Article Text

Coexisting autoantibodies against transcription factor Sp4 are associated with decreased cancer risk in patients with dermatomyositis with anti-TIF1γ autoantibodies
  1. Yuji Hosono1,
  2. Brandon Sie2,
  3. Iago Pinal-Fernandez1,3,
  4. Katherine Pak1,
  5. Christopher A Mecoli4,
  6. Maria Casal-Dominguez1,3,
  7. Blake M Warner5,
  8. Mariana J Kaplan6,
  9. Jemima Albayda4,
  10. Sonye Danoff7,
  11. Thomas E Lloyd3,
  12. Julie J Paik4,
  13. Eleni Tiniakou4,
  14. Rohit Aggarwal8,
  15. Chester V Oddis8,
  16. Siamak Moghadam-Kia8,
  17. Carmelo Carmona-Rivera6,
  18. Jose César Milisenda9,
  19. Josep Maria Grau-Junyent9,
  20. Albert Selva-O'Callaghan10,
  21. Lisa Christopher-Stine3,4,
  22. H Benjamin Larman2,
  23. Andrew Lee Mammen1,3,4
  1. 1 Muscle Disease Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, USA
  2. 2 Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
  3. 3 Department of Neurology and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
  4. 4 Department of Medicine, Division of Rheumatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
  5. 5 National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland, USA
  6. 6 Systemic Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, USA
  7. 7 Department of Medicine, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
  8. 8 Department of Medicine, Division of Rheumatology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
  9. 9 Department of Internal Medicine, Hospital Clinic de Barcelona, Barcelona, Spain
  10. 10 Internal Medicine, Vall d'Hebron University Hospital, Barcelona, Spain
  1. Correspondence to Dr Andrew Lee Mammen, Muscle Disease Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Bethesda, MD 20892, USA; andrew.mammen{at}nih.gov; Dr H Benjamin Larman, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; hlarman1{at}jhmi.edu

Abstract

Objectives In dermatomyositis (DM), autoantibodies are associated with unique clinical phenotypes. For example, anti-TIF1γ autoantibodies are associated with an increased risk of cancer. The purpose of this study was to discover novel DM autoantibodies.

Methods Phage ImmunoPrecipitation Sequencing using sera from 43 patients with DM suggested that transcription factor Sp4 is a novel autoantigen; this was confirmed by showing that patient sera immunoprecipitated full-length Sp4 protein. Sera from 371 Johns Hopkins patients with myositis (255 with DM, 28 with antisynthetase syndrome, 40 with immune-mediated necrotising myopathy, 29 with inclusion body myositis and 19 with polymyositis), 80 rheumatological disease controls (25 with Sjogren’s syndrome, 25 with systemic lupus erythematosus and 30 with rheumatoid arthritis (RA)) and 200 healthy comparators were screened for anti-SP4 autoantibodies by ELISA. A validation cohort of 46 anti-TIF1γ-positive patient sera from the University of Pittsburgh was also screened for anti-Sp4 autoantibodies.

Results Anti-Sp4 autoantibodies were present in 27 (10.5%) patients with DM and 1 (3.3%) patient with RA but not in other clinical groups. In patients with DM, 96.3% of anti-Sp4 autoantibodies were detected in those with anti-TIF1γ autoantibodies. Among 26 TIF1γ-positive patients with anti-Sp4 autoantibodies, none (0%) had cancer. In contrast, among 35 TIF1γ-positive patients without anti-Sp4 autoantibodies, 5 (14%, p=0.04) had cancer. In the validation cohort, among 15 TIF1γ-positive patients with anti-Sp4 autoantibodies, 2 (13.3%) had cancer. By comparison, among 31 TIF1γ-positive patients without anti-Sp4 autoantibodies, 21 (67.7%, p<0.001) had cancer.

Conclusions Anti-Sp4 autoantibodies appear to identify a subgroup of anti-TIF1γ-positive DM patients with lower cancer risk.

  • Dermatomyositis
  • Autoantibodies
  • Autoimmune Diseases

Data availability statement

Data are available upon reasonable request. All data relevant to the study are either included in the article or will be shared upon request.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Patients with dermatomyositis (DM) with anti-TIF1γ autoantibodies have an increased risk of cancer.

