Seasonal patterns of toxicity in melanoma patients treated with combination anti-PD-1 and anti-CTLA-4 immunotherapy.

BACKGROUND: Immune checkpoint inhibitors are frequently associated with the development of immunotherapy-related adverse events (irAEs). The exact etiology, including the role of environmental factors, remains incompletely understood. METHODS: We analyzed the records of 394 melanoma patients from three centers (northern and southern hemisphere). Patients had received at least one cycle of anti-PD-1/anti-CTLA-4 with a minimum follow-up of 3 months. We study the distribution and time to irAEs onset throughout the calendar year. RESULTS: 764 irAEs were recorded; the most frequent were skin rash (35%), hepatitis (32%) and colitis (30%). The irAEs incidence was the highest in autumn and winter, and the ratio for the 'number of irAEs' per 'therapies commenced' was the highest in winter and lowest in summer (2.4 and 1.7, respectively). Season-specific patterns in the time of irAEs onset were observed for pneumonitis (shorter time to onset in autumn, p = 0.025), hepatitis (shorter time to onset in spring, p = 0.016) and sarcoid-like immune reaction (shorter time to onset in autumn, p = 0.041). Season-specific patterns for early-onset irAEs were observed for hepatitis (spring, p = 0.023) and nephritis (summer, p = 0.017). Early-onset pneumonitis was more frequent in autumn-winter (p = 0.008) and early-onset nephritis in spring-summer (p = 0.004). CONCLUSIONS: Environmental factors that are associated with particular seasons may contribute to the development of certain irAEs and suggest the potential effect of environmental triggers. The identification of these factors may enhance preventive and therapeutic strategies to reduce the morbidity of irAEs.

Late-Stage Metastatic Melanoma Emerges through a Diversity of Evolutionary Pathways.

Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing samples from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery. We found KIT extrachromosomal DNA may have contributed to the lack of response to KIT inhibitors of a KIT-driven melanoma. At the lesion-level, MYC amplifications were enriched in ICI nonresponders. Single-cell sequencing revealed polyclonal seeding of metastases originating from clones with different ploidy in one patient. Finally, we observed that brain metastases that diverged early in molecular evolution emerge late in disease. Overall, our study illustrates the diverse evolutionary landscape of advanced melanoma. SIGNIFICANCE: Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense sampling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. See related commentary by Shain, p. 1294. This article is highlighted in the In This Issue feature, p. 1275.

The Genetic Evolution of Metastasis.

Cancer is an evolutionary process that is characterized by the emergence of multiple genetically distinct populations or clones within the primary tumor. Intratumor heterogeneity provides a substrate for the selection of adaptive clones, such as those that lead to metastasis. Comparative molecular studies of primary tumors and metastases have identified distinct genomic features associated with the development of metastases. In this review, we discuss how these insights could inform clinical decision-making and uncover rational antimetastasis treatment strategies.

Assessment of the gene mosaicism burden in blood and its implications for immune disorders.

There are increasing evidences showing the contribution of somatic genetic variants to non-cancer diseases. However, their detection using massive parallel sequencing methods still has important limitations. In addition, the relative importance and dynamics of somatic variation in healthy tissues are not fully understood. We performed high-depth whole-exome sequencing in 16 samples from patients with a previously determined pathogenic somatic variant for a primary immunodeficiency and tested different variant callers detection ability. Subsequently, we explored the load of somatic variants in the whole blood of these individuals and validated it by amplicon-based deep sequencing. Variant callers allowing low frequency read thresholds were able to detect most of the variants, even at very low frequencies in the tissue. The genetic load of somatic coding variants detectable in whole blood is low, ranging from 1 to 2 variants in our dataset, except for one case with 17 variants compatible with clonal haematopoiesis under genetic drift. Because of the ability we demonstrated to detect this type of genetic variation, and its relevant role in disorders such as primary immunodeficiencies, we suggest considering this model of gene mosaicism in future genetic studies and considering revisiting previous massive parallel sequencing data in patients with negative results.

Comprehensive identification of somatic nucleotide variants in human brain tissue.

BACKGROUND: Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. RESULTS: Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. CONCLUSIONS: This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.