De novo autoimmune connective tissue disease and mortality in patients treated with anti-PD-1 and anti-PD-L1 therapy: a population-level cohort study

Using a population-level cohort analysis, our study demonstrates that though rare, de novo autoimmune cutaneous connective tissue disorders (AiCTD) in the setting of immune checkpoint inhibitors (ICI) are not associated with a greater risk of mortality and are overall approaching a statistically significant decrease in mortality when compared to ICI-treated patients without cutaneous immune-related adverse events. These findings are significant and highly relevant to dermatologists and oncologists caring for ICI recipients as it adds to the limited information on development of cutaneous AiCTD following ICI administration, for which enhanced understanding is critical to improving the care for this challenging patient population.

Comprehensive plasma cytokine and chemokine profiling in prurigo nodularis reveals endotypes in Type 2 inflammation

Prurigo nodularis (PN) is a chronic inflammatory skin disease that is associated with variability in peripheral blood eosinophil levels and response to T-helper 2 targeted therapies (Th2). Our objective was to determine whether circulating immune profiles with respect to type 2 inflammation differ by race and peripheral blood eosinophil count. Plasma from 56 PN patients and 13 matched healthy controls was assayed for 54 inflammatory biomarkers. We compared biomarker levels between PN and HCs, among PN patients based on absolute eosinophil count, and across racial groups in PN. Eleven biomarkers were elevated in PN versus HCs including interleukin (IL)-12/IL-23p40, tumor necrosis factor-alpha (TNF-α), Thymic stromal lymphopoietin (TSLP), and macrophage-derived chemokine (MDC/CCL22). Additionally, PN patients with AEC > 0.3 K cells/μL had higher Th2 markers (eotaxin, eotaxin-3, TSLP, MCP-4/CCL13), and African American PN patients had lower eosinophils, eotaxin, and eotaxin-3 versus Caucasian and Asian PN patients (p < 0.05 for all). Dupilumab responders had higher AEC (p < 0.01), were more likely to be Caucasian (p = 0.02) or Asian (p = 0.05) compared to African Americans, and more often had a history of atopy (p = 0.08). This study suggests that blood AEC > 0.3 K and Asian and Caucasian races are associated with Th2 skewed circulating immune profiles and response to Th2 targeted therapies.

Cancer Type and Histology Influence Cutaneous Immunotherapy Toxicities: A Multi-Institutional Cohort Study

BACKGROUND

Cutaneous immune-related adverse events (cirAEs) are the most common toxicities to occur in the setting of immune checkpoint inhibitor (ICI) therapy. Identifying patients who are at increased risk of developing cirAEs may improve quality of life and outcomes.

OBJECTIVE

To investigate the influence of cancer type and histology on the development of cirAEs in the setting of ICI therapy and survival outcomes.

METHODS

This retrospective cohort study included patients between December 1, 2011, and October 30, 2020. They received ICIs from 2011-2020 with follow-up of outcomes through October 2021. We identified 3,668 ICI recipients who were seen at Mass General Brigham and Dana-Farber. Of these, 669 developed cirAEs. Records that were incomplete or categories of insufficient sample size were excluded from the study cohort. Multivariate Cox proportional hazards models were utilized to investigate the impact of cancer organ system and histology on cirAE development, after adjusting for demographics, Charlson Comorbidity Index, ICI type, cancer stage at ICI initiation, and year of ICI initiation. Time-varying Cox proportional hazards modeling was utilized to examine the impact of cirAE development on mortality.

RESULTS

Compared to other non-epithelial cancers (neuroendocrine, leukemia, lymphoma, myeloma, sarcoma, and central nervous system malignancies), cutaneous squamous cell carcinoma (cSCC) (HR = 3.57, p < 0.001), melanoma (HR = 2.09, p < 0.001), head and neck adenocarcinoma (HR = 2.13, p = 0.009), genitourinary transitional cell carcinoma (HR = 2.15, p < 0.001), and genitourinary adenocarcinoma (HR = 1.53, p = 0.037) were at significantly higher risk of cirAEs in multivariate analyses. The increased risk of cirAEs translated into an adjusted survival benefit for melanoma (HR = 0.37, p < 0.001) and cSCC (HR = 0.51, p = 0.011).

CONCLUSIONS

The highest rate of cirAEs and subsequent survival benefits were observed in cutaneous malignancies treated with ICIs. This study improves our understanding of patients who are at highest risk of developing cirAEs and would, therefore, benefit from appropriate counseling and closer monitoring by their oncologists and dermatologists throughout their ICI therapy. Limitations include its retrospective nature and cohort from one geography.

