Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Targeting of immune checkpoint regulator V-domain Ig suppressor of T-cell activation (VISTA) with 89Zr-labelled CI-8993

BACKGROUND

CI-8993 is a fully human IgG1κ monoclonal antibody (mAb) that binds specifically to immune checkpoint molecule VISTA (V-domain Ig suppressor of T-cell activation). Phase I safety has been established in patients with advanced cancer (NCT02671955). To determine the pharmacokinetics and biodistribution of CI-8993 in patients, we aimed to develop 89Zr-labelled CI-8993 and validate PET imaging and quantitation in preclinical models prior to a planned human bioimaging trial.

METHODS

CI-8993 and human isotype IgG1 control were conjugated to the metal ion chelator p-isothiocyanatobenzyl-desferrioxamine (Df). Quality of conjugates were assessed by SE-HPLC, SDS-PAGE, and FACS. After radiolabelling with zirconium-89 (89Zr), radioconjugates were assessed for radiochemical purity, immunoreactivity, antigen binding affinity, and serum stability in vitro. [89Zr]Zr-Df-CI-8993 alone (1 mg/kg, 4.6 MBq) or in combination with 30 mg/kg unlabelled CI-8993, as well as isotype control [89Zr]Zr-Df-IgG1 (1 mg/kg, 4.6 MBq) were assessed in human VISTA knock-in female (C57BL/6 N-Vsirtm1.1(VSIR)Geno, huVISTA KI) or control C57BL/6 mice bearing syngeneic MB49 bladder cancer tumours; and in BALB/c nu/nu mice bearing pancreatic Capan-2 tumours.

RESULTS

Stable constructs with an average chelator-to-antibody ratio of 1.81 were achieved. SDS-PAGE and SE-HPLC showed integrity of CI-8993 was maintained after conjugation; and ELISA indicated no impact of conjugation and radiolabelling on binding to human VISTA. PET imaging and biodistribution in MB49 tumour-bearing huVISTA KI female mice showed specific localisation of [89Zr]Zr-Df-CI-8993 to VISTA in spleen and tumour tissues expressing human VISTA. Specific tumour uptake was also demonstrated in Capan-2 xenografted BALB/c nu/nu mice.

CONCLUSIONS

We radiolabelled and validated [89Zr]Zr-Df-CI-8993 for specific binding to huVISTA in vivo. Our results demonstrate that 89Zr-labelled CI-8993 is now suitable for targeting and imaging VISTA expression in human trials.

A Novel Prognostic Indicator for Immunotherapy Response: Lymphocyte-to-Albumin (LA) Ratio Predicts Survival in Metastatic NSCLC Patients

OBJECTIVE

Immunotherapies are commonly employed for the treatment of non-small-cell lung cancer (NSCLC). However, predictive biomarkers still need to be improved to predict responses to these agents. The lymphocyte-albumin (LA) laboratory index has not been evaluated before in this patient group. The aim of this study was to analyze the relation between the LA index and the survival rate of metastatic NSCLC patients who had immunotherapy after at least one round of chemotherapy.

METHODS

The research included 227 patients diagnosed with metastatic NSCLC, who were administered nivolumab after at least one round of chemotherapy. The LA index was calculated by multiplying lymphocyte count and albumin concentration. The optimal threshold values for the index were established by the examination of the ROC curve for both overall survival (OS) and progression-free survival (PFS). Oncological data were obtained retrospectively from patient files, and survival analyses were performed.

RESULTS

The median follow-up was 7.9 months. Progression was observed in 129 (56.9%) patients. A total of 97 (42.7%) patients died during the follow-up. The cutoff values of the LA index to predict OS and PFS were determined as 52.87 and 57.67, respectively. The low-LA group had significantly lowered OS and PFS compared to the high-LA group. LA was found to be an independent prognostic factor for PFS (hazard ratio 4.47; 95% confidence interval, 2.73-7.34; p < 0.001) and OS (hazard ratio 6.24; 95% confidence interval, 3.46-11.25; p < 0.001) in the multivariate regression analysis.

CONCLUSIONS

In this study, we observed that the LA index independently predicts OS and PFS in immunotherapy-treated metastatic NSCLC patients. Its ease of application, low cost, and noninvasive nature make it a potential guide for clinicians in predicting treatment responses and survival.

