Immunotherapy In Non-small Cell Lung Cancer Research Articles

Abstract 7380: Predicting immunotherapy outcomes from H&E images in lung cancer

Abstract Checkpoint blockade immunotherapy is a cornerstone of lung cancer treatment, but there is a need to improve the identification of patients who will respond favorably. Here, we explored a deep learning approach to predict immunotherapy outcomes from hematoxylin and eosin (H&E) images in non-small cell lung cancer (NSCLC). We included 150 unique cases with metastatic NSCLC (113 adenocarcinoma, 29 squamous cell, 8 other) treated with anti-PD-1/PD-L1 immunotherapy (56 nivolumab, 49 atezolizumab, 44 pembrolizumab, 1 durvalumab) as mono or combination (14 with chemotherapy, 1 with ipilimumab) therapy in a single institution. Each case consisted of a representative H&E whole slide image (53 biopsies, 50 needle core biopsies, 47 resections) obtained prior to immunotherapy, and the outcome reported as the 1-year overall survival (OS). PD-L1 status (tumor proportion score ≥ 1%) was known for 70 cases. We preprocessed the H&E images using two deep learning models previously developed using The Cancer Genome Atlas dataset. First, we used a classification model to identify tumor regions and randomly sampled a fixed number of tumor patches for each case. Then, we used a self-supervised pathology foundation model to obtain a compressed visual representation of each patch, known as an embedding. Next, using our dataset, we trained a deep multiple instance learning (DeepMIL) model with a gated attention mechanism to predict the binary 1-year OS status (0=deceased, 1=alive) for each case. As a baseline, we also trained a linear-probe (logistic regression) model using the averaged embeddings. Given the small dataset size, 5-fold cross-validation was used to train and evaluate both the DeepMIL and linear-probe models, with cases randomly split across folds. For evaluation, we used survival analysis to compare the 0/1 case groups. Overall, across all 150 cases, univariable Cox regression showed that 1-year OS was more strongly associated with the DeepMIL status (46/104, HR=0.55, p=0.03) than the linear-probe status (55/95, HR=0.81, p=0.44). Results were consistent on the subset of 70 cases with known PD-L1 status, whereby OS was most strongly associated with the DeepMIL status (19/51, HR=0.40, p=0.04) compared to the linear-probe status (31/39, HR=0.46, p=0.09) and PD-L1 status (30/40, HR=0.65, p=0.32). In multivariable Cox regression adjusting for age group and smoking status, OS remained more strongly associated with the DeepMIL status (HR=0.45, p=0.08) than PD-L1 status (HR=0.72, p=0.47). In conclusion, the DeepMIL status predicted from H&E images showed a stronger association with outcomes compared to PD-L1 status, a standard biomarker for immunotherapy in NSCLC. These exploratory results demonstrate the potential of deep learning using pathology foundation models to improve immunotherapy outcomes prediction, even with small datasets. Such approaches may even enable the discovery of novel biomarkers from H&E images to advance precision medicine. Citation Format: Jessica Loo, Yang Wang, Pok Fai Wong, Ellery Wulczyn, Jeremy Lai, Peter Cimermancic, David F. Steiner, Shamira S. Weaver. Predicting immunotherapy outcomes from H&E images in lung cancer [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 7380.

Abstract 7323: Tissue resident memory T cell abundances impact non-small-cell lung cancer immune microenvironment and patient prognosis

Abstract Tissue resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, whether TRM exerts any immunosurveillance role in the tumor immune microenvironment (TIME) and progression of non-small-cell lung cancer (NSCLC), which accounts for 85% of all lung cancers, remains unclear. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we could infer the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in TIME and significantly impacts the prognosis of NSCLC patients. In addition, TRM signatures are strongly associated with immune checkpoint genes and the prognosis of NSCLC patients, suggesting that TRM signatures are promising prognostic markers for immunotherapy in NSCLC. We then built a machine learning model to predict patient survival based on the TRM signatures and immune related genes. The accuracy of the model was validated by Kaplan-Meyer survival analysis, receiver operating characteristic curves, principal component analysis, and t-distributed random neighbor embedding. We developed a 4-gene risk score that effectively stratified patients into low-risk and high-risk categories. The patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell activation, macrophage regulation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. Altogether, this study provides valuable insights into the complex interactions between NSCLC TRM and TIME and their impact on patient prognosis, highlighting the importance of TRM in shaping the NSCLC microenvironment. The development of a simplified 4-gene risk score provides a practical prognostic marker for risk stratification. Keywords: Tissue resident memory T cell, non-small-cell lung cancer, prognosis, tumor immune microenvironment, machine learning Citation Format: Aidan Shen, Aliesha Garrett, Junhua Mai, Yangzhi Zhu, Chongming Jiang. Tissue resident memory T cell abundances impact non-small-cell lung cancer immune microenvironment and patient prognosis [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 7323.