Development and validation of time-to-event models to predict metastatic recurrence of localized cutaneous melanoma

BACKGROUND

The recent expansion of immunotherapy for stage IIB/IIC melanoma highlights a growing clinical need to identify patients at high risk of metastatic recurrence and, therefore, most likely to benefit from this therapeutic modality.

OBJECTIVE

To develop time-to-event risk prediction models for melanoma metastatic recurrence.

METHODS

Patients diagnosed with stage I/II primary cutaneous melanoma between 2000 and 2020 at Mass General Brigham and Dana-Farber Cancer Institute were included. Melanoma recurrence date and type were determined by chart review. Thirty clinicopathologic factors were extracted from electronic health records. Three types of time-to-event machine-learning models were evaluated internally and externally in the distant versus locoregional/nonrecurrence prediction.

RESULTS

This study included 954 melanomas (155 distant, 163 locoregional, and 636 1:2 matched nonrecurrences). Distant recurrences were associated with worse survival compared to locoregional/nonrecurrences (HR: 6.21, P < .001) and to locoregional recurrences only (HR: 5.79, P < .001). The Gradient Boosting Survival model achieved the best performance (concordance index: 0.816; time-dependent AUC: 0.842; Brier score: 0.103) in the external validation.

LIMITATIONS

Retrospective nature and cohort from one geography.

CONCLUSIONS

These results suggest that time-to-event machine-learning models can reliably predict the metastatic recurrence from localized melanoma and help identify high-risk patients who are most likely to benefit from immunotherapy.

A Polygenic Risk Score for Predicting Racial and Genetic Susceptibility to Prurigo Nodularis

Prurigo nodularis (PN) is an understudied inflammatory skin disease characterized by pruritic, hyperkeratotic nodules. Identifying the genetic factors underlying PN could help to better understand its etiology and guide the development of therapies. In this study, we developed a polygenic risk score that predicts a diagnosis of PN (OR = 1.41, P = 1.6 × 10-5) in two independent and continentally distinct populations. We also performed GWASs, which uncovered genetic variants associated with PN, including one near PLCB4 (rs6039266: OR = 3.15, P = 4.8 × 10-8) and others near TXNRD1 (rs34217906: OR = 1.71, P = 6.4 × 10-7; rs7134193: OR = 1.57, P = 1.1 × 10-6). Finally, we discovered that Black patients have over a two-times greater genetic risk of developing PN (OR = 2.63, P = 7.8 × 10-4). Combining the polygenic risk score and self-reported race together was significantly predictive of PN (OR = 1.32, P = 4.7 × 10-3). Strikingly, this association was more significant with race than after adjusting for genetic ancestry. Because race is a sociocultural construct and not a genetically bound category, our findings suggest that genetics, environmental influence, and social determinants of health likely affect the development of PN and may contribute to clinically observed racial disparities.

Use of 3-Dimensional Stereophotogrammetry to Detect Disease Progression in Craniofacial Morphea

Importance

Objectively determining disease progression in craniofacial morphea (CM) is challenging, as clinical findings of disease activity are often lacking.

Objective

To evaluate the utility of 3-dimensional (3D) stereophotogrammetry in detecting disease progression in CM over time.

Design, Setting, and Participants

This prospective cohort study included 27 pediatric and adult patients with CM from 2 hospitals in Boston (Boston Children's Hospital and Brigham & Women's Hospital) consecutively enrolled from April 1, 2019, to March 1, 2023. Review of 3D stereophotogrammetry images and data analysis occurred from March 1 to April 1, 2023.

Main Outcomes and Measures

Clinical and 3D stereophotogrammetry assessments were performed at 2- to 12-month intervals, depending on the clinical context. The 3D stereophotogrammetry images were then qualitatively rated as demonstrating no progression or definitive progression by an expert (board-certified plastic craniofacial surgeon) and nonexpert (board-certified dermatologist) in 3D stereophotogrammetry. In addition, κ coefficients were calculated for interrater reliability.

Results

Of 27 patients with CM (19 female; median age, 14 [range, 5-40] years) and 3D stereophotogrammetry images obtained from a minimum of 2 time points (median, 4 [range, 2-10] images) spaced a median of 3 (range, 2-12) months apart, 10 experienced progression of their disease based on clinical assessments performed during the study period. In all cases in which clinical progression was favored, blinded qualitative assessment of 3D stereophotogrammetry images also favored progression with substantial interrater reliability (κ = 0.80 [95% CI, 0.61-0.99]). Furthermore, review of 3D stereophotogrammetry detected occult progression of asymmetry not noted on clinical examination in 3 additional patients.

