Two subtypes of cutaneous melanoma with distinct mutational signatures and clinico-genomic characteristics

Mutational signatures of colorectal cancers according to distinct computational workflows

Tumor mutational signatures have gained prominence in cancer research, yet the lack of standardized methods hinders reproducibility and robustness. Leveraging colorectal cancer (CRC) as a model, we explored the influence of computational parameters on mutational signature analyses across 230 CRC cell lines and 152 CRC patients. Results were validated in three independent datasets: 483 endometrial cancer patients stratified by mismatch repair (MMR) status, 35 lung cancer patients by smoking status and 12 patient-derived organoids (PDOs) annotated for colibactin exposure. Assessing various bioinformatic tools, reference datasets and input data sizes including whole genome sequencing, whole exome sequencing and a pan-cancer gene panel, we demonstrated significant variability in the results. We report that the use of distinct algorithms and references led to statistically different results, highlighting how arbitrary choices may induce variability in the mutational signature contributions. Furthermore, we found a differential contribution of mutational signatures between coding and intergenic regions and defined the minimum number of somatic variants required for reliable mutational signature assignment. To facilitate the identification of the most suitable workflows, we developed Comparative Mutational Signature analysis on Coding and Extragenic Regions (CoMSCER), a bioinformatic tool which allows researchers to easily perform comparative mutational signature analysis by coupling the results from several tools and public reference datasets and to assess mutational signature contributions in coding and non-coding genomic regions. In conclusion, our study provides a comparative framework to elucidate the impact of distinct computational workflows on mutational signatures.

Melanoma Incidence Rates Among Non-Hispanic American Indian/Alaska Native Individuals, 1999-2019

Importance

Non-Hispanic American Indian/Alaska Native people have the second highest incidence rate of invasive cutaneous melanoma in the US after non-Hispanic White people.

Objective

To examine invasive cutaneous melanoma incidence rates and trends over time among non-Hispanic American Indian/Alaska Native people.

Design, Setting, and Participants

This descriptive, observational cross-sectional study used population-based cancer registry data (US Cancer Statistics AI/AN Incidence Analytic Database) linked to the Indian Health Service administrative database to examine incidence rates by age, sex, region, histology, tumor site, stage, and other demographic and clinical characteristics. The study examined trends from 1999 to 2019 time period by age, sex, stage at diagnosis, and region. Non-Hispanic American Indian/Alaska Native people 15 years and older who received a diagnosis of invasive cutaneous melanoma from 1999 to 2019 who were members of federally recognized tribes and resided in Indian Health Service purchased/referred care delivery areas were included in this study to reduce racial misclassification and provide more accurate rates. The data were analyzed in 2022.

Exposures

Demographic and clinical characteristics, such as age, sex, geographic region, histology, stage, and tumor site.

Main Outcomes and Measures

Invasive cutaneous melanoma incidence rates by age group, sex, region, resident county characteristics (poverty level, rurality, education level, and socioeconomic status), stage at diagnosis, tumor site, and histology. Trends over time by age, sex, region, and stage.

Results

From 1999 to 2019, 2151 non-Hispanic American Indian/Alaska Native people (1021 female individuals [47.5%]) received a diagnosis of incident cutaneous melanoma (rate, 10.7 per 100 000; 95% CI, 10.3-11.2). Rates were higher among male than female individuals (13.0 [95% CI, 12.2-13.8] vs 9.2 [95% CI, 8.6-9.8]) and for people 55 years and older (24.2; 95% CI, 22.8-25.7) compared with those aged 15 to 39 years (3.5; 95% CI, 3.2-3.9). Rates were highest for male individuals 55 years and older (34.5; 95% CI, 31.8-37.3) and people living in the Southern Plains (male individuals: 23.8; 95% CI, 21.5-26.2; female individuals: 15.5; 95% CI, 14.0-17.2) and Pacific Coast region (male individuals: 16.5; 95% CI, 14.5-18.7; female individuals: 12.3; 95% CI, 10.9-13.9). Rates increased among female individuals from 1999 to 2019 (average annual percent change [AAPC], 2.5; P < .001); among regional/distant stage tumors (AAPC, 2.5; P = .01) and people 55 years and older (AAPC, 2.8; P = .001).

