de Melo, A. C. | Search bioRxiv

bioRxiv2023

A multi-tissue single-cell tumor microenvironment atlas reveals myeloid-derived cell states with significant impact on clinical outcome

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment response due to their remarkable plasticity and tumorigenic behaviors. We integrated single-cell RNA-Sequencing datasets from seven different cancers, resulting in a comprehensive collection of 29 MDC subpopulations in the tumor microenvironment (TME). Distinguishing resident-tissue from monocyte-derived macrophages, we discovered a resident-tissue-like subpopulation within monocyte-derived macrophages. Additionally, hypoxia-driven macrophages emerged as a prominent TME component. Deconvolution of these profiles revealed five subpopulations as independent prognostic markers across various cancer types. Validation in large cohorts confirmed the FOLR2-expressing macrophage association with poor clinical outcomes in ovarian and triple-negative breast cancer. Moreover, the marker TREM2, commonly used to define immunosuppressive tumor-associated macrophages, cannot solely predict cancer prognosis, as different polarization states of macrophages express this marker in a context-dependent manner. This comprehensive MDC atlas offers valuable insights and a foundation for novel analyses, advancing strategies for treating solid cancers.

cancer biology↗

bioRxiv2021

Oral Lichen Planus and its relation with Oral Squamous Cell Carcinoma: new insights into the potential for malignant transformation

Oral Lichen Planus (OLP) is a chronic inflammatory disorder of unknown etiology. However, evidence suggests that it consists of an immunological process that leads to degeneration of the keratinocytes in the basal layer of the oral mucosa. Despite being recognized by WHO as a potentially malignant disorder with progression to oral squamous cell carcinoma (OSCC), the relationship between both pathologies is still controversial. Different studies have investigated factors associated with the potential for malignant transformation of OLP but it remains unclear. Through a bioinformatics approach, we investigated similarities in gene expression profiles of OLP and OSCC in early and advanced stages. Our results revealed gene expression patterns related to processes of keratinization, keratinocyte differentiation, cell proliferation and immune response in common between OLP and early and advanced OSCC, with the cornified envelope formation and antigen processing cross-presentation pathways in common between OLP and early OSCC. Together, these results reveal that key genes such as PI3, SPRR1B and KRT17, in addition to genes associated with different immune processes such as CXCL-13, HIF1A and IL1B may be involved in this oncogenic process. In addition, we performed an analysis of differentially and co-expressed genes and proposed putative therapeutic targets and associated drugs.

bioinformatics↗

bioRxiv2020

SARS-CoV-2 genomic and quasispecies analyses in cancer patients reveal relaxed intrahost virus evolution

Numerous factors have been identified to influence susceptibility to SARS-CoV-2 infection and disease severity. Cancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. We have determined the full-length SARS-CoV-2 genomic sequences of cancer patients and healthcare workers (HCW; non-cancer controls) by deep sequencing and investigated the within-host viral quasispecies of each infection, quantifying intrahost genetic diversity. Naso- and oropharyngeal SARS-CoV-2+ swabs from 57 cancer patients and 14 healthcare workers (HCW) from the Brazilian Cancer Institute were collected in April-May 2020. Complete genome amplification using ARTIC network V3 multiplex primers was performed followed by next-generation sequencing. Assemblies were conducted in Geneious R11, where consensus sequences were extracted and intrahost single nucleotide variants (iSNVs) were identified. Maximum likelihood phylogenetic analysis was performed using PhyMLv.3.0 and lineages were classified using Pangolin and CoV-GLUE. Phylogenetic analysis showed that all but one strain belonged to clade B1.1. Four genetically linked mutations known as the globally dominant SARS-CoV-2 haplotype (C241T, C3037T, C14408T and A23403G) were found in the majority of consensus sequences. SNV signatures of previously characterized Brazilian genomes were also observed in most samples. Another 85 SNVs were found at a lower frequency (1.4-19.7%). Cancer patients displayed a significantly higher intrahost viral genetic diversity compared to HCW (p = 0.009). Intrahost genetic diversity in cancer patients was independent of SARS-CoV-2 Ct values, and was not associated with disease severity, use of corticosteroids, or use of antivirals, characteristics that could influence viral diversity. Such a feature may explain, at least in part, the more adverse outcomes to which cancer/COVID-19 patients experience. Author SummaryCancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. In this study, phylogenetic and variation analysis of SARS-CoV-2 genomes from cancer patients and non-cancer healthcare workers at the Brazilian National Cancer Institute were characterized by deep sequencing. Viral genomes showed signatures characteristic of Brazilian viruses, consistent with the hypothesis of local, community transmission rather than virus importation from abroad. Despite most genomes in patients and healthcare workers belonging to the same lineage, intrahost variability was higher in cancer patients when compared to non-cancer counterparts. The intrahost genomic diversity analysis presented in our study highlights the relaxed evolution of SARS-CoV-2 in a vulnerable population of cancer patients. The high number of minor variations can result in the selection of immune escape variants, resistance to potential drugs, and/or increased pathogenicity. The impact of this higher intrahost variability over time warrants further investigation.

microbiology↗