Triple-negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer with limited options for clinical intervention. As with many solid tumors, TNBC is known to promote invasiveness and metastasis by secreting extracellular vesicles (EVs) capable of modulating the behaviour of recipient cells. Recent investigations have demonstrated that high expression levels of glucocorticoid receptor (GR) in TNBC are linked to therapy resistance, higher recurrence rates and increased mortality. In addition to activating protein-coding genes, GR is also involved in the expression of short non-coding RNAs including microRNAs (miRNAs or miRs). The molecular mechanisms responsible for the oncogenic effects of GR on TNBC have yet to be fully elucidated; however, emerging evidence suggests that miRNAs may play a pivotal role in tumorigenesis and metastasis. Thus, the aim of this study was to identify GR-regulated cellular and vesicular miRNAs that might contribute to the particularly oncogenic phenotype of TNBC with a high GR expression. We analyzed miRNA profiles of three TNBC cell lines using an in vitro model of GR overexpression. Next-generation sequencing revealed minor, cell line-specific changes in cellular miRNA expression, whereas vesicular miRNAs were not significantly regulated by GR. Additionally, the analysis of predicted miRNA targets failed to establish a causal link between GR-induced miRNA expression and oncogenic signaling. On the whole, given that GR influences miRNA profiles to only a small degree, other mechanisms are more likely to be responsible for the increased mortality of patients with TNBC with a high GR expression.

Intensive efforts have been made to provide better treatments to cancer patients. Currently, nanoparticle-based drug delivery systems have gained propulsion, as they can overcome the drawbacks of free drugs. However, drug stability inside the nanocapsule must be ensured to prevent burst release. To overcome this, drugs conjugated to amphiphilic copolymers, assembled into nanoparticles, can provide a sustained release if endogenously degraded. Thus, we have designed and assessed the drug release viability of polymer-drug conjugates by the human Carboxylesterase 2, for a targeted drug activation. We performed molecular dynamics simulations applying a quantum mechanics/molecular mechanics potential to study the degradation profiles of 30 designed conjugates, where six were predicted to be hydrolyzed by this enzyme. We further analyzed the enzyme-substrate environment to delve into what structural features may lead to successful hydrolysis. These findings contribute to the development of new medicines ensuring effective cancer treatments with fewer side effects.

The primary genetic risk factor for late onset Alzheimer’s disease (LOAD) is the APOE4 allele of Apolipoprotein E (APOE) gene. The three most common variants of APOE are determined by single nucleotide polymorphisms (SNPs) rs429358 and rs7412. Our aim was to estimate allele and genotype frequencies of APOE variants in an Iberian cohort, thus helping to understand differences in APOE-related LOAD risk observed across populations. We analyzed saliva or buccal swab samples from 229 LOAD patients and 89 healthy elderly controls (≥68 years old) from Northern Portugal and Castile and León region, Spain. The genotyping was performed by Sanger sequencing, optimized to overcome GC content drawbacks. Results obtained in our Iberian LOAD and control cohorts are in line with previous large meta-analyses on APOE frequencies in Caucasian populations; however, we found differences in allele frequencies between our Portuguese and Spanish subgroups of AD patients. Moreover, when comparing studies from Iberian and other Caucasian cohorts, differences in APOE2 and APOE4 frequencies and subsequent different APOE-related LOAD risks must be clarified. These results show the importance of studying genetic variation at the APOE gene in different populations (including analyses at a regional level) to increase our knowledge about its clinical significance.

Enzymatic peptide synthesis is a powerful alternative to solid-phase methods, as enzymes can have high regio- and stereoselectivity and high yield and require mild reaction conditions. This is beneficial in formulation research due to the rise of nucleic acid therapies. Peptide nucleic acids (PNAs) have a high affinity toward DNA and RNA, and their solubility and cellular delivery can be improved via conjugation to peptides. Here, we designed and assessed the viability of the papain enzyme to conjugate four PNA-peptide models in water and an organic solvent using QM/MM metadynamics. We found that the reactions in water yield better results, where three conjugates could potentially be synthesized by the enzyme, with the first transition state as the rate-limiting step, with an associated energy of 14.53 kcal mol^-1, although with a slight endergonic profile. The results highlight the importance of considering the enzyme pockets and different substrate acceptivities and contribute to developing greener, direct, and precise synthetic routes for nucleic acid-based therapies. By exploring the enzyme's potential in conjunction with chemical synthesis, current protocols can be simplified for the synthesis of longer nucleic acids and peptide sequences (and, by extension, proteins) from smaller oligo or peptide blocks.

Nucleic acid technologies with designed delivery systems have surged as one the most promising therapies of the future, due to their contribution in combating SARS-CoV-2 severe disease. Nevertheless, the emergence of new variants of concern still represents a real threat in the years to come. It is here that the use of small interfering RNA sequences to inhibit gene expression and, thus, protein synthesis, may complement the already developed vaccines, with faster design and production. Here, we have designed new sequences targeting COVID-19 variants and other related viral diseases through bioinformatics, while also addressing the limited number of delivery peptides by a deep learning approach. Two sequences databases were produced, from which 62 were able to target the virus mRNA, and ten displayed properties present in delivery peptides, which we compared to the broad use TAT delivery peptide.