Biomarkers guiding biological therapeutic strategies in chronic rhinosinusitis with nasal polyps: an emerging challenge

KEYWORDS:

• chronic rhinosinusitis with nasal polyps (CRSwNP)
• biomarker
• biologics
• refractory CRSwNP
• type 2 inflammation

1. Body

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous inflammatory disease that is generally classified into type 2 and non-type 2 endotypes [1]. Type 2 CRSwNP is the predominant endotype of refractory CRSwNP [1]. Type 2-related cytokines (interleukin [IL]-4, IL-5, IL-9, and IL-13), mainly secreted by type 2 helper lymphocytes and group 2 innate lymphoid cells, and alarmins (IL-25, IL-33, and thymic stromal lymphopoietin [TSLP]) released from epithelial cells in response to external insults, orchestrate the complex network of type 2 inflammatory response [2,3]. With great heterogeneity and complexity in pathophysiological mechanisms, the conventional ‘one-size-fits-all’ treatment strategy does not necessarily provide benefits to all patients. To fulfill these unmet medical needs, biologics targeting type 2 inflammation have emerged to provide patients with customized therapy approaches. Currently, dupilumab (anti-IL-4 Rα monoclonal antibody [mAb]), omalizumab (anti-immunoglobulin E [IgE] mAb), and mepolizumab (anti-IL-5 mAb) are approved by the United States Food and Drug Administration and European Medicines Agency for the treatment of inadequately controlled CRSwNP. Phase III trials have been conducted or are ongoing in benralizumab (anti-IL-5 R mAb), fevipiprant (anti-prostaglandin D₂ receptor 2 mAb), and tezepelumab (anti-TSLP mAb).

Clinical trials have revealed that not all patients with CRSwNP respond to biologics, despite being indicated for biologics. For instance, in network meta-analyses that indirectly compare biologics targeting type 2 inflammatory mediators, dupilumab is currently recognized as the most efficacious biologic [4–6]. However, only approximately 65% of patients are identified as dupilumab responders (defined by achieving at least one-point improvement in endoscopic nasal polyp score [NPS]) after 24 weeks of treatment) [7]. In addition, the financial burden is relatively high, with the annual cost of biologics in the United States varying between $10,000–$40,000, depending on different types, dosages, and dosing frequency [8]. Moreover, within the type 2 endotype, the predominant cells and cytokines that contribute to forming this intricate network vary between patients [9]. For instance, different levels of local total IgE have been observed in patients with type 2 CRSwNP [10]. The involvement of other immune cells in type 2-biased inflammation also varies among patients [10–12]. Therefore, biomarkers to predict patients’ response to certain biologics before administration are of great significance to improve overall treatment efficiency and relieve the high financial burden posed on patients due to non-responsiveness.

Currently, biomarkers that may serve as predictors of response to biologics remain scarce. Serum osteoprotegerin (OPG) has recently been identified to be predictive of dupilumab response with an accuracy higher than 80% [13]. OPG belongs to the TNF-receptor superfamily and acts as a secreted decoy receptor of RANK-L (receptor activator of NF-kB ligand). Studies have shown that the levels of OPG in nasal polyps were significantly lower in individuals with recurrent CRSwNP as compared to those with primary CRSwNP [14]. This decrease in OPG levels has been associated with the activation of ILC2 [13]. However, no significant difference was observed between eosinophilic and non-eosinophilic CRSwNP [14]. Furthermore, there is currently no comparison of blood OPG levels between the two groups.

The capacity of baseline blood eosinophil counts to predict the sensitivity to biologics remains uncertain. Subgroup analyses have shown that dupilumab, omalizumab, mepolizumab, and benralizumab improve endoscopic, radiographic, and patient-reported outcomes irrespective of blood eosinophil status [15–18]. However, a trend of higher baseline blood eosinophil counts, accompanied by greater benefits in major efficacy outcomes (including NPS and nasal congestion score), has been observed, but without statistical significance [7,16,17,19]. Given that severe type 2 CRSwNP is typically characterized by blood eosinophilia, there is a compelling need for further investigation to validate the potential of blood eosinophil counts as an indicator of biological treatment response and to determine the appropriate cutoff value.

Because of observations of the high comorbidity of type 2 CRSwNP with asthma, and their shared underlying type 2 inflammation, conclusions drawn in studies evaluating biomarker predictivity in asthma may provide hints to the potential of biomarkers to serve as predictors in patients with CRSwNP. The benefits of dupilumab tend to be more pronounced in patients with a higher fraction of exhaled nitric oxide (FeNO) levels, a marker of type 2 inflammation [20–24]. No correlation has been observed between higher FeNO levels and the effectiveness of omalizumab, mepolizumab, and benralizumab [22,25–27]. This might be attributed to the release of nitric oxide, which is regulated by inducible nitric oxide synthase (iNOS), and the production of iNOS is induced by IL-4 and IL-13 [28]. Therefore, molecules that are strongly stimulated by a signaling pathway may be used as an indicator of the pathway’s activation, and may forecast the response to biologics that target this pathway. This hypothesis is further supported by the induction of OPG by IL-4 and IL-13 [29].