WHAT THIS STUDY ADDS

  • Anti-Sp4 autoantibodies are present in ~11% of patients with DM, ~3% of those with rheumatoid arthritis and ~3% of healthy controls.

  • Among those with DM, 96% of anti-Sp4 autoantibody-positive patients had coexisting anti-TIF1γ autoantibodies.

  • Anti-Sp4 autoantibodies were present in ~43% of patients with DM myositis with anti-TIF1γ autoantibodies.

  • In two cohorts, anti-TIF1γ-positive patients with DM with anti-Sp4 autoantibodies were significantly less likely to have cancer.

  • Anti-Sp4 autoantibodies were not detected in patients with antisynthetase syndrome, immune-mediated necrotising myopathy or inclusion body myositis.

  • Autoantibodies against Sp4 were not detected in those with systemic lupus erythematosus or Sjogren’s syndrome.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • Testing for anti-Sp4 autoantibodies may define a population of anti-TIF1γ-positive patients with DM without a substantially increased risk of cancer.

Introduction

Idiopathic inflammatory myopathies (IIM) are a heterogeneous family of diseases that includes dermatomyositis (DM), immune-mediated necrotising myopathy (IMNM), antisynthetase syndrome (ASyS), polymyositis (PM) and inclusion body myositis (IBM).1 Most patients with IIM have a myositis-specific autoantibody (MSA). Among those with DM, approximately 70% have an MSA recognising either TIF1γ, NXP2, Mi2, MDA5 or SAE. Importantly, each MSA is associated with a unique clinical phenotype. For instance, patients with DM with anti-TIF1γ autoantibodies have a substantially increased risk of cancer,2 whereas those with anti-Mi2 autoantibodies do not.3 Although MSAs are usually mutually exclusive, there are exceptions. For example, some anti-MDA5-positive patients with DM develop a second MSA recognising splicing factor proline/glutamine-rich (SFPQ); these patients have a decreased risk of arthritis compared with anti-MDA5-positive patients without anti-SFPQ autoantibodies.4

Phage ImmunoPrecipitation Sequencing (PhIP-Seq) is a programmable bacteriophage display-based method for high-throughput antibody-binding analysis. Here we performed PhIP-Seq with a library of 274 207 overlapping 90 amino acid long peptides that tile across the human proteome5 6 to identify novel autoantibodies in patients with DM. This approach revealed novel autoantibodies recognising transcription factor Sp4 in patients with DM with coexisting anti-TIF1γ autoantibodies. Furthermore, we show that anti-Sp4 autoantibodies were more prevalent in two cohorts of TIF1γ-positive patients with DM who do not have cancer.

Patients and methods

Patients and serum samples

The discovery cohort consisted of 43 patients enrolled in the Johns Hopkins Myositis Center Longitudinal study between 2002 and 2016 with a diagnosis of DM based on the criteria of Bohan and Peter7 8 whose serum tested negative for all MSAs by the EUROLINE Autoimmune Inflammatory Myopathies 16 Ag (IgG) test kit, which includes the following antigens: Mi-2α, Mi-2β, TIF1γ, MDA5, NXP2, SAE1, Ku, PM-Scl100, PM-Scl75, Jo-1, SRP, PL-7, PL-12, EJ, OJ and Ro-52.

The screening cohort included patients with myositis enrolled in the Johns Hopkins Myositis Center Longitudinal Cohort study between 2002 and 2018. This included patients with DM based on the criteria of Bohan and Peter,7 8 ASyS defined by the presence of an antisynthetase autoantibody in patients with DM or PM according to the criteria of Bohan and Peter, IMNM defined by the presence of anti-signal recognition particle (SRP) or anti-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) autoantibodies in patients with proximal weakness and creatine kinase (CK) elevation as per 2018 European Neuromuscular Centre (ENMC) criteria,9 IBM defined by the Lloyd et al criteria,10 as well as patients with PM defined as those who fulfilled the criteria of Bohan and Peter for PM but who did not have ASyS or IMNM. Patients were considered positive for autoantibodies recognising Mi2, NXP2, MDA5, Jo1, SRP, HMGCR, SAE or PmScl if they tested positive by at least two immunological techniques from among the following: ELISA, in vitro transcription and translation immunoprecipitation, line blotting (EUROLINE Autoimmune Inflammatory Myopathies 16 Ag (IgG) test kit), PhIP-Seq,11 immunoprecipitation from S35-labelled HeLa cell lysates or immunoprecipitation blotting.12–14 All sera identified as anti-TIF1γ-positive were positive by anti-TIF1γ ELISA (MBL, RG-7854R). Except for one sample that did not undergo additional testing due to lack of availability, each ELISA-positive sera also tested positive by at least one additional anti-TIF1γ detection method (see online supplemental figure 1).

