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Immunotherapy biomarkers
Original research
Circulating receptor activator of nuclear factor kappa-B ligand (RANKL) levels predict response to immune checkpoint inhibitors in advanced non-small cell lung cancer (NSCLC)
  1. Michele Iuliani1,
  2. Sonia Simonetti1,
  3. Leonardo Cristofani2,
  4. Silvia Cavaliere1,
  5. Alessio Cortellini1,3,
  6. Marco Russano3,
  7. Bruno Vincenzi1,3,
  8. Giuseppe Tonini1,3,
  9. Daniele Santini4 and
  10. Francesco Pantano1,3
  1. 1Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
  2. 2UOC Oncologia Medica A, University of Rome La Sapienza, Rome, Italy
  3. 3Medical Oncology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy
  4. 4UOC Oncologia Medica A, Policlinico Umberto 1, Università degli Studi di Roma La Sapienza, Rome, Italy
  1. Correspondence to Dr Sonia Simonetti; s.simonetti{at}unicampus.it

  • MI and SS are joint first authors.

  • DS and FP are joint senior authors.

Abstract

Background Receptor activator of nuclear factor kappa-B ligand (RANKL) can directly promote tumor growth and indirectly support tumor immune evasion by altering the tumor microenvironment and immune cell responses. This study aimed to assess the prognostic significance of soluble RANKL in patients with advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD1)/programmed death-ligand 1 (PDL1) checkpoint inhibitor therapy.

Methods Plasma RANKL levels were measured in 100 patients with advanced NSCLC without bone metastases undergoing monotherapy with PD1/PDL1 checkpoint inhibitors. To establish the optimal cut-off value, we used the Cutoff Finder package in R. Survival curves for four distinct patient groups, according to their RANKL and PDL1 levels (high or low), were generated using the Kaplan-Meier method and compared with the log-rank test. The Cox regression model calculated HRs and 95% CIs for overall survival (OS) and progression-free survival (PFS).

Results The optimal RANKL cut-off was established at 280.4 pg/mL, categorizing patients into groups with high or low RANKL levels. A significant association was observed between increased RANKL concentrations and decreased survival rates at 24 months, only within the subgroup expressing high levels of PDL1 (p=0.002). Additionally, low RANKL levels in conjunction with elevated PDL1 expression correlated with improved PFS (median 22 months, 95% CI 6.70 to 50 vs median 4 months, 95% CI 3.0 to 7.30, p=0.009) and OS (median 26 months, 95% CI 20 to not reached vs median 7 months, 95% CI 6 to 13, p=0.003), indicating RANKL’s potential as an indicator of adverse prognosis in these patients. Multivariate analysis identified RANKL as an independent negative prognostic factor for both PFS and OS, regardless of other clinicopathological features.

Conclusion These results highlight the prognostic and predictive value of RANKL specifically in patients with high PDL1 expression.

  • Lung Cancer
  • Immune Checkpoint Inhibitor

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jitc-2024-009432

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • It is established that receptor activator of nuclear factor kappa-B ligand (RANKL) not only directly promotes tumor growth and survival but also indirectly supports tumor immune evasion by altering the tumor microenvironment and modulating immune responses.

    WHAT THIS STUDY ADDS

    • We identified RANKL as a negative prognostic biomarker correlated with reduced progression-free survival (PFS) and overall survival (OS) in advanced non-small cell lung (NSCL) cancer patients with high programmed death-ligand 1 (PDL1) expression (≥50%) undergoing PD1/PDL1 immune checkpoint inhibitors.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • These insights propose that RANKL may act as a prognostic biomarker, assisting healthcare professionals in the decision-making process for patients with high PDL1 expression by identifying those who may benefit from more aggressive treatment strategies. Moreover, RANKL emerges as a potential therapeutic target to improve the response to checkpoint inhibitors in these patients.

    Background

    The development of programmed cell death 1 (PD1)/programmed death-ligand 1 (PDL1) checkpoint inhibitors has revolutionized the treatment of advanced non-small cell lung cancer (NSCLC), enhancing patient survival and quality of life.1–7 However, not all patients with NSCLC respond to PD1/PDL1 checkpoint inhibitors, and some develop resistance after an initial response. The factors influencing response and resistance to PD1/PDL1 checkpoint inhibitors are complex and multifactorial. They include tumor mutational burden (TMB), the tumor microenvironment (TME), immune status and genetic and epigenetic alterations in tumor and immune cells.8–12 One of the most widely used biomarkers for selecting patients with NSCLC for PD1/PDL1 checkpoint inhibitor therapy is the expression of PDL1 on tumor or immune cells.13 Nevertheless, PDL1 expression is not a definitive predictor of response; some patients with high PDL1 expression do not respond to PD1/PDL1 checkpoint inhibitors, while some with low or negative PDL1 expression do respond. This variability may be attributed to the heterogeneity and dynamism of PDL1 expression, as well as other resistance mechanisms independent of the PD1/PDL1 axis.14 15

