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Biomedical subjects

Daniele Santoni

Publications and source records attributed to Daniele Santoni.

3 recordsLinked to original sources

Single-cell profiling reveals a novel CAF subpopulation linking stromal heterogeneity to immune suppression in breast cancer subtypes.

BACKGROUND: The tumor microenvironment critically influences breast cancer (BC) progression, immune surveillance, and therapeutic response. Cancer-associated fibroblasts (CAFs), a heterogeneous stromal population, are key regulators of these processes, yet their subtype-specific contributions in BC remain insufficiently defined. METHODS: We integrated three single-cell RNA sequencing datasets from 29 BC patients to characterize stromal populations. Bulk RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to assess correlations between CAF subsets and immune infiltration. Gene signatures were derived to identify subtype-specific CAF-immune interactions, prognostic markers, and potential predictors of chemotherapy response. RESULTS: Three conserved stromal populations (iCAFs, myCAFs, and pericytes) were identified, along with a previously unrecognized subset, the cluster 3 (CL3) CAF-like cells, referred as metabolic stressed CAF (msCAF). msCAF cells displayed transcriptional programs associated with antigen presentation, stress response, glycolysis, and extracellular matrix remodeling. Their abundance was inversely correlated with T-cell infiltration and function, in a subtype-specific manner: triple negative breast cancer (TNBC) was enriched for msCAFs in immune-infiltrated but functionally constrained microenvironments, whereas Luminal A tumors exhibited weaker immune infiltration with heterogeneous CAF-immune associations. msCAFs were characterized by a conserved gene signature (HLA-A, HLA-C, IL32, EMP3) and subtype-specific genes related to T-cell exhaustion. Several genes demonstrated prognostic relevance with distinct patterns in Luminal A (IER3, TIMP1, TBX3, SEC61G) and TNBC (ADM, C4orf3, LDHA) tumors, as well as shared biomarkers (FN1, LOXL2, P4HA1). Multiple msCAF genes also predicted chemotherapy response, suggesting utility as treatment stratification biomarkers. CONCLUSION: msCAFs represent a clinically relevant CAF subset that drives immune suppression, impacts subtype-specific prognosis, and influences therapy response in BC. These findings highlight msCAFs as promising targets for enhancing immunotherapy and personalizing treatment strategies.

Humans↗

Sequence-dependent DNA torsional rigidity: a tetranucleotide code.

Using fluorescence polarization anisotropy (FPA), we measured the torsional constant of various DNA oligomers in different sequences and calculated the value for each of the 136 unique tetranucleotides. From these values, we obtained a "rigidity profile" for every double-stranded DNA sequence. We tested the code in the analysis of DNA sequences able to form nucleosomes. More than 50% of the sequences studied showed a common 20 and/or 30 bp modulation of the torsional constant. Many other profiles of rigidity were observed in the remaining sequences and this variety in torsional constant modulation may be related to functional differences between nucleosomes.

Animals↗

[Bioinformatics and GenEnv database in biological risk management].

Identification and molecular typing of environmental isolates by molecular techniques requires knowledge of the genetic characteristics of the microbe species being examined. The introduction of automated sequences has greatly speeded up the entire sequencing process as well as improved the accuracy of the collected information. Bioinformatics tools have become indispensable not only for setting up research studies, but also for storing, organizing and managing enormous quantities of sequencing data. Despite its great advantages, the use of bioinformatics is hindered by difficulties in learning how to use its software tools. The GenEnv database was developed to provide operators involved in biological risk management with a user-friendly tool for sequence analysis. Presently, there are over 20.000 sequence records, and over 9000 bacterial species represented in the database. The initial gene set comprises rDNA16S, rpoB, gyrB. The system allows sequence-driven microbe identification as well as the development of study protocols for research on specific microbe species. Nucleotide sequences are represented graphically. The GenEnv database was designed as a tool for public health operators but also offers wide prospects for scientific research.

Computational Biology↗