Immunotherapy In Non-small Cell Lung Cancer Patients Research Articles

Lysosomal degradation of PD-L1 is associated with immune-related adverse events during anti-PD-L1 immunotherapy in NSCLC patients

Background: Immune checkpoint inhibitors (ICIs) can induce immune-related adverse events (irAEs). Liquid biomarkers to predict irAE occurrence are urgently needed. We previously developed an ELISA system to specifically detect soluble PD-L1 (sPD-L1) with PD-1-binding capacity (bsPD-L1). Here, we investigated the relationship between sPD-L1 and bsPD-L1 in gastric cancer (GC) and non-small cell lung cancer (NSCLC) treated with PD-1/PD-L1 blockade and their association with irAEs.Methods: We examined sPD-L1, bsPD-L1, matrix metalloproteinases (MMPs), and proinflammatory cytokine levels by ELISA in plasma samples from 117 GC patients prior to surgery and 72 NSCLC patients prior to and at 2 months after ICI treatment (anti-PD-1, n = 48; anti-PD-L1, n = 24). In mice treated with anti-PD-1/PD-L1 antibodies (Abs), sPD-L1 levels and localization of Abs were examined by ELISA and immunohistochemistry, respectively.Results:sPD-L1 was detected with higher frequency in GC patients than in NSCLC patients, whereas bsPD-L1 was detected with similar frequencies in GC and NSCLC patients. sPD-L1 levels were correlated with IL-1α, IL-1β, TNF-α, and IL-6 levels, while bsPD-L1 levels were correlated with MMP13, MMP3, and IFN-γ levels. In NSCLC patients, anti-PD-L1, but not anti-PD-1, treatment increased sPD-L1, which was associated with irAE development, but not with clinical outcomes. In mice, trafficking of anti-PD-L1 Abs to lysosomes in F4/80+ macrophages resulted in sPD-L1 production, which was suppressed by treatment with lysosomal degradation inhibitor chloroquine and macrophage depletion.Conclusion: Anti-PD-L1-mediated lysosomal degradation induces sPD-L1 production, which can serve as an indicator to predict irAE development during anti-PD-L1 treatment.

Abstract 2531: rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms

Abstract Efficient predictive biomarkers are needed for immune checkpoint inhibitor (ICI)-based immunotherapy in non-small-cell lung cancer (NSCLC). So far, testing the predictive value of single nucleotide polymorphisms (SNPs) in programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) has shown contrasting results. Here, we aimed to validate the predictive value of PD-L1 SNPs in advanced NSCLC patients treated with ICIs as well as to define the molecular mechanisms underlying the role of identified SNP candidate. rs822336 SNP efficiently predicted response to anti-PD-1/PD-L1-based immunotherapy in advanced NSCLC patients as compared to rs2282055 and rs4143815 SNPs. rs822336 SNP mapped on promoter/enhancer region of PD-L1, differentially affecting the induction of PD-L1 expression in human NSCLC cell lines. The induction of PD-L1 expression by rs822336 SNP was predicted by allele-specificity binding of two identified transcription factors: C/EBPβ and NFIC. As a result, silencing of C/EBPβ and NFIC differentially modulated the induction of PD-L1 expression in human NSCLC cell lines carrying different rs822336 genotypes. In addition, binding microarray validated the allele- specificity binding of C/EBPβ and NFIC to PD-L1 promoter/enhancer region based on rs822336 genotype in human NSCLC cell lines. Lastly, the induction of PD-L1 expression by rs822336 genotype differentially affected the susceptibility to anti-PD-1 monoclonal antibody nivolumab of human NSCLC cell lines co-cultured with HLA class I antigen matched PBMC. These results have clinical relevance since identified rs822336 SNP and the induction of PD-L1 expression as novel biomarkers for predicting ICI-based immunotherapy in NSCLC patients. Citation Format: Giovanna Polcaro, Luigi Liguori, Valentina Manzo, Annalisa Chianese, Giuliana Donadio, Alessandro Caputo, Giosuè Scognamiglio, Federica Dell'Annunziata, Maddalena Langella, Graziamaria Corbi, Alessandro Ottaiano, Marco Cascella, Francesco Perri, Margot De Marco, Jessica Dal Col, Valentina Pagliara, Pio Zeppa, Amelia Filippelli, Gianluigi Franci, Fabrizio Dal Piaz, Valeria Conti, Stefano Pepe, Francesco Sabbatino. rs822336 as a predictive biomarker for anti-PD-1/PD-L1 immunotherapy in advanced NSCLC: Unraveling molecular mechanisms [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 2531.

