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Martin, M. Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma. Encyclopedia. Available online: https://encyclopedia.pub/entry/19982 (accessed on 05 December 2025).
Martin M. Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma. Encyclopedia. Available at: https://encyclopedia.pub/entry/19982. Accessed December 05, 2025.
Martin, Maria. "Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma" Encyclopedia, https://encyclopedia.pub/entry/19982 (accessed December 05, 2025).
Martin, M. (2022, February 28). Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma. In Encyclopedia. https://encyclopedia.pub/entry/19982
Martin, Maria. "Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma." Encyclopedia. Web. 28 February, 2022.
Effects of Therapeutic Antibodies on Transcriptome/Proteome of Asthma
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This entry is adapted from the peer-reviewed paper 10.3390/biomedicines10020293

Different gene clusters have been identified to change upon omalizumab treatment, found a reduction in eosinophil-associated gene signatures after benralizumab treatment, and protein profiles were different in patients treated with mepolizumab and in those treated with benralizumab. The main potential biomarkers proposed by the selected studies are shown. These results may contribute to discovering biomarkers of response and selecting the best therapy for each patient.

therapeutic antibody mepolizumab benralizumab omalizumab asthma transcriptome proteome

1. Introduction

During the last few decades, asthma and related diseases have become a global health problem affecting all age groups. The high incidence of asthma in the population of some countries suppose a burden to health care systems and loss of productivity and quality of life. Asthma is a heterogeneous disease, usually characterized by chronic airway inflammation. It is defined by the history of respiratory symptoms, such as wheezing, shortness of breath, chest tightness, and coughing, which vary over time and in intensity, together with variable expiratory airflow limitation [1].
Asthma has been classified as either a T2-type and a non-T2-type [2]. T2-type asthma presents a T2-type immune response, characterized by Th2 cell-driven inflammation and mainly includes allergic asthma, late-onset eosinophilic asthma, and aspirin-exacerbated respiratory disease (AERD) [3]. On the other hand, non-T2-type asthma refers to asthma without a T2-type immune response, with Th1 or Th17 cell-driven inflammatory responses, including neutrophilic asthma and smooth muscle mediated paucigranulocitic asthma [3].
Current treatments for asthma aim to control symptoms and reduce the risk of future exacerbations. Nevertheless, some asthmatic patients have severe asthma with persistent symptoms, reduced lung function, or multiple exacerbations despite maximal treatment [4].
Over the last years, several monoclonal antibodies targeting specific inflammatory pathways have been developed and approved to tackle this problem and improve the patients’ quality of life [5]. These monoclonal antibodies block IL-5 cells, such as mepolizumab, reslizumab [6], IL-5 receptor (IL5-Rα), i.e., benralizumab [7], and IL-4 and IL-13 via IL-4/IL-13 receptor s(IL4-Rα), i.e., dupilumab [8], abrogating their inflammatory signaling pathways in allergic eosinophilic asthma. Omalizumab, which blocks IgE, has also shown efficacy in the treatment of severe allergic asthma [9].
Although biological agents are revolutionizing the management of severe uncontrolled asthma, 13-31% of patients can be unresponsive [10][11][12][13]; in addition, there are currently no parameters to predict the individual response to any biologics. In this sense, there is a remarkable lack of pharmacogenetic biomarkers that allow a more precise and practical selection of patients and establish uniform treatment response criteria. Thus, further effort is needed to identify other potential molecular targets that could be used as prognostic and therapeutic biomarkers that will facilitate therapeutic strategies tailored to each patient’s requirements [14]. It also entails reducing unnecessary expenses in patients who would not obtain any benefit, which is particularly interesting, considering the high costs of biological drugs (upwards of thousands of euros per year).
The genetics of asthma appear to be quite intricate, involving multiple genes and epigenetic mechanisms, each with a small effect size [2]. Therefore, next-generation sequencing techniques may offer an excellent approach to shed light on the complex genetic networks underlying the different endotypes of the disease.

