International Journal of Molecular Sciences Article Association between Changes in the Patterns of Antinuclear Autoantibodies during Immune Checkpoint Inhibition Therapy and the Development of Severe Immune Related Adverse Events Leticia Alserawan 1 , Geòrgia Anguera 2 , Carlos Zamora Atenza 1 , Jorgina Serra López 2 , Laura Martínez-Martínez 3 , Mariona Riudavets Melià 2 , Ivana Sullivan 2 , Andrés Barba Joaquin 2 , Margarita Majem Tarruella 2 and Silvia Vidal 1, * 1 Immunology-Inflammatory Diseases, Biomedical Research Institut Sant Pau, IIB Sant Pau, 08026 Barcelona, Spain 2 Department of Medical Oncology, Hospital de la Santa Creu i Sant Pau, 08026 Barcelona, Spain 3 Department of Immunology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau (IIB Sant Pau), 08026 Barcelona, Spain * Correspondence: svidal@santpau.cat Abstract: Immune-related adverse events (irAEs) are unpredictable autoimmune-like toxicities induced by immune checkpoint inhibitors (ICI). irAEs are a consequence of a breakdown in self- tolerance. ICIs can induce autoantibody formation, and the presence of antinuclear autoantibodies Citation: Alserawan, L.; Anguera, G.; (ANAs) has been reported in patients who developed irAEs. Our goal was to compare ANA patterns Zamora Atenza, C.; Serra López, J.; by indirect immunofluorescence at different timepoints before (baseline) and after the initiation Martínez-Martínez, L.; Riudavets of ICI treatment and to analyze the role of ANA pattern changes as predictors of irAEs. This is Melià, M.; Sullivan, I.; Barba Joaquin, A.; Majem Tarruella, M.; Vidal, S. a 2-year-follow-up prospective study of 152 consecutive patients with solid tumors treated with Association between Changes in the anti-PD-(L)1 blockade agents. They were included from September 2018 until March 2020 in the Patterns of Antinuclear Hospital de la Santa Creu I Sant Pau (Barcelona, Spain). We grouped patients into three groups: Autoantibodies during Immune ANA de novo (patients who showed new ANA patterns at any time after ICI initiation), ANA (ANA Checkpoint Inhibition Therapy and positive at baseline without changes in the ANA patterns after initiation of treatment) and non-ANA the Development of Severe Immune (ANA negative at baseline and after ICI initiation). We did not find any association between the Related Adverse Events. Int. J. Mol. appearance of ANAs and irAE rates or the number and types of irAEs. However, patients in the ANA Sci. 2022, 23, 12641. https://doi.org/ de novo group showed higher severe irAE rates (grade ≥ 3) than the other groups. Additionally, in 10.3390/ijms232012641 most of the patients with severe irAEs (83.3%), changes in ANA patterns preceded irAE onset. In Academic Editor: Federico Cappuzzo conclusion, we found ANA induction during ICI therapies in 22 patients and our results suggest that the appearance of ANAs may predict the severity of the irAE. Received: 29 September 2022 Accepted: 18 October 2022 Keywords: immune-related adverse events (irAEs); anti-PD-(L)1 blocking agents; antinuclear Published: 20 October 2022 autoantibodies (ANA); predictive biomarkers; immune checkpoint inhibitors Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Background Immune checkpoints, such as PD-1 (Programmed cell death 1 receptor) and CTLA-4 (Cytotoxic T lymphocyte antigen 4), are the main regulatory molecules of the immune Copyright: © 2022 by the authors. system that maintain immune homeostasis and self-tolerance. PD-1 is a T cell surface Licensee MDPI, Basel, Switzerland. receptor that recognizes and binds to the endogenous ligands PD-L1 and PD-L2 on antigen- This article is an open access article presenting cells (APCs) and on tumor cells. Its recognition by ligands attenuates T lym- distributed under the terms and phocyte effector function, including proliferation and cytokine production. Similarly, conditions of the Creative Commons CTLA-4 is a co-inhibitory molecule that blocks T-cell activation by direct competition with Attribution (CC BY) license (https:// CD80/CD86 on APCs. Blocking these receptors restores T effector functions and enhances creativecommons.org/licenses/by/ endogenous anti-tumor immunity [1,2]. 