Case report: Immunotherapy guided by molecular profiling of tumors: illustrative cases and literature review

Predictive biomarkers are necessary for the identification of immunotherapy-responsive patients. Tumor mutation burden (TMB), as determined by next-generation sequencing (NGS), and PD-L1 expression, as evaluated by Immunohistochemistry (IHC), are the biomarkers most frequently employed in clinical practice. In addition, microsatellite instability (MSI) was the first biomarker to demonstrate immunotherapy efficacy irrespective of the type of tumor and possesses a high predictive value. However, its limited use across most tumor types limits its therapeutic potential. This report describes two cancer patients with positive TMB and PD-L1 expression. The molecular profile of the tumor indicated that the first patient was responsive to Immune checkpoint inhibitors (ICI), while the second patient was resistant. These case studies demonstrate that tumor molecular analysis in combination with immunotherapy predictive biomarkers, such as PD-L1 expression and TMB, can enhance the prediction of response to ICI for specific patients. This methodology enables an individualized and improved approach to the treatment and management of the disease.

Identification and Application of Emerging Biomarkers in Treatment of Non-Small-Cell Lung Cancer: Systematic Review

Non-small-cell lung cancer (NSCLC) comprises approximately 85% of all lung cancer cases, often diagnosed at advanced stages, which diminishes the effective treatment options and survival rates. This systematic review assesses the utility of emerging biomarkers-circulating tumor DNA (ctDNA), microRNAs (miRNAs), and the blood tumor mutational burden (bTMB)-enhanced by next-generation sequencing (NGS) to improve the diagnostic accuracy, prognostic evaluation, and treatment strategies in NSCLC. Analyzing data from 37 studies involving 10,332 patients from 2020 to 2024, the review highlights how biomarkers like ctDNA and PD-L1 expression critically inform the selection of personalized therapies, particularly beneficial in the advanced stages of NSCLC. These biomarkers are critical for prognostic assessments and in dynamically adapting treatment plans, where high PD-L1 expression and specific genetic mutations (e.g., ALK fusions, EGFR mutations) significantly guide the use of targeted therapies and immunotherapies. The findings recommend integrating these biomarkers into standardized clinical pathways to maximize their potential in enhancing the treatment precision, ultimately fostering significant advancements in oncology and improving patient outcomes and quality of life. This review substantiates the prognostic and predictive value of these biomarkers and emphasizes the need for ongoing innovation in biomarker research.

CDKL1 potentiates the antitumor efficacy of radioimmunotherapy by binding to transcription factor YBX1 and blocking PD-L1 expression in lung cancer

BACKGROUND

The evasion of the immune response by tumor cells through programmed death-ligand 1 (PD-L1) has been identified as a factor contributing to resistance to radioimmunotherapy in lung cancer patients. However, the precise molecular mechanisms underlying the regulation of PD-L1 remain incompletely understood. This study aimed to investigate the role of cyclin-dependent kinase-like 1 (CDKL1) in the modulation of PD-L1 expression and the response to radioimmunotherapy in lung cancer.

METHODS

The tumorigenic roles of CDKL1 were assessed via cell growth, colony formation, and EdU assays and an in vivo nude mouse xenograft model. The in vitro radiosensitization effect of CDKL1 was evaluated using a neutral comet assay, γH2AX foci formation analysis, and a clonogenic cell survival assay. The protein‒protein interactions were confirmed via coimmunoprecipitation and GST pulldown assays. The regulation of PD-L1 by CDKL1 was evaluated via chromatin immunoprecipitation (ChIP), real-time quantitative PCR, and flow cytometry analysis. An in vitro conditioned culture model and an in vivo C57BL/6J mouse xenograft model were developed to detect the activation markers of CD8+ T cells and evaluate the efficacy of CDKL1 overexpression combined with radiotherapy (RT) and an anti-PD-L1 antibody in treating lung cancer.

RESULTS

CDKL1 was downregulated and suppressed the growth and proliferation of lung cancer cells and increased radiosensitivity in vitro and in vivo. Mechanistically, CDKL1 interacted with the transcription factor YBX1 and decreased the binding affinity of YBX1 for the PD-L1 gene promoter, which consequently inhibits the expression of PD-L1, ultimately leading to the activation of CD8+ T cells and the inhibition of immune evasion in lung cancer. Moreover, the combination of CDKL1 overexpression, RT, and anti-PD-L1 antibody therapy exhibited the most potent antitumor efficacy against lung cancer.

CONCLUSIONS

Our findings demonstrate that CDKL1 plays a crucial role in regulating PD-L1 expression, thereby enhancing the antitumor effects of radioimmunotherapy. These results suggest that CDKL1 may be a promising therapeutic target for the treatment of lung cancer.

A novel investigation into the negative impact of opioid use on the efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer patients

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have effectively improved the clinical outcome of advanced non-small cell lung cancer (NSCLC). Opioids are commonly used for pain relief in cancer patients. This study aims to clarify the prognostic impact of opioid use in advanced NSCLC patients receiving ICI therapy.