Supplemental material

A validation cohort included serum from 46 patients with DM from the University of Pittsburgh who tested positive for anti-TIF1γ by ELISA (MBL anti-TIF1γ ELISA, RG-7854R); 23 of these had cancer and 23 of these did not have cancer.

Serum from 30 patients from the Instituto Nacional de Ciencias Medicas y de la Nutricion Salvador Zubiran with rheumatoid arthritis (RA) based on the 2010 European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) classification criteria, as well as 25 patients with systemic lupus erythematosus (SLE) based on the 2019 EULAR/ACR criteria, 25 patients with Sjögren’s syndrome based on the 2016 EULAR/ACR classification criteria, and 200 healthy controls, all enrolled in studies at the National Institutes of Health, were also screened by ELISA for anti-Sp4 autoantibodies. Additional healthy control samples used for the analysis of peptidome data were from subjects self-reported to be free of autoimmune disease. Online supplemental table 1 summarises demographic data for the following cohorts: myositis, healthy control, RA, SLE and Sjogren’s syndrome.

Supplemental material

Of note, sera were obtained from patients when they enrolled in a research study at one of the participating institutions. These patients may have been previously undiagnosed and untreated or already on immunosuppressive therapy for various lengths of time.

In the screening cohort, muscle strength was evaluated by the examining physician using the Medical Research Council scale. This scale was transformed to Kendall’s 0–10 scale for analysis purposes as previously described.15 For the purposes of analyses, right-side and left-side measurements for arm abduction and hip flexion strength were combined and the average was used for calculations (possible range 0–10). Skin manifestations (ie, heliotrope rash or Gottron’s sign), weakness, symptoms of oesophageal involvement, ASyS-associated clinical features (eg, mechanics hands, Raynaud’s phenomenon, arthritis and fever) and other clinical features were documented both retrospectively at the onset of the disease (by asking patients about features present at the onset of disease) and prospectively at each visit. Interstitial lung disease was defined through a multidisciplinary approach as recommended by the American Thoracic Society.16 Cancer-associated myositis was defined as a malignancy occurring within 3 years either before or after the onset of myositis symptoms.

Screening for autoantibodies by PhIP-Seq

The standard PhIP-Seq procedure11 was used to profile sera from 67 patients with DM who were seronegative for Mi2, NXP2, TIF1γ or MDA5 by EUROLINE line blot (discovery cohort). Briefly, the IgG concentration of each serum sample was measured via ELISA assay, which allowed normalisation of the IgG input (2 μg per reaction) into the PhIP-Seq assay. Serum antibody was mixed with the human peptidome library composed of 274 207 90-aa peptides17 and was incubated overnight. Antibody and antibody-bound phage were captured using protein A and protein G coated Dynal magnetic beads (Invitrogen #10 002D & #10 004D). The immunoprecipitated phage DNA library was then amplified using PCR, with sample-specific DNA barcodes added during a second PCR reaction. Pooled amplicons were sequenced using an Illumina NextSeq instrument. An informatics pipeline was used for sample demultiplexing and alignment. On each 96-well plate, 8 wells were reserved for mock immunoprecipitations, in which the PhIP-Seq assay was performed without patient sera to account for background binding of the phage. Then, as described previously,11 patient data normalisation was performed by comparison to mock immunoprecipitations. Briefly, peptide enrichment z-scores are calculated for each peptide and each sample based on the distribution of the corresponding peptide’s reads in the mock immunoprecipitation reactions. Z-scores greater than 7 are considered positive based on prior studies. Finally, the normalised PhIP-Seq profiles were compared against a previously established PhIP-Seq database of 683 healthy volunteers using a custom case–control analysis script to identify reactivities specifically associated with DM (https://brandonsie.github.io/phipcc/). For each peptide, Fisher’s exact test with Bonferroni correction was used to detect a peptide–disease association by considering the proportion of samples with z-scores above the 95th percentile z-score among healthy controls. To identify potentially coassociated peptides, peptides with a significant disease association were subjected to hierarchical clustering with Ward agglomeration using Euclidean distance.