4.0/). Int. J. Mol. Sci. 2022, 23, 12641. https://doi.org/10.3390/ijms232012641 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2022, 23, 12641 2 of 13 Immune checkpoint inhibitors (ICI) improve the survival of patients with solid tumors, such as melanoma and lung cancer [3–6]. Despite their efficacy, these treatments can induce novel toxicities in the form of autoinflammation or autoimmunity, which are commonly named immune-related adverse events (irAEs) [2,7]. irAEs are diverse and unpredictable, potentially affecting almost every organ system at any moment. They can occur in up to 80% of patients treated with ICI [8,9]. While some patients may experience a single irAE, others may develop several autoimmune toxicities, either simultaneously or separated temporally [8]. Up to 25% of irAEs can be severe and may require immunosuppressors or treatment disruption [9,10]. The identification of patients at risk of developing irAEs, especially the most severe forms, is crucial for prompt management in order to prevent complications or prevent treatment suspension. For this reason and due to their unpre- dictability, there is an urgent need to find appropriate meaningful biomarkers predictive of irAEs. Emerging studies indicate that irAEs are a consequence of a breakdown in self- tolerance mediated at least in part by antigen-specific T-cell responses, B cells, autoan- tibodies and cytokines [7,8,10]. This breakdown in central and/or peripheral tolerance might result in the maturation of autoreactive T-cells and B-cells and their subsequent differentiation into antibody-secreting plasma cells [11]. An increase in the levels of plasma cells and autoantibodies during ICI treatment has been reported [12,13]. Autoantibodies are involved in the pathogenesis and inflammation of some traditional autoimmune diseases [14]. The presence of autoantibodies does not necessarily imply the development of an autoimmune disease but could be considered a biological marker for autoimmune predisposition [15,16]. There is a similarity between autoimmunity and irAEs in terms of their clinical and biological phenotypes, and this is consistent with the risk of flares of pre-existent autoimmunity in patients who receive ICI agents [17–20]. Therefore, as in several autoimmune disorders, autoantibody screening could be useful in the prediction, diagnosis and/or prognosis of irAEs. Antinuclear antibodies (ANAs) comprise a spectrum of autoantibodies directed against the nuclear and cytoplasmic components of normal human cells. ANAs are laboratory markers that support the diagnosis of autoimmune-mediated diseases such as systemic lupus erythematosus, systemic sclerosis, Sjögren disease and autoimmune myositis [21,22]. They are not specific markers since positive ANA tests have also been obtained for chronic infectious diseases, cancer and after medications [23]. Additionally, ANAs can also be present in healthy individuals, though usually at low titers (less than 5% of the healthy population at serum dilution 1:160) [24]. Nevertheless, ANAs are valuable diagnostic criteria when accompanied by other clinical manifestations. The presence of ANAs in patients who receive ICI therapies and develop irAEs has been reported. Most published studies have focused on analyzing the predictor role of pre-existing ANAs prior to ICI therapy and their association with the risk of irAEs [25–27]. Seroconversion to ANA positive after ICI initiation has been also reported [28,29]. However, the association between ANA positivity and irAEs is still controversial. Our purpose was to compare ANA patterns at different time points during ICI treatment in patients diagnosed with advanced solid tumors and to associate the changes in patterns with irAE features. First, we analyzed the differences in ANAs between pre- and serial post-treatment, and then we studied the association between ANA changes and the development and rates, type, number and severity of the irAEs. 2. Results 2.1. Patients’ Characteristics Ninety-five (70.9%) patients were male and 39 (29.1%) were female. The mean age was 67.7 (±1.01) years. The most frequent tumor type was non-small cell lung cancer (NSCLC) in 91 (67.9%) patients, followed by 20 (14.9%) cases of melanoma, 10 (7.5%) of renal cancer, nine (6.7%) of head and neck cancer, and four (2.9%) of bladder cancer. In regard to the stage, 82 cases of NSCLC (90.1%), 16 of melanoma (80%), 9 of renal cancer (90%) and 100% Int. J. Mol. Sci. 2022, 23, 12641 3 of 13 of head and neck and bladder cancer cases were metastatic (stage IV). Nine cases of NSCLC (10.1%) and 1 of renal cancer (10%) were stage III locally advanced and 4 cases of melanoma (20%) were stage III resected. None of the patients included in the study had a previous history of autoimmune disease. Sixty-four (47.7%) patients received anti-PD-(L)1 blockade agents as a first-line treat- ment and 57 (42.5%) as a second-line treatment or beyond. Five (3.7%) patients received ICI as an adjuvant therapy and eight (5.9%) patients received it as manteinance therapy after chemoradiation. Anti-PD-(L)1 blockade agents were administered as monotherapy in 104 patients (77.6%), in combination with another immunotherapy agent in 19 (14.2%) patients and with chemotherapy in 11 (8.2%) patients. Based on ANA presence, patients were divided into three study groups: the first group (ANA de novo) included patients with or without ANA in baseline samples who developed new ANA patterns after ICI initiation (n = 22); the second group (ANA) included patients with ANA in all serial samples without changes in patterns (n = 