Effectiveness of Immunotherapy in Non-Small Cell Lung Cancer Patients with a Diagnosis of COPD: Is This a Hidden Prognosticator for Survival and a Risk Factor for Immune-Related Adverse Events?

The interplay between the immune system and chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC) is complex and multifaceted. In COPD, chronic inflammation and oxidative stress can lead to immune dysfunction that can exacerbate lung damage, further worsening the respiratory symptoms. In NSCLC, immune cells can recognise and attack the cancer cells, which, however, can evade or suppress the immune response by various mechanisms, such as expressing immune checkpoint proteins or secreting immunosuppressive cytokines, thus creating an immunosuppressive tumour microenvironment that promotes cancer progression and metastasis. The interaction between COPD and NSCLC further complicates the immune response. In patients with both diseases, COPD can impair the immune response against cancer cells by reducing or suppressing the activity of immune cells, or altering their cytokine profile. Moreover, anti-cancer treatments can also affect the immune system and worsen COPD symptoms by causing lung inflammation and fibrosis. Immunotherapy itself can also cause immune-related adverse events that could worsen the respiratory symptoms in patients with COPD-compromised lungs. In the present review, we tried to understand the interplay between the two pathologies and how the efficacy of immunotherapy in NSCLC patients with COPD is affected in these patients.

CD57-positive CD8 + T cells define the response to anti-programmed cell death protein-1 immunotherapy in patients with advanced non-small cell lung cancer

Immune checkpoint inhibitors have transformed the treatment landscape of non-small cell lung cancer (NSCLC). However, accurately identifying patients who will benefit from immunotherapy remains a challenge. This study aimed to discover potential biomarkers for predicting immunotherapy response in NSCLC patients. Single-cell mass cytometry (CyTOF) was utilized to analyze immune cell subsets in peripheral blood mononuclear cells (PBMCs) obtained from NSCLC patients before and 12 weeks after single-agent immunotherapy. The CyTOF findings were subsequently validated using flow cytometry and multiplex immunohistochemistry/immunofluorescence in PBMCs and tumor tissues, respectively. RNA sequencing (RNA-seq) was performed to elucidate the underlying mechanisms. In the CyTOF cohort (n = 20), a high frequency of CD57+CD8+ T cells in PBMCs was associated with durable clinical benefit from immunotherapy in NSCLC patients (p = 0.034). This association was further confirmed in an independent cohort using flow cytometry (n = 27; p < 0.001), with a determined cutoff value of 12.85%. The cutoff value was subsequently validated in another independent cohort (AUC = 0.733). We also confirmed the CyTOF findings in pre-treatment formalin-fixed and paraffin-embedded tissues (n = 90; p < 0.001). RNA-seq analysis revealed 475 differentially expressed genes (DEGs) between CD57+CD8+ T cells and CD57-CD8+ T cells, with functional analysis identifying DEGs significantly enriched in immune-related signaling pathways. This study highlights CD57+CD8+ T cells as a promising biomarker for predicting immunotherapy success in NSCLC patients.

The prognostic biological markers of immunotherapy for non-small cell lung cancer: current landscape and future perspective.

The emergence of immunotherapy, particularly programmed cell death 1 (PD-1) and programmed cell death ligand-1 (PD-L1) produced profound transformations for treating non-small cell lung cancer (NSCLC). Nevertheless, not all NSCLC patients can benefit from immunotherapy in clinical practice. In addition to limited response rates, exorbitant treatment costs, and the substantial threats involved with immune-related adverse events, the intricate interplay between long-term survival outcomes and early disease progression, including early immune hyperprogression, remains unclear. Consequently, there is an urgent imperative to identify robust predictive and prognostic biological markers, which not only possess the potential to accurately forecast the therapeutic efficacy of immunotherapy in NSCLC but also facilitate the identification of patient subgroups amenable to personalized treatment approaches. Furthermore, this advancement in patient stratification based on certain biological markers can also provide invaluable support for the management of immunotherapy in NSCLC patients. Hence, in this review, we comprehensively examine the current landscape of individual biological markers, including PD-L1 expression, tumor mutational burden, hematological biological markers, and gene mutations, while also exploring the potential of combined biological markers encompassing radiological and radiomic markers, as well as prediction models that have the potential to better predict responders to immunotherapy in NSCLC with an emphasis on some directions that warrant further investigation which can also deepen the understanding of clinicians and provide a reference for clinical practice.

