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Although a large collection of cancer cell lines are useful surrogates for patient samples, the physiological relevance of observed molecular phenotypes in cell lines remains controversial. Because transcriptome data are a representative set of molecular phenotypes in cancers, we systematically analyzed the discrepancy of global gene expression profiles between patient samples and cell lines in breast cancers. While the majority of genes exhibited general consistency between patient samples and cell lines, the expression of genes in the categories of extracellular matrix, collagen trimers, receptor activity, catalytic activity and transporter activity were significantly up-regulated only in tissue samples. Genes in the extracellular matrix, particularly collagen trimers, showed a wide variation of expression in tissue, but minimal expression and variation in cell lines. Further analysis of tissue samples exclusively revealed that collagen genes exhibited a cancer stage-dependent expressional variation based on their supramolecular structure. Prognostic collagen biomarkers associated with survival rate were also readily predicted from tissue-oriented transcriptome analysis. This study presents the limitations of cell lines and the exclusive features of tissue samples in terms of functional categories of the cancer transcriptome. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors unleash inhibitory signals on T cells conferred by tumors and surrounding stromal cells. Despite the clinical efficacy of checkpoint inhibitors, the lack of target expression and persistence of immunosuppressive cells limit the pervasive effectiveness of the therapy. These limitations may be overcome by alternative approaches that co-stimulate T cells and the immune microenvironment. Methods: We analyzed single-cell RNA sequencing data from multiple human cancers and a mouse tumor transplant model to discover the pleiotropic expression of the Interleukin 7 (IL-7) receptor on T cells, macrophages, and dendritic cells. Results: Our experiment on the mouse model demonstrated that recombinant IL-7 therapy induces tumor regression, expansion of effector CD8 T cells, and pro-inflammatory activation of macrophages. Moreover, spatial transcriptomic data support immunostimulatory interactions between macrophages and T cells. Conclusion: These results indicate that IL-7 therapy induces anti-tumor immunity by activating T cells and pro-inflammatory myeloid cells, which may have diverse therapeutic applicability. [ABSTRACT FROM AUTHOR]

Background: Cell surface proteins have provided useful targets and biomarkers for advanced cancer therapies. The recent clinical success of antibody-drug conjugates (ADCs) highlights the importance of finding selective surface antigens for given cancer subtypes. We thus attempted to develop stand-alone software for the analysis of the cell surface transcriptome of patient cancer samples and to prioritize lineage- and/or mutation-specific over-expression markers in cancer cells. Results: A total of 519 genes were selected as surface proteins, and their expression was profiled in 14 cancer subtypes using patient sample transcriptome data. Lineage/mutation-oriented analysis was used to identify subtype-specific surface markers with statistical confidence. Experimental validation confirmed the unique over-expression of predicted surface markers (MUC4, MSLN, and SLC7A11) in lung cancer cells at the protein level. The differential cell surface gene expression of cell lines may differ from that of tissue samples due to the absence of the tumor microenvironment. Conclusions: In the present study, advanced 3D models of lung cell lines successfully reproduced the predicted patterns, demonstrating the physiological relevance of cell line-based 3D models in validating surface markers from patient tumor data. Also QSurface software is freely available at http://compbio.sookmyung.ac.kr/~qsurface. [ABSTRACT FROM AUTHOR]

Background: Controlled turnover of proteins as mediated by the ubiquitin proteasome system (UPS) is an important element in plant defense against environmental and pathogen stresses. E3 ligases play a central role in subjecting proteins to hydrolysis by the UPS. Recently, it has been demonstrated that a specific class of E3 ligases termed the U-box ligases are directly associated with the defense mechanisms against abiotic and biotic stresses in several plants. However, no studies on U-box E3 ligases have been performed in one of the important staple crops, barley. Results: In this study, we identified 67 putative U-box E3 ligases from the barley genome and expressed sequence tags (ESTs). Similar to Arabidopsis and rice U-box E3 ligases, most of barley U-box E3 ligases possess evolutionary well-conserved domain organizations. Based on the domain compositions and arrangements, the barley U-box proteins were classified into eight different classes. Along with this new classification, we refined the previously reported classifications of U-box E3 ligase genes in Arabidopsis and rice. Furthermore, we investigated the expression profile of 67 U-box E3 ligase genes in response to drought stress and pathogen infection. We observed that many U-box E3 ligase genes were specifically up-and-down regulated by drought stress or by fungal infection, implying their possible roles of some U-box E3 ligase genes in the stress responses. Conclusion: This study reports the classification of U-box E3 ligases in barley and their expression profiles against drought stress and pathogen infection. Therefore, the classification and expression profiling of barley U-box genes can be used as a platform to functionally define the stress-related E3 ligases in barley. [ABSTRACT FROM AUTHOR]