Advances in the prediction of long-term effectiveness of immune checkpoint blockers for non-small-cell lung cancer

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.

Validation of Patras Immunotherapy Score model for prediction and prognosis of patients with advanced NSCLC treated with nivolumab or pembrolizumab: results from a European multicentre study

Background:

Recently, the Patras Immunotherapy Score (PIOS) has been developed to estimate the survival benefit of patients with advanced non-small-cell lung cancer (aNSCLC) treated with nivolumab or pembrolizumab. The aim of this study was to validate the clinical value of PIOS in an external cohort of aNSCLC patients.

Methods:

PIOS is a baseline formula produced by the combination of performance status, body mass index, age and line of treatment. In this multicentre study, 626 patients with confirmed NSCLC pathology, who had been treated with nivolumab or pembrolizumab, as well as 444 patients with aNSCLC, who had been managed with chemotherapy alone, were retrospectively enrolled. Predictive and prognostic values of PIOS were finally evaluated.

Results:

Patients treated with immunotherapy and higher PIOS score had an improved progression-free survival not only in univariate [hazard ratio (HR) = 0.621, p = 0.001], but also in multivariable analysis (HR = 0.651, p = 0.003). In addition, improved overall survival with increasing PIOS score was also observed (HR = 0.608, p < 0.001) with this association remaining statistically significant after adjusting for programmed-cell death ligand 1 (PD-L1) expression (HR = 0.620, p < 0.001). In addition, patients with disease progression (PD) had lower scores compared to those with stable disease (SD), partial response (PR) or complete response (CR) in a two-tier model (p < 0.001) as well as in a four-tier model (PD, SD, PR and CR; p < 0.001). Prognostic significance of PIOS score also persisted using a binary logistic regression analysis, adjusted for disease stage and PD-L1 status (p = 0.002, odds ratio: 0.578). Contrarily, PIOS had no prognostic significance in the chemotherapy group; however, upon combined analysis of the two cohorts, PIOS was found to have a significant interaction with the type of treatment (HR = 0.066 with p < 0.001), confirming its predictive value for immunotherapy.

Conclusions:

This study provides further validation of PIOS in aNSCLC patients treated with anti-PD-1 monotherapy.

Three models that predict the efficacy of immunotherapy in Chinese patients with advanced non-small cell lung cancer

Background

Many tools have been developed to predict the efficacy of immunotherapy, such as lung immune prognostic index (LIPI), EPSILoN [Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil‐to‐lymphocyte ratio (NLR)], and modified lung immune predictive index (mLIPI) scores. The aim of this study was to determine the ability of three predictive scores to predict the outcomes in Chinese advanced non‐small cell lung cancer (aNSCLC) patients treated with immune checkpoint inhibitors (ICIs).

Methods

We retrospectively analyzed 429 patients with aNSCLC treated with ICIs at our institution. The predictive ability of these models was evaluated using area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis. Calibration was assessed using the Hosmer–Lemeshow test (H–L test) and Spearman's correlation coefficient. Progression‐free survival (PFS) and overall survival (OS) curves were generated using the Kaplan–Meier method.

Results

The AUC values of LIPI, mLIPI, and EPSILoN scores predicting PFS at 6 months were 0.642 [95% confidence interval (CI):0.590–0.694], 0.720 (95% CI: 0.675–0.762), and 0.633 (95% CI: 0.585–0.679), respectively (p < 0.001 for all models). The AUC values of LIPI, mLIPI, and EPSILON scores predicting objective response rate (ORR) were 0.606 (95% CI: 0.546–0.665), 0.683 (95% CI: 0.637–0.727), and 0.666 (95% CI: 0.620–0.711), respectively (p < 0.001 for all models). The C‐indexes of LIPI, mLIPI, and EPSILoN scores for PFS were 0.627 (95% CI 0.611–6.643), 0.677 (95% CI 0.652–0.682), and 0.631 (95% CI 0.617–0.645), respectively.

Conclusions

As mLIPI scores had the highest accuracy when used to predict the outcomes in Chinese aNSCLC patients, this tool could be used to guide clinical immunotherapy decision‐making.

Immune checkpoint inhibitors in oncogene-addicted non-small cell lung cancer: a systematic review and meta-analysis

BACKGROUND

Treatment of oncogene-addicted non-small cell lung cancer (NSCLC) has been changed by the advent of tyrosine kinase inhibitors (TKIs). Albeit great benefits are achieved with target therapies, resistance invariably occurs and recourse to alternative treatments is unavoidable. Immune checkpoint inhibitors (ICIs) role and the best setting of immunotherapy administration in oncogene-driven NSCLC are matter of debate.

