Distribution of a novel CYP2C haplotype in Native American populations.

The CYP2C19 gene, located in the CYP2C cluster, encodes the major drug metabolism enzyme CYP2C19. This gene is highly polymorphic and no-function (CYP2C19*2 and CYP2C19*3), reduced function (CYP2C19*9) and increased function (CYP2C19*17) star alleles (haplotypes) are commonly used to predict CYP2C19 metabolic phenotypes. CYP2C19*17 and the genotype-predicted rapid (RM) and ultrarapid (UM) CYP2C19 metabolic phenotypes are absent or rare in several Native American populations. However, discordance between genotype-predicted and pharmacokinetically determined CYP2C19 phenotypes in Native American cohorts have been reported. Recently, a haplotype defined by rs2860840T and rs11188059G alleles in the CYP2C cluster has been shown to encode increased rate of metabolism of the CYP2C19 substrate escitalopram, to a similar extent as CYP2C19*17. We investigated the distribution of the CYP2C:TG haplotype and explored its potential impact on CYP2C19 metabolic activity in Native American populations. The study cohorts included individuals from the One Thousand Genomes Project AMR superpopulation (1 KG_AMR), the Human Genome Diversity Project (HGDP), and from indigenous populations living in Brazil (Kaingang and Guarani). The frequency range of the CYP2C:TG haplotype in the study cohorts, 0.469 to 0.598, is considerably higher than in all 1 KG superpopulations (range: 0.014-to 0.340). We suggest that the high frequency of the CYP2C:TG haplotype might contribute to the reported discordance between CYP2C19-predicted and pharmacokinetically verified CYP2C19 metabolic phenotypes in Native American cohorts. However, functional studies involving genotypic correlations with pharmacokinetic parameters are warranted to ascertain the importance of the CYP2C:TG haplotype.

Tissue-specific metabolic profile drives iNKT cell function during obesity and liver injury.

Invariant natural killer T (iNKT) cells are a distinct population of lymphocytes characterized by their reactivity to glycolipids presented by CD1d. iNKT cells are found throughout the body, and little is known about their tissue-specific metabolic regulation. Here, we show that splenic and hepatic iNKT cells are metabolically comparable and rely on glycolytic metabolism to support their activation. Deletion of the pyruvate kinase M2 (Pkm2) gene in splenic and hepatic iNKT cells impairs their response to specific stimulation and their ability to mitigate acute liver injury. In contrast, adipose tissue (AT) iNKT cells exhibit a distinctive immunometabolic profile, with AMP-activated protein kinase (AMPK) being necessary for their function. AMPK deficiency impairs AT-iNKT physiology, blocking their capacity to maintain AT homeostasis and their ability to regulate AT inflammation during obesity. Our work deepens our understanding on the tissue-specific immunometabolic regulation of iNKT cells, which directly impacts the course of liver injury and obesity-induced inflammation.

Connecting multiple microenvironment proteomes uncovers the biology in head and neck cancer.

The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures.

SARS-CoV-2 infects adipose tissue in a fat depot- and viral lineage-dependent manner.

Visceral adiposity is a risk factor for severe COVID-19, and a link between adipose tissue infection and disease progression has been proposed. Here we demonstrate that SARS-CoV-2 infects human adipose tissue and undergoes productive infection in fat cells. However, susceptibility to infection and the cellular response depends on the anatomical origin of the cells and the viral lineage. Visceral fat cells express more ACE2 and are more susceptible to SARS-CoV-2 infection than their subcutaneous counterparts. SARS-CoV-2 infection leads to inhibition of lipolysis in subcutaneous fat cells, while in visceral fat cells, it results in higher expression of pro-inflammatory cytokines. Viral load and cellular response are attenuated when visceral fat cells are infected with the SARS-CoV-2 gamma variant. A similar degree of cell death occurs 4-days after SARS-CoV-2 infection, regardless of the cell origin or viral lineage. Hence, SARS-CoV-2 infects human fat cells, replicating and altering cell function and viability in a depot- and viral lineage-dependent fashion.

Dietary Protein Restriction Improves Metabolic Dysfunction in Patients with Metabolic Syndrome in a Randomized, Controlled Trial.

