Human virome profiling identified CMV as the major viral driver of a high accumulation of senescent CD8+ T cells in patients with advanced NSCLC

Circulating senescent CD8+ T (T8sen) cells are characterized by a lack of proliferative capacities but retain cytotoxic activity and have been associated to resistance to immunotherapy in patients with advanced non-small cell lung cancer (aNSCLC). We aimed to better characterize T8sen and to determine which factors were associated with their accumulation in patients with aNSCLC. Circulating T8sen cells were characterized by a higher expression of SA-βgal and the transcription factor T-bet, confirming their senescent status. Using whole virome profiling, cytomegalovirus (CMV) was the only virus associated with T8sen. CMV was necessary but not sufficient to explain high accumulation of T8sen (T8senhigh status). In CMV+ patients, the proportion of T8sen cells increased with cancer progression. Last, CMV-induced T8senhigh phenotype but not CMV seropositivity itself was associated with worse progression-free and overall survival in patients treated with anti-PD-(L)1 therapy but not with chemotherapy. Overall, CMV is the unique viral driver of T8sen-driven resistance to anti-PD-(L)1 antibodies in patients with aNSCLC.

Argonaute, Vault, and Ribosomal Proteins Targeted by Autoantibodies in Systemic Lupus Erythematosus

OBJECTIVE

To expand, in an unbiased manner, our knowledge of autoantigens and autoantibodies in patients with systemic lupus erythematosus (SLE) and evaluate their associations with serological and clinical variables.

METHODS

Human proteome arrays (> 21,000 proteins) were screened with serum from patients with SLE (n = 12) and healthy controls (n = 6) for IgG and IgA binding. Top hits were validated with 2 cohorts of patients with SLE (cohort 1, n = 49; cohort 2, n = 46) and other rheumatic diseases by ELISA. Clinical associations of the autoantibodies were tested.

RESULTS

Ro60 was the top hit in the screen, and the 10 following proteins included 2 additional known SLE autoantigens plus 8 novel autoantigens involved in microRNA processing (Argonaute protein 1 [AGO1], AGO2, and AGO3), ribosomes (ribosomal protein lateral stalk subunit P2 and ovarian tumor deubiquitinase 5 [OTUD5]), RNA transport by the vault (major vault protein), and the immune proteasome (proteasome activator complex subunit 3). Patient serum contained IgG reactive with these proteins and IgA against the AGO proteins. Using the 95th percentile of healthy donor reactivity, 5-43% were positive for the novel antigens, with OTUD5 and AGO1 showing the highest percentages of positivity. Autoantibodies against AGO1 proteins were more prevalent in patients with oral ulcers in a statistically significant manner. IgG autoantibodies against AGO proteins were also seen in other rheumatic diseases.

CONCLUSION

We discovered new autoantigens existing in cytosolic macromolecular protein assemblies containing RNA (except the proteasome) in cells. A more comprehensive list of autoantigens will allow for a better analysis of how proteins are targeted by the autoimmune response. Future research will also reveal whether specific autoantibodies have utility in the diagnosis or management of SLE.

Development of a Novel Circulating Autoantibody Biomarker Panel for the Identification of Patients with 'Actionable' Pulmonary Nodules

Due to poor compliance and uptake of LDCT screening among high-risk populations, lung cancer is often diagnosed in advanced stages where treatment is rarely curative. Based upon the American College of Radiology's Lung Imaging and Reporting Data System (Lung-RADS) 80-90% of patients screened will have clinically "non-actionable" nodules (Lung-RADS 1 or 2), and those harboring larger, clinically "actionable" nodules (Lung-RADS 3 or 4) have a significantly greater risk of lung cancer. The development of a companion diagnostic method capable of identifying patients likely to have a clinically actionable nodule identified during LDCT is anticipated to improve accessibility and uptake of the paradigm and improve early detection rates. Using protein microarrays, we identified 501 circulating targets with differential immunoreactivities against cohorts characterized as possessing either actionable (n = 42) or non-actionable (n = 20) solid pulmonary nodules, per Lung-RADS guidelines. Quantitative assays were assembled on the Luminex platform for the 26 most promising targets. These assays were used to measure serum autoantibody levels in 841 patients, consisting of benign (BN; n = 101), early-stage non-small cell lung cancer (NSCLC; n = 245), other early-stage malignancies within the lung (n = 29), and individuals meeting United States Preventative Screening Task Force (USPSTF) screening inclusion criteria with both actionable (n = 87) and non-actionable radiologic findings (n = 379). These 841 patients were randomly split into three cohorts: Training, Validation 1, and Validation 2. Of the 26 candidate biomarkers tested, 17 differentiated patients with actionable nodules from those with non-actionable nodules. A random forest model consisting of six autoantibody (Annexin 2, DCD, MID1IP1, PNMA1, TAF10, ZNF696) biomarkers was developed to optimize our classification performance; it possessed a positive predictive value (PPV) of 61.4%/61.0% and negative predictive value (NPV) of 95.7%/83.9% against Validation cohorts 1 and 2, respectively. This panel may improve patient selection methods for lung cancer screening, serving to greatly reduce the futile screening rate while also improving accessibility to the paradigm for underserved populations.

Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19

Pediatric Coronavirus Disease 2019 (pCOVID-19) is rarely severe; however, a minority of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might develop multisystem inflammatory syndrome in children (MIS-C), with substantial morbidity. In this longitudinal multi-institutional study, we applied multi-omics (analysis of soluble biomarkers, proteomics, single-cell gene expression and immune repertoire analysis) to profile children with COVID-19 (n = 110) and MIS-C (n = 76), along with pediatric healthy controls (pHCs; n = 76). pCOVID-19 was characterized by robust type I interferon (IFN) responses, whereas prominent type II IFN-dependent and NF-κB-dependent signatures, matrisome activation and increased levels of circulating spike protein were detected in MIS-C, with no correlation with SARS-CoV-2 PCR status around the time of admission. Transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation. The association of MIS-C with the combination of HLA A*02, B*35 and C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load than pCOVID-19 and pHC. These results identify distinct immunopathological signatures in pCOVID-19 and MIS-C that might help better define the pathophysiology of these disorders and guide therapy.

Using autoantibody signatures to predict immunotherapy discontinuation in melanoma patients

3069

Background: Immune checkpoint inhibitors (ICIs), e.g., ipilimumab (IPI) and/or nivolumab (NIVO), produce durable survival benefit in a substantial proportion of melanoma patients but can also induce severe immune-related adverse events (irAEs) requiring treatment discontinuation. There is no biomarker to predict irAEs in ICI-treated melanoma patients. Given the similar clinical manifestation between irAEs and autoimmune disorders, we hypothesized that a subset of patients possess a subclinical baseline predisposition to developing irAEs that is characterized by specific autoantibodies (autoAbs). Methods: Pre-treatment melanoma patient sera from the CheckMate-238 Phase III trial of adjuvant IPI vs. NIVO were used for autoAb profiling with HuProt proteomic arrays (CDI Labs). The outcome of interest is to predict toxicity events that caused treatment discontinuation. For each treatment arm, we allocated patients to training and testing datasets in a 3:1 ratio. We calculated the area under the curve (AUC) of the receiver operating characteristic curve to select a probability threshold, which was applied to the testing dataset to assess accuracy, sensitivity, and specificity. Functional enrichment among autoAb protein targets was assessed using Metascape. Results: There were 707 irAEs among 597 patients (IPI = 423, NIVO = 174), of which 355 required treatment discontinuation (IPI = 287, NIVO = 68). In the training sets, we identified a 170 autoAbs signature consisting of 102 autoAbs for IPI treatment and 68 autoAbs for NIVO treatment. In the independent testing set, the signatures showed AUC of 0.85 (0.78, 0.92), 82% sensitivity, 78% specificity, and overall accuracy of 81% to predict IPI discontinuation, and AUC of 0.87 (0.74, 0.99), 75% sensitivity, 97% specificity, and overall accuracy of 88% to predict NIVO discontinuation. Enrichment of nuclear lumen-associated protein targets was identified among autoAb signatures that predict IPI or NIVO discontinuation. Conclusions: The identified signature within a large Phase III trial cohort highlights the potential utility of pre-treatment autoAbs for prediction of patients at high risk of developing irAEs in the adjuvant setting necessitating treatment termination. We are currently validating and refining toxicity-associated autoAb signatures with the goal of developing a Clinical Laboratory Improvement Amendments (CLIA)-certified assay to enable clinicians to optimize immunotherapy delivery and patient selection.

Recurrence of head and neck squamous cell cancer following resection may be predicted by assessment of immune infiltrates within the tumor (TUM10P.1056)

Tumor immune infiltrates are prognostic for many histologies, reinforcing the importance of the immune system in patient outcomes. Here we assessed a cohort of resected HPV+ and HPV- HNSCC tumors by multispectral imaging and a 770 gene digital transcript counting platform (NanoString nCounter system) that combines markers for 24 immune populations, 30 cancer antigens and relevant immune response genes. We performed IHC on FFPE and flowcytometry on enzyme-digested tumor allowing us to identify leukocyte subsets. Preliminary results show that while B cells, T cells and myeloid cells alternately predominate in different HNSCC tissue digests, NK cells rarely seen. Roughly half of our cohort has recurred at this time. Gene expression profiles indicate that tumors derived from patients with no evidence of disease contain more immune response related transcripts than tumors from patients that recur. Analysis of our discovery cohort by UPGMA hierarchical clustering indicates that the immune infiltrates in HNSCC may prove prognostic. Importantly, there are transcripts that may indicate a negative prognosis. Among these are a number of chemokines, TGFB2, the TLR4-TRIFF bridge TICAM2 and a molecule associated with anti-viral responses, IFITM1. Since these molecules constitute possible targets for therapeutic intervention, we are working to confirm their preponderance in tumors that recur by assessing a validation cohort as well as protein confirmation by IHC.