METHODS

We performed a systematic literature review through PubMed, in order to gather all the available information regarding ICI activity and efficacy in oncogene-addicted NSCLC, from both prospective trials and retrospective series. A meta-analysis of objective response rate in different molecular subgroups was provided. Combinatorial strategies including ICIs and related toxicities were also recorded.

RESULTS

Eighty-seven studies were included in the qualitative analysis. EGFR mutation may be a biomarker of poor response to single-agent ICIs (7% of EGFR-mutant NSCLC patients achieved disease response in prospective trials), while encouraging results have been shown with combination strategies. KRAS-mutated disease (response rate, RR, 22%) has different clinical and pathological characteristics, and the co-existence of additional mutations (e.g., STK11 or TP53) influence tumor microenvironment and response to immunotherapy. Other molecular alterations have been marginally considered prospectively, and data from clinical practice are variegated, given poor effectiveness of ICIs in ALK-rearranged disease (RR 9.5%, pooling the data of retrospective studies) or some encouraging results in BRAF-(RR 25%, retrospective data) or MET-driven one (with estimations conditioned by the presence of both exon 14 skipping mutations and gene amplification in reported series).

CONCLUSIONS

In oncogene-addicted NSCLC (with the exception of KRAS-mutated), ICIs are usually administered at the failure of other treatment options, but administering single-agent immunotherapy in later disease phases may limit its efficacy. With the progressive administration of TKIs and ICIs in early-stage disease, molecular characterization will become fundamental in this setting.

Immunotherapy in patients with non-small cell lung cancer with ECOG PS 2

Immunotherapy is a new and very promising method of anti-cancer treatment. Unfortunately, not every patient can benefit from this treatment. The Polish drug program determines the selection of patients based on PD-L1 expression and the performance status assessed with the use of Eastern Cooperative Oncology Group Performance Status (ECOG PS) score. Patients with ECOG PS 2 represent a significant proportion of the cancer population, one which is overlooked in most clinical trials of immunotherapy. Often, a reduced performance status is the only factor that excludes the patient from treatment with immunotherapy. Choosing the optimal method of treatment in patients with a worse general condition and with multiple diseases may be a significant problem for the doctor. Assessment of performance status may be a particular problem because not every patient has a worse PS score for the same reasons. In this study, we analyse the results of treatment of patients with a poorer performance status to date, and we present tools that improve the precise assessment of the degree of the performance status, which may enable more patients to access novel lung cancer treatments.

Immunotherapy in advanced non-small-cell lung cancer with EGFR mutations

EGFR-tyrosine kinase inhibitors (EGFR-TKIs) had been regarded as the front-line treatment for advanced non-small-cell lung cancer (NSCLC) patients with EGFR mutations. However, resistance to EGFR-TKIs is inevitable, it remains a major challenge. Immune checkpoint inhibitors (ICIs) had shown superior clinical efficacy in many types of solid tumors, while it exhibited impaired overall efficacy in NSCLC with EGFR mutations. In this review, we will perform a meta-analysis to assess the relationship between the programmed death ligand 1 (PD-L1) expression and clinical benefit of EGFR-TKIs. We also overview the immunotherapy in advanced NSCLC patients with EGFR mutations to investigate the potential biomarkers predicting the ICIs efficiency, and the subgroups that could benefit from ICIs treatment.

Atypical patterns of response and progression in the era of immunotherapy combinations

In the immunoncology era, an acceleration of tumor growth upon immune checkpoint inhibitors (ICI), defined as hyperprogressive disease (HPD) has been observed across different cancers. Although in non-small-cell lung cancer, most of the available evidence regarding HPD has been reported for patients treated with single agent PD-1 and PD-L1 inhibitors, in retrospective series a variable proportion of patients receiving ICI combinations also experienced HPD. Similarly, the shape of survival curves and the progression rates in clinical trials testing combinations of PD-1/PD-L1 inhibitors and anti-CTLA-4 agents suggest the occurrence of HPD. Few data are available regarding pseudoprogression upon ICI combinations. However, considering that pseudoprogression has been reported for anti-PD-1/PD-L1 agents and for CTLA-4 inhibitors separately, it is likely that it may occur also upon combinations of these two classes of drugs.