37); and the third group (non-ANA) included patients without ANA in all serial samples (n = 75). The baseline characteristics of patients segregated into groups are detailed in Table 1. There were no significant differences in sex, age, tumor type and treatment between the three groups, except for atezolizumab. A higher frequency of ANA de novo patients was found in the subgroup of patients with a high expression of PD-L1. Table 1. Patient characteristics and ICI treatment comparison in patients grouped according to the presence of ANA during therapy. ANA De Novo ANA Non-ANA p (n = 22) (n = 37) (n = 75) Sex male, n (%) 17 (77.3) 22 (59.4) 56 (74.7) 0.19 Age, median (IQR) 65 (60–76) 71 (63–74.5) 67 (58–77) 0.62 Tumor type, n (%) NSCLC 17 (77.3) 27 (72.9) 47 (62.7) 0.32 Melanoma 2 (9.1) 4 (10.8) 14 (18.7) 0.38 Renal 1 (4.5) 4 (10.8) 5 (6.7) 0.62 Head and Neck 2 (9.1) 0 (0) 7 (9.3) 0.15 Urothelial 0 (0) 2 (5.4) 2 (2.7) 0.48 ICI schedule, n (%) Anti PD-(L)1 in monotheraphy 17 (77.3) 29 (78.4) 58 (77.3) 0.99 Nivolumab 4 (18.2) 4 (10.8) 17 (22.7) 0.31 Pembrolizumab 9 (40.9) 10 (27) 18 (24) 0.29 Atezolizumab 1 (4.5) 11 (29.7) 12 (16) 0.04 Durvalumab 3 (13.6) 4 (10.8) 6 (8) 0.70 Avelumab 0 (0) 0 (0) 1 (1.3) 0.67 Retifanlimab 0 (0) 0 (0) 4 (5.3) 0.19 Anti PD-(L)1 in combination with immunotherapy 4 (18.2) 5 (13.5) 10 (13.3) 0.84 Anti-CTLA4 (Ipilimumab, Tremelimumab) 0 (0) 3 (8.1) 5 (6.7) 0.41 Anti-LAG3 (Eftilagimod) 3 (13.6) 1 (2.7) 4 (5.3) 0.21 Anti-NKG2A (Monalizumab) 0 (0) 1 (2.7) 1 (1.3) 0.69 Anti-CD73 (Oclelumab) 1 (4.5) 0 (0) 0 (0) 0.07 Anti PD-(L)1 in combination with chemotherapy 1 (4.5) 3 (8.1) 7 (9.3) 0.77 Line of treatment, n (%) 1st line 11 (50) 17 (45.9) 36 (48) 0.95 ≥2nd line 7 (31.8) 17 (45.9) 33 (44) 0.52 Adjuvant 1 (4.5) 1 (2.7) 3 (4) 0.92 Maintenance 3 (13.6) 2 (5.4) 3 (4) 0.24 PD-L1 expression *, n (%) Negative (0–1%) 2 (9.1) 2 (5.4) 8 (10.7) 0.65 Low (1–49%) 2 (9.1) 9 (24.3) 12 (16) 0.29 High (≥50%) 10 (45.5) 9 (24.3) 10 (13.3) 0.005 * Tumoral PD-L1 expression was available only in 64 patients. Eighty-one patients (60.4%) developed irAEs: the median number of iR (IQR 1-2.5). 39 (29.1%) patients developed 1 irAE and 42 (31.3%) patients de or more irAEs. The maximum number of irAEs developed per patient was s Int. J. Mol. Sci. 2022, 23, 12641 4 of 13 of 154 irAEs developed in 81 patients. Mild irAEs (grades ≤ 2) were more f severe irAEs (grades ≥ 3): according to CTCAE, 85 (55.2%) irAEs were grade 2.2. IrAE Characteristics were grade 2; 15 (9.7%) were grade 3 and 7 (4.5%) were grade 4. No grade Eighty-one patients (60.4%) developed irAEs: the median number of iRAEs was two developed. (IQR 1–2.5). 39 (29.1%) patients developed 1 irAE and 42 (31.3%) patients developed two or more irAEs. The maximum number of irAEs developed per patient was seven. A With regard to the type of irAE, dermatological toxicities includi total of 154 irAEs developed in 81 patients. Mild irAEs (grades ≤ 2) were more frequent pruritus were the most than severe frequent irAEs (grades manifestations ≥ 3): according and irAEs to CTCAE, 85 (55.2%) were wereobserved grade 1; 47 in 5 (30.5%) were grade 2; 15 (9.7%) were grade 3 and 7 (4.5%) were grade 4. No grade 5 irAEs patients, followed by endocrine manifestations in 21 (15.7%) patients, he were developed. (8.9%) patientsWith andregard colitis to thein 10of(7.5%) type patients.toxicities including rash and pruritus irAE, dermatological were the most frequent manifestations and were observed in 56 (41.8%) of patients, followed The earliest toxicity by endocrine was rash; manifestations the patients, in 21 (15.7%) median time hepatitis of(8.9%) in 12 onset was patients and28 (IQR 9- colitis contrast, thein latest 10 (7.5%)toxicities patients. developed were artralgias and colitis, which ap The earliest toxicity was rash; the median time of onset was 28 (IQR 9–50.5) days. 128 (28.5–196) and 110.5 In contrast, (61.75–187.3) the latest days. toxicities developed were The characteristics artralgias and colitis, whichof the irAEs appeared after 128 (28.5–196) and 110.5 (61.75–187.3) days. Figure 1. The most severe irAEs (grade ≥ 3) affect hepatic, respiratory The characteristics of the irAEs are an shown in Figure 1. The most severe irAEs (grade ≥ 3) affect hepatic, respiratory and endocrine systems. systems. Figure 1. Description of immune-related adverse events. The time of onset and severity of the irAEs Figure 1. Description occurred in allofpatients immune-related adverse in the study, according events. to the type of irAE.The Eachtime of onsetanand point represents irAE sever occurred in all (n =patients 154). Typesin the are of irAE study, ordered according to the from the highest to thetype lowestof irAE. Each frequency. point Endocrine irAEsrepres included hypothyroidism (n = 12), hyperthyroidism (n = 4, hypophysitis (n = 4), and diabetes mellitus = 154). Types(n of irAE are ordered from the