Thus, the predictive significance of typical type 2 biomarkers remains to be verified. Eosinophil cationic protein, eotaxins, thymus and activation-regulated chemokine, and pulmonary and activation‐regulated chemokine demonstrate rapid concentration changes after biologics administration [7,30]. Analyzing the relationship between biomarker levels and differences in patients’ responses will verify the predictivity of these biomarkers. More broadly, the potential of type 2 cytokine-induced proteins, such as cystatin SN, arachidonate 15-lipoxygenase, and periostin to indicate and monitor patients’ response to biologics are also of great interest [2,31,32]. Screening biomarkers using novel techniques is another feasible method. The successful application of transcriptomics, proteomics, and other high-throughput technologies to reveal the underlying pathogenesis, distinguish endotypes, and predict CRSwNP postoperative recurrence provides possibilities for these novel techniques to be adopted for the screening of biomarkers. Potential markers to predict the outcome of biologics can be identified through post-hoc studies. By utilizing the aforementioned technologies, genes or proteins that exhibit differential expression between responder and non-responder groups can be screened. These markers can subsequently be subjected to further validation to ascertain their effectiveness in distinguishing responders. As mentioned above, proteomic analyses performed through Olink have identified the predictive significance of OPG to differentiate dupilumab responders [13].

To be clinically applicable, an ideal biomarker should be measurable, quantifiable, reproducible, and obtained in a minimally invasive and cost‐efficient way, such as obtained from blood, nasal secretions, nasal-brushing samples, or bronchoalveolar lavage fluid. A predictive biomarker should also be directly involved in the pathogenesis, or indirectly reflect CRSwNP onset or progression. In terms of indicating patients’ response, biomarkers need to be efficient enough to determine the optimal biologics choice for each individual, even though different patients are highly heterogeneous for the key driver of type 2 inflammation [9]. After discontinuation, improvements in efficacy outcomes are maintained over a period of time [7]; in other words, patients may not need to continuously receive biologics. Thus, regular tracking of biomarker variations that parallel disease control status and indicate the point of time to restart biologics treatment is one of the most cost-efficient ways to monitor patients’ status after biologics withdrawal.

At present, no marker has been employed in actual clinical practice. As previously noted, the efficacy of blood eosinophil and FeNO in identifying patients who are appropriate candidates for treatment of biologics has yet to be confirmed in real-world investigations. While OPG and other type 2 cytokine-induced molecules may have the capacity to classify patients, the outcomes must be validated by substantial cohorts. Nonetheless, in an era of precision medicine, clinical biologics use has shed light on CRSwNP treatment. With the burst of biologics targeting diverse mediators of type 2 inflammation, accurate biologics selection for each individual is increasingly complicated. Thus, efficiently stratifying patients using biomarkers to guide clinical biologics use and to facilitate the real-life application of tailored therapy is an area waiting to be explored.

2. Expert opinion

Biologics have emerged to fulfill the unmet needs of patients with refractory CRSwNP. With evidence from randomized controlled trials, post-hoc analyses, indirect treatment comparisons, and real-world studies, biologics are not completely efficient in the overall population. Thus, there is a growing interest in comprehending how to tailor biological therapy to individual patients to increase the overall control rate of CRSwNP.

Adopting precisely-defined and reproducible biomarkers to guide treatment decisions throughout the treatment period is a viable approach to accomplish these objectives. To ensure the appropriate selection of biologics, it is crucial to identify biomarkers that can predict treatment response. Consequently, using these preliminary findings, it is possible to stratify potential responders and non-responders before commencing biologics. Moreover, the identification of biomarkers with the ability to dynamically monitor the status of patients throughout treatment is crucial. Specifically, biomarkers that can indicate the appropriate time to initiate biologic administration, the optimal point to discontinue biological treatment, or the viability of adopting a reduced dosage or extended dosing interval are essential for effective patient management throughout the treatment process.

Currently, verifying the predictivity of type 2 biomarkers which involves the pathogenesis, progression, or prognosis of CRSwNP, and screening biomarkers through novel techniques, are applicable methods to identify biomarkers and to promote their robust development. However, to date, no biomarker has progressed beyond the laboratory to real clinical practice. This is due to the lack of clinical trials that validate laboratory findings under real-world conditions, as well as the absence of standardized criteria for measuring biomarkers and assessing outcomes. These challenges must be addressed before biomarkers can be applied from bench to bedside. We anticipated that development in the identification and gradual application of predictive biomarkers will be seen in the near future to guide the selection of tailored biological therapy strategies for patients with CRSwNP.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This work was supported by grants from the national key R&D program of China (2022YFC2504100); National Natural Science Foundation of China (81900917, 82171108, 82025010, and 81870698); Changjiang Scholars and Innovative Research Team (IRT13082); CAMS Innovation Fund for Medical Sciences (2019-I2M-5-022); Beijing Municipal Science and Technology Project (Z181100001618002 and Z211100002921057); Capital’s Funds for Health Improvement and Research (CFH2022-1-1091); Beijing Municipal Science & Technology Commission (No. Z221100007422009; Z211100002921057); Beijing Municipal Administration of Hospitals’ Mission Plan (SML20150203); Beijing Municipal Administration of Hospitals’ Dengfeng plan (DFL20190202), and Dongcheng District Outstanding Talent Nurturing Program (2022-dchrcpyzz-3).