Human Mesenchymal Stem Cells (hMSCs) are multipotent stem cells capable of renewing themselves and differentiation in vitro into different kinds of tissues. In vivo hMSCs are sources of trophic factors modulating the immune system and inducing intrinsic stem cells to repair damaged tissues. Currently, there are multiple clinical trials (CT) using hMSCs for therapeutic purposes in a large number of clinical settings. The search strategy on clinicaltrials.gov has focused on the key term "Mesenchymal Stem Cells", and the inclusion and exclusion criteria were separated into two stages. Stage 1, CT on phases 1-4: location, the field of application, phase, and status. For stage 2, CT that have published outcome results: field of application, treatment, intervention model, source, preparation methods, and results. By July 2020, there were a total of 1,138 registered CT. Most studies belong to either phase 2 (61.0%) or phase 1 (30.8%); most of them focused in the fields of traumatology, neurology, cardiology, and immunology. Only 18 clinical trials had published results: the most common source of isolation was bone marrow; the treatment varied from 1-200 M hMSCs; all of them have similar preparation methods; all of them have positive results with no serious adverse effects. There appears to be a broad potential for the clinical use of hMSCs with no reported serious adverse events. There are many trials in progress, their future results will help to explore the therapeutic potential of these promising cellular sources of medicinal signals.

The dawn of the liquid biopsy in the fight against cancer The dawn of the liquid biopsy in the fight against cancer

Persistent high-risk human papillomavirus (HR-HPV) infections play a major role in the development of invasive cervical cancer (CC), and screening for such infections is in many countries the primary method of detecting and preventing CC. HPV typing can be used for triage and risk stratification of women with atypical squamous cells of undetermined significance (ASC-US)/low-grade cervical lesions (LSIL), though the current clinical practice in Mexico is to diagnose CC or its preceding conditions mainly via histology and HR-HPV detection. Additional information regarding these HPV infections, such as viral load and co-infecting agents, might also be useful for diagnosing, predicting, and evaluating the possible consequences of the infection and of its prevention by vaccination. The goal of this follow-up hospital case study was to determine if HPV types, multiple HPV infections, and viral loads were associated with infection persistence and the cervical lesion grade. A total of 294 cervical cytology samples drawn from patients with gynecological alterations were used in this study. HPV types were identified by real-time PCR DNA analysis. A subset of HPV-positive patients was reevaluated to identify persistent infections. We identified HPV types 16, 18, and 39 as the most prevalent. One hundred five of the patients (59%) were infected with more than one type of HPV. The types of HPV associated with multiple HPV infections were 16, 18, and 39. In the follow-up samples, 38% of patients had not cleared the initially detected HPV infection, and these were considered persistent. We found here an association between multiple HPV infections and high viral loads with and infection persistence. Our findings suggest there are benefits in ascertaining viral load and multiple HPV infections status of HR-HPV infections for predicting the risk of persistence, a requirement for developing CC. These findings contribute to our understanding of HPV epidemiology and may allow screening programs to better assess the cancer-developing risks associated with individual HR-HPV infections.

Cellular therapy has used mesenchymal stem cells (MSCs), which in cell culture are multipotent progenitors capable of producing a variety of cells limited to the mesoderm layer. There are two types of MSC sources: (1) adult MSCs, which are obtained from bone marrow, adipose tissue, peripheral blood, and dental pulp; and (2) neonatal-tissue-derived MSCs, obtained from extra-embryonic tissues such as the placenta, amnion, and umbilical cord. Until April 2023, 1120 registered clinical trials had been using MSC therapies worldwide, but there are only 12 MSC therapies that have been approved by regulatory agencies for commercialization. Nine of the twelve MSC-approved products are from Asia, with Republic of Korea being the country with the most approved therapies. In the future, MSCs will play an important role in the treatment of many diseases. However, there are many issues to deal with before their application and usage in the medical field. Some strategies have been proposed to face these problems with the hope of reaching the objective of applying these MSC therapies at optimal therapeutic levels.

Mutations in KRAS, NRAS, and BRAF (RAS/BRAF) genes are the main predictive biomarkers for the response to anti-EGFR monoclonal antibodies (MAbs) targeted therapy in metastatic colorectal cancer (mCRC). This retrospective study aimed to report the mutational status prevalence of these genes, explore their possible associations with clinicopathological features, and build and validate a predictive model. To achieve these objectives, 500 mCRC Mexican patients were screened for clinically relevant mutations in RAS/BRAF genes. Fifty-two percent of these specimens harbored clinically relevant mutations in at least one screened gene. Among these, 86% had a mutation in KRAS, 7% in NRAS, 6% in BRAF, and 2% in both NRAS and BRAF. Only tumor location in the proximal colon exhibited a significant correlation with KRAS and BRAF mutational status (p-value = 0.0414 and 0.0065, respectively). Further t-SNE analyses were made to 191 specimens to reveal patterns among patients with clinical parameters and KRAS mutational status. Then, directed by the results from classical statistical tests and t-SNE analysis, neural network models utilized entity embeddings to learn patterns and build predictive models using a minimal number of trainable parameters. This study could be the first step in the prediction for RAS/BRAF mutational status from tumoral features and could lead the way to a more detailed and more diverse dataset that could benefit from machine learning methods.