IMPORTANCE Immunotherapy with checkpoint inhibitors targeting the PD-1 (programmed cell death 1) axis has brought notable progress in patients with non-small cell lung cancer (NSCLC) and other cancers. However, autoimmune toxic effects are frequent and poorly understood, making it important to understand the pathophysiologic processes of autoimmune adverse effects induced by checkpoint inhibitor therapy. OBJECTIVE To gain mechanistic insight into autoimmune skin toxic effects induced by anti-PD-1 treatment in patients with non-small cell lung cancer. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study was conducted from July 1, 2016, to December 31, 2018. Patients (n = 73) with non-small cell lung cancer who received anti-PD-1 therapy (nivolumab or pembrolizumab) were recruited from 4 different centers in Switzerland (Kantonsspital St Gallen, Spital Grabs, Spital Wil, and Spital Flawil). Peripheral blood mononuclear cells, tumor biopsy specimens and biopsies from sites of autoimmune skin toxic effects were collected over a 2-year period, with patient follow-up after 1 year. MAIN OUTCOMES AND MEASURES Response to treatment, overall survival, progression-free survival, and development of autoimmune toxic effects (based on standard laboratory values and clinical examinations). RESULTS Of the cohort of 73 patients with NSCLC (mean [SD] age, 68.1 [8.9] years; 44 [60%] men), 25 (34.2% [95% CI, 24.4%-45.7%]) developed autoimmune skin toxic effects, which were more frequent in patients with complete remission or partial remission (68.2% [95% CI, 47.3%-83.6%]) than those with progressive or stable disease (19.6% [95% CI, 11.0%-32.5%]) (χ 2 = 14.02, P < .001). Nine T-cell antigens shared between tumor tissue and skin were identified. These antigens were able to stimulate CD8 + and CD4 + T cells in vitro. Several of the antigen-specific T cells found in blood samples were also present in autoimmune skin lesions and lung tumors of patients who responded to anti-PD-1 therapy. CONCLUSIONS AND RELEVANCE These findings highlight a potential mechanism of checkpoint inhibitor-mediated autoimmune toxic effects and describe the association between toxic effects and response to therapy; such an understanding will help in controlling adverse effects, deciphering new cancer antigens, and further improving immunotherapy.

These results support the utility of SAFB for pretransplant risk assessment and organ allocation, and suggest that improvement of the positive predictive value of HLA-DSA defined by SAFB will require an enhanced definition of pathogenic factors of HLA-DSA.

Glycolysis is linked to the rapid response of memory CD8 T cells, but the molecular and subcellular structural elements enabling enhanced glucose metabolism in nascent activated memory CD8 T cells are unknown. We found that rapid activation of protein kinase B (PKB or AKT) by mammalian target of rapamycin complex 2 (mTORC2) led to inhibition of glycogen synthase kinase 3β (GSK3β) at mitochondria-endoplasmic reticulum (ER) junctions. This enabled recruitment of hexokinase I (HK-I) to the voltage-dependent anion channel (VDAC) on mitochondria. Binding of HK-I to VDAC promoted respiration by facilitating metabolite flux into mitochondria. Glucose tracing pinpointed pyruvate oxidation in mitochondria, which was the metabolic requirement for rapid generation of interferon-γ (IFN-γ) in memory T cells. Subcellular organization of mTORC2-AKT-GSK3β at mitochondria-ER contact sites, promoting HK-I recruitment to VDAC, thus underpins the metabolic reprogramming needed for memory CD8 T cells to rapidly acquire effector function.

In 90% of patients, pretransplant HLA-DSA are composed of isolated strong or a mixture of strong and weak/no complement-activating IgG subclasses. Because outcomes in these two groups were similar, pretransplant IgG subclass analysis is likely not providing substantial value beyond the standard IgG SAFB assay for pretransplant risk stratification.

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Preformed donor-specific HLA-antibodies antibodies (DSA) are a major risk for early antibody-mediated rejection (AMR). This prospective study evaluated the accuracy of pretransplant risk assessment using virtual crossmatching (virtualXM) (i.e. comparing HLAtyping of the donor with the recipient's HLA-antibody specificities determined by flow-beads). Sixty-five consecutive patients were stratified according to virtualXM results: patients without DSA (n = 56) were considered low risk and received standard immunosuppression; patients with DSA (n = 9) were considered high risk and received additional induction with anti-T-lymphocyte-globulin (ATG) and intravenous immunoglobulins. Despite induction therapy 4 of 9 patients with DSA (44%) had clinical/subclinical AMR, whereas only 2 of 56 patients without DSA (4%) (p = 0.002). Notably, one of these two patients had early AMR likely induced by non-HLA-antibodies; the other had subclinical AMR at month 6 consistent with de novo DSA. The results of virtualXM and retrospectively obtained flow-cytometric crossmatches (FCXM) (n = 59) were concordant in 51 patients (86%), four patients (7%) were virtualXM−/FCXM+ and none had AMR, four patients (7%) were virtualXM+/FCXM− and one had AMR. VirtualXM can accurately define absence or presence of DSA and may become an invaluable tool for organ allocation and pretransplant risk assessment. However, further studies need to address whether all HLA-antibodies detected by flow-beads are clinically relevant.

C1q binding on SAB is strongly associated with IgGpan MFI. IgG subclass information only marginally improves prediction of C1q binding likely because complement-binding IgG1 and IgG3 subclasses dominate regarding frequency and relative amounts. A negative C1q assay result does not indicate the absence of strong complement-binding IgG subclasses.

Summary The virtual crossmatch (virtual‐XM) has been proposed for accurate identification of donor‐specific HLA‐antibodies, but large prospective studies assessing its value for pretransplant risk stratification are lacking. A total of 233 consecutive renal allograft recipients were prospectively stratified according to the virtual‐XM. In patients with a negative virtual‐XM (n = 190, 82%), prospective cytotoxicity crossmatches (CDC‐XM) were omitted, and they received standard immunosuppression. Virtual‐XM positive patients were only transplanted if CDC‐XM were negative. They received additional induction with anti‐T‐lymphocyte‐globulin and intravenous immunoglobulins (n = 43, 18%). The cumulative incidence of clinical/subclinical antibody‐mediated rejection (AMR) at 1 year was lower in the negative virtual‐XM than in the positive virtual‐XM group [15/190 (8%) vs. 18/43 (42%); P < 0.0001]. After a median follow‐up of 2.6 years, allograft loss because of AMR occurred less often in the negative virtual‐XM group (1% vs. 7%; P = 0.04) and death‐censored allograft survival at 2 years was higher (98% vs. 91%; P = 0.02). Serum creatinine was not different at the last follow‐up (129 μm vs. 130 μm; P = 0.58). We conclude that a negative virtual‐XM defines patients at low risk for AMR and early allograft loss, while a positive virtual‐XM represents a significant risk for AMR despite enhanced induction therapy. This supports the utility of the virtual‐XM for risk stratification and treatment allocation.