BP180-specific IgG is associated with skin adverse events, therapy response and overall survival in non-small cell lung cancer patients treated with checkpoint inhibitors

BACKGROUND: Anti-PD1/PD-L1 therapy frequently entails immune-related adverse events (irAEs) and biomarkers to predict irAEs are lacking. While checkpoint inhibitors have been found to re-invigorate T-cells, the relevance of autoantibodies remains elusive. OBJECTIVE: Our aim was to explore whether IgG autoantibodies directed against co-expressed antigens by tumor tissue and healthy skin correlate with skin irAEs and therapy outcome. METHODS: We measured skin-specific IgG via ELISA in non-small cell lung cancer (NSCLC) patients, who received anti-PD1/PD-L1 treatment between July 2015 and September 2017 at the Kantonsspital St. Gallen. Sera were sampled at baseline and during therapy after 8 weeks. RESULTS: Analysis of publicly available tumor expression data revealed that NSCLC and skin co-express BP180, BP230 and type VII collagen. Of 40 recruited patients, 16 (40%) developed a skin irAE. Only elevated anti-BP180 IgG at baseline significantly correlated with the development of skin irAEs (P=.04), therapy response (P=.01) and overall survival (P=.04). LIMITATIONS: The patients were recruited in a single tertiary care center. CONCLUSIONS: Our data suggest that the level of anti-BP180 IgG of NSCLC patients at baseline is associated with better therapy response, overall survival and a higher probability to develop skin irAEs during anti-PD1/PD-L1 treatment

Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors

Background: Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs. Methods: In this prospective multi-center study, we combined a multi-omics approach including unbiased single-cell profiling of over 300 peripheral blood mononuclear cell (PBMC) samples and high-throughput proteomics analysis of over 500 serum samples to characterize the systemic immune compartment of patients with melanoma or NSCLC before and during treatment with ICIs. Findings: When we combined the parameters obtained from the multi-omics profiling of patient blood and serum, we identified potential predictive biomarkers for ICI-induced irAEs. Specifically, an early increase in CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks after the start of therapy are likely indicators of heightened risk of developing irAEs. In addition, an early expansion of Ki-67+ regulatory T cells (Tregs) and Ki-67+ CD8+ T cells is also likely to be associated with increased risk of irAEs. Conclusions: We suggest that the combination of these cellular and proteomic biomarkers may help to predict which patients are likely to benefit most from ICI therapy and those requiring intensive monitoring for irAEs. Funding: This work was primarily funded by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, and the Forschungsförderung of the Kantonsspital St. Gallen

Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors.

BACKGROUND Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs. METHODS In this prospective multi-center study, we combined a multi-omics approach including unbiased single-cell profiling of over 300 peripheral blood mononuclear cell (PBMC) samples and high-throughput proteomics analysis of over 500 serum samples to characterize the systemic immune compartment of patients with melanoma or NSCLC before and during treatment with ICIs. FINDINGS When we combined the parameters obtained from the multi-omics profiling of patient blood and serum, we identified potential predictive biomarkers for ICI-induced irAEs. Specifically, an early increase in CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks after the start of therapy are likely indicators of heightened risk of developing irAEs. In addition, an early expansion of Ki-67+ regulatory T cells (Tregs) and Ki-67+ CD8+ T cells is also likely to be associated with increased risk of irAEs. CONCLUSIONS We suggest that the combination of these cellular and proteomic biomarkers may help to predict which patients are likely to benefit most from ICI therapy and those requiring intensive monitoring for irAEs. FUNDING This work was primarily funded by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, and the Forschungsförderung of the Kantonsspital St. Gallen

Community detection in graphs

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.Comment: Review article. 103 pages, 42 figures, 2 tables. Two sections expanded + minor modifications. Three figures + one table + references added. Final version published in Physics Report

Ocular Adverse Events Induced by Immune Checkpoint Inhibitors: A Comprehensive Pharmacovigilance Analysis

