Immunotherapy In Non-small Cell Lung Cancer Patients Research Articles

Spatial profiling of non-small cell lung cancer provides insights into tumorigenesis and immunotherapy response

Lung cancer is the second most common cancer worldwide and a leading cause of cancer-related deaths. Despite advances in targeted therapy and immunotherapy, the prognosis remains unfavorable, especially in metastatic cases. This study aims to identify molecular changes in non-small cell lung cancer (NSCLC) patients based on their response to treatment. Using tumor and matched immune cell rich peritumoral tissues, we perform a retrospective, comprehensive spatial transcriptomic analysis of a proven malignant NSCLC sample treated with immune checkpoint inhibitor (ICI). In addition to T cells, other immune cell types, such as B cells and macrophages, were also activated in responders to ICI treatment. In particular, B cells and B cell-mediated immunity pathways are consistently found to be activated. Analysis of the histologic subgroup (lung squamous cell carcinoma, LUSC; lung adenocarcinoma, LUAD) of NSCLC also confirms activation of B cell mediated immunity. Analysis of B cell subtypes shows that B cell subtypes were more activated in immune cell-rich tissues near tumor tissue. Furthermore, increased expression of B cell immunity-related genes is associated with better prognosis. These findings provide insight into predicting ICI treatment responses and identifying appropriate candidates for immunotherapy in NSCLC patients.

CircPTP4A2 knockdown suppresses NSCLC progression via regulating proliferation and activating anti-tumor immunity

BackgroundWith a considerable variety of cancer subtypes, Non-small cell lung cancer (NSCLC) poses a substantial threat to public health, affecting a large number of individuals and resulting in a high mortality rate. Circular RNA (circRNA) has been applied in various diseases, including cancers. This study aims to investigate the clinial significance and functional role of circPTP4A2 in NSCLC.MethodsThe serum and tissue samples were collected for detecting circPTP4A2 expression in NSCLC using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Actinomycin D was used to treat NSCLC cells to detect circPTP4A2 stability. The CCK-8 and Transwell assays were utilized to assess the effects of circPTP4A2 in NSCLC cells. The ELISA assay and cytotoxicity analysis were used to detect the roles of circPTP4A2 in immune escape.ResultsThe serum and tissue circPTP4A2 expression was upregulated in NSCLC. The high circPTP4A2 had a relatively high value in differentiating NSCLC patients from healthy individuals. The proliferation, invasion, and immune escape were repressed by circPTP4A2 knockdown.ConclusionsHigh circPTP4A2 has the potential to be a diagnostic biomarker in NSCLC. Silencing of circPTP4A2 receded the progression of NSCLC and enhanced antitumor immunity, which might provide potential targets and new ideas for improving the diagnosis and effect of immunotherapy in NSCLC patients.

Immune checkpoint expression as prognostic biomarker candidates in non-small cell lung carcinoma patients.

Cancer immunotherapy has had an important role in oncologic therapeutics for patients with non-small cell lung cancer (NSCLC) using checkpoint inhibitors. We will explore the possible prognosis biomarker candidates such as: soluble OX40 (sOX40), OX40L (sOX40L), Glucocorticoid-induced tumor necrosis factor receptor family-related receptor (GITR), and their ligand (GITRL), 4-1BB or tumor necrosis factor receptor superfamily 9 (TNFRS9) and inducible T cell co-stimulator (ICOS) in peripheral blood of NSCLC patients. Fifty-eight patients were diagnosed with advanced NSCLC between January 2019 and March 2020. High sOX40 and low s4-1BB levels in smokers compared non-smoker NSCLC patients. Lower sOX40L levels were found in the male than female (p < 0.05). High sOX40 and sGITRL in stage III compared to the stage IV (p < 0.05). With follow-up at 21.4 months, 44.1% and 91.1% were alive in the sGITRhigh and sGITRlow groups, respectively (p = 0.02), and 73.3% and 27.7% were alive in the sGITRLhigh and sGITRLlow groups, respectively (p = 0.02). At 22 months, 38.7% and 92.3% were alive in the sOX40Lhigh and sOX40Llow groups, respectively (p = 0.01). sGITR, sGITRL, and sOX40L levels were potential prognostic biomarkers and could have an important role as new targets of immunotherapy in NSCLC patients. sGITR, sGITRL, sOX40L, and sOX40 levels were associated with smoking, sex, stage, and age in NSCLC.

Efficacy of immunotherapy in RET fusion-positive NSCLC: A meta-analysis

BackgroundThe Rearranged during Transfection (RET) gene represents a rare driver mutation in non-small cell lung cancer (NSCLC) occurring in only 1 %–2 % of cases, with implications in targeted carcinogenesis. Despite the significant efficacy demonstrated by immunotherapy in advanced NSCLC with wild-type driver genes, its validation in RET fusion-positive patients is yet to be established. ObjectivesThis meta-analysis aims to systematically evaluate the effectiveness of immunotherapy in patients with RET fusion-positive NSCLC. Data sourcesand Methods: PubMed and Web of Science databases were systematically searched for relevant studies. Outcomes including objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were extracted for further analysis. ResultsTen real-world evidence (RWE) studies involving 7145 patients were enrolled in this meta-analysis. In terms of tumor response, the pooled ORR and DCR were 24.0 % and 61.0 %, respectively. Regarding survival analysis, the pooled median PFS and median OS were 4.17 months [95 % confidence interval (CI): 3.40–5.02) and 17.22 months (95 % CI: 11.58–23.91)], respectively. Subgroup analyses showed that immunotherapies plus chemotherapy were superior to single-immunotherapy in terms of ORR, DCR, and median PFS, which were 43 % (95 % CI: 31%–55 %) vs. 17 % (95 % CI: 11%–25 %), 74 % (95 % CI: 60%–84 %) vs. 45 % (95 % CI: 31%–59 %) and 6.69 months (95 % CI: 4.91–8.93) vs. 2.96 months (95 % CI: 2.25–3.78), respectively. ConclusionsTo date, RET fusions appear to be associated with poor response to immunotherapy in NSCLC patients, and immunotherapy combined with chemotherapy seems to offer greater clinical benefits than mono-immunotherapy.

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients

BackgroundThe non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunotherapy response, based on the integration of deep learning and habitat radiomics in patients with advanced non-small cell lung cancer (NSCLC).MethodsIndependent patient cohorts from three medical centers were enrolled for training (n = 164) and test (n = 82). Habitat imaging radiomics features were derived from sub-regions clustered from individual’s tumor by K-means method. The deep learning features were extracted based on 3D ResNet algorithm. Pearson correlation coefficient, T test and least absolute shrinkage and selection operator regression were used to select features. Support vector machine was applied to implement deep learning and habitat radiomics, respectively. Then, a combination model was developed integrating both sources of data.ResultsThe combination model obtained a strong well-performance, achieving area under receiver operating characteristics curve of 0.865 (95% CI 0.772–0.931). The model significantly discerned high and low-risk patients, and exhibited a significant benefit in the clinical use.ConclusionThe integration of deep-leaning and habitat radiomics contributed to predicting response to immunotherapy in patients with NSCLC. The developed integration model may be used as potential tool for individual immunotherapy management.

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.

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.

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.

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.