Dietary restriction (DR) reduces adiposity and improves metabolism in patients with one or more symptoms of metabolic syndrome. Nonetheless, it remains elusive whether the benefits of DR in humans are mediated by calorie or nutrient restriction. This study was conducted to determine whether isocaloric dietary protein restriction is sufficient to confer the beneficial effects of dietary restriction in patients with metabolic syndrome. We performed a prospective, randomized controlled dietary intervention under constant nutritional and medical supervision. Twenty-one individuals diagnosed with metabolic syndrome were randomly assigned for caloric restriction (CR; n = 11, diet of 5941 ± 686 KJ per day) or isocaloric dietary protein restriction (PR; n = 10, diet of 8409 ± 2360 KJ per day) and followed for 27 days. Like CR, PR promoted weight loss due to a reduction in adiposity, which was associated with reductions in blood glucose, lipid levels, and blood pressure. More strikingly, both CR and PR improved insulin sensitivity by 62.3% and 93.2%, respectively, after treatment. Fecal microbiome diversity was not affected by the interventions. Adipose tissue bulk RNA-Seq data revealed minor changes elicited by the interventions. After PR, terms related to leukocyte proliferation were enriched among the upregulated genes. Protein restriction is sufficient to confer almost the same clinical outcomes as calorie restriction without the need for a reduction in calorie intake. The isocaloric characteristic of the PR intervention makes this approach a more attractive and less drastic dietary strategy in clinical settings and has more significant potential to be used as adjuvant therapy for people with metabolic syndrome.

Single Nucleotide Variants as Proxies for HLA-A*31:01 in Native American Populations.

Carbamazepine triggers dermatologic hypersensitivity reactions, associated with specific human leukocyte antigens (HLAs), especially HLA-B*15:02 and HLA-A*31:01. Previous efforts to identify single nucleotide variants (SNVs) with high predictive value as HLA proxies, revealed that rs1061235 and rs17179220 fulfill these requirements for HLA-A*31:01 in some but not all populations. Herein we explored the predictive performance of rs1061235 and rs17179220 as HLA-A*31:01 tags in populations of Native American ancestry, which are largely underrepresented in pharmacogenomic studies. The study cohorts comprised the overall Admixed American superpopulation of the 1000 Genomes Project (1 KG_AMR), a subcohort of individuals with predominant Native American ancestry (1 KG_NAT), the Native American population of the Human Genome Diversity Project (HGDP), plus Kaingang (KRC) and Guarani (GRC and GKW) adults from indigenous reservation areas in Brazil. The diversity of cohorts is reflected in the range of frequencies of HLA-A*31:01 (0.02-0.65), rs1061235 (0.03-0.13) and rs17179220 (0.12-0.66), as well as in the predictive performance of these SNVs as HLA-A*31:01 proxies. NPV (negative predictive value), the metric of primary interest for pharmacogenetic-informed carbamazepine prescription was maximal (NPV = 1.0) for both SNVs in 1 KG_AMR and 1 KG_NAT, for rs17179220, but not rs1061235 (NPV = 0.91) in HGDP, and for rs17179220 in GWK, but not GRC (NPV = 0.88) or KRC (NPV = 0.80). Collectively, the data support the notion that rs1061235 and rs17179220 are not optimal proxies for HLA-A*31:01 across populations of Native American ancestry.

In silico analysis of mutant epitopes in new SARS-CoV-2 lineages suggest global enhanced CD8+ T cell reactivity and also signs of immune response escape.

SARS-CoV-2 variants of concern have emerged since the COVID-19 outburst, notably the lineages detected in the UK, South Africa, and Brazil. Their increased transmissibility and higher viral load put them in the spotlight. Much has been investigated on the ability of those new variants to evade antibody recognition. However, little attention has been given to pre-existing and induced SARS-CoV-2-specific CD8+ T cell responses by new lineages. In this work, we predicted SARS-CoV-2-specific CD8+ T cell epitopes from the main variants of concern and their potential to trigger or hinder CD8+ T cell response by using HLA binding and TCR reactivity in silico predictions. Also, we estimated the population's coverage for different lineages, which accounts for the ability to present a set of peptides based on the most frequent HLA alleles of a given population. We considered binding predictions to 110 ccClass I HLA alleles from 29 countries to investigate differences in the fraction of individuals expected to respond to a given epitope set from new and previous lineages. We observed a higher population coverage for the variant detected in the UK (B.1.1.7), and South Africa (B.1.351), as well as for the Brazilian P.1 lineage, but not P.2, compared to the reference lineage. Moreover, individual mutations such as Spike N501Y and Nucleocapsid D138Y were predicted to have an overall stronger affinity through HLA-I than the reference sequence while Spike E484K shows signs of evasion. In summary, we provided evidence for the existence of potentially immunogenic and conserved epitopes across new SARS-CoV-2 variants, but also mutant peptides exhibiting diminished or abolished HLA-I binding. It also highlights the augmented population coverage for three new lineages. Whether these changes imply more T cell reactivity or potential to evade from CD8+ T cell responses requires experimental verification.