Abstract 5101: Comparative genomic analysis reveals distinctive immune profiles in MET exon 14 mutated and MET amplified lung cancer

Abstract Background: In non-small cell lung cancer (NSCLC), the MET tyrosine kinase receptor can be mutated or amplified resulting in dysregulation of receptor function leading to tumor proliferation. MET exon 14 (METEx14) mutated and MET amplified NSCLC tumors have shown varied response to immunotherapy. Therefore, we sought to compare the genomic and immune landscape of MET-altered NSCLC. Methods: The genomic profiles of 3,821 NSCLC tumors sequenced using the Strata Select assay on the Strata Oncology Platform were analyzed. Tumors were sorted based on METex14 mutations, MET amplification (METamp) defined as copy number gain (CNG) ≥6 and MET wild-type (METwt). The RNA expression of 19 immune regulatory genes, tumor mutation burden (TMB), Strata Immunotherapy Response Signature (IRS) score and the frequency of gene co-alterations were compared across groups. Statistical comparisons of medians were done with Kruskal-Wallis testing and categorical comparisons with Chi square using R Studio version 4.3.2. Results: 122 (3.2%) METex14, 70 (1.8%) METamp, and 3,629 (95.0%) METwt were identified. Patients with METex14 were older and more frequently female. MET gene expression was found to be higher in METamp (median 14.4) compared to METex14 (median 12.3) (P<0.01). TMB was lowest in METex14 (median 2.7) group compared to METamp (median 7.1) and METwt (median 5.1) (P<0.001). High PD-L1 expression occurred in 71.4% of METamp, 68.0% of METex14 and 41.3% of METwt (P<0.001). Overall, METamp tumors had a greater proportion of high IRS scores (52.9%) compared to METex14 (35.2%) and METwt (45.4%) (P<0.01). mRNA expression of immune checkpoints CTLA4, PD-1, LAG3, IDO1, TIGIT and HAVCR2 were all higher in METex14 compared to METamp and METwt (P<0.001 for all). METex14 tumors also exhibited higher gene expression of CD4, CD8A and FOXP3 compared to METamp and METwt (p<0.001). METex14 had higher prevalence of MDM2 amplification (34% vs 3% vs 4%) and lower prevalence of alterations in EGFR (0.8% vs 22% vs 21%), KRAS (0.8% vs 10% vs 26%), CDKN2A (17% vs 29% v 28%) and TP53 (34% vs 87% vs 64%) compared with METamp and METwt tumors, respectively (p<0.05). Conclusion: METex14 and METamp tumors harbor distinct immune-gene expression profiles and co-occurring gene alterations that distinguish themselves from each other and METwt tumors. Further analysis must be conducted to determine how these variations impact immunotherapy in MET-altered NSCLC. Citation Format: Saahil Javeri, Rachel Minne, Shrey Ramesh, Andrew Baschnagel, Randy Kimple, Laura Lamb, Scott Tomlins, Bryan Johnson, Nickolay Khazanov. Comparative genomic analysis reveals distinctive immune profiles in MET exon 14 mutated and MET amplified lung cancer [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 5101.

Identification of cellular senescence-associated genes as new biomarkers for predicting the prognosis and immunotherapy response of non-small cell lung cancer and construction of a prognostic model

BackgroundGlobally, lung carcinoma remains the leading cause of death, with its associated morbidity and mortality rates remaining elevated. Despite the slow advancement of treatment, the outlook remains bleak. Cellular senescence represents a halt in the cell cycle, encompassing a range of physiological and pathological activities, along with diverse phenotypic alterations, including variations in secretory phenotype, macromolecular harm, and metabolic disturbances. Research has revealed its vital function in the formation and growth of tumors. This study aimed to examine cellular senescence-related mRNAs linked to the outlook of non-small cell lung cancer (NSCLC) and to formulate a predictive risk framework for NSCLC. MethodsWe acquired the NSCLC expression data from The Cancer Genome Atlas (TCGA) to examine mRNAs linked to cellular senescence. Both single-variable and multiple-variable cox proportion risk assessments were utilized to determine the traits of cellular senescence-related mRNAs linked to NSCLC prognosis. Subsequently, the prognostic model for cellular senescence-related mRNAs was integrated with clinical-pathological characteristics to create a prognostic nomogram. Furthermore, the study delved into the risk-oriented predictive model, examining immune infiltration and responses to immunotherapy among both high and low-risk categories. ResultsUtilizing both univariate and multivariate Cox proportion risk assessments, a risk model comprising 12 mRNAs associated with cellular aging was ultimately developed: IGFBP1, TLR3, WT1, ID1, PTTG1, ERRFI1, HEPACAM, MAP2K3, RAD21, NANOG, PRKCD, SOX5. Univariate analysis and multivariate analysis illustrated that the risk score served as a standalone indicator for prognosis, and the hazard ratio (HR) of the risk score were 1.182 (1.139–1.226) (p < 0.001) and 1.162 (1.119 − 1.206) (p < 0.001), respectively. Individual prognoses were forecasted using nomogram, c-index, and principal component analysis (PCA). Furthermore, the risk-oriented model revealed notable statistical variances in immune infiltration and response to immunotherapy among the high and low risk categories. ConclusionsThis study shows that mRNAs related to cell senescence associated with prognosis are reliable predictors of NSCLC immunotherapy reaction and prognosis.

