HLA-G gene editing in tumor cell lines as a novel alternative in cancer immunotherapy.

Cancer immunotherapies based mainly on the blockade of immune-checkpoint (IC) molecules by anti-IC antibodies offer new alternatives for treatment in oncological diseases. However, a considerable proportion of patients remain unresponsive to them. Hence, the development of novel clinical immunotherapeutic approaches and/or targets are crucial.W In this context, targeting the immune-checkpoint HLA-G/ILT2/ILT4 has caused great interest since it is abnormally expressed in several malignancies generating a tolerogenic microenvironment. Here, we used CRISPR/Cas9 gene editing to block the HLA-G expression in two tumor cell lines expressing HLA-G, including a renal cell carcinoma (RCC7) and a choriocarcinoma (JEG-3). Different sgRNA/Cas9 plasmids targeting HLA-G exon 1 and 2 were transfected in both cell lines. Downregulation of HLA-G was reached to different degrees, including complete silencing. Most importantly, HLA-G - cells triggered a higher in vitro response of immune cells with respect to HLA-G + wild type cells. Altogether, we demonstrated for the first time the HLA-G downregulation through gene editing. We propose this approach as a first step to develop novel clinical immunotherapeutic approaches in cancer.

Integrin alpha-5 subunit is critical for the early stages of human pluripotent stem cell cardiac differentiation.

The stem cell niche has a strong influence in the differentiation potential of human pluripotent stem cells with integrins playing a major role in communicating cells with the extracellular environment. However, it is not well understood how interactions between integrins and the extracellular matrix are involved in cardiac stem cell differentiation. To evaluate this, we performed a profile of integrins expression in two stages of cardiac differentiation: mesodermal progenitors and cardiomyocytes. We found an active regulation of the expression of different integrins during cardiac differentiation. In particular, integrin α5 subunit showed an increased expression in mesodermal progenitors, and a significant downregulation in cardiomyocytes. To analyze the effect of α5 subunit, we modified its expression by using a CRISPRi technique. After its downregulation, a significant impairment in the process of epithelial-to-mesenchymal transition was seen. Early mesoderm development was significantly affected due to a downregulation of key genes such as T Brachyury and TBX6. Furthermore, we observed that repression of integrin α5 during early stages led to a reduction in cardiomyocyte differentiation and impaired contractility. In summary, our results showed the link between changes in cell identity with the regulation of integrin α5 expression through the alteration of early stages of mesoderm commitment.

Deep Learning Neural Networks Highly Predict Very Early Onset of Pluripotent Stem Cell Differentiation.

Deep learning is a significant step forward for developing autonomous tasks. One of its branches, computer vision, allows image recognition with high accuracy thanks to the use of convolutional neural networks (CNNs). Our goal was to train a CNN with transmitted light microscopy images to distinguish pluripotent stem cells from early differentiating cells. We induced differentiation of mouse embryonic stem cells to epiblast-like cells and took images at several time points from the initial stimulus. We found that the networks can be trained to recognize undifferentiated cells from differentiating cells with an accuracy higher than 99%. Successful prediction started just 20 min after the onset of differentiation. Furthermore, CNNs displayed great performance in several similar pluripotent stem cell (PSC) settings, including mesoderm differentiation in human induced PSCs. Accurate cellular morphology recognition in a simple microscopic set up may have a significant impact on how cell assays are performed in the near future.