Clinical and Genetic Tumor Characteristics of Responding and Non-Responding Patients to PD-1 Inhibition in Hepatocellular Carcinoma.

Immune checkpoint inhibitors (ICIs) belong to the therapeutic armamentarium in advanced hepatocellular carcinoma (HCC). However, only a minority of patients benefit from immunotherapy. Therefore, we aimed to identify indicators of therapy response. This multicenter analysis included 99 HCC patients. Progression-free (PFS) and overall survival (OS) were studied by Kaplan-Meier analyses for clinical parameters using weighted log-rank testing. Next-generation sequencing (NGS) was performed in a subset of 15 patients. The objective response (OR) rate was 19% median OS (mOS)16.7 months. Forty-one percent reached a PFS > 6 months; these patients had a significantly longer mOS (32.0 vs. 8.5 months). Child-Pugh (CP) A and B patients showed a mOS of 22.1 and 12.1 months, respectively. Ten of thirty CP-B patients reached PFS > 6 months, including 3 patients with an OR. Tumor mutational burden (TMB) could not predict responders. Of note, antibiotic treatment within 30 days around ICI initiation was associated with significantly shorter mOS (8.5 vs. 17.4 months). Taken together, this study shows favorable outcomes for OS with low AFP, OR, and PFS > 6 months. No specific genetic pattern, including TMB, could identify responders. Antibiotics around treatment initiation were associated with worse outcome, suggesting an influence of the host microbiome on therapy success

Patients' and dermatologists' preferences in artificial intelligence–driven skin cancer diagnostics: a prospective multicentric survey study

To the Editor: Artificial intelligence (AI) has shown promise for improving diagnostics of skin cancer by matching or surpassing experienced clinicians.1 However, the successful clinical application depends on acceptance by patients and dermatologists. In this prospective multicentric survey study with a response rate of 63%, we therefore investigate the criteria required for patients and dermatologists to accept AI-systems and assess their importance on patients’ and dermatologists’ decision-making when considering the use of such systems. To this end, we perform an adaptive choice-based conjoint analysis and analyze it using hierarchical Bayes estimation.2 By employing an adaptive choice-based conjoint analysis, we investigate multiple influencing AI-features simultaneously (see Table I) whilst accounting for possible trade-offs (see Fig 1). For details on questionnaire development, participant recruitment, and statistical analysis, see Supplementary Methods, available via Mendeley at https://data.mendeley.com/datasets/2chcwnhpwj/1

Distinct Mutation Patterns Reveal Melanoma Subtypes and Influence Immunotherapy Response in Advanced Melanoma Patients

The detection of somatic driver mutations by next-generation sequencing (NGS) is becoming increasingly important in the care of advanced melanoma patients. In our study, we evaluated the NGS results of 82 melanoma patients from clinical routine in 2017. Besides determining the tumor mutational burden (TMB) and annotation of all genetic driver alterations, we investigated their potential as a predictor for resistance to immune checkpoint inhibitors (ICI) and as a distinguishing feature between melanoma subtypes. Melanomas of unknown primary had a similar mutation pattern and TMB to cutaneous melanoma, which hints at its cutaneous origin. Besides the typical hotspot mutation in BRAF and NRAS, we frequently observed CDKN2A deletions. Acral and mucosal melanomas were dominated by CNV alterations affecting PDGFRA, KIT, CDK4, RICTOR, CCND2 and CHEK2. Uveal melanoma often had somatic SNVs in GNA11/Q and amplification of MYC in all cases. A significantly higher incidence of BRAF V600 mutations and EGFR amplifications, PTEN and TP53 deletions was found in patients with disease progression while on ICI. Thus, NGS might help to characterize melanoma subtypes more precisely and to identify possible resistance mechanisms to ICI therapy. Nevertheless, NGS based studies, including larger cohorts, are needed to support potential genetic ICI resistance mechanisms