Systematic screening reveals synergistic interactions that overcome MAPK inhibitor resistance in cancer cells.

OBJECTIVE: Effective adjuvant therapeutic strategies are urgently needed to overcome MAPK inhibitor (MAPKi) resistance, which is one of the most common forms of resistance that has emerged in many types of cancers. Here, we aimed to systematically identify the genetic interactions underlying MAPKi resistance, and to further investigate the mechanisms that produce the genetic interactions that generate synergistic MAPKi resistance. METHODS: We conducted a comprehensive pair-wise sgRNA-based high-throughput screening assay to identify synergistic interactions that sensitized cancer cells to MAPKi, and validated 3 genetic combinations through competitive growth, cell viability, and spheroid formation assays. We next conducted Kaplan-Meier survival analysis based on The Cancer Genome Atlas database and conducted immunohistochemistry to determine the clinical relevance of these synergistic combinations. We also investigated the MAPKi resistance mechanisms of these validated synergistic combinations by using co-immunoprecipitation, Western blot, qRT-PCR, and immunofluorescence assays. RESULTS: We constructed a systematic interaction network of MAPKi resistance and identified 3 novel synergistic combinations that effectively targeted MAPKi resistance (ITGB3 + IGF1R, ITGB3 + JNK, and HDGF + LGR5). We next analyzed their clinical relevance and the mechanisms by which they sensitized cancer cells to MAPKi exposure. Specifically, we discovered a novel protein complex, HDGF-LGR5, that adaptively responded to MAPKi to enhance cancer cell stemness, which was up- or downregulated by the inhibitors of ITGB3 + JNK or ITGB3 + IGF1R. CONCLUSIONS: Pair-wise sgRNA library screening provided systematic insights into elucidating MAPKi resistance in cancer cells. ITGB3- + IGF1R-targeting drugs (cilengitide + linsitinib) could be used as an effective therapy for suppressing the adaptive formation of the HDGF-LGR5 protein complex, which enhanced cancer stemness during MAPKi stress.

Selection of candidate genes affecting meat quality and preliminary exploration of related molecular mechanisms in the Mashen pig.

OBJECTIVE: The aim of this study was to select the candidate genes affecting meat quality and preliminarily explore the related molecular mechanisms in the Mashen pig. METHODS: The present study explored genetic factors affecting meat quality in the Mashen pig using RNA sequencing (RNA-Seq). We sequenced the transcriptomes of 180-day-old Mashen and Large White pigs using longissimus dorsi to select differentially expressed genes (DEGs). RESULTS: The results indicated that a total of 425 genes were differentially expressed between Mashen and Large White pigs. A gene ontology enrichment analysis revealed that DEGs were mainly enriched for biological processes associated with metabolism and muscle development, while a Kyoto encyclopedia of genes and genomes analysis showed that DEGs mainly participated in signaling pathways associated with amino acid metabolism, fatty acid metabolism, and skeletal muscle differentiation. A MCODE analysis of the protein-protein interaction network indicated that the four identified subsets of genes were mainly associated with translational initiation, skeletal muscle differentiation, amino acid metabolism, and oxidative phosphorylation pathways. CONCLUSION: Based on the analysis results, we selected glutamic-oxaloacetic transaminase 1, malate dehydrogenase 1, pyruvate dehydrogenase 1, pyruvate dehydrogenase kinase 4, and activator protein-1 as candidate genes affecting meat quality in pigs. A discussion of the related molecular mechanisms is provided to offer a theoretical basis for future studies on the improvement of meat quality in pigs.

A comparison of dynamic distributions of intestinal microbiota between Large White and Chinese Shanxi Black pigs.

Intestinal microbiota has been widely recognized to influence on their hosts with respect to digestion and absorption of nutrients, but little is known about the structure and composition of microbial communities at different growth periods of hosts as yet. In this case, 16S rRNA gene amplicon sequencing was applied to decode the microbiota architecture in four distinct intestinal compartments (duodenum, jejunum, ileum, and cecum) of both Large White pigs and Chinese Shanxi Black pigs at the weaning, nursery, and fast-growth developmental stages. In our study, the intestinal ecosystems were dynamically changing and influenced by host maturity and diets at different development stages. Species phylogenetically affiliated to phyla Firmicutes, Proteobacteria, and Bacteroidetes were abundant in both pig breeds; at the genus level, microbial communities were dominated by Prevotella, followed by Acinetobacter and Lactobacillus. Further inspection revealed that Lactobacillus was identified to be positively associated with villus height, whereas Acinetobacter and Prevotella were prone to reside in deep crypts. Furthermore, intestinal microbiota in Shanxi Black pigs had more metabolic and less infectious functions than that in Large White pigs. In short, our data present here indicated that microbiota with longitudinal diversity and lower infection in Shanxi Black pigs might contribute to the relatively stronger adaptability in comparison with Large White pigs.