Targeting METTL3 reprograms the tumor microenvironment to improve cancer immunotherapy

The tumor microenvironment (TME) is a heterogeneous ecosystem containing cancer cells, immune cells, stromal cells, cytokines, and chemokines which together govern tumor progression and response to immunotherapies. Methyltransferase-like 3 (METTL3), a core catalytic subunit for RNA N6-methyladenosine (m6A) modification, plays a crucial role in regulating various physiological and pathological processes. Whether and how METTL3 regulates the TME and anti-tumor immunity in non-small-cell lung cancer (NSCLC) remain poorly understood. Here, we report that METTL3 elevates expression of pro-tumorigenic chemokines including CXCL1, CXCL5, and CCL20, and destabilizes PD-L1 mRNA in an m6A-dependent manner, thereby shaping a non-inflamed TME. Thus, inhibiting METTL3 reprograms a more inflamed TME that renders anti-PD-1 therapy more effective in several murine lung tumor models. Clinically, NSCLC patients who exhibit low-METTL3 expression have a better prognosis when receiving anti-PD-1 therapy. Collectively, our study highlights targeting METTL3 as a promising strategy to improve immunotherapy in NSCLC patients.

Breaking the 'Undruggable' Barrier: Anti-PD-1/PD-L1 Immunotherapy for Non-Small Cell Lung Cancer Patients with KRAS Mutations-A Comprehensive Review and Description of Single Site Experience.

Kirsten rat sarcoma viral oncogene homologue (KRAS) gene mutations are among the most commonly found oncogenic alterations in non-small cell lung cancer (NSCLC) patients. Unfortunately, KRAS mutations have been considered "undruggable" for many years, making treatment options very limited. Immunotherapy targeting programmed death-ligand 1 (PD-L1), programmed death 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) has emerged as a promising therapeutic option for NSCLC patients. However, some studies have suggested a lower response rate to immunotherapy in KRAS-mutated NSCLC patients with the coexistence of mutations in the STK11 (Serine/Threonine Kinase 11) gene. However, recent clinical trials have shown promising results with the combination of immunotherapy and chemotherapy or immunotherapy and KRAS inhibitors (sotorasib, adagrasib) in such patients. In other studies, the high efficacy of immunotherapy has been demonstrated in NSCLC patients with mutations in the KRAS gene that do not coexist with other mutations or coexist with the TP53 gene mutations. In this paper, we review the available literature on the efficacy of immunotherapy in KRAS-mutated NSCLC patients. In addition, we presented single-site experience on the efficacy of immunotherapy in NSCLC patients with KRAS mutations. The effectiveness of chemoimmunotherapy or immunotherapy as well as KRAS inhibitors extends the overall survival of advanced NSCLC patients with the G12C mutation in the KRAS gene to 2-3 years. This type of management has become the new standard in the treatment of NSCLC patients. Further studies are needed to clarify the potential benefits of immunotherapy in KRAS-mutated NSCLC patients and to identify potential biomarkers that may help predict response to therapy.

Cerebrospinal fluid immunological cytokines to predict intracranial tumor response to immunotherapy in non-small cell lung cancer patients with brain metastases: GASTO 1060.