Conclusions and Relevance

The results of this study suggest that additional studies could potentially identify risk factors among non-Hispanic American Indian/Alaska Native people.

Biomarker-Driven Personalization of Neoadjuvant Immunotherapy in Melanoma

The introduction of immunotherapy has ushered in a new era of anticancer therapy for many cancer types including melanoma. Given the increasing development of novel compounds and combinations and the investigation in earlier disease stages, the need grows for biomarker-based treatment personalization. Stage III melanoma is one of the front-runners in the neoadjuvant immunotherapy field, facilitating quick biomarker identification by its immunogenic capacity, homogeneous patient population, and reliable efficacy readout. In this review, we discuss potential biomarkers for response prediction to neoadjuvant immunotherapy, and how the neoadjuvant melanoma platform could pave the way for biomarker identification in other tumor types.

SIGNIFICANCE

In accordance with the increasing rate of therapy development, the need for biomarker-driven personalized treatments grows. The current landscape of neoadjuvant treatment and biomarker development in stage III melanoma can function as a poster child for these personalized treatments in other tumors, assisting in the development of new biomarker-based neoadjuvant trials. This will contribute to personalized benefit-risk predictions to identify the most beneficial treatment for each patient.

A self-assembling CXCR4-targeted pyroptosis nanotoxin for melanoma therapy

While immunotherapy has emerged as a promising strategy to treat melanoma, the limited availability of immunotherapeutic agents in tumors due to the immunosuppressive tumor microenvironment dampens its efficacy. Pyroptosis is a gasdermin-mediated programmed necrosis that triggers the inflammatory tumor microenvironment and enhances the efficacy of tumor immunotherapy. Here, we prove that the CXCR4 antagonist T22 peptide specially targeted and became internalized into CXCR4⁺ melanoma cells. Then we report a self-assembling nanotoxin that can be used to spatiotemporally target CXCR4-expression melanoma cells and enable tunable cellular pyroptosis. Specific activation of caspase 3 signal transduction triggers gasdermin-E-mediated pyroptosis. This nanotoxin induces pyroptotic cell death resulting in enhanced antitumor efficacy and minimized systemic side effects toward melanoma in vivo. This study offers new insights into how to engineer nanotoxins with tunable pyroptosis activity through specifically targeting CXCR4 for biomedical applications.

The Analysis of Trends in Survival for Patients with Melanoma Brain Metastases with Introduction of Novel Therapeutic Options before the Era of Combined Immunotherapy-Multicenter Italian-Polish Report

Stage IV melanoma patients develop melanoma brain metastases (MBM) in 50% of cases. Their prognosis is improving, and its understanding outside the context of clinical trials is relevant. We have retrospectively analyzed the clinical data, course of treatment, and outcomes of 531 subsequent stage IV melanoma patients with BM treated in five reference Italian and Polish melanoma centers between 2014 and 2021. Patients with MBM after 2017 had a better prognosis, with a significantly improved median of overall survival (OS) after 2017 in the worst mol-GPA prognostic groups (mol-GPA ≤ 2): a median OS >6 months and HR 0.76 vs. those treated before 2017 (CI: 0.60−0.97, p = 0.027). In our prognostic model, mol-GPA was highly predictive for survival, and symptoms without steroid use did not have prognostic significance. Local therapy significantly improved survival regardless of the year of diagnosis (treated before or after 2017), with median survival >12 months. Systemic therapy improved outcomes when it was combined with local therapy. Local surgery was associated with improved OS regardless of the timing related to treatment start (i.e., before or after 30 days from MBM diagnosis). Local and systemic treatment significantly prolong survival for the poorest mol-GPA prognosis. Use of modern treatment modalities is justified in all mol-GPA prognostic groups.