2. Effects of Therapeutic Antibodies on Gene and Protein Signatures in Asthma Patients

2.1. Omalizumab

Upchurch et al. [15] published an expression profiling study on 45 patients with uncontrolled asthma under omalizumab treatment compared to 17 healthy controls (HC). They reported 34 patients as responders to omalizumab and 11 as non-responders and took samples at baseline and 6, 14, and 26 weeks of treatment. All data are publicly available at the GEO repository (GSE134544).
When analyzing the data, the authors found that both responder and non-responder expression profiles were similar to HC during the first six weeks of treatment. Eight gene clusters were identified, including genes related to protein synthesis (cluster 1), T cell/NK cell/cytotoxicity (cluster 2), hematopoiesis (cluster 3), cell cycle control and proliferation (cluster 4), T cell regulation and activation (cluster 5), monocytes (cluster 6), glucose metabolism (cluster 7), and inflammation (cluster 8). Significant changes between responders and non-responders were found in clusters 2, 3, 7, and 8 at baseline; in clusters 2, 3, and 7 at 6 weeks; in clusters 3 and 7 at 14 weeks; and in cluster 8 at the final time point of 26 weeks. After modular analysis, the largest number of variations between asthmatic patients and HC occurred before treatment, and this difference slowly decreased upon omalizumab therapy in responders while non-responders showed a higher number of differentially expressed modules when compared with HC at week 26. Regarding pathway analysis, the 293 transcripts overexpressed in responders were related to Th2 and Th1 responses. The 496 transcripts under expressed in non-responders were connected to the suppression of inflammation, and other connections were associated with the promotion of allergic inflammation. In summary, responders showed increased immune cell motility while non-responders showed increased cytokine signaling and inflammation networks.

2.2. Mepolizumab

Buchheit et al. [16] investigated how mepolizumab treatment improved respiratory inflammation in AERD patients. A group of 18 AERD patients receiving standard of care was compared with 18 received mepolizumab for at least three months. Different blood cell populations were analyzed by flow cytometry, and nasal epithelium mRNA expression was also investigated. Regarding gene expression, 242 genes were differentially regulated in subjects treated with mepolizumab. The 94 upregulated genes included TJP3, ACTN4, and AMOT, which are involved in tight junctions. Among the 148 downregulated genes, authors highlighted CLDN17, which is also related to tight junctions. CRTH2 surface expression was higher on blood cells of treated patients than on those from non-treated subjects, although eosinophils and basophils count decreased in the mepolizumab group.

2.3. Benralizumab

Sridhar et al. [17] investigated the effects of benralizumab subcutaneous 100 mg every eight weeks on blood inflammatory markers through proteomic and gene expression analyses during two Phase II studies of patients with eosinophilic asthma. Results demonstrated that only two protein analytes, eotaxin-1 and eotaxin-2, were significantly upregulated following treatment with benralizumab in both asthma and chronic obstructive pulmonary disease (COPD), with higher levels in eosinophil-high patients than in eosinophil-low patients in both studies. Benralizumab was also associated with a significant reduction in the expression of genes related to eosinophils and basophils, such as CLC, IL5RA, and PFSS33; immune signaling complex genes (FCER1A); G-protein-coupled receptor genes (HRH4, ADORA3, P2RY14); and other immune-related genes (ALOX15 and OLIG2).

Severe asthma patients can show a steroid-resistant asthma phenotype. Benralizumab reduces the oral corticosteroid dosage while maintaining control in severe asthmatics with peripheral eosinophilia [18]. To elucidate whether benralizumab modified corticosteroid sensitivity by suppressing type-2 inflammation, Hirai et al. [19] analyzed the gene expression changes on T cells from patients with severe asthma treated with benralizumab. The study demonstrated that treatment with benralizumab in patients with severe corticodependent asthma could restore the expression levels of key molecules involved in steroid response through the PI3K pathway inactivation.

2.4. Mepolizumab and Benralizumab

A couple of studies by the same authors compared patients treated with mepolizumab and patients treated with benralizumab [20][21]. Both studies compared serum proteomic profiles from patients with severe eosinophilic asthma at baseline and after one month of treatment.
In the first study [20], ten patients were treated with mepolizumab and eight with benralizumab. Four HCs were also included. The authors reported 38 differences among patient proteomic profiles. Two spots were exclusively found at baseline, while ten spots only appeared after one month of benralizumab treatment and five spots were only detected after one month of mepolizumab treatment. Benralizumab-treated patients showed increased plasmin, alpha-1-antitrypsin, plasminogen, alpha-2-macroglobulin, and ceruloplasmin levels, while mepolizumab patients showed increases in albumin, fibrinogen gamma, and factor B levels, among others. The most significant change related to benralizumab treatment was the increase of full-length ceruloplasmin, which was associated with lower serum oxidation levels in those patients.