2040 Background: Immunotherapy has been the standard first-line therapy in patients with advanced non-small cell lung cancer (NSCLC), and shown a certain efficacy for patients with brain metastases. however, the appropriate predictive biomarkers for intracranial tumor response to immunotherapy are unclear. We conducted this prospective study to explore the immunological cytokines in cerebrospinal fluid (CSF) to predict intracranial tumor response to immunotherapy in NSCLC patients with brain metastases. Methods: We prospectively enrolled treatment-naive, EGFR/ALK wild-type NSCLC patients with brain metastases in this study. Patients received chemotherapy plus camrelizumab (a humanized anti-PD-1 monoclonal antibody) as first-line treatment, and paired plasma and cerebrospinal fluid (CSF) samples were collected at baseline and first treatment evaluation (8-week). All samples were detected for 92 Immuno-Oncology cytokines using the Olink panels, and were explored for predictive biomarkers to immunotherapy. The Mann-Whitney U test was performed to compare the immunological cytokine expression between intracranial response and non-response groups. And logistic LASSO regression model was used to variate selection and develop a CSF immuno-cytokine model to predict intracranial tumor response. Results: Between April 2020 and May 2022, a total of 28 patients were enrolled this study.At baseline, most immunological cytokines were significantly lower in paired CSF than in plasma, whereas a subset including CD83, PTN, TNFRSF21, TWEAK, ICOSLG, DCN, IL-18 and MCP-1 were increasing expressed in CSF samples. For patients with objective intracranial tumor response compared to patients with non-response, the baseline CSF levels of LAMP3 were significantly higher, whereas the CXCL10, IL-12, CXCL11, IL-18, TIE2, HGF and PDCD1 levels were significantly lower. And patients with lower HGF, IL-18 or PDCD1 levels had significantly longer intracranial progression-free survival to immunotherapy. The above CSF immunological cytokines were significantly decreased at first treatment evaluation in patients with intracranial tumor response. Our logistic CSF immuno-cytokine model selected TIE2, IL-18, LAMP3, PDCD1 and IL-12 that were significantly associated with intracranial tumor response, and yielded a mean AUC of 0.91, compared to PD-L1 expression (mean AUC of 0.72). Conclusions: Immunological cytokines in CSF could predict intracranial tumor response to immunotherapy in NSCLC patients with brain metastases, and findings require validation in a larger prospective cohort.

Effects of concomitant chronic obstructive pulmonary disease on immune microenvironment in non-small cell lung cancer patients.

e20522 Background: Chronic obstructive pulmonary disease (COPD) as a progressive deterioration of lung function, has caused significant morbidity and mortality, especially in developing countries. Persistent lung inflammation and potential lung stroma remodeling in COPD may be important causes of lung cancer. Previous studies have shown that non-small cell lung cancer (NSCLC) patients with COPD have a worse prognosis than those without, but the reasons have not been determined. Due to the increasing application of ICIs in the NSCLC, the characteristics of the immune microenvironment in the NSCLC patients concomitant COPD are worth exploring. Methods: Immune microenvironment and the next generation sequencing (NGS) data of twenty NSCLC patients from Sun Yat-sen Memorial Hospital were analyzed. Formalin-fixed paraffin-embedded biopsy tissue before first-line treatment to prepare tumor tissue slides. Samples were stained using an Opal automation mIF Detection Kit (Akoya) for immune cells. The immune cell infiltration were reported as percentages and density from each individual cell subpopulation in the tumor or stromal area. The landscape of gene mutantions was obtained by NGS detection of 733-gene panel, sequencing depth was 35000x. Results: There were 8 (40%) patients concomitant COPD, and the median age was 65.5-year-old. Analysis the immune cell infiltration in all patients, including T cells, B cells, macrophages and NK cells through 13 markers, showed no difference between COPD and non-COPD groups. However, comparing the differences between tumor and stromal immune microenvironment, it was found that there was a significant difference in the percentages of M1 macrophages between tumor and stromal in COPD group (P = 0.031), but no difference in non-COPD group (P = 0.47). Further analysis of the difference in cell density between tumor and stroma showed that the stromal M1 macrophages in the COPD group was significantly higher than that in the non-COPD group (P = 0.017), as well as PD-1+CD8+ T cells (P = 0.05). Additionally, a preliminary analysis of the gene mutation characteristics had done. In COPD patients with somatic mutations, the most frequently mutated gene was EGFR (60%), followed by TP53 (50%) and GLI2 (50%), which were similar as non-COPD patients. The most common variant of COPD patients are the missense mutation of EGFR L858R, but it was EGFR 19del in non-COPD. Conclusions: The results showed that the COPD was correlated with the infiltration status of M1 macrophages and PD-1+CD8+ T cell, and poor immune cell infiltration in tumor of COPD patients may be the potential influencing factors for the worse prognosis. The characteristics of immune microenvironment suggest that promoting the entry of immune cells from stroma into tumor may be a potential mechanism for the benefit of immunotherapy in NSCLC patients with COPD.

Clinical value of peripheral blood circulating tumor DNA in predicting the efficacy of immunotherapy for non-small cell lung cancer.

