Neutrophils in the era of single-cell RNA sequencing: functions and targeted therapies in cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Qin J
PROVIDER: S-EPMC10845925 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
Publications
Neutrophils in the era of single-cell RNA sequencing: functions and targeted therapies in cancer.
Qin Jing J Wei Feng F Ren Xiubao X
Cancer biology & medicine 20240201 12
Similar Datasets
Project description: Not available
| S-EPMC8819738 | biostudies-literature
Project description:Pancreatic cancer, one of the most prevalent tumors of the digestive system, has a dismal prognosis. Cancer of the pancreas is distinguished by an inflammatory tumor microenvironment rich in fibroblasts and different immune cells. Neutrophils are important immune cells that infiltrate the microenvironment of pancreatic cancer tumors. The purpose of this work was to examine the complex mechanism by which neutrophils influence the carcinogenesis and development of pancreatic cancer and to construct a survival prediction model based on neutrophil marker genes. We incorporated the GSE111672 dataset, comprising RNA expression data from 27,000 cells obtained from 3 patients with PC, and conducted single-cell data analysis. Thorough investigation of pancreatic cancer single-cell RNA sequencing data found 350 neutrophil marker genes. Using The Cancer Genome Atlas (TCGA), GSE28735, GSE62452, GSE57495, and GSE85916 datasets to gather pancreatic cancer tissue transcriptome data, and consistent clustering was used to identify two categories for analyzing the influence of neutrophils on pancreatic cancer. Using the Random Forest algorithm and Cox regression analysis, a survival prediction model for pancreatic cancer was developed, the model showed independent performance for survival prognosis, clinic pathological features, immune infiltration, and drug sensitivity. Multivariate Cox analysis findings revealed that the risk scores derived from predictive models is independent prognostic markers for pancreatic patients. In conclusion, based on neutrophil marker genes, this research created a molecular typing and prognostic grading system for pancreatic cancer, this system was very accurate in predicting the prognosis, tumor immune microenvironment status, and pharmacological treatment responsiveness of pancreatic cancer patients.
| S-EPMC10564426 | biostudies-literature
Project description:Human Epidermal Growth Factor Receptor 2-positive breast cancer (HER2+ BC) is defined by increased amplification of the ERBB2/neu oncogene and/or overexpression of its associated HER2 transmembrane receptor protein. HER2+ BC represents approximately 15-20% of breast cancer, and it is independently associated with a higher grade, more aggressive phenotype, and worse prognosis. With the advent of trastuzumab, the prognostic landscape for HER2+ BC patients has considerably improved. However, both de novo and acquired resistance to trastuzumab remain a significant obstacle for many patients, requiring novel therapies for further clinical benefit. Over the last two decades, there has been extraordinary progress in the development of HER2+ BC treatment regimens, with extensions into HER2-amplified gastroesophageal junction cancer via the NCI-MATCH precision medicine trial program (NCT02465060). Trastuzumab, pertuzumab, T-DM1, and lapatinib are commonly recommended as a single agent (along with chemotherapy) or in combinations of anti-HER2 agents in neoadjuvant, adjuvant and metastatic settings according to National Comprehensive Cancer Network (NCCN) guidelines. Currently, the combination of trastuzumab, pertuzumab, and taxane chemotherapy are first-line for HER2+/HR- metastatic breast cancer with potential breakthrough therapies such as trastuzumab-deruxtecan (DS-8201a), margetuximab and tucatinib (ONT-380) on the horizon. Furthermore, recent clinical trials have demonstrated the potential utility of hormone receptor status, PAM-50 luminal intrinsic subtype, PD-L1, and TIL as predictive biomarkers for response to HER2+ therapies. We briefly introduce the origin of HER2, the invention of trastuzumab, and the classification of HER2+ BC. Each HER2-targeted therapy is then presented by indication, mechanism of action, and relevant clinical trials with subsequent elaboration and contextualization within clinical settings with an epilogue of potential future biomarkers for clinical use in HER2+ BC. We summarize the most significant and updated research in clinical practice relevant to HER2+ BC management and highlight the clinical status of upcoming anti-HER2 agents as well as immunotherapy drugs in combination with anti-HER2 agents.
| S-EPMC7191090 | biostudies-literature
Project description:Analyzing every cell in a diverse sample provides insight into population-level heterogeneity, but abundant cell types dominate the analysis and rarer populations are scarcely represented in the data. To focus on specific cell types, the current paradigm is to physically isolate subsets of interest prior to analysis; however, it remains difficult to isolate and then single-cell sequence such populations because of compounding losses. Here, we describe an alternative approach that selectively merges cells with reagents to achieve enzymatic reactions without having to physically isolate cells. We apply this technique to perform single-cell transcriptome and genome sequencing of specific cell subsets. Our method for analyzing heterogeneous populations obviates the need for pre- or post-enrichment and simplifies single-cell workflows, making it useful for other applications in single-cell biology, combinatorial chemical synthesis, and drug screening.
| S-EPMC8182774 | biostudies-literature
Project description:Single-cell CRISPR screens enable the exploration of mammalian gene function and genetic regulatory networks. However, use of this technology has been limited by reliance on indirect indexing of single-guide RNAs (sgRNAs). Here we present direct-capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct-capture Perturb-seq enables detection of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries that contain dual-guide expression vectors. We demonstrate the utility of this approach for high-throughput investigations of genetic interactions and, leveraging this ability, dissect epistatic interactions between cholesterol biogenesis and DNA repair. Using direct capture Perturb-seq, we also show that targeting individual genes with multiple sgRNAs per cell improves efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for single-cell screens. Last, we show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments.