MAIT cells are associated with responsiveness to neoadjuvant immunotherapy in COPD-associated NSCLC.

Patients with non-small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) experience worse clinical outcomes but respond better to immunotherapy than patients with NSCLC without COPD. Mucosal-associated invariant T (MAIT) cells, a versatile population of innate immune T lymphocytes, have a crucial function in the response to infection and tumors. This study investigated the distribution of MAIT cells in COPD-associated NSCLC and their involvement in the immune response. Flow cytometry, immunohistochemistry, and immunofluorescence were performed on tissue samples of patients with NSCLC, with or without COPD, treated with or without anti-programmed death 1 (PD1) immunotherapy. MAIT cells were stimulated with 5-OP-RU using a mouse subcutaneous tumor model. Tumors contained significantly more MAIT cells than paraneoplastic tissues, and CD8+ MAIT cells accounted for more than 90% of these cells. Patients with NSCLC and COPD had higher CD8+ MAIT cell counts than those with NSCLC without COPD. Additionally, patients with NSCLC and COPD displayed reduced expression of the activation marker, CD69, and functional markers, granzyme B (GZMB) and interferon γ (IFNγ), and higher expression of the immune exhaustion marker, PD1. Among patients who received immunotherapy, the proportion with a complete or partial response was higher in those with COPD than in those without COPD. In patients with NSCLC and COPD, the major pathologic response (MPR) group had higher MAIT levels than those in the no major pathologic response (NPR) group. In the mouse subcutaneous tumor model stimulation of MAIT cells using 5-OP-RU enhanced the antitumor effects of anti-PD1. In patients with NSCLC and COPD, response to immunotherapy is associated with accumulation of CD8+ MAIT cells showing immune exhaustion. These findings may contribute to innovative approaches for immunotherapy targeting CD8+ MAIT cells.

Dual immunotherapy in advanced or metastatic non-small cell lung cancer: A network meta-analysis

Recently, there has been extensive research on dual immunotherapy for advanced or metastatic non-small cell lung cancer (NSCLC), yet a comprehensive evaluation is lacking. This study aimed to rank the available treatment options and assess the efficacy and safety of dual immunotherapy regimens through the implementation of a Bayesian network meta-analysis (NMA). A thorough search was conducted to recognize eligible randomized controlled trials (RCTs) on March 20, 2023. Overall survival (OS), progression-free survival (PFS), treatment-related adverse events (TRAEs) and grade ≥3 TRAEs were evaluated to identify the efficacy and safety of dual immunotherapy regimens. The surface under the cumulative ranking curve (SUCRA) and P score were employed to rank the treatments. Eleven clinical trials involving six different regimens were included in this study. The combination of anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) antibodies with anti-T-cell immunoglobulin and ITIM domain (TIGIT) antibodies emerged as the most promising regimen for improving OS and PFS, followed by anti-PD-1/PD-L1+anti-cytotoxic T lymphocyte antigen 4 (CTLA-4)+chemotherapy treatment and anti-PD-1/PD-L1+anti-CTLA-4 treatment. The forest plots demonstrated that these three regimens were all superior to chemotherapy. The above results were observed in both unselected treatment line and first-line settings. The least likely to be associated with TRAEs and grade ≥3 TRAEs were respectively anti-CTLA-4 treatment and anti-PD-1/PD-L1+anti-TIGIT treatment, with anti-PD-1/PD-L1+anti-CTLA-4+chemotherapy treatment to be the worst. This NMA validated the promising efficacy and safety of dual immunotherapy in advanced or metastatic NSCLC. Among them, anti-PD-1/PD-L1+anti-TIGIT regimen emerges as a highly potential therapeutic approach. Ongoing research efforts should focus on improving treatment regimens, identifying biomarkers, and managing TRAEs to optimize the patient benefits of dual immunotherapy.

Identification of macrophage-related genes correlated with prognosis and immunotherapy efficacy in non-small cell lung cancer

BackgroundMalignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. MethodsWe employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. ResultsIn our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. ConclusionThese findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

Perioperative immunotherapy: the main clinical treatment for resectable non-small cell lung cancer.