highest to the lowest frequency. Endo = 1). Other irAEs include grade ≥ 3 myocarditis (n = 1) and thrombocytopenia (n = 1), grade 2 cluded hypothyroidism (n =psoriasis vasculitis (n = 1) and 12), hyperthyroidism (n = 1), and grade 1 myalgia(n(n== 4, hypophysitis 1) and vitiligo (n = 1). (n = 4), and di (n = 1). Other2.3.irAEs include ANA Pattern grade Appearance ≥ 3ICI during myocarditis Therapy (n = 1) and thrombocytopenia ( vasculitis (n = 1) Forty-five and psoriasis (n = 1),had (33.6%) patients andANAgrade 1 myalgia at baseline samples, (n and=591) andpatients (44%) vitiligo had(n = 1) ANA after ICI initiation. The comparison of IIF patterns between samples collected at baseline and after ICI initiation revealed that 22 (16.4%) patients (14 patients who were 2.3. ANA Pattern Appearance ANA negative during and eight patients ICI who Therapy were ANA positive in baseline samples) developed ANAs de novo after ICI initiation. Representative IIF images are shown in Figure 2. Forty-five (33.6%) patients had ANA at baseline samples, and 59 (44%) ANA after ICI initiation. The comparison of IIF patterns between sample baseline and after ICI initiation revealed that 22 (16.4%) patients (14 patients who were ANA negative and eight patients who were ANA positive in baseline samples) developed Int. J. Mol. Sci. 2022, 23, 12641 ANAs de novo after ICI initiation. Representative IIF images are shown 5 of in 13 Figure 2. Figure 2. Indirect immunofluorescence images that show differences in ANA patterns in pre- and Figure 2. Indirect immunofluorescence post-treatment serum samplesimages that of patients show who differences developed in ANA ANA during patternsRepresentative ICI treatment. in pre- and post-treatment serum samples of patients who developed ANA during ICI treatment. Representa- IIF images of pre-treatment and post-treatment serum samples from patients who developed ANA tive IIF images of pre-treatment patterns de novo afterandICBpost-treatment serum initiation (A) without samplesANA pre-existing from patients and (B) with who developed pre-existing ANA. ANA patterns de novo Days afterafter passed ICBICI initiation initiation (A) without pre-existing in post-treatment samples areANA and in indicated (B) with each pre-existing image. Negative ANA. Days passed after ICI pre-treatment initiation samples are not in post-treatment samples are indicated in each image. represented. Negative pre-treatment samples are not represented. The individual characteristics of patients from the ANA de novo group are detailed in Table 2. The most frequent ANA de novo pattern was the nuclear speckled pattern in The individual characteristics 10 patients, followed by theof cytoplasmic patients from theinANA fibrillar de novo five patients. group Other are detailed less frequent ANA in Table 2. Thepatterns most frequent ANA (three were: nucleolar de novo pattern patients), was thespeckled cytoplasmic nuclearpattern speckled(threepattern in patients), intercellular bridge pattern (two patients), rods & rings (one patient), 10 patients, followed by the cytoplasmic fibrillar in five patients. Other less frequent NuMa-like pattern ANA patterns(one patient), spindle fibers (one patient) and cytoplasmic dots (one patient). ANA de novo were: nucleolar (three patients), cytoplasmic speckled pattern (three appeared at different times after ICI initiation; the median time of appearance was 51 (IQR patients), intercellular bridge 40.5–111.5) days. pattern As the (two63.6% table shows, patients), rods in&thisrings of the patients (one patient), group developed irAEs, NuMa-like pattern (one patient), with pruritus as the mostspindle frequentfibers (one irAE (six patient) patients), and cytoplasmic followed by hepatitis (fivedots (one patients). patient). ANA The de novo appeared ANA patterns at different developed were nottimes after specific ICI types. to irAE initiation; the median No common clinical time of features (solid tumor type, ICI agent, type, severity or number of irAE manifestations) appearance was 51 (IQR 40.5–111.5) days. As the table shows, 63.6% of the patients in this were found among patients who developed the same ANA pattern, nor in patients who developed group developed irAEs, with pruritus as the most frequent irAE (six patients), followed ANA de novo. by hepatitis (five patients). The ANA patterns developed were not specific to irAE types. No common clinical features (solid tumor type, ICI agent, type, severity or number of irAE manifestations) were found among patients who developed the same ANA pattern, nor in patients who developed ANA de novo. Int. J. Mol. Sci. 2022, 23, 12641 6 of 13 Table 2. Clinical features and ANA patterns in pre- and post-treatment samples of patients who developed ANA de novo during ICI treatment. Pre-Treatment Post-Treatment ANA irAEs Line of Grade of Patient Sex Age Tumor Treatment ANA Patterns a ANA