2.5. Other Biologicals

Rial et al. studied serum miRNAs after anti-IL-5 biological treatment of severe asthma as possible response-biomarkers [22]. After eight weeks, sera of ten severe asthmatic patients treated with reslizumab and six patients treated with mepolizumab were analyzed. miR-338-3p, which is involved in essential pathways in asthma, such as MAPK and TFGβ signaling pathways, was dysregulated after treatment independently of the biological treatment. Authors concluded that miR-338-3p could be used as a biomarker of early response to reslizumab and mepolizumab in severe eosinophilic asthmatics and could be involved in airway remodeling and targeting genes related to MAPK and TGFB.
Badi et al. [23] proposed a different but interesting approach in their study. Taking advantage of a previously reported genetic signature of atopic dermatitis (AD) in patients who responded to anti-IL-22 (fezakinumab, FZ), they searched for such transcriptomic signatures in adults with severe asthma to determine whether they could be successfully treated with this biological. AD patients were classified as per their clinical response to FZ after 12 weeks of treatment, identifying those genes that changed significantly upon FZ treatment (FZ-DOWN). The FZ-DOWN signature included inflammation, Th2 response, and Th17/Th22 activation genes. Interestingly, the FZ-DOWN signature was also significantly enriched in the blood of severe asthmatics, mainly those with neutrophilic (adj.p = 0.0002) and mixed granulocytic asthma (adj.p = 0.0098) when compared with HC. Thus, the enrichment score of the FZ-DOWN signature in sputum of severe asthma patients was used for categorizing them into predicted-responders and predicted-non-responders to FZ. This approach could suggest that FZ might benefit T2-low severe neutrophilic asthmatics.

3. Summary

The first therapeutic antibody approved by FDA and EMA for persistent allergic asthma was the anti-IgE omalizumab (2003 and 2005, respectively). Anti-IL-5 monoclonal antibodies -mepolizumab and reslizumab- were approved by EMA for severe asthma with peripheral eosinophilia in 2015 and 2016, respectively. Dupilumab, an anti-IL4Rα, was approved in Europe in 2017 for atopic dermatitis and in 2019 for T2 asthma, while the anti-IL-5Rα benralizumab was approved for eosinophilic asthma in 2018 [24]. Therefore, their use for severe uncontrolled asthma is now usual, and many studies have been published regarding efficacy, safety, asthma control, and economic impact of all five biologicals in clinical settings [24][25][26].

Despite being widely used, few molecular studies have been conducted up to date in this field, and most of them refer to the expression of a specific gene or protein either in blood or airway tissues. Being the therapeutic antibodies directed against crucial molecules, such as IL-4, IL-5, or IgE, it is expected that a plethora of genes and proteins rather than a single one would be affected by the therapeutic antibody. Thus, a gene/protein signature, including both up and downregulated species, would constitute a more accurate measurement of response to treatment.

Current treatment guidelines for patients with severe, uncontrolled asthma with eosinophilia recommend anti-IL-5 therapy [1]. The mechanism of response to these anti-IL-5 antibodies, i.e., mepolizumab and reslizumab, has been mainly attributed to inhibition of IL-5 response on eosinophils. However, a recent study using dexpramipexole, which completely depletes all eosinophils, failed to show any significant improvement of symptoms [27], suggesting that eosinophils are not the only effector cells, and other cell types may also be involved. Also, targeting the IL-5 may not completely deplete eosinophils, leading to a poor response to therapy. Conversely, anti-IL-5Rα (benralizumab) rapidly depleted eosinophils and significantly reduced the rate of exacerbations for patients with uncontrolled eosinophilic asthma [28].

While mepolizumab and reslizumab target the same molecule and are likely to behave similarly, evaluation of anti-IL-5 (mepolizumab) and anti-IL-5Rα (benralizumab) in parallel may raise significant differences in gene expression. A couple of studies conducted by the same group compared serum proteomics of a severe asthmatic treated with mepolizumab or benralizumab and healthy controls [20][21]. When comparing the baseline with one month of treatment, an increase in ceruloplasmin was seen in the benralizumab-treated group but not in the mepolizumab-treated patients. Ceruloplasmin is a ferroxidase enzyme that forms free radicals [29], contributing to the antioxidant effect of treatment. The authors confirmed this result in a later article, and proposed ceruloplasmin as a potential biomarker for monitoring benralizumab treatment.

