Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumor research, enabling exploration of molecular complexities at the individual cell level. It offers new technical possibilities for advancing tumor research and is anticipated to yield significant breakthroughs. However, deciphering meaningful insights from scRNA-seq data poses challenges, particularly in cell annotation and tumor subpopulation identification. Efficient algorithms are needed to unravel the intricate biological processes of cancer. To address these challenges, benchmarking datasets are essential to validate bioinformatics tools focusing on the analysis of single-cell omics in oncology. Here, we present a 10XGenomics scRNA-seq experiment, providing a controlled heterogeneity environment using lung cancer cell lines characterised by expressing seven different driver genes (EGFR, ALK, MET, ERBB2, KRAS, BRAF, ROS1), which are characterised by the presence of partial overlaps in their functional pathways. Furthermore, PBMC from a healthy donor were also sequenced

ORGANISM(S): Homo sapiens

PROVIDER: GSE243665 | GEO | 2023/12/02

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Mig6 mediates adaptive and acquired resistance to ALK and ROS1 fusion kinase inhibition through feedback activation of EGFR: H3122

Project description:ALK and ROS1 fusions defines subsets of lung adenocarcinoma. Although ALK/ROS1 inhibitors improved therapeutic outcome of patients harboring those oncogenic fusions, complete responses were rare, and resistance eventually develops from the residual tumor. To under the mechanisms contributing to residual tumor formation, we performed phosphoproteomics to explore the signaling adaption shortly after ALK/ROS1 inhibition. We found the phosphorylation of Mig6, a potent inhibitor for EGFR, was decreased following ALK/ROS1 inhibition, impairing Mig6 binding and inhibition on EGFR. Furthermore, Mig6 mRNA and protein levels were decreased rapidly by ALK/ROS1 inhibitors, potentiating EGFR activity to support cell survival. We also uncovered a novel mechanism mediated by Mig6 to regulate EGFR activity without impacting EGFR phosphorylation, but rather altering signaling adaptor SHC1 binding to EGFR. Mig6 expression was also lost following long-term exposure to ALK/ROS1 inhibitors to support EGFR-mediated acquired resistance. Finally, a Mig6 EGFR-binding domain truncation mutation was identified in a patient-derived ROS1 cell line, rendering its resistance to ROS1 inhibitors but sensitivity to HER family inhibitors. Our work established a rationale to evaluate combinations of ALK/ROS1 and EGFR inhibitors to limit residual tumor formation, therefore preventing or delaying subsequent resistance emergence.

2023-09-12 | PXD036772 | Pride

Mig6 mediates adaptive and acquired resistance to ALK and ROS1 fusion kinase inhibition through feedback activation of EGFR: Cuto28

2023-09-12 | PXD036771 | Pride

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods

Project description:Single cell RNA sequencing (scRNA-seq) technology has undergone rapid development in recent years and brings new challenges in data processing and analysis. This has led to an explosion of tailored analysis methods for scRNA-seq to address various biological questions. However, the current lack of gold-standard benchmarking datasets makes it difficult for researchers to evaluate the performance of the many methods available in a systematic manner. Here, we designed and generated a cross-platform benchmark dataset that has in-built truth in various forms and varying levels of biological noise. We used this dataset to compare different protocols and data analysis methods. We found that different protocols have different data quality and ERCC spike-in works independently to endogenous RNA. We found significant differences in the results from the methods compared and we associated the results with data characteristics to identify methods that perform well in different situations. Our dataset and analysis provide a valuable resource for algorithm selection in different biological settings.

2019-12-19 | GSE142286 | GEO

A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity.

Project description:Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumour research, enabling the exploration of molecular complexities at the individual cell level. It offers new technical possibilities for advancing tumour research with the potential to yield significant breakthroughs. However, deciphering meaningful insights from scRNA-seq data poses challenges, particularly in cell annotation and tumour subpopulation identification. Efficient algorithms are therefore needed to unravel the intricate biological processes of cancer. To address these challenges, benchmarking datasets are essential to validate bioinformatics methodologies for analysing single-cell omics in oncology. Here, we present a 10XGenomics scRNA-seq experiment, providing a controlled heterogeneous environment using lung cancer cell lines characterised by the expression of seven different driver genes (EGFR, ALK, MET, ERBB2, KRAS, BRAF, ROS1), leading to partially overlapping functional pathways. Our dataset provides a comprehensive framework for the development and validation of methodologies for analysing cancer heterogeneity by means of scRNA-seq.

| S-EPMC10837414 | biostudies-literature

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (Cel_Seq)

2018-08-18 | GSE118704 | GEO

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (RNAmix_CEL-seq2 )

2018-08-19 | GSE117617 | GEO

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (Drop-Seq)

2018-08-18 | GSE118706 | GEO

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (RNAmix_Sort-seq)

2018-07-25 | GSE117618 | GEO

Acquired resistance to entrectinib or crizotinib drives differential gene expression in ROS1+ NSCLC

Project description:Utilizing primary, patient tumor-derived ROS1+ NSCLC cell lines, we derived TKI-resistant cell lines by chronic exposure to TKI in the media. One of our parental, ROS1 TKI-sensitive cell lines harbors a TPM3-ROS1 fusion (CUTO28) and the other harbors a CD74-ROS1 fusion (CUTO37). Entrectinib-resistant (-ER) and crizotinib-resistant (-CR) lines are so named when they are stably proliferating at 500nM concentration of the respective TKI. We sought to investigate transcriptome changes with acquired resistance to entrectinib or crizotinib.

2022-10-06 | GSE214715 | GEO