Conclusions and Relevance

In this prospective cohort study, blinded assessment of sequential 3D stereophotogrammetry images in patients with CM not only corroborated clinical assessment of disease progression but also detected occult progression of facial asymmetry not appreciable on clinical examination alone. Therefore, 3D stereophotogrammetry may serve as a useful adjunct to clinical examination of patients with CM over time. Future investigations are warranted to validate 3D stereophotogrammetry as an outcome measure in CM.

Anifrolumab for Adolescent Discoid Lupus Erythematosus

This case series describes the outcomes among adolescent patients with systemic lupus erythematosus and refractory discoid lupus erythematosus treated with anifrolumab.

Somatic mutations reveal hyperactive Notch signaling and racial disparities in prurigo nodularis

Prurigo nodularis (PN) is a chronic inflammatory skin disease that disproportionately affects African Americans and is characterized by pruritic skin nodules of unknown etiology. Little is known about genetic alterations in PN pathogenesis, especially relating to somatic events which are often implicated in inflammatory conditions. We thus performed whole-exome sequencing on 54 lesional and nonlesional skin biopsies from 17 PN patients and 10 atopic dermatitis (AD) patients for comparison. Somatic mutational analysis revealed that PN lesional skin harbors pervasive somatic mutations in fibrotic, neurotropic, and cancer-associated genes. Nonsynonymous mutations were most frequent in NOTCH1 and the Notch signaling pathway, a regulator of cellular proliferation and tissue fibrosis, and NOTCH1 mutations were absent in AD. Somatic copy-number analysis, combined with expression data, showed that recurrently deleted and downregulated genes in PN lesional skin are associated with axonal guidance and extension. Follow-up immunofluorescence validation demonstrated increased NOTCH1 expression in PN lesional skin fibroblasts and increased Notch signaling in PN lesional dermis. Finally, multi-center data revealed a significantly increased risk of NOTCH1-associated diseases in PN patients. In characterizing the somatic landscape of PN, we uncover novel insights into its pathophysiology and identify a role for dysregulated Notch signaling in PN.

Germline variants associated with toxicity to immune checkpoint blockade

Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3-5) and (2) all-grade events. We identified 3 genome-wide significant associations (P < 5 × 10-8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined P = 3.6 × 10-11; hazard ratio (HR) = 2.1); rs75824728 near IL22RA1 (combined P = 3.5 × 10-8; HR = 1.8); and rs113861051 on 4p15 (combined P = 1.2 × 10-8, HR = 2.0); rs16906115 was replicated in 3 independent studies. The association near IL7 colocalized with the gain of a new cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation, which was itself predictive of downstream irAEs and improved survival.

iCAT: diagnostic assessment tool of immunological history using high-throughput T-cell receptor sequencing

The pathogen exposure history of an individual is recorded in their T-cell repertoire and can be accessed through the study of T-cell receptors (TCRs) if the tools to identify them were available. For each T-cell, the TCR loci undergoes genetic rearrangement that creates a unique DNA sequence. In theory these unique sequences can be used as biomarkers for tracking T-cell responses and cataloging immunological history. We developed the immune Cell Analysis Tool (iCAT), an R software package that analyzes TCR sequencing data from exposed (positive) and unexposed (negative) samples to identify TCR sequences statistically associated with positive samples. The presence and absence of associated sequences in samples trains a classifier to diagnose pathogen-specific exposure. We demonstrate the high accuracy of iCAT by testing on three TCR sequencing datasets. First, iCAT successfully diagnosed smallpox vaccinated versus naïve samples in an independent cohort of mice with 95% accuracy. Second, iCAT displayed 100% accuracy classifying naïve and monkeypox vaccinated mice. Finally, we demonstrate the use of iCAT on human samples before and after exposure to SARS-CoV-2, the virus behind the COVID-19 global pandemic. We were able to correctly classify the exposed samples with perfect accuracy. These experimental results show that iCAT capitalizes on the power of TCR sequencing to simplify infection diagnostics. iCAT provides the option of a graphical, user-friendly interface on top of usual R interface allowing it to reach a wider audience.

MegaR: an interactive R package for rapid sample classification and phenotype prediction using metagenome profiles and machine learning

BACKGROUND

Diverse microbiome communities drive biogeochemical processes and evolution of animals in their ecosystems. Many microbiome projects have demonstrated the power of using metagenomics to understand the structures and factors influencing the function of the microbiomes in their environments. In order to characterize the effects from microbiome composition for human health, diseases, and even ecosystems, one must first understand the relationship of microbes and their environment in different samples. Running machine learning model with metagenomic sequencing data is encouraged for this purpose, but it is not an easy task to make an appropriate machine learning model for all diverse metagenomic datasets.