Besides ceruloplasmin, other potential biomarkers of response to benralizumab have been proposed. Thus, Nakajima et al. [30] identified four transcriptional clusters in blood from severe asthmatics, cluster 2 being the one that agglutinated most of the super-responders. These patients had the highest numbers of eosinophils, higher numbers of basophils, and higher expressions of genes related to eosinophil activities. Conversely, cluster 1 included poor responders to benralizumab. It was characterized by the upregulation of genes related to neutrophils, such as OLFM4, which is produced by neutrophils and has been associated with asthma inflammation [31], and CTSG, the neutrophil protease cathepsin G, which has been involved in neutrophilic asthma [32]. In this sense, it has been described that increased sputum neutrophils can be associated with exacerbations in patients treated with benralizumab [33]. Sridhar et al. also reported a significant reduction in the eosinophil signature upon benralizumab treatment, mainly in genes, such as CLC, OLIG2, and FCER1A [17]. CLCs are known as a classical hallmark of eosinophilic inflammation [34], OLIG2 is expressed in eosinophils and associated with the control of SIGLEC 8 expression [35], and FcεR1A (FCER1A) is the high affinity receptor for IgE and expressed on eosinophils and basophils [36].

Benralizumab treatment seemed to alter the expression level of genes and miRNAs related to the PI3K/Akt signaling pathway [19], which is known to have a regulatory role in allergic asthma [37]. Also, the inactivation of this pathway could modify the response to steroids, supporting the reduction of oral corticosteroid dosage observed in benralizumab-treated patients [25]. Other miRNAs have been proposed as biomarkers of response to treatment, i.e., miR-1246, miR-5100, and miR-338-3p [38], opening a new window of monitoring of the patient evolution.

Taking advantage of the use of anti-IL-22 (fezakinumab) in atopic dermatitis patients, Badi et al. built an FZ-response gene expression signature and evaluated whether it could be identified in severe asthmatic patients [23]. IL-22 is involved in atopic dermatitis and may be relevant in the atopic march [39]. Interestingly, they found that the FZ-response signature was enriched in neutrophilic (low T2) asthma patients, and therefore, they could benefit from fezakinumab treatment. It is worth noting that to date, there is no approved biologic for T2-low asthma [25], so this approach may open a new opportunity for these patients.

Although limited, data about changes on genomic and proteomic upon biological treatments for asthma published to date are very promising and may set the path for the use of biomarkers in response to these therapeutic antibodies. New trials that go deeper into the subject are mandatory to contrast and validate the current information, and some clinical trials aiming at studying the effects of benralizumab, omalizumab, and mepolizumab on transcriptome and proteome of patients are currently ongoing. Studies focused on the molecular aspects will be conducted and published in the coming years, as more and more patients benefit from this type of treatment. Multicenter, multiethnic, multiage trials including such a perspective would provide comprehensive information about the effects of biological therapies in a diverse population, allowing for a more accurate clustering of patients according to their molecular background. Strict inclusion criteria, exhaustive clinical characterization of patients, and best procedural and analytical practices will permit comparison between treatments, which stands out as a requirement for the efficient and cost-effective management of severe asthma.

Table 1. Summary of potential biomarkers of response to treatment. All molecules/pathways are upregulated upon treatment unless otherwise indicated (↓)

Treatment

Genes/miRNAs

Proteins

Pathways

Omalizumab

CD3E

 

Th2 response (CSF3, IL4, IL5, IL18 and SPI1)

 

CD79

 

Th1 response (STAT1, STAT4, IL2 and SMARCR4)

 

 

 

↓ Suppression of inflammation (TWIST1, FOXO1, FOXO3, TP53, CTNNB1, and SIM 1)

Benralizumab

↓miR-21-5p

plasmin

PI3K-associated genes (HDAC2, NFE2L2, GLCCI1, and PTEN)

 

↓miR-1246

α-1antitrypsin

 

 

↓miR-5100

plasminogen

α-2 macroglobulin

 

 

↓miR-338-3p

ceruloplasmin

 

 

 

eotaxin-1

 

 

 

eotaxin-2

 

Mepolizumab

↓miR-195-5p

 

Tight junction function (TJP3, ACTN4, and AMOT)

 

↓miR-27b-3p

 

 

 

miR-1260a

 

 

 

miR-193a-5p

 

 

 

miR-338-3p

 

 

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