Patterns a Development irAEs Onset b Treatment Severity b (Titer) (Titer) (Days) (Days) Pembrolizumab Rash, pruritus, 1 M 60 NSCLC Adjuvant Negative Cytoplasmic speckled (1:320) 6 1, 1, 2 230, 230, 6 + Chemotherapy hepatotoxicity Nuclear speckled (1:160), 2 M 83 NSCLC Pembrolizumab 1st Negative 41 Hepatotoxicity 3 41 Cytoplasmic fibrillar (1:160) Nuclear speckled (1:320), 3 M 58 NSCLC Pembrolizumab 1st Negative Cytoplasmic fibrillar (1:160), 39 Hypertiroidism 1 60 Intercellular Bridge (1:160) Diabetes 4 F 63 Melanoma Pembrolizumab 1st Negative Nuclear speckled (1:320) 41 1 41 Mellitus Hypophisitis, 5 M 67 NSCLC Pembrolizumab 2nd Negative Nuclear speckled (1:640) 18 3, 2 259, 207 arthitis Cytoplasmic fibrillar (1:640), 6 F 66 NSCLC Durvalumab Maintenance Negative 113 No _ _ NuMa-like (1:640) Pembrolizumab 7 F 73 NSCLC 1st Negative Cytoplasmic dots (1:160) 41 No _ _ + Eftilagimod Nuclear speckled (1:160), Pruritus, 8 M 61 NSCLC Durvalumab Maintenance Negative 35 1,1 91, 11 Spindle fibers (1:160) mucositis Neck and 9 M 62 Head Nivolumab 3rd Negative Nuclear speckled (1:160) 53 No _ _ Carcinoma 10 M 64 NSCLC Pembrolizumab 1st Negative Nuclear speckled (1:160) 70 No _ _ Durvalumab + 11 M 76 NSCLC Maintenance Negative Cytoplasmic fibrillar (1:1280) 27 Pneumonitis 3 55 Oleclumab 12 M 39 NSCLC Durvalumab 2nd Negative Cytoplasmic fibrillar (1:1280) 53 Pruritus 1 9 13 F 64 NSCLC Atezolizumab 3rd Negative Nuclear speckled (1:160) 41 Colitis 3 108 14 M 76 Renal Cancer Nivolumab 2nd Negative Cytoplasmic speckled (1:160) 111 No _ _ Cytoplasmic Cytoplasmic speckled (1:160), Pneumonitis, 15 M 76 NSCLC Pembrolizumab 2nd 49 4,4 196, 196 speckled (1:320) Rods & Rings (1:1280) hepatotoxicity Nuclear speckled Nuclear speckled (1:160), 16 M 60 NSCLC Pembrolizumab 1st 126 No _ _ (1:160) Nucleolar (1:160) Nuclear speckled Nuclear speckled (1:320), Pruritus, hy- 17 F 84 Melanoma Nivolumab 1st 68 1,2 40, 83 (1:160) Cytoplasmic speckled (1:320) pothiroidism Nuclear speckled Nuclear speckled (1:160), 18 M 78 NSCLC Pembrolizumab 1st 121 No _ _ (1:160) Nucleolar (1:160) Cytoplasmic Cytoplasmic reticular (1:160), 19 M 60 NSCLC Nivolumab 1st 118 Hepatotoxicity 3 167 reticular (1:640) Nuclear speckled (1:320) Int. J. Mol. Sci. 2022, 23, 12641 7 of 13 Table 2. Cont. Pre-Treatment Post-Treatment ANA irAEs Line of Grade of Patient Sex Age Tumor Treatment ANA Patterns a ANA Patterns a Development irAEs Onset b Treatment Severity b (Titer) (Titer) (Days) (Days) Neck and PCNA-like (1:640), PCNA-like (1:640), 20 M 59 Head Pembrolizumab 2nd Nucleolar (1:640), 167 No _ _ Nucleolar (1:640) Carcinoma Intercellular bridge (1:320) Pembrolizumab Nuclear coarse Nuclear fine dense Rash, pruritus, 21 M 73 NSCLC 1st 43 2, 1, 1 7, 7, 203 + Eftilagimod speckled (1:640) speckled (1:320) colitis Nuclear speckled Nuclear speckled (1:320), Pembrolizumab Rash, pruritus, 22 M 67 NSCLC 1st (1:320), Centromeric Centromeric CENP-F-like 105 2, 2, 2 33, 105, 11 + Eftilagimod psoriasis CENP-F-like (1:160) (1:160), Nucleolar (1:320) a. Nomenclature of ANA patterns according to a competent level of ICAP includes: Nuclear speckled (AC-4,5); Nucleolar (AC-8, 9, 10); CENP-F-like (AC-14); Cytoplasmic fibrillar (AC-15, 16, 17); Cytoplasmic speckled (AC-19, 20); Rods&Rings (AC-23); Spindle fibers (AC-25); NuMa-like (AC-26); Intercellular bridge (AC-27). b. Data of grade and day of onset are in the same order as their related irAE type. 2.4. Association between ANA Development and IrAEs Int. J. Mol. Sci. 2022, 23, 12641 8 of 13 Preexisting ANA at baseline was not associated with irAE development. There were 53 patients without preexisting ANA who developed irAEs and 17 patients with 2.4. ANA preexisting Association whobetween did notANA Development develop irAEsand IrAEsthe follow-up period (p = 0.85). during Considering Preexisting ANA only patients at baseline who was not developed associated irAEs, with irAE 28 (34.5%) development. patients presented There were with ANA at 53 patientsand baseline without preexisting 37 (45.6%) ANA who had ANA developed at any irAEsThere time point. and 17was patients with preexisting no difference in ANA whobetween irAE prevalence did not develop irAEsof the groups during the follow-up patients: ANA deperiod novo,(pANA = 0.85). andConsidering non-ANAonly groups (rates 63.6%, 62.2% and 58.7% respectively). Among the groups, there were and patients who developed irAEs, 28 (34.5%) patients presented with ANA at baseline no 37 (45.6%) had ANA at any time point. There was no difference in irAE prevalence between differences in either the number of irAEs developed or the time of appearance and the the groups of patients: ANA de novo, ANA and non-ANA groups (rates 63.6%, 62.2% and type of irAE (Supplementary Figure S1). However, the ANA de novo group showed 58.7% respectively). Among the groups, there were no differences in either the number of higher rates of