Utility of Plasma-Based NGS for Advanced-Stage NSCLC Patients with Insufficient or Unavailable Tumor Tissue