Phase 3 clinical trials of perioperative immunotherapy for resectable non-small cell lung cancer (NSCLC): In recent years, immunotherapy for NSCLC is not only limited to advanced disease, but also has shown gratifying efficacy for early resectable NSCLC. With the publication of the results of several phase 3 clinical trials, perioperative immunotherapy will become one of the main treatment modalities for resectable NSCLC.

Dynamic surveillance of lymphocyte subsets in patients with non-small cell lung cancer during chemotherapy or combination immunotherapy for early prediction of efficacy.

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide. Lymphocytes are the primary executors of the immune system and play essential roles in tumorigenesis and development. We investigated the dynamic changes in peripheral blood lymphocyte subsets to predict the efficacy of chemotherapy or combination immunotherapy in NSCLC. This retrospective study collected data from 81 patients with NSCLC who received treatments at the First Affiliated Hospital of Zhengzhou University from May 2021 to May 2023. Patients were divided into response and non-response groups, chemotherapy and combination immunotherapy groups, and first-line and multiline groups. We analyzed the absolute counts of each lymphocyte subset in the peripheral blood at baseline and after each treatment cycle. Within-group and between-group differences were analyzed using paired Wilcoxon signed-rank and Mann-Whitney U tests, respectively. The ability of lymphocyte subsets to predict treatment efficacy was analyzed using receiver operating characteristic curve and logistic regression. The absolute counts of lymphocyte subsets in the response group significantly increased after the first cycle of chemotherapy or combination immunotherapy, whereas those in the non-response group showed persistent decreases. Ratios of lymphocyte subsets after the first treatment cycle to those at baseline were able to predict treatment efficacy early. Combination immunotherapy could increase lymphocyte counts compared to chemotherapy alone. In addition, patients with NSCLC receiving chemotherapy or combination immunotherapy for the first time mainly presented with elevated lymphocyte levels, whereas multiline patients showed continuous reductions. Dynamic surveillance of lymphocyte subsets could reflect a more actual immune status and predict efficacy early. Combination immunotherapy protected lymphocyte levels from rapid decrease and patients undergoing multiline treatments were more prone to lymphopenia than those receiving first-line treatment. This study provides a reference for the early prediction of the efficacy of clinical tumor treatment for timely combination of immunotherapy or the improvement of immune status.

KEAP1 promotes anti-tumor immunity by inhibiting PD-L1 expression in NSCLC

Immunotherapy has become a prominent first-line cancer treatment strategy. In non-small cell lung cancer (NSCLC), the expression of PD-L1 induces an immuno-suppressive effect to protect cancer cells from immune elimination, which designates PD-L1 as an important target for immunotherapy. However, little is known about the regulation mechanism and the function of PD-L1 in lung cancer. In this study, we have discovered that KEAP1 serves as an E3 ligase to promote PD-L1 ubiquitination and degradation. We found that overexpression of KEAP1 suppressed tumor growth and promoted cytotoxic T-cell activation in vivo. These results indicate the important role of KEAP1 in anti-cancer immunity. Moreover, the combination of elevated KEAP1 expression with anti-PD-L1 immunotherapy resulted in a synergistic effect on both tumor growth and cytotoxic T-cell activation. Additionally, we found that the expressions of KEAP1 and PD-L1 were associated with NSCLC prognosis. In summary, our findings shed light on the mechanism of PD-L1 degradation and how NSCLC immune escape through KEAP1-PD-L1 signaling. Our results also suggest that KEAP1 agonist might be a potential clinical drug to boost anti-tumor immunity and improve immunotherapies in NSCLC.

Subsequent surgical treatment or maintenance immunotherapy in stage III lung cancer patients achieving a favorable response following neoadjuvant immunotherapy: A matched retrospective cohort study from the surgical perspective.