severe irAE than the other two groups (p = 0.05) (Figure 3a). irAEs developed or the time of appearance and the type of irAE (Supplementary Figure S1). However, the ANA de novo group showed higher rates of severe irAE than the other two groups (p = 0.05) (Figure 3A). Figure 3. Comparison of irAE onset and severity between groups. (A) Association of severity of irAEs and ANA development. (B) Staircase graphs show the percentage of patients without grade ≥3 irAE Figure 3. Comparison of irAE onset and severity between groups. (A) Association of severity of over time in patients grouped according to ANA presence during ICI treatment. (C) Relationship irAEs and ANA development. (B) Staircase graphs show the percentage of patients without grade between the moment of appearance of new ANAs during ICB treatment and the moment of irAE ≥3 irAE over time in patients grouped according to ANA presence during ICI treatment. (C) onset. Each bar represents one patient. Log-rang Mantel–Cox test was used for analysis of patient Relationship between the moment of appearance of new ANAs during ICB treatment and the groups during the 365 days of follow-up. moment of irAE onset. Each bar represents one patient. Log-rang Mantel–Cox test was used for analysis of patient groups during the 365 days of follow-up. When we compared the presence of irAEs during the 12 months of follow-up among the three groups, we found differences in the time of grade ≥3 irAEs onset (Figure 3B,C). When Wewedidcompared not observethe presenceinofthe differences irAEs timeduring of irAE the onset12between monthspatients of follow-up among with and without the threepreexisting groups, weANA,found differences in the time of grade ≥3 irAEs onset (Figures regardless of the grade of irAEs (data not shown). Additionally, 3b,c). in the We did ANAnot observe differences de novo group, in the we found thattime in theof83.3% irAEpatients onset whobetween patients suffered with grade ≥ and(five 3 irAEs without patients), preexisting ANA, the irAE regardless manifestation wasofpreceded the gradeby ANA of appearance irAEs (data not3C). (Figure shown). The other Additionally, in the 16.6% of thepatients ANA de (onenovo group, patient) we found developed ANA atthat the in thetime same 83.3% patients as irAE. who in In contrast, suffered patients grade ≥3with grade(five irAEs 1–2 irAEs (eightthe patients), patients), ANA development irAE manifestation was was produced preceded by after ANAirAE appearancemanifestation (Figure 3c). (six patients, The 75%). The other 16.6% of themean days of patients ANA (one appearance patient) 88.6 (±at36.6) were ANA developed the samedays timeprior to grade as irAE. ≥3 irAEs In contrast, inand 20.3 (± patients 13.4)grade with days after grade(eight 1–2 irAEs 1–2 irAEs. patients), ANA In addition, we compared the treatment responses development was produced after irAE manifestation (six patients, 75%). in the three groups. ANAdays The mean de novo group showed superior OS and significant superior PFS (p = 0.01). These results were also Int. J. Mol. Sci. 2022, 23, 12641 9 of 13 confirmed in the NSCLC population (the major and most homogeneous population in our cohort) (Supplementary Figure S2). 3. Discussion To the best of our knowledge, this is the first study that specifically associates ANA pattern development after ICI initiation with the clinical features of irAEs according to three study groups: ANA de novo, ANA and non-ANA. Our results showed the development of ANAs in a subset of patients after ICI initiation. Although these patients did not share common clinical characteristics and we did not find an association between the presence of ANAs and the development of irAEs in patients who received ICI, the ANA de novo group showed higher severe IRAE rates than the other two groups. In most patients with severe irAEs (83.3%), ANA development preceded irAE onset, which suggests that ANA screening could help predict the severity of the irAE. We showed that 16.6% of patients receiving ICI developed ANAs de novo, suggesting, in line with other authors, that checkpoint blockade is related to the T-cell-dependent acti- vation of autoreactive B cells and autoantibody production [30,31]. It has been postulated that cancer cells can induce an immunological response, resulting in the production of tumor-associated autoantibodies [32–34]. However, the possibility that antibody produc- tion is a spontaneous consequence of tumoral antigenicity, independent of ICI treatment, cannot be completely ruled out. We did not find differences in irAE prevalence between patients with and without pre-existing ANAs nor between patients with and without ANAs in serial samples after ICI initiation. These results are consistent with other studies [25–27,29]. Considering the clinical similarity between autoimmune diseases and irAEs, the lack of association between the presence