Blood Biomarkers of Response to Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Siglec 15 as a biomarker or a druggable molecule for non-small cell lung cancer

Lung cancer has been the main cause of cancer mortality worldwide. Furthermore, lung cancer rates of new cases per year evidenced a large incidence of this neoplasm in both men and women. Because there is no biomarker for early detection, it is frequently detected late, at an advanced state. The introduction of multiple lines of tyrosine kinase inhibitors in patients with EGFR, ALK, ROS1, and NTRK mutations has modified the therapy of lung cancer. Immunotherapy advances have resulted in substantial improvements in overall survival and disease-free survival, making immune checkpoint inhibitors (ICIs) a potential option for lung cancer treatment. Current PD-1/PD-L1/CTLA-4 immunotherapies have resulted in important response and survival rates. However, existing medicines only function in around 20% of unselected, advanced NSCLC patients, and primary and acquired resistance remain unsolved obstacles. Therefore, precise predictive indicators must be identified to choose the best patients for ICI treatment. Thus, Sialic acid-binding immunoglobulin-like lectin 15 (Siglec-15) stands out as a potential tumor biomarker, with distinctive expression in normal tissues, in tumor immune involvement, and a high structural similarity to PD-L1. Understanding the tumor immune response and the search for new therapeutic targets leads to the improvement of therapeutic pathways directed at the tumor microenvironment. The present review aims to analyze Siglec-15 potential as a diagnostic, prognostic, and response biomarker in lung cancer, considering its results evidenced in the current literature.

Plasmacytoid Dendritic Cell, Slan+-Monocyte and Natural Killer Cell Counts Function as Blood Cell-Based Biomarkers for Predicting Responses to Immune Checkpoint Inhibitor Monotherapy in Non-Small Cell Lung Cancer Patients

The advent of immune checkpoint inhibitors (ICIs), for instance, programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) blockers, has greatly improved the outcome of patients affected by non-small cell lung cancer (NSCLC). However, most NSCLC patients either do not respond to ICI monotherapy or develop resistance to it after an initial response. Therefore, the identification of biomarkers for predicting the response of patients to ICI monotherapy represents an urgent issue. Great efforts are currently dedicated toward identifying blood-based biomarkers to predict responses to ICI monotherapy. In this study, more commonly utilized blood-based biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR) and the lung immune prognostic index (LIPI) score, as well as the frequency/number and activation status of various types of circulating innate immune cell populations, were evaluated in NSCLC patients at baseline before therapy initiation. The data indicated that, among all the parameters tested, low plasmacytoid dendritic cell (pDC), slan+-monocyte and natural killer cell counts, as well as a high LIPI score and elevated PD-L1 expression levels on type 1 conventional DCs (cDC1s), were independently correlated with a negative response to ICI therapy in NSCLC patients. The results from this study suggest that the evaluation of innate immune cell numbers and phenotypes may provide novel and promising predictive biomarkers for ICI monotherapy in NSCLC patients.

Linkage between Psychological Factors and Response to Immune Checkpoint Inhibitor Therapy: A Preliminary Study

Substantial evidence has accumulated showing that psychological distress affects immune regulation, the response to cancer treatment, and survival. The effect of psychological parameters on the effectiveness of immune checkpoint inhibitor (ICI) treatment has not yet been studied. This preliminary study aimed to (a) examine the associations between psychological factors and responses to ICI treatment and (b) assess the associations between psychological factors and blood measures of sPD-1, sCTLA-4, and cytokines that may alter the effect of ICI treatment. The participants were 62 individuals with advanced cancer, aged 18 years or older, who were candidates for ICI treatment as a new line of treatment. The participants answered questionnaires and provided blood samples and medical data prior to the start of ICI treatment and 3 months after. Perceived health status was positively associated with better responses to ICI treatment. In the subsample of participants with biomarkers, worse health-related quality of life was associated with higher IL-6 and sCTLA-4; emotional distress and sleep difficulties were associated with higher sCTLA-4; and better perceived health was associated with lower IL-6 and TNFα. sPD-1 was not associated with psychological measures. This preliminary study found for the first time that some psychological measures could be linked to responses to cancer treatment, possibly via pro-inflammatory cytokines and sCTLA-4.