Current treatment strategies for advanced non-small cell lung cancer (NSCLC) are highly individualized and subject to ongoing debates. In the era of immunotherapy, surgery assumes a critical role. The aim of this study was to investigate if subsequent surgical intervention, following a favorable response to immunotherapy and chemotherapy, could yield a more favorable prognosis for patients with advanced stage III NSCLC compared to the continuation of immunotherapy and chemotherapy. We included patients whose tumors exhibited a favorable response (including partial response [PR] and complete response [CR]) to immunotherapy and chemotherapy. These patients were categorized into two groups based on their subsequent treatment plans: surgical and nonsurgical (continuation of maintenance immunotherapy and chemotherapy). The efficacy and long-term prognosis of these groups were compared after matching them in a 1:1 ratio using propensity scores. In total, 186 patients (93 in each group) were included in this study after matching via propensity scores. The 1- and 3-year overall survival (OS) and progression-free survival (PFS) rates were 96.0%, 88.5%, and 93.1%, 80.7% in the surgical group, and 93.2%, 83.1%, and 57.7%, 50.4% in the nonsurgical group, respectively. Patients in the surgical group exhibited significantly superior PFS and OS compared to those in the nonsurgical group (p = 0.025 and p = 0.00086). Univariate and multivariate analyses confirmed ΔBMI, Δtumor size reduction, tumor response, earlier clinical stage (IIIb vs. IIIa), and surgery as independent protective factor for patient prognosis. We further selected 101 patients with CR (39 in the surgical group and 62 in the nonsurgical group) and found that patients in the surgical group were significantly better in both PFS and OS. Our subgroup analysis in postoperative patients demonstrated that different surgical strategies did not significantly affect the long-term prognosis of patients (PFS and OS) but could impact their perioperative experience. Patients with advanced stage III NSCLC, whose tumors achieved PR and CR after 2-4 cycles of immunotherapy combined with chemotherapy, experience a more promising prognosis with subsequent surgical intervention compared with the continued immunotherapy. Despite encountering formidable obstacles, such as protracted surgical procedures and associated trauma, we must rise to the challenge and unleash the power of surgery after immunotherapy in advanced NSCLC.

MicroRNA-126 selected with broad-spectrum analysis of microRNAs - a new predictive factor for the effectiveness of immunotherapy or chemoimmunotherapy in advanced NSCLC patients?

Expression of PD-L1 on cancer cells is the only validated predictive factor for immunotherapy in NSCLC (Non-Small Cell Lung Cancer) patients. However, on this basis, it is difficult to predict the occurrence of resistance to immune checkpoint inhibitors (ICIs). MicroRNAs are widely studied as biomarkers of cancers. Our study was designed to determine whether microRNAs can be sensitive predictive factors in the qualification of NSCLC patients to first-line immunotherapy or chemoimmunotherapy. The two-stage research on validation group (n=20) and study group (n=35) of patients with advanced NSCLC was conducted. Analysis of microRNAs expression by qPCR in plasma collected prior to the start of immunotherapy (pembrolizumab) or chemoimmunotherapy (combination ofpembrolizumab with chemotherapy) was made. Broad-spectrum analysis of microRNAs expression was used in the studied group. Three microRNAs selected in that group as important for the effectiveness of ICIs were then examined in the validation group. In the studied group, significantly higher expression of miRNA-126-3p, miR-144-3p and miR-146-5p was observed in patients with long PFS compared to those with short PFS. In the validation group, low miRNA-126 expression indicated lower median progression-free survival and overall survival (2.3 vs. 5.0 months and 5.2 vs 11.2, respectively). These patients had a significantly higher risk of progression (HR= 2.92, 95% CI: 1.01 to 8.40, p=0.04) and death (HR=3.64, 95% CI: 1.22 to 10.84, p=0.02). Our study showed that the expression of miR-126 in blood plasma may be a predictive factor for the effectiveness of first-line immunotherapy or chemoimmunotherapy in advanced NSCLC patients.

Two-stage stratified designs with survival outcomes and adjustment for misclassification in predictive biomarkers.

Biomarker stratified clinical trial designs are versatile tools to assess biomarker clinical utility and address its relationship with clinical endpoints. Due to imperfect assays and/or classification rules, biomarker status is prone to errors. To account for biomarker misclassification, we consider a two-stage stratified design for survival outcomes with an adjustment for misclassification in predictive biomarkers. Compared to continuous and/or binary outcomes, the test statistics for survival outcomes with an adjustment for biomarker misclassification is much more complicated and needs to take special care. We propose to use the information from the observed biomarker status strata to construct adjusted log-rank statistics for true biomarker status strata. These adjusted log-rank statistics are then used to develop sequential tests for the global (composite) hypothesis and component-wise hypothesis. We discuss the power analysis with the control of the type-I error rate by using the correlations between the adjusted log-rank statistics within and between the design stages. Our method is illustrated with examples of the recent successful development of immunotherapy in nonsmall-cell lung cancer.

Predicting programmed death-ligand 1 (PD-L1) expression with fluorine-18 fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in resectable non-small cell lung cancer.

Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). PD-L1 and glucose transporter 1 expression are closely associated, and studies demonstrate correlation of PD-L1 with glucose metabolism. The aim of this study was to investigate the association of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters with PD-L1 expression in primary lung tumour and lymph node metastases in resected NSCLC. We conducted a retrospective analysis of 210 patients with node-positive resectable stage IIB-IIIB NSCLC. PD-L1 tumour proportion score (TPS) was determined using the DAKO 22C3 immunohistochemical assay. Semi-automated techniques were used to analyse pre-operative [18F]FDG-PET/CT images to determine primary and nodal metabolic parameter scores (including max, mean, peak and peak adjusted for lean body mass standardised uptake values (SUV), metabolic tumour volume (MTV), total lesional glycolysis (TLG) and SUV heterogeneity index (HISUV)). Patients were predominantly male (57%), median age 70 years with non-squamous NSCLC (68%). A majority had negative primary tumour PD-L1 (TPS < 1%; 53%). Mean SUVmax, SUVmean, SUVpeak and SULpeak values were significantly higher (p < 0.05) in those with TPS ≥ 1% in primary tumour (n = 210) or lymph nodes (n = 91). However, ROC analysis demonstrated only moderate separability at the 1% PD-L1 TPS threshold (AUCs 0.58-0.73). There was no association of MTV, TLG and HISUV with PD-L1 TPS. This study demonstrated the association of SUV-based [18F]FDG-PET/CT metabolic parameters with PD-L1 expression in primary tumour or lymph node metastasis in resectable NSCLC, but with poor sensitivity and specificity for predicting PD-L1 positivity ≥ 1%. Whilst SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography metabolic parameters may not predict programmed death-ligand 1 positivity ≥ 1% in the primary tumour and lymph nodes of resectable non-small cell lung cancer independently, there is a clear association which warrants further investigation in prospective studies. Non-applicable KEY POINTS: • Programmed death-ligand 1 immunohistochemistry has a predictive role in non-small cell lung cancer immunotherapy; however, it is both heterogenous and dynamic. • SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters were significantly higher in primary tumour or lymph node metastases with positive programmed death-ligand 1 expression. • These SUV-based parameters could potentially play an additive role along with other multi-modal biomarkers in selecting patients within a predictive nomogram.

Evaluating for Correlations between Specific Metabolites in Patients Receiving First-Line or Second-Line Immunotherapy for Metastatic or Recurrent NSCLC: An Exploratory Study Based on Two Cohorts.

Immune checkpoint inhibitors (ICI) have displayed impressive clinical efficacy in the context of non-small cell lung cancer (NSCLC). However, most patients do not achieve long-term survival. Minimally invasive collected samples are attracting significant interest as new fields of biomarker study, and metabolomics is one of these growing fields. We concentrated on the augmented value of the metabolomic profile in differentiating long-term survival from short-term survival in patients with NSCLC subjected to ICIs. We prospectively recruited 97 patients with stage IV NSCLC who were treated with anti-PD-1 inhibitor, including patients treated with monoimmunotherapy as second-line treatment (Cohort 1), and patients treated with combination immunotherapy as first-line treatment (Cohort 2). Each cohort was divided into long-term and short-term survival groups. All blood samples were collected before beginning immunotherapy. Serum metabolomic profiling was performed by UHPLC-Q-TOF MS analysis. Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis were performed. In Cohort 1, the mPFS and mOS of long-survival patients are 27.05 and NR months, respectively, and those of short-survival patients are 2.79 and 10.59 months. In Cohort 2, the mPFS and mOS of long-survival patients are 27.35 and NR months, respectively, and those of short-survival patients are 3.77 and 12.17 months. A total of 41 unique metabolites in Cohort 1 and 47 in Cohort 2 were screened. In Cohorts 1 and 2, there are 6 differential metabolites each that are significantly associated with both progression-free survival and overall survival. The AUC values for all groups ranged from 0.73 to 0.95. In cohort 1, the top 3 enriched KEGG pathways, as determined through significant different metabolic pathway analysis, were primary bile acid biosynthesis, African trypanosomiasis, and choline metabolism in cancer. In Cohort 2, the top 3 enriched KEGG pathways were the citrate cycle (TCA cycle), PPAR signaling pathway, and primary bile acid biosynthesis. The primary bile acid synthesis pathway had significant differences in the long-term and short-term survival groups in both Cohorts 1 and 2. Our study suggests that peripheral blood metabolomic analysis is critical for identifying metabolic biomarkers and pathways responsible for the patients with NSCLC treated with ICIs.

Exploring the relationship between intestinal microbiota and immune checkpoint inhibitors in the treatment of non-small cell lung cancer: insights from the "lung and large intestine stand in exterior-interior relationship" theory.