of ANA and the risk of irAE could be explained by two main reasons. First, the presence of ANA could be considered a biological marker of autoimmune predisposition, but it does not necessarily entail the development of clinical manifestations. Second, as in certain autoimmune diseases, some irAEs may be not ANA-related but rather due to cell-mediated immune mechanisms or autoantibody-mediated mechanisms different from ANA [35]. In line with this second reason, other authors have correlated the presence of autoantibodies with higher irAE rates [36,37], though these studies considered a broader spectrum of different autoantibodies, not specifically ANAs, which may explain the different results. ANA development was not associated with higher rates of irAEs, the number of irAEs or the type of irAE. However, a trend toward its association with the severity of irAE was found. In addition, the ANA de novo group showed a higher OS and PFS. Considering that the development of irAEs is associated with immune checkpoint blockade response [38], this is not unexpected since checkpoint blockade can enhance anti-tumoral T cell response at different grades and severe irAEs could reflect stronger immunological T cell responses. In contrast with our results, another study did not find any association between autoantibody induction and a higher grade of irAEs [27]. This discordance may be due to the heterogeneity in the antibodies tested and the patient cohorts. Other authors associated seroconversion to positive ANAs, extractable nuclear autoantibodies (ENA) or anti-smooth muscle autoantibodies (ASMA) in the first 30 days after ICI initiation with better treatment outcomes and a higher risk of irAEs [28]. Similar to our results, other studies did not find a significant association between ANA development and irAE rates [27,30,39]. We showed that ANA appearance preceded irAE manifestations in 83.3% of the patients who suffered grade ≥ 3 irAEs. This finding suggests that the early appearance of ANA could be a useful predictive biomarker of severe irAEs. In concordance with our results, Das et al. showed that patients with early B-cell changes experienced higher rates of grade 3 irAEs [13]. They found a treatment-induced decline in circulating B cells and an increase in CD21low B cells and plasmablasts and these changes in B cells preceded and correlated with both the frequency and timing of irAEs. Int. J. Mol. Sci. 2022, 23, 12641 10 of 13 We are aware that our study has some limitations. Although we included a large cohort, few patients developed the same irAE subtype so as to be studied as a subgroup. It is well known that autoantibody positivity can differ depending on the organ affected. Interestingly, after ICI, autoantibody positivity is frequent in irAEs involving endocrine function, skin and muscle, but rare in irAEs affecting other organs or systems [40]. Addi- tionally, the heterogenicity in the type of tumors, ICI agents and treatment schedules may have influenced the results and conclusions should be taken with caution until the valida- tion of results in larger cohorts. Another limitation is that we do not know the antigenic target against which the autoantibodies react with the analysis of IIF patterns, even though it is a reliable method for screening ANAs. Further studies designed to identify common autoantigens would be of great interest. On the other hand, it is also important to highlight the main strengths of our study. None of the previous studies considered patients with a background of ANA positivity. This novel analysis approach to changes in ANA patterns and not only ANA positivity allowed us to also consider ANA development in patients with a background of ANA positivity, who should not be underestimated. In conclusion, our findings suggest that antinuclear autoantibody screening during immune checkpoint-blockade therapies could be useful for monitoring patients to predict severe irAEs. This screening could consequently improve the early detection and man- agement of irAEs and avoid treatment interruption. However, further studies integrating humoral and cellular autoreactivity are needed to elucidate the role of these autoantibodies in the pathogenesis of irAEs. 