Urinary Immune Complexes Reflect Renal Pathology in Lupus Nephritis by Chenling Tang, Aygun Teymur, Tianfu Wu

“…Results: We identified 78 biomarkers, with 14 overlapping across transcriptomic categories. Novel urinary biomarkers, including SERPING1, SLPI, and CD48, were validated. …”
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Multi-task benchmarking of spatially resolved gene expression simulation models by Xiaoqi Liang, Marni Torkel, Yue Cao, Jean Yee Hwa Yang

“…Abstract Background Computational methods for spatially resolved transcriptomics (SRT) are often developed and assessed using simulated data. …”
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Identification of anoikis-related genes to develop a risk model and predict the prognosis and tumor microenvironment in rectal adenocarcinoma by Bing Zhao, Xuegui Tang

“…Immune microenvironment analysis suggested distinct differences in immune cells between the two risk groups. …”
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A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning by A. Sheryl Oliver, Md Shohel Sayeed, Siti Fatimah Abdul Razak

“…These two types grow differently and are treated differently. This review explores the application of advanced deep learning (DL) techniques in enhancing biosignature immunotherapy tools for the prediction of immune phenotypes in lung cancer patients. …”
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Identification of Energy Metabolism-Related Subtypes and Diagnostic Biomarkers for Osteoarthritis by Integrating Bioinformatics and Machine Learning by Xu S, Ye J, Cai X

“…We assessed the immune infiltration levels in OA samples using the IOBR platform and the CIBERSORT algorithm.Results: We classified OA patients into two molecular subtypes, which exhibited distinct differences in immune infiltration levels. Subsequently, we successfully identified two characteristic genes, NUP98 and RPIA, and demonstrated statistically significant differences (P < 0.05) and diagnostic performance in the validation cohort. …”
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The multi-omics analysis identifies a novel endoplasmic reticulum stress and immune related genes signature in lung adenocarcinoma by Danhe Huang, Yuying Liu, Mingyu Yuan, Xiongwei Wang, Lianqing Hong

“…Methods Utilizing transcriptomic and clinical data from the TCGA-LUAD cohort, we developed an ERS-immune prognostic signature through Least Absolute Shrinkage and Selection Operator algorithm. …”
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miR-210 promotes the anti-inflammatory phenotype and M2 polarization in murine macrophages by Carmen Alexandra Neculachi, Evelyn-Gabriela Nastase-Rusu, Laudy Cherry, Catalina Iolanda Marinescu-Colan, Spyros Tastsoglou, Bogdan Paul Cosman, Alina Madalina Popa, Cristina Panciuc, Germana Zaccagnini, Germana Zaccagnini, Sergiu Bogdan Catrina, Sergiu Bogdan Catrina, Maya Simionescu, Fabio Martelli, Fabio Martelli, Mihai Bogdan Preda, Alexandrina Burlacu

“…However, miR-210 KO cells exhibited increased phagocytosis in both M0 and M2 states, potentially as an adaptive response to their metabolic limitations. Transcriptomic analysis revealed distinct clustering between the M0 and M2 states, along with several notable differences in the transcriptional patterns between the two genotypes. …”
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Genomic landscape of breast cancer in elderly patients by Pier Selenica, Higinio Dopeso, Matteo Repetto, Thais Basili, Andrea M. Gazzo, Christopher J. Schwartz, Fatemeh Derakhshan, Antonio Marra, Lorenzo Ferrando, Regina G. H. Beets-Tan, Y. H. Wen, Dara S. Ross, Edi Brogi, Hong Zhang, Larry Norton, Sarat Chandarlapaty, Pedram Razavi, Diana Mandelker, Jorge S. Reis-Fiho, Britta Weigelt, Fresia Pareja

“…Abstract Breast cancer (BC) displays age-related histopathologic and transcriptomic heterogeneity. Whether BC in elderly patients differs genetically from that of younger individuals remains unclear. …”
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Deciphering tryptophan metabolism in colorectal cancer through multi-omics analysis by Chengcheng Zhang, Zhijing Rao, Xiangyang Zhan, Jingru Qin, Lu Yang, Qianqian Yin, Junqing Ji, Xiaoxue Zhao, Yiyi Liu, Zhanhui Lu, Guoying Wang, Xingshuai Huang, Wenbo Shi, Wan Su, Zhongqi Wang

“…In this study, we performed untargeted metabolomics analyses and identified significant differences between CRC tissues and matched adjacent tissues, highlighting alterations in tryptophan metabolism. …”
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Avelumab induces greater Fc-Fc receptor-dependent natural killer cell activation and dendritic cell crosstalk compared to durvalumab by Nicole Osborne, Amit Rupani, Vladimir Makarov, Timothy A. Chan, Raghvendra M. Srivastava

“…We show a robust enhancement in NK-cell effector function, DC maturation, reciprocal NK:DC crosstalk and DC editing that is unique to avelumab treatment using multiple functional immune assays. By transcriptomic analysis, we show for the first time pivotal differences in gene sets involved in NK-cell effector function, DC maturation, immunoregulatory interactions, and cytokine production between innate immune cells treated with avelumab versus durvalumab. …”
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Prioritizing perturbation-responsive gene patterns using interpretable deep learning by Yan Cui, Zhiyuan Yuan