RESULTS

We introduce MegaR, an R Shiny package and web application, to build an unbiased machine learning model effortlessly with interactive visual analysis. The MegaR employs taxonomic profiles from either whole metagenome sequencing or 16S rRNA sequencing data to develop machine learning models and classify the samples into two or more categories. It provides various options for model fine tuning throughout the analysis pipeline such as data processing, multiple machine learning techniques, model validation, and unknown sample prediction that can be used to achieve the highest prediction accuracy possible for any given dataset while still maintaining a user-friendly experience.

CONCLUSIONS

Metagenomic sample classification and phenotype prediction is important particularly when it applies to a diagnostic method for identifying and predicting microbe-related human diseases. MegaR provides various interactive visualizations for user to build an accurate machine-learning model without difficulty. Unknown sample prediction with a properly trained model using MegaR will enhance researchers to identify the sample property in a fast turnaround time.

Parallel Concerted Evolution of Ribosomal Protein Genes in Fungi and Its Adaptive Significance

Ribosomal protein (RP) genes encode structural components of ribosomes, the cellular machinery for protein synthesis. A single functional copy has been maintained in most of 78–80 RP families in animals due to evolutionary constraints imposed by gene dosage balance. Some fungal species have maintained duplicate copies in most RP families. The mechanisms by which the RP genes were duplicated and maintained and their functional significance are poorly understood. To address these questions, we identified all RP genes from 295 fungi and inferred the timing and nature of gene duplication events for all RP families. We found that massive duplications of RP genes have independently occurred by different mechanisms in three distantly related lineages: budding yeasts, fission yeasts, and Mucoromycota. The RP gene duplicates in budding yeasts and Mucoromycota were mainly created by whole genome duplication events. However, duplicate RP genes in fission yeasts were likely generated by retroposition, which is unexpected considering their dosage sensitivity. The sequences of most RP paralogs have been homogenized by repeated gene conversion in each species, demonstrating parallel concerted evolution, which might have facilitated the retention of their duplicates. Transcriptomic data suggest that the duplication and retention of RP genes increased their transcript abundance. Physiological data indicate that increased ribosome biogenesis allowed these organisms to rapidly consume sugars through fermentation while maintaining high growth rates, providing selective advantages to these species in sugar-rich environments.

Identifying and Tracking Low-Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing

Tracking antigen-specific T cell responses over time within individuals is difficult because of lack of knowledge of antigen-specific TCR sequences, limitations in sample size, and assay sensitivities. We hypothesized that analyses of high-throughput sequencing of TCR clonotypes could provide functional readouts of individuals' immunological histories. Using high-throughput TCR sequencing, we develop a database of TCRβ sequences from large cohorts of mice before (naive) and after smallpox vaccination. We computationally identify 315 vaccine-associated TCR sequences (VATS) that are used to train a diagnostic classifier that distinguishes naive from vaccinated samples in mice up to 9 months post-vaccination with >99% accuracy. We determine that the VATS library contains virus-responsive TCRs by in vitro expansion assays and virus-specific tetramer sorting. These data outline a platform for advancing our capabilities to identify pathogen-specific TCR sequences, which can be used to identify and quantitate low-frequency pathogen-specific TCR sequences in circulation over time with exceptional sensitivity.

Heterogeneous rates of genome rearrangement contributed to the disparity of species richness in Ascomycota

Background

Chromosomal rearrangements have been shown to facilitate speciation through creating a barrier of gene flow. However, it is not known whether heterogeneous rates of chromosomal rearrangement at the genome scale contributed to the huge disparity of species richness among different groups of organisms, which is one of the most remarkable and pervasive patterns on Earth. The largest fungal phylum Ascomycota is an ideal study system to address this question because it comprises three subphyla (Saccharomycotina, Taphrinomycotina, and Pezizomycotina) whose species numbers differ by two orders of magnitude (59,000, 1000, and 150 respectively).

Results

We quantified rates of genome rearrangement for 71 Ascomycota species that have well-assembled genomes. The rates of inter-species genome rearrangement, which were inferred based on the divergence rates of gene order, are positively correlated with species richness at both ranks of subphylum and class in Ascomycota. This finding is further supported by our quantification of intra-species rearrangement rates based on paired-end genome sequencing data of 216 strains from three representative species, suggesting a difference of intrinsic genome instability among Ascomycota lineages. Our data also show that different rates of imbalanced rearrangements, such as deletions, are a major contributor to the heterogenous rearrangement rates.

Conclusions

Various lines of evidence in this study support that a higher rate of rearrangement at the genome scale might have accelerated the speciation process and increased species richness during the evolution of Ascomycota species. Our findings provide a plausible explanation for the species disparity among Ascomycota lineages, which will be valuable to unravel the underlying causes for the huge disparity of species richness in various taxonomic groups.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4683-0) contains supplementary material, which is available to authorized users.