Immunoprecipitation using 35S-labelled in vitro transcription/translated (IVTT) Sp4

DNA encoding full-length human Sp4 was purchased (Origene) and used in IVTT reactions (Promega), generating 35S-labelled Sp4 protein. Immunoprecipitation of radiolabelled Sp4 was performed using patient serum or a mouse monoclonal anti-Sp4-positive control antibody (sc-515738, Santa Cruz Biotechnology), as previously described.12 Immunoprecipitates were reduced, boiled, subjected to electrophoresis on 10% sodium dodecyl sulfate–polyacrylamide gels and visualised using a Typhoon FLA 9500 scanner (GE Healthcare Life Sciences, Pennsylvania, USA; online supplemental figure 3).

Supplemental material

Anti-Sp4 and negative control ELISAs

ELISA plates (96-well) were coated overnight at 4°C with 100 ng of human recombinant Sp4 protein that included a GST tag (H00006671-P01; Abnova Corporation, Taipei, Taiwan) diluted in 100 mL of phosphate-buffered saline (PBS). After washing the plates with PBS including 0.05% Tween-20 (PBS-T) and blocking with 300 µL of 5% bovine serum albumin (BSA) in PBS-T for 1 hour at 37°C, the plates were washed with PBS-T. Diluted human serum samples (100 µL, 1:400 with 1% BSA/PBS-T) were added to each well and incubated for 1 hour at 37°C. After washing with PBS-T, 100 µL of HRP-labelled goat anti-human IgG antibody that reacts with the whole human IgG molecule as well as with the light chains of other human immunoglobulins (1:10,000, catalogue# 109-036-088; Jackson ImmunoResearch Lab, Pennsylvania, USA) was added and incubated for 30 min at 37°C in the dark. After washing the plate with PBS-T and PBS, 100 µL of SureBlue TMB microwell peroxidase enzyme substrate kit (95 059–286; KPL, Massachusetts, USA) was added. Reactions were stopped after 8 min. The absorbance at 450 nm was determined. Test sample absorbances were normalised to the sera of an arbitrary positive control sample, a reference sample included in every ELISA. The cut-off for a normal anti-Sp4 autoantibody titre (0.29 arbitrary units) was defined as the mean plus 2 SD of the normalised absorbances of the 200 healthy comparators. This cut-off was determined to be optimal based on a graphical analysis of the normalised absorbances.

To control for potential reactivity against the GST tag included in the Sp4 protein used for ELISA, sera that tested positive for anti-Sp4 autoantibodies by ELISA were also screened for anti-GST reactivity by ELISA. Several sera samples were positive by ELISA for both Sp4-GST and GST alone; these were considered negative for anti-Sp4 autoantibodies.

Statistical analysis

Dichotomous variables were expressed as percentages and absolute frequencies, and continuous features were reported as means and SD. Pairwise comparisons for categorical variables between groups were made using the χ2 test or Fisher’s exact test, as appropriate. Student’s t-test was used to compare continuous variables among groups, and paired t-test was used to compare the level of weakness of different muscle groups. CK, a highly positively skewed variable, was expressed as median, first and third quartiles for descriptive purposes, and was transformed through a base-10 logarithm for regression analysis.

Statistical analyses related to clinical variables were performed using Stata/MP V.14.1. A two-sided p value of 0.05 or less was considered statistically significant with no adjustment for multiple comparisons.

Patient and public involvement statement

Patients and the public were not involved in the design, conduct, reporting or dissemination plans of the present research.

Data availability statement

All data relevant to the study are either included in the article or will be shared on request.