The high expression of programmed cell death 1-ligand 1 (PD-L1) is a valid biological indicator of the therapeutic benefit of pembrolizumab in non-small cell lung cancer (NSCLC) patients. However, the response rate of NSCLC patients with positive PD-L1 expression to anti-PD-1/PD-L1 therapy is still low. From January 2019 to January 2021, a retrospective study was conducted at the Fujian Medical University Xiamen Humanity Hospital. In total, 143 patients with advanced NSCLC were treated with immune checkpoint inhibitors, and the efficacy of the treatment [complete remission (CR), partial remission (PR), stable disease (SD), or progression disease (PD)] was evaluated. Patients with a CR and PR were defined as an objective response (OR) group (n=67), and the other patients were defined as a control group (n=76). The differences in the circulating tumor DNA (ctDNA) and clinical features between the 2 groups were compared, and the receiver operating characteristic (ROC) curve was used to analyze the value of ctDNA in predicting the failure to achieve an OR after immunotherapy in patients with NSCLC, and a multivariate regression analysis was conducted to analyze the factors affecting the OR after immunotherapy in NSCLC patients. R4.0.3 statistical software (Ross Ihaka Robert Gentleman, New Zealand) was used to establish and verify the prediction model of OR after immunotherapy in NSCLC patients. CtDNA was valuable in predicting the non-OR of patients with NSCLC after immunotherapy, and the area under the curve was 0.750 [95% CI: 0.673-0.828, P<0.001]. CtDNA <3.72 ng/µL can be used to predict which NSCLC patients will achieve objective remission after immunotherapy (P<0.001). Based on the regression model, a prediction model was established. The data set was randomly divided into the training set and validation set. The sample size of the training set was 72 and that of the validation set was 71. The area under the ROC curve of the training set was 0.850 (95% CI: 0.760-0.940), and that of the validation set was 0.732 (95% CI: 0.616-0.847). CtDNA was valuable in predicting the efficacy of immunotherapy in NSCLC patients.

Peripheral changes in T cells predict efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer

The application of programmed cell death protein 1 (PD-1) antibodies has brought great benefits to non-small cell lung cancer (NSCLC) patients. Nevertheless, not all patients respond to anti-PD-1 immunotherapy. This study aimed to find response markers to predict efficacy of anti-PD-1 immunotherapy in NSCLC patients. 80 patients with NSCLC who would accept anti-PD-1 immunotherapy were recruited, and peripheral blood was obtained before and after treatment. Flow cytometry was used to detect proportions of circulating cell subsets and expression of co-stimulatory molecules, co-inhibitory molecules and cytokines in T cells from pre- and post-treatment patients. Results showed that proportions of CD4+ and CD8+ T cells, NK, γδT and mucosal-associated invariant T (MAIT) cells were higher and regulatory T cells (Tregs) were lower in responders (n = 50) after treatment but no obvious difference was found in non-responders (n = 30). After treatment, responders showed an increase in the frequency of co-stimulatory and co-inhibitory molecules, as well as the production of cytokines in T cells. This study indicates that monitoring the alterations of immune markers in circulating cells from NSCLC patients may be helpful to discriminate responders and non-responders, which provides a potential novel way to assess efficacy of anti-PD-1 immunotherapy.

Association between response to anti-PD-1 treatment and blood soluble PD-L1 and IL-8 changes in patients with NSCLC

In this study, we explored the dynamic changes in blood sPD-L1 and its clinical value during anti-PD-1 immunotherapy in non-small cell lung cancer (NSCLC) patients. First, we established a sandwich ELISA for functional sPD-L1 that can bind to PD-1 and has biological functions. By monitoring functional sPD-L1 in 39 NSCLC patients treated with anti-PD-1 antibodies, we found a positive correlation between baseline sPD-L1 and tissue PD-L1 (P = 0.0376, r = 0.3581), with patients with lymph node metastasis having higher sPD-L1 levels (P = 0.0037) than those without lymph node metastasis. Although baseline functional sPD-L1 and PFS did not correlate significantly in this study, changes in sPD-L1 in patients with different clinical responses showed different trends. Blood sPD-L1 increased in 93% of patients after two cycles of anti-PD-1 treatment (P = 0.0054); sPD-L1 in nonresponsive patients continued to increase (P = 0.0181), but sPD-L1 started to decline in responsive patients. Blood IL-8 levels were associated with tumor load, and when combined with IL-8, the evaluation accuracy of sPD-L1 improved to 86.4%. This study preliminarily shows that the combination of sPD-L1 and IL-8 is a convenient and effective method for monitoring and evaluating the effectiveness of anti-PD-1 immunotherapy in NSCLC patients.