PURPOSE Characterize ocular adverse events (oAEs) caused by immune checkpoint inhibitors (ICIs). METHODS Retrospective analysis of 41,674 cancer patients in the FDA Adverse Event Reporting System (FAERS) pharmacovigilance database receiving anti-PD-1/PD-L1, anti-CTLA-4, or anti-PD-1+ anti-CTLA-4 combination. Reporting odds ratio (ROR) was used to approximate oAE rate across regimens and indications. RESULTS The most common indications were lung cancer (27.3%) and melanoma (22.7%); 76.3% received anti-PD-1/PD-L1 monotherapy. 1,268 patients (3.0%) reported oAEs, namely vision disorders (30.8%), uveitis (15.1%), and retinal, lacrimal, and optic nerve disorders (10.7%, 9.0%, 8.4%). Melanoma showed the highest proportion of uveitis (117/9,471 cases; 1.2%). Addition of anti-CTLA-4 to anti-PD-1 increased the ROR of uveitis from 4.77 (95% CI 3.83-5.94) to 17.1 (95% CI 12.9-22.7). Among anti-PD-1/PD-L1 cases, uveitis was differentially reported in melanoma (ROR 14.7, 95% CI 10.7-20.2) compared with lung cancer (ROR 2.67, 95% CI 1.68-4.23). CONCLUSION ICI-induced oAEs are rare, and uveitis is significantly associated with melanoma and anti-PD-1+ anti-CTLA-4 combination

Survival-Inferred Fragility Index of Phase 3 Clinical Trials Evaluating Immune Checkpoint Inhibitors

Importance In science and medical research, extreme and dichotomous conclusions may be drawn based on whether the P value falls above or below the threshold. The fragility index (ie, the minimum number of changes from nonevents to events resulting in loss of statistical significance) captures the vulnerability of statistics in trials with binary outcomes. There are a growing number of clinical trials of immune checkpoint inhibitors (ICIs), as well as expanding eligibility for patients to receive them. The robustness of survival outcomes in randomized clinical trials (RCTs) should be evaluated using the fragility index extended to time-to-event data. Objective To calculate the fragility of survival data in RCTs evaluating ICIs. Design, Setting, and Participants In this cross-sectional study, data on phase 3 prospective RCTs investigating ICIs included in PubMed from inception until January 1, 2020, were extracted. Two- or three-group studies reporting results for overall survival were eligible for the survival-inferred fragility index (SIFI) calculation, which is the minimum number of reassignments of the best survivors from the interventional group to the control group resulting in loss of significance (defined as P < .05 by log-rank test). For nonsignificant results, a negative SIFI was calculated by reversing the direction of reassignment (from the control group to the interventional group). Main Outcomes and Measures Survival-inferred fragility index. Results A total of 45 phase 3 prospective RCTs (4 of which had 3 groups, for a total of 49 groups) were identified, of which 6 (13%) investigated anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) agents, 25 (56%) investigated anti-programmed cell death 1 (PD-1) agents, 12 (27%) investigated anti-programmed cell death 1 ligand 1 agents, and 3 (7%) investigated the combination of anti-CTLA-4 and anti-PD-1 agents. The median SIFI was 5 (interquartile range, -4 to 12) for the intention-to-treat analysis; for these trials, the SIFI was 1% or less of the total sample size in 17 of 49 populations (35%). In 25 of the 49 intention-to-treat populations (51%), the SIFI was less than the number of censored patients in the intervention group shortly after randomization (defined as <5% of the follow-up time). Conclusions and Relevance This study suggests that many phase 3 RCTs evaluating ICI therapies have a low SIFI for overall survival, resulting in uncertainty regarding their potential clinical benefit. Although not a definitive solution for the problems arising from dichotomization, SIFI provides an additional means of assessing and communicating the strength of statistical conclusions

Association Between Immune-Related Adverse Events During Anti–PD-1 Therapy and Tumor Mutational Burden