Results

Identification of Sp4 as a novel autoantigen

In an effort to discover novel DM-associated autoantibodies, we assembled a cohort of sera from patients with DM who were negative for MSAs by EUROIMMUN line blot, which tests for DM-specific autoantibodies including anti-TIF1γ, anti-NXP2, anti-Mi2, anti-MDA5 and anti-SAE. These 43 serum samples were used in the PhIP-Seq assay with a T7 phage display library of 274 207 peptides spanning all open reading frames in the human genome as overlapping 90 amino acid peptides.17 While PhIP-Seq does not detect antibodies directed against discontinuous or post-translational epitopes, the approach is unbiased and provides a high resolution map of autoantibody binding specificities.18 An average of 122 human peptides per sample (95% CI 84 to 159 peptides) were considered significantly reactive (see the Patients and methods section). A case–control analysis compared PhIP-Seq profiles of the DM discovery cohort against profiles of 663 healthy controls to detect DM-associated antibodies (see the Patients and methods section). Among the 43 serum samples analysed, 13 recognised from 1 to 4 peptides corresponding to transcription factor Sp4 (table 1). Recognition of non-overlapping epitopes is indicative of a polyclonal antibody response that is more likely to be antigen driven.

Table 1

Sp4 peptides identified by PhIP-Seq

To determine which sera had immunoreactivity against native Sp4, we generated full-length radiolabelled Sp4 protein by IVTT and used human serum or a rabbit anti-Sp4-positive control antibody to immunoprecipitate the protein (figure 1). The positive control anti-Sp4 antibody and each of the six serum samples that recognised three or four distinct Sp4 peptides by PhIP-Seq (figure 1, lanes 3–8) efficiently immunoprecipitated full-length Sp4 protein. In contrast, serum samples that recognised just one or two Sp4 peptides only weakly immunoprecipitated full-length Sp4 protein (lanes 9–15).

Figure 1

Human serum samples from patients with DM immunoprecipitate full-length Sp4 protein. Sera from patients with DM that recognised at least one Sp4 peptide by PhIP-Seq were used to immunoprecipitate radiolabelled full-length Sp4 protein. The Sp4 peptides recognised by each serum using PhIP-Seq are indicated below each lane. Those serum samples recognising three to four distinct Sp4 peptides (lanes 3–8) by PhIP-Seq immunoprecipitated full-length Sp4 protein more efficiently than those serum samples that recognised only one to two Sp4 peptides by PhIP-Seq (lanes 9–15). The input Sp4 protein used for immunoprecipitation is shown in lane 1. A commercial rabbit anti-Sp4 autoantibody was used to immunoprecipitate radiolabelled Sp4 in lane 2. Healthy control sera did not immunoprecipitate full-length Sp4 protein (lanes 16–19). DM, dermatomyositis; PhIP-Seq, phage immunoprecipitation sequencing.

Unexpectedly, since they had each tested negative for anti-TIF1γ autoantibodies by EUROIMMUN line blot, we noted that all six serum samples that efficiently immunoprecipitated full-length Sp4 protein also recognised a peptide corresponding to TIF1γ by the PhIP-Seq assay (data not shown). We subsequently confirmed that these six serum samples were anti-TIF1γ-positive by ELISA. This demonstrates the high sensitivity of PhIP-Seq and suggests that the line blot test may not be a sufficiently sensitive assay for detecting anti-TIF1γ autoantibodies. Indeed, a recent report showed that the EUROIMMUN line blot has good specificity but poor sensitivity for detecting anti-TIFγ autoantibodies compared with immunoprecipitation detection methods.19

Screening for anti-Sp4 autoantibodies in patients with IIM and other rheumatological conditions, and healthy controls

To screen patients rapidly for anti-Sp4 autoantibodies, we developed an ELISA using Sp4 protein with a GST tag. We defined a serum sample as being positive for anti-Sp4 autoantibodies if the relative absorbance was 2 SD or higher than the mean value of 200 healthy control subjects and the serum sample was not reactive against the GST tag in an anti-GST ELISA (see the Patients and methods section). Using this method, we found that 6 of the 13 samples recognising Sp4 peptides by PhIP-Seq were also ELISA positive; these were the same six samples that recognised three or four Sp4 peptides and which most efficiently immunoprecipitated full-length Sp4 protein (figure 1, lanes 3–8). In contrast, among the 30 samples that did not recognise Sp4 peptides by PhIP-Seq, 26 were available for further testing and each of these was negative for anti-Sp4 autoantibodies by ELISA.