    The soluble receptor activator of nuclear factor kappa-B ligand (RANKL) is a cytokine pivotal in bone metabolism and immune regulation.16 Studies have indicated that RANKL is overexpressed in various cancers, including NSCLC, correlating with tumor progression, metastasis and poor prognosis.17–19 RANKL can directly foster tumor growth and survival by activating the RANK signaling pathway in tumor cells and indirectly bolster tumor immune evasion by modulating the TME and immune responses.16 20 21 Furthermore, RANKL can induce PDL1 expression on dendritic cells (DCs) and tumor cells, potentially inhibiting T cell responses and diminishing the efficacy of PD1/PDL1 checkpoint inhibitors.22 Our group has identified RANKL as a negative predictive biomarker for the efficacy of PD1/PDL1 checkpoint inhibitors in patients with metastatic renal cancer.23 Building on this evidence, we investigated the plasma levels of RANKL in 100 patients with advanced NSCLC who were candidates to receive PD1/PDL1 checkpoint inhibitor therapy as a monotherapy.

    Methods

    Sample size estimation and post hoc power analysis

    Given that PDL1 expression delineates distinct patient cohorts in terms of disease biology, prognosis and responsiveness to PD1/PDL1 checkpoint inhibitors, our primary aim was to determine the prognostic value of RANKL within subsets of patients with high (≥50%) and low (<50%) PDL1 expression. We calculated the sample size needed to compare the 2-year survival rates between two groups of patients with metastatic NSCLC treated with PD1/PDL1 checkpoint inhibitors, stratified by their RANKL levels (low or high). Assuming a one-sided alpha of 0.05, a power of 80% and drawing on previous studies,5 23 24 we postulated that the survival rate at 24 months would be 20% in the RANKLhigh group and 60% in the RANKLlow group. Employing the formula for comparing two proportions (inequality, two independent groups, unconditional and z-test unpooled), we determined a requirement of 16 patients per group to discern this difference with the intended power (online supplemental figure 1A). To accommodate all potential combinations of PDL1 status (preplanned to be 50% low and 50% high PDL1 patients) and plausible RANKL cut-off points that divide our cohort into low and high groups within a range from 50% to 66%, we estimated a total sample size of 96 patients. A post hoc analysis was conducted to evaluate the actual power achieved by the observed proportions in the two groups (OR) and the sample sizes in the RANKLhigh PDL1high (22 patients) and RANKLlow PDL1high (28 patients) groups (online supplemental figure 1B).

    Supplemental material

    Supplemental material

    Study design and patient characteristics

    Between 2017 and 2021, a cohort of 248 patients with advanced NSCLC was treated with PD1/PDL1 checkpoint inhibitors as monotherapy at Fondazione Policlinico Universitario Campus Bio-Medico. The follow-up continued until December 2023. The study adhered to the Helsinki Declaration principles, and all experimental protocols received approval from the Internal Review and Ethics Boards of the Campus Bio-Medico University of Rome (Protocol No. 48.17OSS). Informed consent was obtained from all participants. A retrospective selection of 100 patients was made based on inclusion and exclusion criteria, high sample quality and adequate follow-up (>24 months) (online supplemental figure 2). Inclusion criteria encompassed patients aged 18 years or older, with a performance status of 0–1, no active autoimmune diseases and no bone metastases or history of osteoporotic fractures. Exclusion criteria included conditions impacting bone, vitamin D or calcium metabolism (such as chronic liver disease (bilirubin>1.5×upper limit of normal (ULN), alanine transaminase, aspartate aminotransferase>2.5×ULN), Paget’s disease, renal failure (creatinine>1.5×ULN), malabsorption and hypercortisolism), as well as medications affecting bone metabolism (eg, denosumab, bisphosphonates, teriparatides, glucocorticoids, aromatase inhibitors and estrogen). Plasma samples were collected on the day of the initial treatment cycle, prior to infusion. Patient disease was required to be measurable according to Response Evaluation Criteria in Solid Tumors V.1.1 at baseline and assessed for treatment response via radiological evaluation (CT scan) every 12 weeks. Progression-free survival (PFS) was defined as the interval from the first infusion of PD1/PDL1 checkpoint inhibitors to the first recorded tumor progression. Overall survival (OS) was the interval from the initial infusion to death or the last update.

    Supplemental material

    Plasma RANKL assessment

    RANKL concentrations in plasma samples were quantified using the Human TRANCE-RANKL/TNFSF11 assay kit (R&D Systems), following the manufacturer’s protocol. Upon completion of the assay, a stop solution was introduced to the ELISA plates, inducing a colorimetric shift from blue to yellow. The optical density was measured at 450 nm with a Tecan Infinite M200Pro microplate reader. A standard curve was generated to facilitate data interpretation, and the results were reported in pg/mL.