Modeling strategies to analyse longitudinal biomarker data: An illustration on predicting immunotherapy non-response in non-small cell lung cancer

Serum tumor markers acquired through a blood draw are known to reflect tumor activity. Their non-invasive nature allows for more frequent testing compared to traditional imaging methods used for response evaluations. Our study aims to compare nine prediction methods to accurately, and with a low false positive rate, predict progressive disease despite treatment (i.e. non-response) using longitudinal tumor biomarker data. Bi-weekly measurements of CYFRA, CA-125, CEA, NSE, and SCC were available from a cohort of 412 advanced stage non-small cell lung cancer (NSCLC) patients treated up to two years with immune checkpoint inhibitors. Serum tumor marker measurements from the first six weeks after treatment initiation were used to predict treatment response at 6 months. Nine models with varying complexity were evaluated in this study, showing how longitudinal biomarker data can be used to predict non-response to immunotherapy in NSCLC patients.

EP16.01-022 A Signature of B Cells-Related Gene Pairs Predicts Oncologic Outcomes and Response to Immunotherapy in NSCLC Patients

Tumor-infiltrating B cells accompanying several widely used B cell-related biomarkers, such as CD19 and CD20, have inconsistent clinical prognostic values in non-small-cell lung cancer (NSCLC) patients. Considering only one B cell-related biomarker could not distinguish the anti-tumor and pro-tumor B cell subsets in tumor, we aimed to construct a more accurate B-cells related gene pairs (BRGPs) prognostic model and evaluate its potential predictive ability to immunotherapy in NSCLC patients.

Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer.

BackgroundImmune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure.MethodsWe evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation.ResultsWe found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset.ConclusionOur study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients.

Immunotherapy in NSCLC Patients with Brain Metastases.

Approximately 40% of unselected non-small cell lung cancer (NSCLC) patients develop brain metastases (BMs) during their disease, with considerable morbidity and mortality. The management of BMs in patients with NSCLC is a clinical challenge and requires a multidisciplinary approach to gain effective intracranial disease control. Over the last decade, immune checkpoint inhibitors (ICIs) have emerged as a game-changer in the treatment landscape of advanced NSCLC, with significant improvements in survival outcomes, although patients with BMs are mostly underrepresented in randomized clinical trials. Moreover, the safety and activity of ICIs and radiotherapy combinations compared with single-agent or sequential modalities is still under evaluation to establish the optimal management of these patients. The aim of this review is to summarize the state-of-the-art of clinical evidence of ICIs intracranial activity and the main challenges of incorporating these agents in the treatment armamentarium of NSCLC patients with BMs.

Radiotherapy-immunotherapy related pneumonitis prediction from pre-treatment CT using a deep graph-based integrative model.

2580 Background: Early prediction of symptomatic pneumonitis (grade ≥ 2) could potentially assist the comprehensive management for non-small cell lung cancer (NSCLC) patients who received radiotherapy combined with immunotherapy. A more accurate integrative model for symptomatic pneumonia prediction using CT images is needed. Methods: This retrospective study contains 243 NSCLC patients (62 symptomatic pneumonitis) who underwent radiotherapy combined with immunotherapy between January 2015 and June 2021. Five-fold cross-validation was performed for training and testing. There were 195 cases in the training set (50 symptomatic pneumonitis) and 48 cases in the validation set (12 symptomatic pneumonitis) in each fold. The deep graph integrative model (DG) was composed of two pre-trained 3D UNet encoders to extract deep features from tumor and lung volumes of pre-treatment CT images, respectively, and a graph attention layer (GAT) for integration and classification. The encoders were fine-tuned using manually segmented tumor and lung CT volumetric patches from the training set. Evaluation measures include area under ROC curve (auc), sensitivity (sen), and specificity (spe). Results: Our new DG achieved auc, sen, and spe of 0.823, 0.767, and 0.810, which outperformed conventional CT radiomics model (auc 0.743, sen 0.620, spe 0.752), 3D UNet based deep radiomics model (auc 0.761, sen 0.746, spe 0.737), and our model without GAT (auc 0.796, sen 0.762, spe 0.782). The improvement was statistically significant (p &lt; 0.001). Conclusions: Our DG model improved symptomatic pneumonia prediction using CT images, which can be used as a tool to effectively improve the safety and personalized treatment of combined radiotherapy with immunotherapy for NSCLC patients.