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-Based Biomarker Analysis for Predicting Efficacy of Chemoradiotherapy and Durvalumab in Patients with Unresectable Stage III Non-Small Cell Lung Cancer

We recruited 50 patients with unresectable stage III NSCLC who received CCRT between March 2020 and March 2021. Durvalumab consolidation (DC) was administered to patients (n = 23) without progression after CCRT and programmed death-ligand 1 (PD-L1) ≥ 1%. Blood samples were collected before (C0) and after CCRT (C1) to calculate PBC counts and analyze CTCs. CTCs, isolated by the CD-PRIME^TM system, exhibited EpCAM/CK+/CD45- phenotype in BioViewCCBS^TM. At median follow-up of 27.4 months, patients with residual CTC clusters at C1 had worse median PFS than those without a detectable CTC cluster (11.0 vs. 27.8 months, p = 0.032), and this trend was noted only in the DC group (p = 0.034). Patients with high platelets at C1 (PLT^hi, >252 × 10³/µL) had worse median PFS than those with low platelets (PLT^lo) (5.9 vs. 17.1 months, p < 0.001). In multivariable analysis, PLT^hi and residual CTC clusters at C1 were independent risk factors for PFS, and DC group with PLT^hi and residual CTC clusters at C1 showed the worst median PFS (2.6 months, HR 45.16, p = 0.001), even worse than that of the CCRT alone group with PLT^hi (5.9 months, HR 15.39, p = 0.001). The comprehensive analysis of CTCs and PBCs before and after CCRT revealed that the clearance of CTC clusters and platelet counts at C1 might be potential biomarkers for predicting survival.

Monitoring Blood Immune Cells in Patients with Advanced Small Cell Lung Cancer Undergoing a Combined Immune Checkpoint Inhibitor/Chemotherapy

In this exploratory prospective observational study on 40 small cell lung cancer (SCLC) patients treated with a combination of chemotherapy and immune checkpoint inhibitors, blood immune cells were characterized by multi-color flow cytometry at the baseline and at the third therapy cycle. The numbers of neutrophils and of T-, B-, and NK cells, as well as the frequency of HLA-DR^low monocytes, 6-SulfoLacNAc (slan)+ non-classical monocytes and circulating dendritic cell (DC) subtypes were determined. The prognostic value of the parameters was evaluated by the patient's survival analysis with overall survival (OS) as the primary endpoint. In addition, blood cell parameters from SCLC patients were compared to those from non-SCLC (NSCLC). The global median OS of patients was 10.4 ± 1.1 months. Disease progression (15% of patients) correlated with a higher baseline neutrophil/lymphocyte ratio (NLR), more HLA-DR^low monocytes, and lower NK cell and DC numbers. The risk factors for poor OS were the presence of brain/liver metastases, a baseline NLR ≥ 6.1, HLA-DR^low monocytes ≥ 21% of monocytes, slan+ non-classical monocytes < 0.12%, and/or CD1c+ myeloid DC < 0.05% of leukocytes. Lymphocytic subpopulations did not correlate with OS. When comparing biomarkers in SCLC versus NSCLC, SCLC had a higher frequency of brain/liver metastases, a higher NLR, the lowest DC frequencies, and lower NK cell numbers. Brain/liver metastases had a substantial impact on the survival of SCLC patients. At the baseline, 45% of SCLC patients, but only 24% of NSCLC patients, had between three and five risk factors. A high basal NLR, a high frequency of HLA-DR^low monocytes, and low levels of slan+ non-classical monocytes were associated with poor survival in all lung cancer histotypes. Thus, the blood immune cell signature might contribute to a better prediction of SCLC patient outcomes and may uncover the pathophysiological peculiarities of this tumor entity.

Choosing the optimal immunotherapeutic strategies for non-small cell lung cancer based on clinical factors

The treatment landscape of advanced non-small cell lung cancer (NSCLC) has changed dramatically since the emergence of immune checkpoint inhibitors (ICIs). Although some patients achieve long survival with relatively mild toxicities, not all patients experience such benefits from ICI treatment. There are several ways to use ICIs in NSCLC patients, including monotherapy, combination immunotherapy, and combination chemoimmunotherapy. Decision-making in the selection of an ICI treatment regimen for NSCLC is complicated partly because of the absence of head-to-head prospective comparisons. Programmed death-ligand 1 (PD-L1) expression is currently considered a standard biomarker for predicting the efficacy of ICIs, although some limitations exist. In addition to the PD-L1 tumor proportion score, many other clinical factors should also be considered to determine the optimal treatment strategy for each patient, including age, performance status, histological subtypes, comorbidities, status of oncogenic driver mutation, and metastatic sites. Nevertheless, evidence of the efficacy and safety of ICIs with some specific conditions of these factors is insufficient. Indeed, patients with poor performance status, oncogenic driver mutations, or interstitial lung disease have frequently been set as ineligible in randomized clinical trials of NSCLC. ICI use in these patients is controversial and remains to be discussed. It is important to select patients for whom ICIs can benefit the most from these populations. In this article, we review previous reports of clinical trials or experience in using ICIs in NSCLC, focusing on several clinical factors that are associated with treatment outcomes, and then discuss the optimal ICI treatment strategies for NSCLC.