In the early, online version of the Proceedings of the National Academy of Sciences, researchers from Rice University and Baylor College of Medicine explore three-dimensional chromosome structures with the help of epigenetic profiling. Using chromatin immunoprecipitation sequencing-based epigenetic profiling, combined with genomic compartment cues gleaned from H-C proximity ligation, the team established a chromatin organization model based on neural network-based machine learning strategies. The model was trained on odd-numbered chromosomes before being applied for even-numbered chromosome conformation predictions, leading to three-dimensional predictions that were subsequently verified by fluorescence microscopy and DNA interaction assays.
A University of Tübingen-led team profiles the antigens, or human leukocyte antigen ligand collection, that may be flagged by T immune cells in ovarian carcinoma cancers. The team turned to immunohistochemistry, RNA sequencing, and mass spectrometry-based immunopeptidomics to assess HLA-presented antigens in more than two dozen ovarian cancer samples and roughly as many matched normal fallopian tube tissue samples. "[O]ur study provides deep insights into the immunopeptidome of [epithelial ovarian cancer], highlighting new rational targets based on frequently naturally presented and immunogenic HLA ligands, which can be further developed for different immunotherapeutic approaches," the authors write.
Finally, investigators from the University of Arizona, the University of Wisconsin-Madison, and the University of California, Los Angeles, explore potential ties between language use, adverse social conditions, and the expression of immune cell genes implicated in stress response, together termed the "conserved transcriptional response to adversity" (CTRA). By bringing together microarray-based gene expression patterns for 50 CTRA-related genes, natural language use data in tens of thousands of audio recordings, and self-reported stress, depression, anxiety clues for 143 healthy adults, the team uncovered potential ties between language markers of adversity and expression of CTRA indicator genes. Based on these findings, the authors argue that "patterns of natural language use may provide a useful behavioral indicated of non-consciously evaluated well-being."