Project description:Inferring in humans biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to M-^StranslateM-^T the results to humans. In this context, the Systems Biology Verification for Industrial Methodology for Process Verification in Research (SBV IMPROVER) initiative had run a Species Translation Challenge for the scientific community to explore and understand the limit of translatability from rodent to human using systems biology. Therefore, a multi-layer omics dataset was generated that comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, the generation, processing and quality control analysis of the multi-layer omics dataset. The datasets are accessible in public repositories could be leveraged for further translation studies.
Project description:Embryonic genome activation (EGA) marks the onset of embryonic program and enables the transition toward the first lineage specification. However, the molecular features of EGA and the transcription factors (TFs) orchestrating this process remain unclear. Here, by performing single-cell RNA-seq on bovine embryos, we reveal that major EGA is asynchronously initiated among blastomeres at the 8-cell stage. Integrative analyses reveal distinctive protein accumulation compared to transcription and translation activation during bovine EGA. Furthermore, we investigate the role of SP1, a TF activated at the minor EGA stage, with motifs enriched in accessible chromatin during major EGA stage in bovine and human embryos. SP1 deficiency leads to morula arrest in bovine and impairs EGA in human embryos. Multi-omics analysis demonstrates that SP1 promotes early lineage gene expression by modulating nearby chromatin states in bovine and directly targets key EGA genes in human embryos. Together, our study delineates the dynamics of bovine EGA and uncovers the conserved and species-specific roles of SP1 in regulating EGA and early development in mammals.
Project description:The Quartet Project aims to provide resources for QC of multiple types of omic technologies and the effective integration of diverse datasets from various scenarios. Large quantities of multi-omics materials, datasets, and best practices for their QC utilities were developed for whole process QC of large-scale, multi-center, and longitudinal multi-omics profiling.
Project description:Despite early clinical success, the mechanisms of action of low-dose interleukin-2 (LD-IL-2) immunotherapy remain only partly understood. This dataset was generated using samples from the DILfrequency clinical trail, to examine the effects of interval administration of low-dose recombinant IL-2 (iLD-IL-2) using high-resolution, single-cell multi-omics.
Project description:The development of single cell transcriptomic technologies yields large datasets comprising multimodal informations such as transcriptomes and immunophenotypes. Currently however, there is no software to easily and simultaneously analyze both types of data. Here, we introduce Single-Cell Virtual Cytometer, an open-source software for flow cytometry-like visualization and exploration of multi-omics single cell datasets. Using an original CITE-seq dataset of PBMC from an healthy donor, we illustrate its use for the integrated analysis of transcriptomes and epitopes of functional maturation in peripheral T lymphocytes from healthy donors. So this free and open-source algorithm constitutes a unique resource for biologists seeking for a user-friendly analytic tool for multimodal single cell datasets.
Project description:Early cancer detection remains a major clinical challenge. Circulating immune biomarkers provide a promising, non-invasive diagnostic opportunity, yet their potential remains insufficiently defined. Here, we present an integrated multi-omics analysis of peripheral blood mononuclear cells (PBMCs) from treatment-naïve cancer patients, combining immune phenotyping (flow cytometry, FC), multiplex cytokine profiling, and single-cell RNA sequencing (sc-RNA-seq). Compared with healthy controls, patients exhibited widespread immune dysregulation, including expansion of FOXP3+ regulatory T cells, depletion of CD16+CD11b+ monocytes and CD56dim NK cells, and elevated plasma IL-6/IL-4 levels. Sc-RNA-seq identified novel cancer-specific immune signatures, notably consistent upregulation of THBS1 and CH25H, indicative of systemic imprinting by tumor-derived cues. Deep learning models integrating single cell multi-omics data (sc-FC + sc-RNA-Seq) achieved performance comparable to clinical models, enabling cancer-type stratification and mechanistic insight. These findings establish a framework for immune-based, multi-omics diagnostics in early cancer detection and disease monitoring.
Project description:Total RNA-seq of blasts derived 100 adult T-ALL cases, 211 AML cases and 13 mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, CD34+ HSPCs derived from 9 healthy donors are used as a control. Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011054, EGAD00001007646, EGAD00001007581 (datasets).
Project description:KRAS mutation is widely presumed to confer independence from upstream RTK signalling, however emerging evidence from mouse models of lung cancer suggests that ERBB RTKs may amplify signalling through RAS isoforms and participate in mutant RAS-driven lung cancer. This is one of 3 datasets where we examined the transcriptional impact of treatment of KRAS mutant human lung cancer cell lines with the multi-ERBB inhibitor Neratinib
Project description:KRAS mutation is widely presumed to confer independence from upstream RTK signalling, however emerging evidence from mouse models of lung cancer suggests that ERBB RTKs may amplify signalling through RAS isoforms and participate in mutant RAS-driven lung cancer. This is one of 3 datasets where we examined the transcriptional impact of treatment of KRAS mutant human lung cancer cell lines with the multi-ERBB inhibitor Neratinib
Project description:KRAS mutation is widely presumed to confer independence from upstream RTK signalling, however emerging evidence from mouse models of lung cancer suggests that ERBB RTKs may amplify signalling through RAS isoforms and participate in mutant RAS-driven lung cancer. This is one of 3 datasets where we examined the transcriptional impact of treatment of KRAS mutant human lung cancer cell lines with the multi-ERBB inhibitor Neratinib