The screening cohort consisted of 371 serum samples from patients with myositis seen at the Johns Hopkins Myositis Centre (255 with DM, 28 with ASyS (all anti-Jo1-positive), 40 with IMNM, 19 with PM and 29 with IBM). Among these, 27 (7.3%) sera were anti-Sp4-positive by ELISA (figure 2) and all of them had DM. Thus, 10.5% of patients with DM were anti-Sp4-positive. Of the anti-SP4-positive DM samples, 96.3% were also TIF1γ-positive (n=26). Out of 194 anti-TIF1γ-negative patients with DM, just 1 (0.5%), a single anti-NXP2-positive patient, had anti-Sp4 autoantibodies. In contrast, no patient with anti-MDA5, anti-Mi2, anti-SAE or anti-PMScl autoantibodies also had anti-Sp4 autoantibodies.

Figure 2

Anti-Sp4 autoantibody titres determined by ELISA in sera from patients with myositis, other rheumatological conditions and healthy comparators. Anti-Sp4 titres were determined by ELISA for sera from 371 adult patients with myositis, 25 patients with lupus, 25 patients with Sjogren’s syndrome, 30 patients with rheumatoid arthritis and 200 healthy controls. The dotted line indicates the cut-off used to define anti-Sp4-positive sera. Blue dots represent samples that were anti-TIF1γ-negative, and orange dots represent samples that were anti-TIF1γ-positive. Several serum samples reacted on ELISA with both the Sp4 protein (which has a GST tag) and with the GST protein alone. For clarity, these samples were excluded from this figure but are included as anti-TIF1γ-negative samples in the subsequent analyses.

We also tested for anti-Sp4 autoantibodies in 25 patients with Sjogren’s syndrome, 25 patients with SLE and 30 patients with RA. One (3.3%) of the patients with RA was anti-Sp4-positive, whereas the rest of the patients with other rheumatological conditions were negative for these autoantibodies (figure 2). Overall, compared with healthy controls (3%), there were significant increases in the prevalence of anti-Sp4 antibodies in the following groups: myositis (7.3%, p=0.02), DM (10.5%, p=0.0009) and anti-TIF1γ-positive DM (42.6%, p=1.5e-16). The prevalence of anti-Sp4 autoantibodies was the same in RA and the healthy control groups (~3%). Taken together, these results indicate that anti-Sp4 autoantibodies are strongly associated with anti-TIF1γ-positive DM.

Clinical features of TIF1-positive patients with DM with and without coexisting anti-Sp4 autoantibodies

Most demographic (table 2) and clinical (table 3 and online supplemental table 2) features were similar between TIF1γ-positive patients with DM with and without anti-Sp4 autoantibodies. However, patients with anti-Sp4 autoantibodies had measures of muscular strength that were significantly higher than those who were anti-Sp4-negative (online supplemental table 2). We also noted that among 26 TIF1γ-positive patients from Johns Hopkins with anti-Sp4 autoantibodies, none had cancer. In contrast, among 35 TIF1γ-positive patients without anti-Sp4 autoantibodies, 5 (14%) had cancer (p=0.04). To confirm that anti-Sp4 autoantibodies are associated with absence of cancer in anti-TIF1γ-positive patients with DM, we screened an additional cohort of 46 TIF1γ-positive patients with DM from the University of Pittsburgh (figure 3). Among 15 TIF1γ-positive patients with anti-Sp4 autoantibodies, 2 (13.3%) had cancer. By comparison, among 31 TIF1γ-positive patients without anti-Sp4 autoantibodies, 21 (67.8%, p<0.001) had cancer. Thus, anti-Sp4 autoantibodies are associated with a reduced risk of cancer in anti-TIF1γ-positive patients with DM. Conversely, patients with anti-TIF1γ autoantibodies that do not co-express anti-Sp4 autoantibodies are at very high risk of cancer.

Supplemental material

Figure 3

Anti-Sp4 autoantibody titres in the Pittsburgh cohort of anti-TIF1γ-positive subjects. Serum samples from 23 anti-TIF1γ-positive subjects with cancer and 23 anti-TIF1γ-positive subjects without cancer were screened for anti-Sp4 autoantibodies by ELISA. The dotted line indicates the cut-off used to define anti-Sp4-positive sera.