PIOS (Patras Immunotherapy Score) Score Is Associated with Best Overall Response, Progression-Free Survival, and Post-Immunotherapy Overall Survival in Patients with Advanced Non-Small-Cell Lung Cancer (NSCLC) Treated with Anti-Program Cell Death-1 (PD-1) Inhibitors

Immunotherapy with immune checkpoint inhibitors (ICIs) has changed the therapeutic management of advanced non-small cell lung cancer (aNSCLC) over the last decade. However, there is an unmet need for clinically useful biomarkers in this patient subgroup. The aim of this study was to combine baseline clinical characteristics of aNSCLC patients, in the form of a scoring system, and to investigate its predictive and prognostic value in NSCLC patients treated with ICIs. A total of 112 patients with advanced (stages IIIA to IV) NSCLC, treated with nivolumab or pembrolizumab, were enrolled in this study. Patras Immunotherapy Score (PIOS) was developed based on four of the studied parameters (performance status (PS), body mass index (BMI), age, and lines of treatment (LOT), which were incorporated into our formula (PS × BMI/ LOT × age). PIOS score was strongly associated with best overall responses (BOR), with those patients having benefit/good response (stable disease (SD) or partial (PR) or complete response (CR), achieving a higher score compared to patients who developed progressive disease (PD) (p < 0.001). Furthermore, PIOS score was associated with progression-free survival (PFS), since high-score patients had longer PFS (p < 0.001, hazard ratio (HR) = 0.469). Moreover, PIOS was associated with post-immunotherapy overall survival (OS), with high-score patients having improved OS (log-rank p = 0.019). This study suggests that a combination of baseline parameters, which give rise to PIOS score, may predict the best response of NSCLC patients treated with anti-program cell death -1 (PD-1) monotherapy as well as it may have a potent prognostic value for PFS and post immunotherapy OS.

Hyperprogressive Disease upon Immune Checkpoint Blockade: Focus on Non-small Cell Lung Cancer

PURPOSE OF REVIEW

Describe the controversial aspects of hyperprogressive disease (HPD) definition, mechanisms, and biomarkers.

RECENT FINDINGS

Although immune checkpoint inhibitors (ICIs) demonstrated a survival benefit in non-small cell lung cancer (NSCLC), an acceleration of tumor growth during ICI, defined as HPD, was reported in ~ 13-26% of NSCLC patients and correlated with worse survival compared with conventional progression. Different criteria have been used for HPD definition. The main limitation for the use of tumor growth rate and tumor growth kinetics variations is its inapplicability for patients without a pre-baseline imaging or progressing on non-measurable lesions. On the contrary, time to treatment failure and clinical criteria (i.e., worsening of performance status, presence of new lesions, or metastatic spread to different sites) can be useful in the above-mentioned settings but do not consent an assessment of tumor growth before ICI initiation. Several mechanisms of HPD have been proposed so far, involving both adaptive and innate immunity or based on cell-autonomous signals of cancer growth triggered by ICI. The characterization of HPD biomarkers and the identification and validation on large series of one or more mechanistic explanations for the HPD phenomenon are of paramount significance to avoid detrimental immunotherapy in a subgroup of patients and exploit novel therapeutic targets for future immunotherapy combinations. HPD occur in a subgroup of NSCLC patients treated with ICI. Several definitions and mechanisms have been proposed and a consensus on HPD criteria and biological bases is currently lacking.

EPSILoN: A Prognostic Score Using Clinical and Blood Biomarkers in Advanced Non-Small-cell Lung Cancer Treated With Immunotherapy

BACKGROUND

Second-line immunotherapy (IO) has shown an overall survival benefit. However, only 18% to 20% of patients with advanced non-small-cell lung cancer (aNSCLC) will respond, with a median progression-free survival (PFS) of 2 to 4 months. Thus, biomarkers to select those patients most likely to benefit from IO are greatly needed.

PATIENTS AND METHODS

We conducted a retrospective analysis of 154 patients with aNSCLC who had received anti-programmed cell death 1 therapy as second line or further treatment. We assessed the absolute neutrophil, lymphocyte, monocyte, and eosinophil counts at baseline (T0) and the second (T1) and third (T2) cycles. The neutrophil/lymphocyte ratio (NLR), derived-NLR (dNLR), lymphocyte/monocyte ratio (LMR), and their percentage of change at T1 and T2 compared with T0 were evaluated. The clinical characteristics and lactate dehydrogenase (LDH) level were also considered. Univariate and multivariate analyses were performed. Significant biomarkers for PFS on multivariate analysis were combined in a prognostic score.