This study is aim to discern the Traditional Chinese Medicine (TCM) syndrome classifications relevant to immunotherapy sensitive in non-small cell lung cancer (NSCLC) patients, and to delineate intestinal microbiota biomarkers and impact that wield influence over the efficacy of NSCLC immunotherapy, grounded in the TCM theory of "lung and large intestine stand in exterior-interior relationship." The study cohort consisted of patients with advanced NSCLC who received treatment at the Oncology Department of Chengdu Fifth People's Hospital. These patients were categorized into distinct TCM syndrome types and subsequently administered immune checkpoint inhibitors (ICIs), specifically PD-1 inhibitors. Stool specimens were collected from patients both prior to and following treatment. To scrutinize the differences in microbial gene sequences and species of the intestinal microbiota, 16S rRNA amplicon sequencing technology was employed. Additionally, peripheral blood samples were collected, and the analysis encompassed the assessment of T lymphocyte subsets and myeloid suppressor cell subsets via flow cytometry. Subsequently, alterations in the immune microenvironment pre- and post-treatment were thoroughly analyzed. The predominant clinical manifestations of advanced NSCLC patients encompassed spleen-lung Qi deficiency syndrome and Qi-Yin deficiency syndrome. Notably, the latter exhibited enhanced responsiveness to ICIs with a discernible amelioration of the immune microenvironment. Following ICIs treatment, significant variations in microbial abundance were identified among the three strains: Clostridia, Lachnospiraceae, and Lachnospirales, with a mutual dependency relationship. In the subset of patients manifesting positive PD-L1 expression and enduring therapeutic benefits, the study recorded marked increases in the ratios of CD3+%, CD4+%, and CD4+/CD8+ within the T lymphocyte subsets. Conversely, reductions were observed in the ratios of CD8%, Treg/CD4+, M-MDSC/MDSC, and G-MDSC/MDSC. The strains Clostridia, Lachnospiraceae, and Lachnospirales emerge as potential biomarkers denoting the composition of the intestinal microbiota in the NSCLC therapy. The immunotherapy efficacy of ICIs markedly accentuates in patients displaying durable treatment benefits and those expressing positive PD-L1.

Gut microbes as medical signature for the effectiveness of immunotherapy in patients with advanced non-small cell lung cancer.

Lung cancer (LC) is the most common cause of cancer-related death worldwide and poses a severe threat to public health. Immunotherapy with checkpoint blockers has improved the outlook for advanced non-small cell lung cancer (NSCLC) therapy. For the treatment of patients with advanced NSCLC, antibodies such as anti-programmed death 1 (anti-PD1), anti-programmed death ligand 1 (anti-PD-L1), and anti-cytotoxic T lymphocyte-associated antigen 4 (anti-CTLA-4) are of paramount importance. Anti-PD-1 and anti-PD-L1 monoclonal antibody therapies are used to block the PD-1/PD-L1 pathway and identify cancerous cells to the body's defenses. Antibodies directed against CTLA-4 (anti-CTLA-4) have also been shown to improve survival rates in patients with NSCLC. Currently, other immunotherapy approaches like neoadjuvant immune checkpoint inhibitors (NAICIs) and chimeric antigen receptor T-cell (CAR-T) therapies are applied in NSCLC patients. NAICIs are used for resectable and early stage NSCLC and CAR-T is used to find more useful epitope sites for lung tumors and destroy cancer cells. A patient's gut microbiota might influence how their immune system reacts to NSCLC immunotherapy. The majority of intestinal microbes stimulate helper/cytotoxic T cells, induce natural killer (NK) cells, activate various toll-like receptors (TLR), build up cluster of differentiation 8 (CD8), increase PD-1 production, and attract chemokine receptors towards cancer cells. Thus, they serve as immune inducers in NSCLC immunotherapy. Nonetheless, certain bacteria can function as immune suppressors by inhibiting DC proliferation, stopping CD28 trafficking, restoring CD80/CD86, increasing immunological tolerance, and upsetting Th17 cells. Therefore, they are prevalent in non-responders with NSCLC immunotherapy.