    Statistical analysis

    To identify the optimal cut-off for RANKL in our sample cohort, we used the Cutoff Finder package in R.25 We applied a mixture model of two Gaussian distributions to the RANKL histogram data using the flexmix function from the same package.26 The optimal cut-off was established at the point where the probability density functions of the two distributions intersected. The association between OS at 24 months and RANKL levels was assessed using the Wilcoxon-Mann-Whitney test. Survival curves were generated using the Kaplan-Meier method and compared via the log-rank test for univariate analysis. Univariate HRs were computed using the log-rank method. A multivariable Cox regression model was employed to calculate HRs and 95% CIs for OS and PFS. Variables demonstrating statistical significance at a p value of less than 0.05 were included.

    Results

    The RANKL cut-off was optimized within the entire cohort. The determined best RANKL cut-off was 280.4 pg/mL, categorizing the patients into 37 with high RANKL and 63 with low RANKL (figure 1).

    Figure 1
    Figure 1

    Histogram of RANKL levels in 100 patients. The vertical lines designate the optimal cut-off derived from the mixture model. RANKL, receptor activator of nuclear factor kappa-B ligand.

    The clinicopathological features of the patients did not differ significantly between the RANKLhigh and RANKLlow groups (table 1).

    View this table:
    Table 1

    Clinicopathological features according to RANKL status

    The median follow-up was 54 months (95% CI 51–not reached). A significant association between RANKL levels and the 24-month survival rate was observed exclusively in the PDL1 high group (p=0.002) (figure 2A). Specifically, RANKL was higher in patients who were not alive versus alive at 24 months (median 335 pg/mL vs 148 pg/mL, respectively; p=0.042) (figure 2B).

    Figure 2
    Figure 2

    (A) Survival rate at 24 months according to RANKL status in PDL1high and PDL1low patients. (B) RANKL levels PDL1high and PDL1low patients who were alive or not at 24 months. PDL1, programmed death-ligand 1; RANKL, receptor activator of nuclear factor kappa-B ligand.

    Survival analysis indicated that patients with low RANKL and high PDL1 expression had improved outcomes in terms of PFS (median 22 months, 95% CI 6.70–50 vs median 4 months, 95% CI 3–7.30, p=0.009) and OS (median 26 months, 95% CI 20–not reached vs median 7 months, 95% CI 6–13, p=0.003) (figure 3). These findings suggest that RANKL may serve as a potential biomarker for poor prognosis in the PDL1 high patient population. Additionally, within the low RANKL group, patients with high PDL1 expression exhibited significantly longer PFS (p=0.003) and OS (p=0.019) compared with those with low PDL1 expression (figure 3).

    Figure 3
    Figure 3

    Kaplan-Meier curves for (A) progression-free survival and (B) overall survival according to RANKL and PDL1 status. PDL1, programmed death-ligand 1; RANKL, receptor activator of nuclear factor kappa-B ligand.

    Post hoc analysis confirmed that our study had sufficient power (power=0.89) (online supplemental figure 1B). Multivariate analysis revealed that RANKL is an independent negative prognostic factor for PFS and OS, independent of primary clinicopathological characteristics (sex, age, smoking status, histotype and Eastern Cooperative Oncology Group performance status) (figure 4).

    Figure 4
    Figure 4

    Multivariate analysis for (A) PFS and (B) OS. OS, overall survival; PFS, progression-free survival.

    Discussion

    In this study, we explored the potential prognostic significance of soluble RANKL in relation to PDL1 status. Our findings suggest that elevated RANKL levels correlate with poorer PFS and OS in patients with high PDL1 expression (≥50%). Conversely, no such correlation was observed in the PDL1 low subset.

    Previous research indicates that RANKL may serve as a chemotactic agent for tumor cells, facilitating their migration and invasion into bone and other tissues.27 28 Notably, RANKL appears to influence the immune system by promoting the differentiation and activation of DCs and T cells, as well as by stimulating PDL1 expression on both tumor and immune cells.16 Additionally, RANKL can stimulate the secretion of chemokines by M2 macrophages, leading to an increased proliferation of regulatory T cells (TREG).29 Furthermore, RANKL has been shown to activate the immune regulatory functions of myeloid-derived suppressor cells (MDSCs) and promote the expansion of monocytic MDSCs.30 In this regard, we have conducted a bioinformatics analysis on The Cancer Genome Atlas datasets to investigate whether the expression of tumor RANKL correlates with the presence of a specific immune infiltrate. Data obtained showed a significant association between high expression of RANKL and an enrichment of immunosuppressive cells such as TREG cells and MSDCs (online supplemental figure 3). Therefore, high RANKL levels could signify more aggressive tumor behavior and an immunosuppressive milieu, potentially diminishing the efficacy of PD1/PDL1 checkpoint inhibitors.