Immune checkpoint inhibitors (ICIs) that target the programmed death 1 receptor (anti–programmed cell death 1 [PD-1] therapy) have ushered in a new era of cancer therapy. However, their application has been curtailed by serious immune-related adverse events (irAEs), such as colitis, pneumonitis, and myocarditis, that remain largely unpredictable. Although the use of tumor mutational burden (TMB) as a biomarker for expected therapy response has been advocated,1 a similar parameter for irAEs is lacking. In an attempt to fill this clinically relevant knowledge gap, we investigated the association between irAEs reported during anti–PD-1 therapy and TMB by comparing large-scale surveillance data of irAEs with the median TMB across multiple cancer types. Methods We retrieved postmarketing data of adverse events from the US Food and Drug Administration Adverse Event Reporting System (FAERS) from July 1, 2014, to March 31, 2019. According to the ethics committee policy of the EKOS (Ethikkommission Ostschweiz, Switzerland), this study was exempt from ethical review because all analyzed datasets are deidentified and publicly available. We considered only reports for which the anti–PD-1 agents nivolumab or pembrolizumab were the suspected cause of adverse events. Anti–PD-1 and anti-cytotoxic T-lymphocyte–associated protein 4 combination treatment was excluded. Closely related indications were aggregated to unified terms; for example, “malignant melanoma” was aggregated to “melanoma.” To limit our analysis to irAEs, we filtered terms to match broadly accepted diagnoses that were outlined in peer-reviewed irAE management guidelines. The median TMB in tumor tissue was obtained from previously published comprehensive genomic profiling.2,3 Lastly, we only considered cancers for which there were at least 100 cases of adverse events during anti–PD-1 therapy reported in FAERS. To assess the risk of a patient developing any irAE, we estimated reporting odds ratios (RORs) by comparing the odds of reporting these irAEs rather than others for the anti–PD-1 agents with the odds for all other drugs in the database, which represents standard practice for quantitative analyses of data in FAERS and similar databases.4 Results Our search strategy identified a total of 47 304 adverse events (AEs) in 16 397 patients reported as treated with anti–PD-1 monotherapy for 19 different cancer types. Of these patients, 3661 had at least 1 irAE (22.3%; 95% CI, 21.7-23.0). The comparator group comprised 16 411 749 AE reports from 5 160 064 patients. Our analysis revealed a significant positive correlation between the ROR of reporting an irAE during anti–PD-1 therapy and the corresponding TMB across multiple cancer types, with a higher ROR of irAE associated with a higher median number of coding somatic mutations per megabase of DNA (Figure; Pearson correlation coefficient R = 0.704; P < .001). The correlation coefficient suggests that 50% of the differences in the irAE risk across cancer types may be attributed to the TMB. Discussion Our analysis indicates that cancers with a high TMB, such as melanoma and non–small cell lung cancer, are associated with a higher irAE ROR during anti–PD-1 therapy, strongly suggesting that these cancers are associated with a higher risk of irAEs than cancers with a low TMB. A possible explanation for this finding may be the different neoantigenic load across cancer types. Additionally, studies have shown that T cells that react against a neoantigen can crossreact against the corresponding wild-type protein.5 Another contributing mechanism may be antigen spreading, where tumor cell death releases antigens, including neoantigens, that prime lymphocytes against the wild-type antigens in healthy tissue. Given the results of the analysis, we propose that the association between irAEs and improved response to anti–PD-1 treatment are linked via an underlying neoantigenic potential that stems from a high TMB. A limitation of the study is the use of spontaneous reports for indirectly measuring the risk of irAE. Furthermore, patients with cancers with a high TMB may receive a longer course of anti–PD-1 treatment. However, most irAEs reported during anti–PD-1 therapy develop within the first few weeks of treatment.6 This finding suggests that therapy duration is unlikely to influence the statistical outcome. In conclusion, a high TMB may be a useful biomarker for assessing patients’ risk of irAEs during anti–PD-1 therapy, which has particular relevance for vulnerable patient groups

Individualized prediction of leukemia-free survival after autologous stem cell transplantation in acute myeloid leukemia

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Tumor infiltrating lymphocytes in lymph node metastases of stage III melanoma correspond to response and survival in nine patients treated with ipilimumab at the time of stage IV disease

Prognosis of metastatic melanoma improved with the development of checkpoint inhibitors. The role of tumor infiltrating lymphocytes (TILs) in lymph node metastases of stage III melanoma remains unclear. We retrospectively characterized TILs in primary melanomas and matched lymph node metastases (stage III melanoma) of patients treated with the checkpoint inhibitor ipilimumab. Tumor infiltrating lymphocytes were characterized for CD3, CD4, and CD8 expressions by immunohistochemistry. 4/9 patients (44%) responded to treatment with ipilimumab (1 complete and 2 partial remissions, 1 stable disease). All responders exhibited CD4 and CD8 T-cell infiltration in their lymph node metastases, whereas all non-responders did not show an infiltration of the lymph node metastasis with TILs. The correlation between the presence and absence of TILs in responders vs. non-responders was statistically significant (p = 0.008). Median distant metastases free survival, i.e., progression from stage III to stage IV melanoma, was similar in responders and non-responders (22.1 vs. 19.3 months; p = 0.462). Median progression free and overall survival show a trend in favor of the patients having TIL rich lymph node metastases (6.8 vs. 3.3 months, p = 0.09; and all alive at last follow-up vs. 8.2 months, respectively, p = 0.08). Our data suggest a correlation between the T-cell infiltration of the lymph node metastases in stage III melanoma and the response to ipilimumab once these patients progress to stage IV disease