Signature based on B cells-related gene pairs could predict prognosis and immunotherapeutic response in NSCLC.

e21051 Background: Tumor-infiltrating B cells accompanying several widely used B cell-related biomarkers, such as CD19 and CD20, have inconsistent clinical prognostic values in non-small-cell lung cancer (NSCLC) patients. Considering only one B cell-related biomarker could not distinguish the anti-tumor and pro-tumor B cell subsets in tumor, we aimed to construct a more accurate B-cells related gene pairs (BRGPs) prognostic model and evaluate its potential predictive ability to immunotherapy in NSCLC patients. Methods: Using public single-cell RNA sequencing data, the B cells-related genes (BRGs) in NSCLC samples were identified. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were utilized to construct the BRGPs model which was not affected by the technical bias of different platforms. With no dependence upon specific gene expression levels, a novel signature based on BRGPs was established in this study. In addition, the prognostic value and immunotherapeutic response for this signature with regard to the TME components and potential molecular mechanism were explored. Results: Based on the TCGA database, we built a novel prognostic signature of 23 BRGPs comprising 28 unique BRGs. This risk model showed significant power in distinguishing good or poor prognosis and could serve as an independent prognostic factor for NSCLC patients in the TCGA cohort. The prognostic accuracy of the model was further verified in the GSE31210 dataset from the GEO database. Likewise, the prognostic value of the risk score for the BRGPs model was demonstrated in the GEO cohorts by the univariate and multivariate cox regression analysis. In addition, the risk model was significantly associated with sex, TNM stage, immune score, tumor purity and various tumor-infiltrating immune cells. GSEA analysis indicated that low-risk group enriched with several immune-related pathways, such as activation of immune response, antigen receptor mediated signaling pathway, B cell activation and B cell mediated immunity, whereas several proliferation-related pathways, such as nuclear chromosome segregation, sister chromatid segregation and mitotic sister chromatid segregation were most enriched in high-risk group. Besides, the tumor mutational burden (TMB) score rather than CD274(PD-L1 mRNA) expression was positively correlated with the risk score (P＜0.001; P = 0.94, respectively). NSCLC patients with high-risk exhibited significantly higher TMB score compared with low-risk patients (P &lt; 0.001). Correspondingly, we demonstrated that immune checkpoint blockade therapy may be more efficacious in high-risk group NSCLC patients according to TIDE method (P＜0.01). Conclusions: This novel BRGPs model can assess the prognosis of patients with NSCLC, and may be helpful to guide immune checkpoint inhibitors treatment in our clinical practice.

Possibilities of applying a combination of targeted molecular therapies and immunotherapy in NSCLC patients

Non-small cell lung cancer (NSCLC) advanced or metastatic with driver mutations ( EGFR , ALK , ROS1 ) is treated with ty­rosine kinase inhibitors (TKIs), respectively anti-EGFR, anti-ALK or anti-ROS1. Immunotherapy with checkpoint inhibitors (anti-PD-1 or anti-PD-L1) alone or in combination with TKIs was considered as a treatment option in several studies, but results are not promising, furthermore the toxicity profile of such a combination is potentially unacceptable. The initial findings suggest that combination therapy has failed to demonstrate clinically meaningful efficacy and there are no strong signals of its future development.

Exosomal PD-L1 predicts response with immunotherapy in NSCLC patients.

Immune Check-Point Inhibitors (ICIs) have shown remarkable promise in treating tumors, including non-small cell lung cancer (NSCLC). Nevertheless, the treatment response rate is low. Studies have found that the high expression of exosomal PD-L1 is one of the reasons for the low treatment response. Therefore, this study focused on the relationship between the exosomal PD-L1 and the clinical response to immunotherapy in NSCLC patients to evaluate whether it could be used as a biomarker to predict the efficacy of ICIs. In this study, clinical information and blood samples of 149 NSCLC patients receiving ICIs were collected. The expression level of exosomal PD-L1 was detected by enzyme-linked immunosorbent assay method, and the relationship between exosomal PD-L1 and the efficacy of ICIs was explored. Overall, our study found that the expression level of exosomal PD-L1 was lower at pre-treatment, or the max fold increasing change higher at 3-6 weeks had a higher disease control rate and longer progression-free survival. It revealed that the exosomal PD-L1 was associated with the treatment response of patients using ICIs and provided a new tool for the evaluation of clinical efficacy of lung cancer immunotherapy.