    Supplemental material

    The paradoxical observation that RANKL’s negative prognostic impact is confined to patients with high PDL1 warrants further investigation. One hypothesis is that RANKL’s immunomodulatory effects vary with PDL1 expression levels. Given RANKL’s role in upregulating PDL1 on DCs and T cells, it might enhance PD1/PDL1 interactions, leading to immune cell exhaustion and tolerance.16 This phenomenon could be more pronounced in patients with elevated PDL1 levels, who likely harbor a greater number of PDL1-positive and PD1-positive cells within the TME. In contrast, for patients with lower PDL1 expression, RANKL might exert a reduced inhibitory impact on the immune system due to decreased PD1/PDL1 engagement and the presence of PD1-independent immune regulatory mechanisms.15 31 32 Thus, RANKL could act as a negative feedback mechanism for the PD1/PDL1 axis, explaining its prognostic significance exclusively in patients with high PDL1 expression. In such cases, RANKL might intensify PDL1’s immunosuppressive effects, rendering tumors more resistant to checkpoint inhibition. However, in the PDL1 low cohort, RANKL’s influence on immune function might be minimal or non-existent, as the PD1/PDL1 pathway may not be the primary mode of immune evasion. Here, other parameters like TMB, neoantigen load and the presence of tumor-infiltrating lymphocytes could be more predictive of the checkpoint inhibitor response.15 31 32

    We also chose to exclude patients with bone metastases from our analysis to avoid potential confounding influences on RANKL levels and checkpoint inhibitor responses. RANKL is a pivotal cytokine for osteoclast differentiation and activity, and its expression is known to be elevated by both tumor and bone cells within the bone metastatic niche.33–35 Hence, individuals with bone metastases might exhibit higher RANKL levels, independent of their tumor characteristics and immune profile. Additionally, bone metastases could alter the efficacy of checkpoint inhibitors by establishing an immune-privileged sanctuary for tumor cells, allowing them to evade systemic and local immune responses.36–38

    One of the advantages of this study is the inclusion of patients with low PDL1 expression who received PD1/PDL1 checkpoint inhibitors as monotherapy. This allowed us to assess the true prognostic significance of RANKL in relation to PDL1 expression without the confounding influence of chemotherapy. This was feasible because patients were retrospectively enrolled before the adoption of a chemotherapy-immunotherapy combination in clinical practice for those with PDL1 expression below 50%. However, it is important to interpret the results with the understanding that the cohort of patients with high PDL1 expression completely coincides with those receiving first-line treatment.

    While our study did not encompass a large patient population, it was sufficiently powered by preliminary sample size estimations and post hoc power analysis to demonstrate RANKL’s potential prognostic value. However, it is essential to recognize several limitations. The retrospective design of the analysis may introduce biases typical of observational studies, which should be taken into account. While the exclusion of patients with bone metastases aims to reduce confounding factors, it also limits the applicability of the findings to the broader patient population. Moreover, the study assessed RANKL levels only at baseline. Repeated measurements over time could provide more insight into the dynamics of RANKL levels and their relationship with disease progression and treatment response. Finally, the significant association between RANKL levels and survival rates observed exclusively in the PDL1 high group suggests that RANKL may not be a universal biomarker for all patient populations.

    Clinically, the measurement of RANKL may serve as an instrumental tool in the decision-making process for the treatment of patients exhibiting high PDL1 expression. Significantly, RANKL can act as a prognostic biomarker, identifying individuals who may experience a more aggressive disease and potentially poorer outcomes. Furthermore, this biomarker could facilitate treatment stratification, aiding clinicians in prioritizing or intensifying treatment for patients with elevated RANKL levels. Additionally, RANKL presents itself as a potential therapeutic target to augment the efficacy of PD1/PDL1 checkpoint inhibitors in patients with high PDL1 expression. Nonetheless, the utility of RANKL as a prognostic tool and therapeutic target necessitates validation through larger, prospective studies.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study involves human participants. The study adhered to the Helsinki Declaration principles, and all experimental protocols received approval from the Internal Review and Ethics Boards of the Campus Bio-Medico University of Rome (Protocol No. 48.17OSS). Participants gave informed consent to participate in the study before taking part.

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    Supplementary materials

    Footnotes

    • Contributors Conceptualization: DS; methodology: FP; formal analysis: FP; investigation: MI, SS, LC and SC; writing original draft: SS and MI; writing review and editing: DS, AC, MR, GT, BV, MI, SS, LC, SC and FP; visualization: MI and SS; guarantor: FP; supervision: DS, FP, GT and BV. DS and FP are joint last authors.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.