High infiltration of B cells in tertiary lymphoid structures, TCR oligoclonality, and neoantigens are part of esophageal squamous cell carcinoma microenvironment.

Esophageal squamous cell carcinoma (ESCA) exhibits high intratumoral molecular heterogeneity posing a challenge to cancer therapy. Immune checkpoint blockade therapy has been approved for this disease, but with modest results. RNA-Seq data from paired tumor and surrounding nonmalignant tissue from 14 patients diagnosed with ESCA without previous treatment and from The Cancer Genome Atlas-ESCA cohort were analyzed. Herein, we investigated ESCA immune landscape including mutation-derived neoantigens and immune cell subpopulations. Tumor-associated antigen expression was determined by in silico analyses and confirmed by immunohistochemistry showing that PRAME, CEACAM4, and MAGEA11 proteins are expressed on tumors. Immune checkpoint molecules gene expression was higher in the tumor compared with surrounding nonmalignant tissue, but its expression varies greatly among patients. TCR repertoire and BCR transcripts analysis evidenced low clonal diversity with one TCR clone predicted to be specific for a MAGEA11-derived peptide. A high number of B-cell clones infiltrating the tumors and the abundance of these cells in tertiary lymphoid structures observed in ESCA tumors support B cells as a potential immune modulator in this tumor.

Extracellular vesicle-mediated crosstalk between melanoma and the immune system: Impact on tumor progression and therapy response.

Melanoma is a very lethal tumor type that easily spreads and colonizes regional and distant tissues. Crucial phenotypic changes that favor melanoma metastasis are interposed by the tumor microenvironment (TME), representing a complex network in which malignant cells communicate not only with each other but also with stromal and immune cells. This cell-cell communication can be mediated by extracellular vesicles (EVs), which are lipid bilayer-delimited particles capable of carrying a wide variety of bioactive compounds. Both melanoma-derived or TME-derived EVs deliver important pro- and antitumor signals implicated in various stages of tumor progression, such as proliferation, metastasis, and treatment response. In this review, we highlight the recent advances in EV-mediated crosstalk between melanoma and immune cells and other important cells of the TME, and address different aspects of this bidirectional interaction as well as how this may hinder or trigger the development and progression of melanoma. We also discuss the potential of using EVs as biomarkers and therapeutic strategies for melanoma.

Poor clinical outcome in metastatic melanoma is associated with a microRNA-modulated immunosuppressive tumor microenvironment.

BACKGROUND: Interaction between malignant cells and immune cells that reside within the tumor microenvironment (TME) modulate different aspects of tumor development and progression. Recent works showed the importance of miRNA-containing extracellular vesicles in this crosstalk. METHODS: Interested in understanding the interplay between melanoma and immune-related TME cells, we characterized the TCGA's metastatic melanoma samples according to their tumor microenvironment profiles, HLA-I neoepitopes, transcriptome profile and classified them into three groups. Moreover, we combined our results with melanoma single-cell gene expression and public miRNA data to better characterize the regulatory network of circulating miRNAs and their targets related to immune evasion and microenvironment response. RESULTS: The group associated with a worse prognosis showed phenotypic characteristics that favor immune evasion, including a strong signature of suppressor cells and less stable neoantigen:HLA-I complexes. Conversely, the group with better prognosis was marked by enrichment in lymphocyte and MHC signatures. By analyzing publicly available melanoma single-cell RNA and microvesicle microRNAs sequencing data we identified circulating microRNAs potentially involved in the crosstalk between tumor and TME cells. Candidate miRNA/target gene pairs with previously reported roles in tumor progression and immune escape mechanisms were further investigated and demonstrated to impact patient's overall survival not only in melanoma but across different tumor types. CONCLUSION: Our results underscore the impact of tumor-microenvironment interactions on disease outcomes and reveal potential non-invasive biomarkers of prognosis and treatment response.