Table 2

General features of anti-TIF1γ patients with and without anti-Sp4 autoantibodies

Table 3

Cumulative clinical features of anti-TIF1γ patients with and without anti-Sp4 autoantibodies

We next analysed the evolution of anti-Sp4 autoantibody titres during the disease course by analysing longitudinally collected serum samples. We found that titres decreased in many patients but did not normalise after treatment of the DM (online supplemental figure 2). Finally, to determine whether anti-TIF1γ-positive patients without anti-Sp4 autoantibodies at their initial visit to the Johns Hopkins Myositis Centre might develop them during the course of the disease, we screened the most recently collected serum samples from 24 TIF1γ-positive and anti-Sp4-negative patients. During an average of 4.7 years (SD 2.3) between the collection of the first and most recent serum samples, only two (8.3%) of these became positive for anti-Sp4 autoantibodies.

Supplemental material

Discussion

In this study, we used PhIP-Seq, a programmable bacteriophage display-based method, to identify Sp4 as a candidate autoantigen in patients with DM; this finding was confirmed by immunoprecipitation of full-length Sp4 protein with patient sera. Using an anti-Sp4 ELISA, we screened several cohorts of patients with myositis and controls and found that anti-Sp4 autoantibodies were found in 10.5% of DM, 3% of healthy controls, 3% of RA patients, but not in patients with SLE or Sjogren’s syndrome. Unexpectedly, among patients with DM, anti-Sp4 autoantibodies were found almost exclusively among those with coexisting anti-TIF1γ autoantibodies. Moreover, although anti-TIF1γ-positive patients with DM have an increased risk of cancer, we discovered that the prevalence of cancer was relatively decreased in those with coexisting anti-Sp4 autoantibodies in two independent cohorts.

It is unclear why an immune response against TIF1γ would be associated with an increased prevalence of cancer in patients with DM, while a coexisting immune response against Sp4 would be associated with a relatively reduced prevalence of malignancy compared with other anti-TIF1γ-positive patients. It has been proposed that in some patients, tumours elicit an immune response against autoantigens such as TIF1γ that is redirected to skin and muscle, causing DM, but is insufficient to eradicate the underlying tumor20; these patients would present with anti-TIF1γ-positive DM along with a clinically apparent malignancy. In other patients, we hypothesise that an antitumour immune response against TIF1γ becomes redirected to skin and muscle, causing DM, but that an additional immune response is raised against Sp4, which causes or is associated with effective eradication of the tumour; these patients would present with both anti-TIF1γ and anti-Sp4 autoantibodies but no tumour. This speculative model remains to be validated.

Recently, autoantibodies against other targets, including the cell division cycle and apoptosis regulator 1 (CCAR1) protein, were also found to be associated with decreased cancer prevalence among anti-TIF1γ-positive patients with DM21; anti-CCAR autoantibodies were present in 36% of those without cancer and in 22% of those with cancer. When the two cohorts of anti-TIF1γ-positive patients used in the current study are combined, anti-Sp4 autoantibodies were present in 49.4% (39 of 79) of those without cancer and 7.1% (2 of 28) of those with cancer. Future studies looking at both anti-CCAR1 and anti-Sp4 autoantibodies in larger cohorts of patients with DM will be required to determine which antibody or combination of antibodies has a stronger association with low cancer prevalence in anti-TIF1γ-positive patients with DM.

This study has several limitations. First, PhIP-Seq only detects antibodies recognising 90 amino acid-long peptides. Thus, autoantibodies recognising discontinuous epitopes or post-translational modifications will not be detected using this method. Second, the Sp4 protein used for the anti-Sp4 ELISA also included a GST tag, and we found that several sera recognised the GST tag. Although we overcame this limitation by identifying such sera using a secondary anti-GST ELISA, we plan to develop a more specific anti-Sp4 ELISA using Sp4 protein without a tag. Third, our cohorts of disease control sera were relatively small, and screening larger cohorts of patients with various autoimmune diseases would be of interest.