Abstract A021: Evolutionary immunotherapy in NSCLC: An integrated approach

Abstract Purpose: Our study examines tumor growth dynamics and immunosuppression under the presence of immune attack to identify optimal immune pulsing treatment strategies. Motivation: Checkpoint inhibitors disrupting the PD-1/PD-L1 axis are used in multiple cancer subtypes. However, not all patients respond, and predictive biomarkers are needed to better stratify patients. Therapy for PD-L1, the most studied biomarker, has given mixed results in non-small cell lung cancer (NSCLC). The complexity of the immune response and plastic nature of PD-L1/PD-1 expression on tumor and immune cells contributes to the heterogeneity of success. IFN-γ, a cytokine released by activated immune cells, induces PD-L1 expression in some tumor cells. Chronic IFN-γ results in long-term PD-L1 expression. However, relaxation dynamics following removal of IFN-γ remains unexplored. In this study, we investigate these complex PD-L1 dynamics through a unique combination of in vitro studies and mathematical modeling. METHODS: In vitro experimental data: We have collected in vitro and temporal confocal microscopy images of PD-L1 expression on NSCLC cells, which were either untreated or treated for 48 hours with high dose IFN-γ followed by chronic low dose IFN-γ for 21 days.Agent-based model: To reinforce our in vitro experiments and findings, we developed a hybrid agent-based model (ABM) to study PD-L1 dynamics. The agents in the ABM are tumor cells having variable PD-L1 expression, and immune cells that secrete IFN-γ. Tumor cells can be randomly seeded or seeded as a cluster of cells. IFN-γ is modeled as either a binary well-mixed pulse (to simulate the in vitro experimental setup), or as a diffusible via a reaction-diffusion process (to simulate the tumor-immune cell interactions in an in-vivo spatial manner). This allows us to investigate the effects of various pulsing strategies of immunotherapy on tumor evolution where each pulse can be a variable dose of immune cells, given at regular or irregular intervals. RESULTS: Our in vitro experimental data and microscopy images confirm that PD-L1 expression continues to increase within the cells after a 48-hour IFN-γ exposure followed by low levels of IFN-γ. Our ABM has been calibrated to capture in vitro data dynamics for different conditions. Our initial results indicate that pulsing immunotherapy may lead to better overall immune efficacy than continuous immunotherapy, by preventing sustained suppression that increases immune cell exhaustion, despite the potential for tumor regrowth between pulses. We also hypothesize that pulsing immunotherapy will have different immunosuppression effects when tumors are clustered or randomly distributed. CONCLUSION: We have quantified the temporal dynamics of PD-L1 expression in NSCLC cells under different conditions of IFN-γ, and built an ABM to study tumor-immune evolution under various pulsing strategies. The results of this work could lead to improved therapy schedules in patients responsive to checkpoint inhibitors that exploit the complex dynamics of immune response and suppression. Citation Format: Sandhya Prabhakaran, Taylor M. Bursell, Kimberly Luddy, Julian Pineiro, Rafael Bravo, Jeffrey West, Megan Johnson, Mark Robertson-Tessi, Amer A. Beg, Jhanelle E. Gray, Scott Antonia, Robert A. Gatenby, Alexander R. A. Anderson. Evolutionary immunotherapy in NSCLC: An integrated approach [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A021.

Gut microbiota and dietary intervention: affecting immunotherapy efficacy in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) accounts for 80-85% of all lung cancers. In recent years, treatment with immune checkpoint inhibitors (ICIs) has gradually improved the survival rate of patients with NSCLC, especially those in the advanced stages. ICIs can block the tolerance pathways that are overexpressed by tumor cells and maintain the protective activity of immune system components against cancer cells. Emerging clinical evidence suggests that gut microbiota may modulate responses to ICIs treatment, possibly holding a key role in tumor immune surveillance and the efficacy of ICIs. Studies have also shown that diet can influence the abundance of gut microbiota in humans, therefore, dietary interventions and the adjustment of the gut microbiota is a novel and promising treatment strategy for adjunctive cancer therapy. This review comprehensively summarizes the effects of gut microbiota, antibiotics (ATBs), and dietary intervention on the efficacy of immunotherapy in NSCLC, with the aim of informing the development of novel strategies in NSCLC immunotherapy.

Immunotherapy for advanced non-small cell lung cancer with negative programmed death-ligand 1 expression: a literature review.

Lung cancer, mainly non-small cell lung cancer (NSCLC), is a serious threat to human life. In particular, the prognosis for advanced patients is poor, with the 5-year survival rate being exceedingly low. In recent years, immune checkpoint inhibition has changed the pattern of the treatment of a variety of cancers, including lung cancer; however, not all patients can benefit from immunotherapy, and thus finding the right biomarkers is particularly important for guiding precise treatment. Programmed death-ligand 1 (PD-L1) expression is one of the most valuable biomarkers for predicting the efficacy of lung cancer immunotherapy. Several studies have confirmed that patients with high PD-L1 expression are more likely to benefit from immunotherapy, but there is a high proportion of people with negative PD-L1 expression constituting a patient population that cannot be ignored. This article reviews the distribution of PD-L1 expression, the methods for evaluating PD-L1, and the effectiveness of immunotherapy for advanced NSCLC with negative PD-L1 expression. We performed a literature review to identify relevant data published until September 2022. In order to organize related information, we searched for literature in PubMed; abstracts and reports published in the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO), the World Conference on Lung Cancer (WCLC), and other congresses; and clinical trial information registered on ClinicalTrials.gov. Information on the distribution of PD-L1 expression, detection of PD-L1, and immunotherapy efficacy for NSCLC with negative PD-L1 expression was collated and reviewed. The incidence of PD-L1 expression in patients with stage IIIB/IV NSCLC is similar in all regions of the world, but PD-L1 expression level is associated with certain clinicopathological features. The expression of PD-L1 can be evaluated by various detecting methods. Some immunotherapy regimens have better efficacy than traditional chemotherapy in patients with negative PD-L1 expression. Patients with NSCLC and negative PD-L1 expression can receive better survival benefits under some immunotherapy types, and these may represent a better treatment option for this relatively small patient population.