Class I HLA Allele Predicted Restricted Antigenic Coverages for Spike and Nucleocapsid Proteins Are Associated With Deaths Related to COVID-19.

The world is dealing with one of the worst pandemics ever. SARS-CoV-2 is the etiological agent of COVID-19 that has already spread to more than 200 countries. However, infectivity, severity, and mortality rates do not affect all countries equally. Here we consider 140 HLA alleles and extensively investigate the landscape of 3,723 potential HLA-I A and B restricted SARS-CoV-2-derived antigens and how 37 countries in the world are predicted to respond to those peptides considering their HLA-I distribution frequencies. The clustering of HLA-A and HLA-B allele frequencies partially separates most countries with the lowest number of deaths per million inhabitants from the other countries. We further correlated the patterns of in silico predicted population coverage and epidemiological data. The number of deaths per million inhabitants correlates to the predicted antigen coverage of S and N derived peptides and its module is influenced if a given set of frequent or rare HLA alleles are analyzed in a given population. Moreover, we highlighted a potential risk group carrying HLAs associated with an elevated number of deaths per million inhabitants. In addition, we identified three potential antigens bearing at least one amino acid of the four-length insertion that differentiates SARS-CoV-2 from previous coronavirus strains. We believe these data can contribute to the search for peptides with the potential to be used in vaccine strategies considering the role of herd immunity to hamper the spread of the disease. Importantly, to the best of our knowledge, this work is the first to use a populational approach in association with COVID-19 outcome.

Immunological-based approaches for cancer therapy.

The immunologic landscape of tumors has been continuously unveiled, providing a new look at the interactions between cancer cells and the immune system. Emerging tumor cells are constantly eliminated by the immune system, but some cells establish a long-term equilibrium phase leading to tumor immunoediting and, eventually, evasion. During this process, tumor cells tend to acquire more mutations. Bearing a high mutation burden leads to a greater number of neoantigens with the potential to initiate an immune response. Although many tumors evoke an immune response, tumor clearance by the immune system does not occur due to a suppressive tumor microenvironment. The mechanisms by which tumors achieve the ability to evade immunologic control vary. Understanding these differences is crucial for the improvement and application of new immune-based therapies. Much effort has been placed in developing in silico algorithms to predict tumor immunogenicity and to characterize the microenvironment via high-throughput sequencing and gene expression techniques. Each sequencing source, transcriptomics, and genomics yields a distinct level of data, helping to elucidate the tumor-based immune responses and guiding the fine-tuning of current and upcoming immune-based therapies. In this review, we explore some of the immunological concepts behind the new immunotherapies and the bioinformatic tools to study the immunological aspects of tumors, focusing on neoantigen determination and microenvironment deconvolution. We further discuss the immune-based therapies already in clinical use, those underway for future clinical application, the next steps in immunotherapy, and how the characterization of the tumor immune contexture can impact therapies aiming to promote or unleash immune-based tumor elimination.

Immunological-based approaches for cancer therapy

The immunologic landscape of tumors has been continuously unveiled, providing a new look at the interactions between cancer cells and the immune system. Emerging tumor cells are constantly eliminated by the immune system, but some cells establish a long-term equilibrium phase leading to tumor immunoediting and, eventually, evasion. During this process, tumor cells tend to acquire more mutations. Bearing a high mutation burden leads to a greater number of neoantigens with the potential to initiate an immune response. Although many tumors evoke an immune response, tumor clearance by the immune system does not occur due to a suppressive tumor microenvironment. The mechanisms by which tumors achieve the ability to evade immunologic control vary. Understanding these differences is crucial for the improvement and application of new immune-based therapies. Much effort has been placed in developing in silico algorithms to predict tumor immunogenicity and to characterize the microenvironment via high-throughput sequencing and gene expression techniques. Each sequencing source, transcriptomics, and genomics yields a distinct level of data, helping to elucidate the tumor-based immune responses and guiding the fine-tuning of current and upcoming immune-based therapies. In this review, we explore some of the immunological concepts behind the new immunotherapies and the bioinformatic tools to study the immunological aspects of tumors, focusing on neoantigen determination and microenvironment deconvolution. We further discuss the immune-based therapies already in clinical use, those underway for future clinical application, the next steps in immunotherapy, and how the characterization of the tumor immune contexture can impact therapies aiming to promote or unleash immune-based tumor elimination.