4. Materials and Methods 4.1. Patients One hundred and fifty-two consecutive patients diagnosed with solid tumors treated with anti-PD-(L)1 blockade agents alone or in combination with chemotherapy or other immunotherapy drugs at Hospital de la Santa Creu I Sant Pau (Barcelona, Spain) were prospectively included from September 2018 to March 2020 and monitored by the Depart- ment of Medical Oncology and the Department of Immunology. The end of the follow-up was September 2020. Patients with prior autoimmune diseases were excluded from the study. All patients included received at least one dose of ICI. We could not collect the pre-treatment (baseline) samples of 10 patients. After the first dose of ICI, eight patients discontinued ICI treatment due to progression criteria and no additional samples were collected after ICI-initiation. Thus, in line with our goal, we included samples at baseline and after ICI initiation from 134 patients. Written informed consent was obtained from each patient and ethical approval for the study was granted by the Institutional Ethics Committee (Institutional Review Board number: IIBSP-PDL-2017-82). Patients’ data were collected from electronic medical records. IrAEs were defined as adverse events with a potential immunologic basis that required close monitoring and/or potential intervention with immunosuppressive or hormone replacement. Patient symptoms, physical examination and laboratory data were assessed every 3–4 weeks. Thyroid function was evaluated at baseline and every six weeks thereafter. IrAE severity was graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 [41]. 4.2. Sample Collection Serial serum samples from each patient were collected at baseline and after initiation of ICI treatment for a maximum of six months of follow-up (at 0, 4, 10, 18 and 24 weeks after ICI initiation). Additionally, when a patient experienced a grade ≥2 irAE, an extra sample was collected. All samples were frozen and stored at −20 ◦ C until autoantibody determination. 4.3. Detection of Antinuclear Antibodies The detection of ANA was based on indirect immune-fluorescence (IIF) in agreement with international recommendations [42]. Assays were performed on a fully automated Int. J. Mol. Sci. 2022, 23, 12641 11 of 13 system (QUANTA-Lyser, Werfen, Spain). Briefly, a patient’s serum was incubated with human epithelial cell line 2 (HEp-2) as a substrate attached to a slide (Innova, Werfen, Spain) to allow the specific binding of autoantibodies to substrate antigens on the slide. After washing, anti-human antibody (IgG) conjugated to fluorescein was added as a detection reagent. Next, the slide was examined under a microscope by trained personnel for fluorescence pattern interpretation according to the international consensus on antinuclear antibody pattern ICAP [42]. Samples with ANA titers equal to or superior to 1:160 were considered positive. All serum samples from a single patient were analyzed with the same batches of reagents to avoid bias in the fluorescence pattern interpretation. 4.4. Statistical Analysis To describe our population, numbers and percentages were used for qualitative vari- ables, while means (± standard error of the mean, SEM) and medians (interquartile ranges, IQR) were calculated for quantitative variables with normal and non-normal distributions, respectively. The Kolmogorov–Smirnov test was applied to analyze the data distribution. Comparisons between groups were tested with Student’s t or the Mann–Whitney test according to normal distribution. ANOVA and Kruskal–Wallis tests were used to com- pare more than two groups. Fisher and Chi-square tests were used for the comparison of frequencies. The long-rank Mantel–Cox test was used to analyze differences in overall survival (OS), progression-free survival (PFS) and the moment of irAE onset during the follow-up period. All p values lower than 0.05 were considered statistically significant. All analyses were performed using Graph Pad Prism 7 software. Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms232012641/s1. Author Contributions: All authors were involved in revising intellectual content, and all authors approved the final version to be published. L.A. and L.M.-M. performed ANA detection; L.A., G.A. and C.Z.A. analyzed results; L.A. and C.Z.A. collected samples and G.A., J.S.L., M.R.M., I.S. and A.B.J. collect clinical data; L.A. and S.V. performed statistical analysis. L.A., M.M.T. and S.V. wrote the manuscript. M.M.T. and S.V. design the study. All authors have read and agreed to the published version of the manuscript. Funding: This research was partially supported by Bristol Myers Squibb. Institutional Review Board Statement: This study was conducted in accordance with the Helsinki Declaration and approved by the Research Ethics Board of the Hospital de la Santa Creu i Sant Pau, Barcelona (IIBSP-PDL-2017-82). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The experimental data generated during the current study are available from the corresponding author on reasonable request. Acknowledgments: Silvia Vidal was supported by Fondo de Investigaciones Sanitarias (FIS) and is a participant in the Program for the Stabilization of Investigators of the Direcció d’Estrategia i Coordinació del Departament de Salut, Generalitat de Catalunya. This work has been performed within the Immunology Program of Universitat Autònoma de Barcelona (UAB). Conflicts of Interest: The authors declare no conflict of interest. References 1. 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