These limitations notwithstanding, we have shown that anti-Sp4 autoantibodies are predominantly found in anti-TIF1γ-positive patients with DM without cancer. Future prospective studies including larger numbers of patients will be required to establish whether testing for anti-Sp4 autoantibodies may have clinical utility in identifying a subpopulation of anti-TIF1γ-positive patients who may be safely spared aggressive malignancy screening.

Data availability statement

Data are available upon reasonable request. All data relevant to the study are either included in the article or will be shared upon request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by the institutional review boards (IRBs) at Johns Hopkins (IRB# 00235256), the National Institutes of Health (IRB# AR-0196), the University of Pittsburgh (IRB# MOD19090054-001) and the Instituto Nacional de Ciencias Medicas y de la Nutricion Salvador Zubiran (reference# 1243); written informed consent was obtained from each participant.

References

Supplementary materials

Footnotes

  • HBL and ALM are joint senior authors.

  • YH, BS, IP-F and KP are joint first authors.

  • Handling editor Josef S Smolen

  • Twitter @docrota, @H Benjamin Larman @larmanlab

  • HBL and ALM contributed equally.

  • Contributors ALM is responsible for the overall content as guarantor and accepts full responsibility for the finished work and/or the conduct of the study, had access to the data, and controlled the decision to publish. ALM, HBL, YH, IP-F, BS, and KP contributed to the conception and/or design of the work. All authors contributed to the acquisition, analysis, or interpretation of data for the work. ALM, IP-F, HBL, and BS worked on the initial draft of the manuscript. All authors had the opportunity to revise the work critically for important intellectual content. All authors gave final approval of the version to be published. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  • Funding This work was supported, in part, by the Intramural Research Program of the National Institutes of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health (AR041203). The Johns Hopkins Rheumatic Diseases Research Core Center, where some of the autoantibodies were assayed, is supported by NIH P30-AR070254. This work was also supported by the Hyuai and Siuling Zhang Discovery Fund and Dr Peter Buck.

  • Competing interests YJ, IP-F, KP, MC-D, MJK, JA, TEL, ET, CVO, SM-K, CC-R, JCM, JMG-J, AS-O'C and ALM report no competing interests. CAM has received support from NIH grant 1K23AR075898 and the Jerome L. Greene Foundation; reconsulting fees from Guidepoint Consultations and Boehringer Ingelheim; and payment for expert testimony from the Department of Justice–Vaccine Injury Compensation Program. BMW received support from NIH grant Z01-DE000704. SD received support grants or contract from BMS, Boehringer-Ingelheim and Genentech/Roche; royalties or licences from UpToDate; consulting fees from Boehringer-Ingelheim; payment for presentations from France Foundation; support for travel from Boehringer-Ingelheim; participates in an advisory board for Galecto and Galapagos; and is a senior medical advisor for the Pulmonary Fibrosis Foundation and the American Thoracic Society. JJP received support from NIH grant K23AR073927; grants or contracts from Pfizer, Kezer and Corbus; royalties from UpToDate; and consulting fees from Pfizer, Kezar, EMD Serono, Proivant and Guidepoint Consultation. RA received grants or contracts from Mallinckrodt, Q32, Pfizer, EMD-Serono and Bristol Myers-Squibb; and consulting fees from Mallinckrodt, EMD Serono, Octapharma, Kezar, CSL Behring, Pfizer, Bristol Myers-Squibb, Astrazeneca, Alexion, Boehringer-Ingelheim, Argenx, Corbus, Roivant, Jannsen, Merck, Kyverna, Galapagos, Actigraph, Abbvie, Scipher, Horizon Therapeutics, Teva and Beigene. LC-S received grants or contracts from Pfizer, Corbus and Kezar; royalties from Inova Diagnostics; consulting fees from Janssen, Boehringer-Ingelheim, Mallinckrodt, EMD-Serono, Argenx, Allogene and Horizon Therapeutics; expert testimony for Bendin Sumrall and Ladner LLC, Feldman, Kleidman Coffey, & Sappe LLP Downs Ward Bender Hauptmann & Herzog, P.A., and Sulloway and Hollis; and patents from Inova Diagnostics and RDL. HBL received support from NIH grant R01GM136724; is a founder of ImmuneID, Portal Bioscience and Alchemab; and is an advisor to TScan Therapeutics.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

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

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