Peripheral Blood Biomarkers Predictive of Efficacy Outcome and Immune-Related Adverse Events in Advanced Gastrointestinal Cancers Treated with Checkpoint Inhibitors

Neutrophil-to-Lymphocyte Ratio Predicts Immune-related Adverse Events in Patients With Hepatocellular Carcinoma Treated With Atezolizumab Plus Bevacizumab

Background/Aim

Atezolizumab in combination with bevacizumab is an approved systemic chemotherapy regimen for advanced hepatocellular carcinoma (HCC). However, immune checkpoint inhibitors (ICIs), such as atezolizumab, frequently lead to immune-related adverse events (irAEs). The identification of biomarkers that can predict the occurrence of irAEs is crucial for the optimal management of patients undergoing ICI treatment.

Patients and Methods

Between October 2020 and June 2023, we conducted a study involving 69 patients with advanced HCC who received treatment with atezolizumab plus bevacizumab. We conducted an analysis of blood-based biomarkers to identify independent risk factors associated with irAEs.

Results

In our study, 12 out of 69 patients (17.4%) experienced irAEs. Our investigation into blood-based biomarkers revealed that a neutrophil-to-lymphocyte ratio (NLR) <2.04 at three weeks after the initiation of treatment had high predictive power (area under the curve: 0.77) for irAEs. Furthermore, multivariate logistic analysis identified NLR at three weeks (hazard ratio=0.23; p=0.037) and non-viral infection (hazard ratio=4.47; p=0.037) as independent factors contributing to the occurrence of irAEs. Patients who developed irAEs demonstrated a more favorable overall response rate (75.0% vs. 28.1%, p=0.005), disease control rate (91.6% vs. 52.6%, p=0.016), and progression-free survival (12.1 months vs. 6.0 months, p=0.010) than those who did not experience irAEs.

Conclusion

An NLR <2.04 at three weeks after the initiation of treatment may serve as a valuable biomarker for predicting irAEs in patients with HCC undergoing atezolizumab plus bevacizumab therapy.

Neutrophil to Lymphocyte ratio as a predictor for immune-related adverse events in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in immune-related adverse events (irAEs), which can cause treatment discontinuation and even fatal reactions. The purpose of this study was to evaluate the usefulness of the peripheral biomarker neutrophil to lymphocyte ratio (NLR) in predicting irAEs.

Methods

A systematic search of databases was conducted to identify studies on the predictive value of NLR for irAEs. The standardized mean difference (SMD) was used to compare continuous NLR, while crude odds ratios (ORs) were calculated for categorized NLR if adjusted ORs and 95% confidence intervals (CIs) were not provided in the original study.

Results

The meta-analysis included 47 studies with a total of 11,491 cancer patients treated with ICIs. The baseline continuous NLR was significantly lower in patients with irAEs compared to those without (SMD=-1.55, 95%CI=-2.64 to -0.46, P=0.006). Similarly, categorized NLR showed that lower baseline NLR was associated with increased irAEs (OR=0.55, 95%CI=0.41-0.73, P<0.001). Subgroup analysis revealed that the OR for predicting irAEs with NLR cut-off values of 3 and 5 was 0.4 and 0.59, respectively. Interestingly, increased baseline NLR was associated with a higher incidence of immune-related liver injury (OR=2.44, 95%CI=1.23-4.84, I2 = 0%, P=0.010).

Conclusion

Our study suggests that lower baseline NLR is associated with a higher risk of overall irAEs. However, further studies are needed to determine the best cut-off value and explore the efficacy of NLR in predicting specific types of irAEs.

Predictors of immune checkpoint inhibitor-related adverse events in older patients with lung cancer: a prospective real-world analysis

PURPOSE

Older patients with cancer are underrepresented in pivotal trials of immune checkpoint inhibitors (ICIs). This study aimed to investigate immune-related adverse events (irAEs) that occur in older patients with lung cancer treated with ICIs, and explore predictors of the occurrence of irAEs.

METHODS

A prospective analysis was performed on older patients with lung cancer aged ≥ 65 years who were treated with anti-programmed cell death-1/-ligand 1 (PD-1/PD-L1) inhibitors in Beijing Hospital from January 2018 to December 2022. The incidence and risk factors of irAEs were estimated by the Chi-square test or Wilcoxon rank-sum tests. The predictive power of Geriatric-8 (G-8) for irAEs was tested by receiver operating characteristic (ROC) curve analysis. Lymphocyte counts were measured by flow cytometry. Cytokine levels were tested by Enzyme-linked immunosorbent assay, respectively. Kaplan-Meier method was used to calculated progression-free survival (PFS) curves, and the log-rank test was used to evaluate differences.