RESULTS

For overall survival, the negative prognostic biomarkers were Eastern Cooperative Oncology Group (ECOG) performance status (PS) 2, NLR at T0, and dNLR at T1; the LMR at T0, T1, and T2 was identified as a positive prognostic biomarker. For PFS, the negative prognostic biomarkers were ECOG PS 2, liver metastases, NLR at T0, dNLR at T1 and T2, and ≥ 30% increase of NLR from T0 to T1; the positive prognostic biomarkers were heavy smoking, LDH, and LMR at T2. The ≥ 30% increase of LMR from T0 to T1 and T0 to T2 correlated with the overall response rate. A prognostic score (EPSILoN score; smoking, ECOG PS, liver metastases, LDH, NLR) identified 3 prognostic groups (median PFS, 10.2, 4.9, and 1.7 months, respectively; P < .001).

CONCLUSIONS

The EPSILoN score combines 5 baseline clinical and blood biomarkers and can help to identify patients with aNSCLC who will most likely benefit from second-line IO. Further studies are warranted.

EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort

BACKGROUND

Beyond programmed death ligand 1 (PD-L1), no other biomarkers for immunotherapy are used in daily practice. We previously created EPSILoN (Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR)) score, a clinical/biochemical prognostic score, in 154 patients treated with second/further-line immunotherapy. This study's aim was to validate EPSILoN score in a different population group.

METHODS

193 patients were included at National Cancer Institute of Milan (second-line immunotherapy, 61%; further-line immunotherapy, 39%). Clinical/laboratory parameters such as neutrophil-to-lymphocyte ratio and lactate dehydrogenase levels were collected. Kaplan-Meier and Cox hazard methods were used for survival analysis.

RESULTS

Overall median progression-free survival and median overall survival were 2.3 and 7.6 months, respectively. Multivariate analyses for Progression-Free Survival (PFS) identified heavy smokers (hazard ratio (HR) 0.71, p = 0.036) and baseline LDH < 400 mg/dL (HR 0.66, p = 0.026) as independent positive factors and liver metastases (HR 1.48, p = 0.04) and NLR ≥ 4 (HR 1.49, p = 0.029) as negative prognostic factors. These five factors were included in the EPSILoN score which was able to stratify patients in three different prognostic groups, high, intermediate and low, with PFS of 6.0, 3.8 and 1.9 months, respectively (HR 1.94, p < 0.001); high, intermediate and low prognostic groups had overall survival (OS) of 24.5, 8.9 and 3.4 months, respectively (HR 2.40, p < 0.001).

CONCLUSIONS

EPSILoN, combining five baseline clinical/blood parameters (ECOG PS, smoking, liver metastases, LDH, NLR), may help to identify advanced non-small-cell lung cancer (aNSCLC) patients who most likely benefit from immune checkpoint inhibitors (ICIs).

Molecular basis and rationale for combining immune checkpoint inhibitors with chemotherapy in non-small cell lung cancer

Immunotherapy has prompted a paradigm shift in advanced non-small cell lung cancer (NSCLC) treatment, by demonstrating superior efficacy to chemotherapy alone both in second- and in first-line setting. Novel insights on molecular mechanisms and regimens to enhance the efficacy of immunotherapy are warranted, as only a minority of patients (˜20%) respond to checkpoint blockade. Taking into account the multiple mechanisms adopted by tumor cells to evade the immune system through cancer immunoediting, the frontline combination of immune checkpoint inhibitors with chemotherapy appears to be a successful strategy as: 1) it enhances the recognition and elimination of tumor cells by the host immune system (immunogenic cell-death), and 2) it reduces the immunosuppressive tumor microenvironment. Remarkably, the immune checkpoint inhibitors pembrolizumab and atezolizumab have already been approved by the FDA in combination with chemotherapy for the first-line treatment of advanced NSCLC and many other chemo-immunotherapeutic regimens have been evaluated as an initial therapeutic approach in metastatic NSCLC. Concurrently, several preclinical studies are evaluating the molecular mechanisms underlying immunomodulation by conventional chemotherapeutic agents (platinum salts, antimitotic agents, antimetabolites and anthracyclines), unraveling drug- and dose/schedule-dependent effects on the immune system that should be exploited to achieve synergistic clinical activity. The current review provides a detailed overview of the immunobiological rationale and molecular basis for combining immune checkpoint inhibitors with chemotherapy for the treatment of advanced NSCLC. Moreover, current evidence and future perspectives towards a better selection of patients who are more likely to benefit from chemo-immunotherapy combinations are discussed.