Posttranslational modifications induce autoantibodies with risk prediction capability in patients with small cell lung cancer.

Small cell lung cancer (SCLC) elicits the generation of autoantibodies that result in unique paraneoplastic neurological syndromes. The mechanistic basis for the formation of such autoantibodies is largely unknown but is key to understanding their etiology. We developed a high-dimensional technique that enables detection of autoantibodies in complex with native antigens directly from patient plasma. Here, we used our platform to screen 1009 human plasma samples for 3600 autoantibody-antigen complexes, finding that plasma from patients with SCLC harbors, on average, fourfold higher disease-specific autoantibody signals compared with plasma from patients with other cancers. Across three independent SCLC cohorts, we identified a set of common but previously unknown autoantibodies that are produced in response to both intracellular and extracellular tumor antigens. We further characterized several disease-specific posttranslational modifications within extracellular proteins targeted by these autoantibodies, including citrullination, isoaspartylation, and cancer-specific glycosylation. Because most patients with SCLC have metastatic disease at diagnosis, we queried whether these autoantibodies could be used for SCLC early detection. We created a risk prediction model using five autoantibodies with an average area under the curve of 0.84 for the three cohorts that improved to 0.96 by incorporating cigarette smoke consumption in pack years. Together, our findings provide an innovative approach to identify circulating autoantibodies in SCLC with mechanistic insight into disease-specific immunogenicity and clinical utility.

CD133 as a Biomarker for an Autoantibody-to-ImmunoPET Paradigm for the Early Detection of Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a deadly neuroendocrine tumor for which there are no screening methods sensitive enough to facilitate early, effective intervention. We propose targeting the neuroendocrine tumor neoantigen CD133 via antibody-based early detection and PET (immunoPET) to facilitate earlier and more accurate detection of SCLC. Methods: RNA sequencing datasets, immunohistochemistry, flow cytometry, and Western blots were used to quantify CD133 expression in healthy and SCLC patients. CD133 was imaged in vivo using near-infrared fluorescence (NIRF) immunoimaging, and 89Zr immunoPET. Anti(α)-CD133 autoantibody levels were measured in SCLC patient plasma using antibody microarrays. Results: Across 6 publicly available datasets, CD133 messenger RNA was found to be higher in SCLC tumors than in other tissues, including healthy or normal adjacent lung and non-SCLC samples. Critically, the upregulation of CD133 messenger RNA in SCLC was associated with a significant increase (hazard ratio, 2.62) in death. CD133 protein was expressed in primary human SCLC, in SCLC patient-derived xenografts, and in both SCLC cell lines tested (H82 and H69). Using an H82 xenograft mouse model, we first imaged CD133 expression with NIRF. Both in vivo and ex vivo NIRF clearly showed that a fluorophore-tagged αCD133 homed to lung tumors. Next, we validated the noninvasive visualization of subcutaneous and orthotopic H82 xenografts via immunoPET. An αCD133 antibody labeled with the positron-emitting radiometal 89Zr demonstrated significant accumulation in tumor tissue while producing minimal uptake in healthy organs. Finally, plasma αCD133 autoantibodies were found in subjects from cohort studies up to 1 year before SCLC diagnosis. Conclusion: In light of these findings, we conclude that the presence of αCD133 autoantibodies in a blood sample followed by CD133-targeted 89Zr-immunoPET could be an effective early detection screening strategy for SCLC.