RESULTS

A total of 201 older patients aged ≥ 65 years with lung cancer were enrolled in this study. The most common irAEs were interstitial pneumonia, dermatological toxicity and hypothyroidism, with rates of 17.2%, 16.1% and 5.6%, respectively. ROC showed that G-8 could predict the occurrence of irAEs in patients aged 65-71 years (≥ G2 irAEs: AUC = 0.757, p < 0.001; ≥ G3 irAEs: AUC = 0.862, p < 0.001), but not for patients aged ≥ 71 years. NLR, LMR, PNI, hypertension and diabetes were associated with irAEs. Lower CD4 + T cells and B cells, and lower levels of IL-10 were associated with the development of irAEs.

CONCLUSION

Our study confirmed the accuracy of G-8 for predicting irAEs in older patients. We also identified several predictors of irAEs in older patients with lung cancer.

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

New biomarkers exploration and nomogram construction of prognostic and immune-related adverse events of advanced non-small cell lung cancer patients receiving immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICIs) are regarded as the most promising treatment for advanced-stage non-small cell lung cancer (aNSCLC). Unfortunately, there has been no unified accuracy biomarkers and systematic model specifically identified for prognostic and severe immune-related adverse events (irAEs). Our goal was to discover new biomarkers and develop a publicly accessible method of identifying patients who may maximize benefit from ICIs.

METHODS

This retrospective study enrolled 138 aNSCLC patients receiving ICIs treatment. Progression-free survival (PFS) and severe irAEs were end-points. Data of demographic features, severe irAEs, and peripheral blood inflammatory-nutritional and immune indices before and after 1 or 2 cycles of ICIs were collected. Independent factors were selected by least absolute shrinkage and selection operator (LASSO) combined with multivariate analysis, and incorporated into nomogram construction. Internal validation was performed by applying area under curve (AUC), calibration plots, and decision curve.

RESULTS

Three nomograms with great predictive accuracy and discriminatory power were constructed in this study. Among them, two nomograms based on combined inflammatory-nutritional biomarkers were constructed for PFS (1 year-PFS and 2 year-PFS) and severe irAEs respectively, and one nomogram was constructed for 1 year-PFS based on immune indices. ESCLL nomogram (based on ECOG PS, preSII, changeCAR, changeLYM and postLDH) was constructed to assess PFS (1-, 2-year-AUC = 0.893 [95% CI 0.837-0.950], 0.828 [95% CI 0.721-0.935]). AdNLA nomogram (based on age, change-dNLR, changeLMR and postALI) was constructed to predict the risk of severe irAEs (AUC = 0.762 [95% CI 0.670-0.854]). NKT-B nomogram (based on change-CD3+CD56+CD16+NKT-like cells and change-B cells) was constructed to assess PFS (1-year-AUC = 0.872 [95% CI 0.764-0.965]). Although immune indices could not be modeled for severe irAEs prediction due to limited data, we were the first to find CD3+CD56+CD16+NKT-like cells were not only correlated with PFS but also associated with severe irAEs, which have not been reported in the study of aNSCLC-ICIs. Furthermore, our study also discovered higher change-CD4+/CD8+ ratio was significantly associated with severe irAEs.

CONCLUSIONS

These three new nomograms proceeded from non-invasive and straightforward peripheral blood data may be useful for decisions-making. CD3+CD56+CD16+NKT-like cells were first discovered to be an important biomarker for treatment and severe irAEs, and play a vital role in distinguishing the therapy response and serious toxicity of ICIs.

Blood cell counts can predict adverse events of immune checkpoint inhibitors: A systematic review and meta-analysis

Background

Cancer is concerning owing to its high mortality rate. Consequently, methods of prolonging the life of patients with cancer have become the primary focus of attention research. In recent years, immune checkpoint inhibitors (ICIs) have achieved good clinical efficacy as antitumor drugs; however, their severe adverse effects have made their use challenging. In order to clarify the predictors of adverse effects, scientists have conducted a series of studies. Blood counts can potentially monitor risk factors associated with the occurrence of immune-related adverse events (irAEs). Herein, a meta-analysis was performed to clarify further the guiding significance of blood counts in the clinical setting.

Methods

Studies that satisfied the inclusion criteria were obtained by searching the database. Included studies were those in which irAEs had been observed, and evidence of an association between blood counts and irAEs was reported. The included ones were evaluated for quality. In addition to sensitivity analysis and subgroup analysis, a meta-analysis was performed using the odds ratio (OR) and 95% confidence interval (CI) for each study.

Results

A total of 18 articles were included in our study. The analyses were performed separately according to different blood cell count indicators. The blood cell count metrics associated with irAEs were: absolute eosinophil count, neutrophil: lymphocyte ratio, and platelet: lymphocyte ratio.

Conclusion

Our review and meta-analysis of studies suggest that absolute eosinophil count, neutrophil: lymphocyte ratio, and platelet: lymphocyte ratio may serve as predictors of the emergence of irAEs. Given the small number of studies focusing on the relationship between patient blood cell counts and the risk of irAEs, future studies need to further explore the mechanisms of occurrence and potential associations.