| S-EPMC7416462 | biostudies-literature
Project description:Over 90% of head and neck cancers overexpress the epidermal growth factor receptor (EGFR). In diverse tumor types, EGFR overexpression has been associated with poorer prognosis and outcomes. Therapies targeting EGFR include monoclonal antibodies, tyrosine kinase inhibitors, phosphatidylinositol 3-kinase (PI3K) inhibitors, and antisense gene therapy. Few EGFR-targeted therapeutics are approved for clinical use. The monoclonal antibody cetuximab is a Food and Drug Administration (FDA)-approved EGFR-targeted therapy, yet has exhibited modest benefit in clinical trials. The humanized monoclonal antibody nimotuzumab is also approved for head and neck cancers in Cuba, Argentina, Colombia, Peru, India, Ukraine, Ivory Coast, and Gabon in addition to nasopharyngeal cancers in China. Few other EGFR-targeted therapeutics for head and neck cancers have led to as significant responses as seen in lung carcinomas, for instance. Recent genome sequencing of head and neck tumors has helped identify patient subgroups with improved response to EGFR inhibitors, for example, cetuximab in patients with the KRAS-variant and the tyrosine kinase inhibitor erlotinib for tumors harboring MAPK1E322K mutations. Genome sequencing has furthermore broadened our understanding of dysregulated pathways, holding the potential to enhance the benefit derived from therapies targeting EGFR.
| S-EPMC5693744 | biostudies-literature
Project description:Adaptive T and B lymphocytes expand, respond, and persist across a multitude of separable cell differentiation states. Small compartments of these cells present defined cell surface phenotype, but express potentially divergent immune functions. Here, we use high resolution flow cytometry to provide direct access to rare lymphocyte subpopulations for evaluation of steady-state or reactive transcriptional programs. We sort and index single cells by phenotype in 384-well format for quantification of targeted gene amplification through RNA sequencing (single cell qtSEQ). For complete details on the use and execution of this profile, please refer to Dufaud et al. (2021).
| S-EPMC8715333 | biostudies-literature
Project description:Targeted therapies require information on specific defective signaling pathways or mutations. Advances in genomic technologies and cell biology have led to identification of new therapeutic targets associated with signal-transduction pathways. Survival times of patients with colorectal cancer (CRC) can be extended with combinations of conventional cytotoxic agents and targeted therapies. Targeting EGFR- and VEGFR-signaling systems has been the major focus for treatment of metastatic CRC. However, there are still limitations in their clinical application, and new and better drug combinations are needed. This review provides information on EGFR and VEGF inhibitors, new therapeutic agents in the pipeline targeting EGFR and VEGFR pathways, and those targeting other signal-transduction pathways, such as MET, IGF1R, MEK, PI3K, Wnt, Notch, Hedgehog, and death-receptor signaling pathways for treatment of metastatic CRC. Additionally, multitargeted approaches in combination therapies targeting negative-feedback loops, compensatory networks, and cross talk between pathways are highlighted. Then, immunobased strategies to enhance antitumor immunity using specific monoclonal antibodies, such as the immune-checkpoint inhibitors anti-CTLA4 and anti-PD1, as well as the challenges that need to be overcome for increased efficacy of targeted therapies, including drug resistance, predictive markers of response, tumor subtypes, and cancer stem cells, are covered. The review concludes with a brief insight into the applications of next-generation sequencing, expression profiling for tumor subtyping, and the exciting progress made in in silico predictive analysis in the development of a prescription strategy for cancer therapy.
| S-EPMC4821380 | biostudies-literature
Project description:Cancer stem cells (CSC) play a critical role in metastasis, relapse, and therapy resistance in colorectal cancer. While characterization of the normal lineage of cell development in the intestine has led to the identification of many genes involved in the induction and maintenance of pluripotency, recent studies suggest significant heterogeneity in CSC populations. Moreover, while many canonical colorectal cancer CSC marker genes have been identified, the ability to use these classical markers to annotate stemness at the single-cell level is limited. In this study, we performed single-cell RNA sequencing on a cohort of 6 primary colon, 9 liver metastatic tumors, and 11 normal (nontumor) controls to identify colorectal CSCs at the single-cell level. Finding poor alignment of the 11 genes most used to identify colorectal CSC, we instead extracted a single-cell stemness signature (SCS_sig) that robustly identified "gold-standard" colorectal CSCs that expressed all marker genes. Using this SCS_sig to quantify stemness, we found that while normal epithelial cells show a bimodal distribution, indicating distinct stem and differentiated states, in tumor epithelial cells stemness is a continuum, suggesting greater plasticity in these cells. The SCS_sig score was quite variable between different tumors, reflective of the known transcriptomic heterogeneity of CRC. Notably, patients with higher SCS_sig scores had significantly shorter disease-free survival time after curative intent surgical resection, suggesting stemness is associated with relapse.ImplicationsThis study reveals significant heterogeneity of expression of genes commonly used to identify colorectal CSCs, and identifies a novel stemness signature to identify these cells from scRNA-seq data.
| S-EPMC10987274 | biostudies-literature
Project description:Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.
| S-EPMC10985232 | biostudies-literature