METHODS

A systematic literature review was carried out using online databases before July 2023. The meta-analysis was used to clarify the correlation of opioid use with the overall survival (OS) or progression-free survival (PFS) of ICI-treated NSCLC patients, both of which were determined using hazard ratios (HRs) coupled with 95 % confidence intervals (CIs). Then, an independent cohort enrolling 181 NSCLC patients was utilized for validation. Finally, a comprehensive bioinformatics analysis based on TCGA cohort was performed to investigate the prognostic significance of opioid target genes (OTGs) and their correlation with immune infiltration in NSCLC patients.

RESULTS

A total of 8 studies enrolling 1174 patients were included in the meta-analysis. Opioid use was negatively associated with worse PFS (HR = 2.16, 95 %CI: 1.26-3.71) and OS (HR = 2.02, 95 %CI: 1.54-2.63) in ICI-treated NSCLC patients. The retrospective validation confirmed the above result and identified opioid use as an independent unfavorable predictor for PFS and OS in both the entire cohort and ICI subgroup. The bioinformatic analysis identified 14 prognostic OTGs (CYP17A1, PDYN, PYCARD, FGA, NTSR1, FABP1, HPCA, PENK, PDGFB, LIN7A, FKBP5, TYMS, CACNA1H and LDHA), most of which were correlated with immune infiltration in NSCLC. A risk model was constructed based on 14 OTGs and found to effectively stratify the clinical outcome in both the training and validation set, independent of age, gender and TNM staging system. The model was also significantly correlated with infiltration of activated dendritic cells, neutrophils and tumor infiltrating lymphocytes. Finally, a nomogram was constructed based on the model, age, gender and TNM stage, which could predict well the 1-, 3- and 5-year survival of NSCLC patients.

CONCLUSION

Opioid use is correlated with the poor clinical outcome in ICI-treated NSCLC patients. Precise pain management is highly advocated and opioids are recommended to be cautiously used in these patients. OTGs have the potential to be prognostic biomarkers for NSCLC patients and their role in tumor immunity needs to be further investigated.

Identification of C-PLAN index as a novel prognostic predictor for advanced lung cancer patients receiving immune checkpoint inhibitors

Objective

Increasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.

Methods

The clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan-Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.

Results

A total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p<0.001). The multivariate analysis revealed high C-PLAN index was an independent unfavorable factor affecting PFS (hazard ratio (HR)=1.821; 95%confidence interval (CI)=1.291-2.568) and OS (HR=2.058, 95%CI=1.431-2.959). The high C-PLAN index group had a significantly lower disease control rate than the low C-PLAN index group (p=0.024), while no significant difference was found for objective response rate (p=0.172). The subgroup analysis based on clinical features (pathological type, therapy strategy, TNM stage and age) confirmed the prognostic value of C-PLAN index, except for patients receiving ICI monotherapy or with age ranging from 18 to 65 years old. Finally, a nomogram was constructed based on C-PLAN index, age, gender, TNM stage and smoking status, which could predict well the 1-, 2- and 3-year survival of ICI-treated lung cancer patients.

Conclusion

The C-PLAN index has great potential to be utilized as a non-invasive, inexpensive and reliable prognostic predictor for advanced lung cancer patients receiving ICI-based anti-cancer therapies.

Killing a fly with a sledgehammer: Atezolizumab exposure in real-world lung cancer patients

Atezolizumab is an anti-PDL1 approved for treating lung cancer. A threshold of 6 μg/mL in plasma has been associated with target engagement. The extent to which patients could be overexposed with the standard 1200 mg q3w dosing remains unknown. Here, we monitored atezolizumab peak and trough levels in 27 real-world patients with lung cancer as part of routine therapeutic drug monitoring. Individual pharmacokinetic (PK) parameters were calculated using a population approach and optimal dosing-intervals were simulated with respect to the target trough levels. No patient had plasma levels below 6 μg/mL. The results showed that the mean trough level after the first treatment was 78.3 ± 17 μg/mL, that is, 13 times above the target concentration. The overall response rate was 55.5%. Low-grade immune-related adverse events was observed in 37% of patients. No relationship was found between exposure metrics of atezolizumab (i.e., minimum plasma concentration, maximum plasma concentration, and area under the curve) and pharmacodynamic end points (i.e., efficacy and toxicity). Further simulations suggest that the dosing interval could be extended from 21 days to 49 up to 136 days (mean: 85.7 days, i.e., q12w), while ensuring plasma levels still above the 6 μg/mL target threshold. This observational, real-world study suggests that the standard 1200 mg q3w fixed-dose regimen of atezolizumab results in significant overexposure in all the patients. This was not associated with increased side effects. As plasma levels largely exceed pharmacologically active concentrations, interindividual variability in PK parameters did not impact efficacy. Our data suggest that dosing intervals could be markedly extended with respect to the target threshold associated with efficacy.