“…Abstract Spatially resolved transcriptomics enables mapping of multiplexed gene expression within tissue contexts. …”
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An R package for survival-based gene set enrichment analysis by Xiaoxu Deng, Jeffrey Thompson

“…Functional enrichment analysis is usually used to assess the effects of experimental differences. However, researchers sometimes want to understand the relationship between transcriptomic variation and health outcomes like survival. …”
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Gibberellic acid-mediated transcriptional divergence underlies cold stress adaptation in two diploid cotton species by Dong Wang, Juyun Zheng, Ke Liu, Yanchao Xu, Dingsha Jin

“…Methods To explore the genetic basis of this difference, we conducted a comparative transcriptomic analysis under cold stress at 4 °C, identifying 697 and 311 species-specific differentially expressed genes (DEGs) in G. thurberi and G. trilobum, respectively. …”
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Comparison of baseline global gene expression profiles of prostate cancer cell lines LNCaP and DU145 by Khalid Ahmed, Zhannur Omarova, Alisalman Sheikh, Gulzhan Abuova, Kulsoom Ghias, Syed Hani Abidi

“…Characterizing their baseline transcriptomics profiles (without any intervention) can offer insights into baseline genetic features and oncogenic pathways that should be considered while interpreting findings after various experimental interventions such as exogenous gene transfection or drug treatment. …”
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A TRIM Family-Based Strategy for TRIMCIV Target Prediction in a Pan-Cancer Context with Multi-Omics Data and Protein Docking Integration by Yisha Huang, Jiajia Xuan, Jiayan Liang, Xixi Liu, Yonglei Luo, Xuejuan Gao, Wanting Liu

“…To achieve the precise identification of TRIMCIV targets, we developed TRIMCIVtargeter with predictive models that systematically integrates multi-dimensional PPI features—expression differences and correlations in specific cancer, comparable protein-docking scores, and cancer-specific context. …”
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An mRNA expression atlas for the duck with public RNA-seq datasets by Qiuyu Tao, Anqi Huang, Jingjing Qi, Zhao Yang, Shihao Guo, Yinjuan Lu, Xinxin He, Xu Han, Shuaixue Jiang, Mengru Xu, Yuan Bai, Tao Zhang, Shenqiang Hu, Liang Li, Lili Bai, HeHe Liu

“…A thorough understanding of the functional genomic and transcriptomic sequences is crucial for improving production efficiency. …”
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Melatonin alleviates ferroptosis triggered by cadmium via regulating ferritinophagy and iron metabolism in spermatogonia by Didi Jia, Wei Huang, Qizi Yin, Han Wang, Ziyue Wang, Mingming Zhang, Wenjing Gong, Rong Wang, Yan Zhu, Yanli Ji

“…Exposure to Cd resulted in a reduction of the mitochondrial membrane potential of the cells. The transcriptomics analysis revealed significant differences in gene expression associated with ferroptosis and autophagy. …”
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Proteomic profiling of gliomas unveils immune and metabolism-driven subtypes with implications for anti-nucleotide metabolism therapy by Jinsen Zhang, Rui Sun, Yingying Lyu, Chaxian Liu, Ying Liu, Yuan Feng, Minjie Fu, Peter Jih Cheng Wong, Zunguo Du, Tianming Qiu, Yi Zhang, Dongxiao Zhuang, Zhiyong Qin, Yu Yao, Wei Zhu, Tiannan Guo, Wei Hua, Hui Yang, Ying Mao

“…Despite substantial progress has been made at the genomic and transcriptomic levels, comprehensive proteomic characterization and its implications remain largely unexplored. …”
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Elevated TIM3 expression on bone marrow T cells drives immune dysfunction in early relapsed blood cancer after allogeneic hematopoietic stem cell transplantation by Thi Thuy Duong Pham, Su-Young Choi, Jeong Suk Koh, Bu-Yeon Heo, Sang-Woo Lee, Myung-Won Lee, Wonhyoung Seo, Yunseon Jang, Jung-Hyun Park, Deog-Yeon Jo, Seungyeul Yoo, Jaeyul Kwon, Ik-Chan Song

“…Moreover, regulatory T cells (Tregs) showed elevated TIM3 levels, contributing to an immunosuppressive microenvironment after allo-HSCT. Transcriptomic analysis revealed downregulation of cytotoxic granules and effector genes in DNT cells from ER patients. …”
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Mitigating Cell Cycle Effects in Multi‐Omics Data: Solutions and Analytical Frameworks by Rui Nie, Caihong Zheng, Likun Ren, Yue Teng, Yaoyu Sun, Lifei Wang, Junya Li, Jun Cai

“…Moreover, for DNA methylation and transcriptomic analyses, cell cycle‐sorted data outperformed direct comparison in elucidating the biological features of compared cells. …”
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