New therapeutic agents able to block HIV-1 replication are eagerly sought after to increase the possibilities of treatment of resistant viral strains. In this report, we describe a rational strategy to identify small peptide sequences owning the dual property of penetrating within lymphocytes and of binding to a protein target. Such sequences were identified for two important HIV-1 regulatory proteins, Tat and Rev. Their association to a stabilizing domain consisting of human small ubiquitin-related modifier-1 (SUMO-1) allowed the generation of small proteins named SUMO-1 heptapeptide protein transduction domain for binding Tat (SHPT) and SUMO-1 heptapeptide protein transduction domain for binding Rev (SHPR), which are stable and efficiently penetrate within primary lymphocytes. Analysis of the antiviral activity of these proteins showed that one SHPR is active in both primary lymphocytes and macrophages, whereas one SHPT is active only in the latter cells. These proteins may represent prototypes of new therapeutic agents targeting the crucial functions exerted by both viral regulatory factors.

Preventing the cytokine storm observed in COVID-19 is a crucial goal for reducing the occurrence of severe acute respiratory failure and improving outcomes. Here, we identify Aldo-Keto Reductase 1B10 (AKR1B10) as a key enzyme involved in the expression of pro-inflammatory cytokines. The analysis of transcriptomic data from lung samples of patients who died from COVID-19 demonstrates an increased expression of the gene encoding AKR1B10. Measurements of the AKR1B10 protein in sera from hospitalised COVID-19 patients suggests a significant link between AKR1B10 levels and the severity of the disease. In macrophages and lung cells, the over-expression of AKR1B10 induces the expression of the pro-inflammatory cytokines Interleukin-6 (IL-6), Interleukin-1β (IL-1β) and Tumor Necrosis Factor a (TNFα), supporting the biological plausibility of an AKR1B10 involvement in the COVID-19-related cytokine storm. When macrophages were stressed by lipopolysaccharides (LPS) exposure and treated by Zopolrestat, an AKR1B10 inhibitor, the LPS-induced production of IL-6, IL-1β, and TNFα is significantly reduced, reinforcing the hypothesis that the pro-inflammatory expression of cytokines is AKR1B10-dependant. Finally, we also show that AKR1B10 can be secreted and transferred via extracellular vesicles between different cell types, suggesting that this protein may also contribute to the multi-organ systemic impact of COVID-19. These experiments highlight a relationship between AKR1B10 production and severe forms of COVID-19. Our data indicate that AKR1B10 participates in the activation of cytokines production and suggest that modulation of AKR1B10 activity might be an actionable pharmacological target in COVID-19 management.

Breast cancer is characterized by genetic and epigenetic deregulations, leading to aberrant expression of tissue-specific genes that are normally silent in healthy breast tissue. Our previous work identified the embryonic stem cell-specific gene DNMT3B, a de novo DNA methyltransferase, as aberrantly activated in breast cancer, correlating with aggressive tumour behaviour and high relapse risk, regardless of molecular subtype. Through integrative bioinformatic analyses of DNA methylation and transcriptomic data, we identified 154 genes downregulated via DNMT3B-driven promoter hypermethylation, many of which are associated with high relapse risk. Notably, the tumour suppressor gene GATA3 emerged as a primary target of functional inactivation through either loss-of-function mutations or DNMT3B-controlled hypermethylation, in a mutually exclusive manner. Both mechanisms of GATA3 inactivation were associated with similar molecular signatures linked to tumour progression, increased malignancy, and poorer prognosis. However, distinct differences were observed, with immune- and inflammation-related genes enriched in GATA3 hypermethylation cases but depleted in mutation-driven silencing. Additionally, our analysis uncovered other potential tumour suppressor genes epigenetically repressed in aggressive breast cancers. These findings underscore a broader role of GATA3 inactivation beyond genetic alterations and suggest therapeutic opportunities to target epigenetically silenced tumour suppressors in aggressive breast tumours.

We developed machine-learning models to predict isocitrate dehydrogenase (IDH) mutation status in acute myeloid leukemia (AML) from gene expression profiles and to reconstruct missing IDH annotations across public datasets. Transcriptomic data from 19 cohorts (5844 samples) were harmonized using batch correction, and 1546 samples with known IDH status were used to train a feed-forward neural network and a logistic regression (LR) classifier within a nested cross-validation framework, followed by independent validation in the TCGA-LAML dataset. The LR model showed superior performance, achieving receiver operating characteristic area under the curve $=$ 0.994 $\pm$ 0.007, accuracy $=$ 0.983 $\pm$ 0.006, balanced accuracy $=$ 0.979 $\pm$ 0.005, sensitivity for the IDH-mutant (IDH-MUT) class $=$ 0.972 $\pm$ 0.010, and specificity $=$ 0.986 $\pm$ 0.008, and correctly classified all IDH-MUT cases in the independent cohort. Applying the final model to samples lacking annotations enabled reconstruction of IDH status for 4148 AML cases, expanding the number of molecularly characterized transcriptomes available for downstream analyses. Predicted groups recapitulated known IDH-associated transcriptional signatures, supporting biological validity. This work demonstrates that IDH mutation status can be accurately inferred from transcriptomic data alone and provides a scalable framework to recover missing genomic annotations, thereby enhancing the utility of public AML resources for large-scale biological and translational research.

Breast cancer is characterized by genetic and epigenetic deregulations, leading to aberrant expression of tissue-specific genes that are normally silent in healthy breast tissue. Our previous work identified the embryonic stem cell-specific gene DNMT3B , a de novo DNA methyltransferase, as aberrantly activated in breast cancer, correlating with aggressive tumour behaviour and high relapse risk, regardless of molecular subtype. Through integrative bioinformatic analyses of DNA methylation and transcriptomic data, we identified 154 genes downregulated via DNMT3B -driven promoter hypermethylation, many of which are associated with high relapse risk. Notably, the tumour suppressor gene GATA3 emerged as a primary target of functional inactivation through either loss-of-function mutations or DNMT3B -controlled hypermethylation, in a mutually exclusive manner. Both mechanisms of GATA3 inactivation were associated with similar molecular signatures linked to tumour progression, increased malignancy, and poorer prognosis. However, distinct differences were observed, with immune- and inflammation-related genes enriched in GATA3 hypermethylation cases but depleted in mutation-driven silencing. Additionally, our analysis uncovered other potential tumour suppressor genes epigenetically repressed in aggressive breast cancers. These findings underscore a broader role of GATA3 inactivation beyond genetic alterations and suggest therapeutic opportunities to target epigenetically silenced tumour suppressors in aggressive breast tumours.