Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Cell passage number: an intrinsic factor influencing the reproducibility of cell experiments

ABSTRACT: The reproducibility of scientific research has been increasingly challenged in recent years. While extrinsic factors (e.g., cross-contamination, mycoplasma infection, serum variability) are well-studied, the role of intrinsic attributes like cell passage number remains underexplored. Using two tumor cell lines (ACHN and Renca), we employed RNA sequencing to analyze transcriptomic dynamics across passages (P3 to P39). Results revealed a nonlinear transcriptomic shift: mid-passage cells (P10/P11, P17) showed heightened activity in cell cycle, metabolism, and stress response, whereas low (P3) and high passages (P24/P39) exhibited stable and similar profiles. KEGG analysis indicated significant alterations in signaling, immune, and metabolic pathways during passaging. This study demonstrates that passage number shapes transcriptional landscapes and impacts experimental reproducibility. We advocate for strict passage control and explicit reporting of passage information to enhance reliability. These findings underscore the need for standardized cell culture practices to improve research reproducibility.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE308793 | GEO | 2025/09/24

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Discovery of progenitor signatures by time series synexpression analysis during Drosophila cell immortalization [RNA-Seq]

Project description:To characterize the sequence of events associated with RasV12 immortalization of Drosophila embryonic cells, we generated transcriptional time series during cell line establishment, from primary cultures until passage (P) 19. We generated three transcriptional time series from three cell lines (R1, R4 and R5) by sampling the cultures at successive stages, early (P2-4), intermediate (P4-11), and late (P16-19), characterized by different passage times. Time points for the R1 time-series were: P2, P3, P4, P5, P7, P8, P10, P11, P16, P17 and P19; for the R4 time-series: P2, P3, P4, P5, P6, P7, P9, P11, P12, P16, P17 and P19; and for the R5 time-series: P2, P3, P4, P6, P7, P8, P16, P17 and P19

2015-09-24 | E-GEOD-73353 | biostudies-arrayexpress

Protein microarray epitope mapping of monoclonal antibody 5H2 raised by human immunization with the 4CMenB vaccine formulation containing the fusion antigen NHBA-NMB1030.

Project description:The aim of the study was to determine the epitope targeted by 5H2 human Fab directed against NHBA and the crossreactivity aginst a panel of nine different NHBA long and short peptide variants (p2, p3, p5, p10, p17, p20, p21, p24, p29). 5H2 were diluted at 1:2000 and incubated on a non-commercial Protein Microarray platform printed with NHBAp2 specific recombinant protein fragments and full length NHBA of different variants.

2018-08-30 | GSE112752 | GEO

Discovery of progenitor signatures by time series synexpression analysis during Drosophila cell immortalization [Microarray Expression]

Project description:To characterize the sequence of events associated with RasV12 immortalization of Drosophila embryonic cells, we generated transcriptional time series during cell line establishment, from primary cultures until passage (P) 19. We generated two transcriptional time series from two cell lines (R3 and R7) by sampling the cultures at successive stages, early (P2-4), intermediate (P4-11), and late (P16-19), characterized by different passage times. Time points for the R3 time-series were: P2, P2 (replicate), P5, P6, P7, P8, P16, P17 and P19; for the R7 time-series: P2, P2 (replicate), P3, P4, P7, P8, P16, P17 and P19.

2015-09-23 | E-GEOD-73335 | biostudies-arrayexpress

Campylobacter jejuni murine adaptation: unadapted v. adapted

Project description:Expression arrays comparing Campylobacter jejuni 11168 before and after serial passage in C57 BL/6 IL-10 deficient mice. Gene expression was compared during exponential growth in Bolton broth. Unpassaged (p0) C. jejuni 11168 was compared to the same strain after 1 passage (p1) and after three passages (p3) through the mice. Biological replicates: 4 for p0 v. p1, 3 for p0 v. p3

2009-08-07 | E-GEOD-17562 | biostudies-arrayexpress

Campylobacter jejuni murine adaptation: unadapted v. adapted during growth in C57 BL/6 IL-10-/- germ-free mice.

Project description:Expression arrays comparing Campylobacter jejuni 11168 before and after serial passage in C57 BL/6 IL-10 deficient mice. Transcript abundance was compared between C. jejuni variants during growth in the ceca of C57 BL/6 IL-10 deficient germ-free mice. Unpassaged (p0) C. jejuni 11168 was compared to the same strain after three passages (p3) through the mice. Biological replicates: 4; 2 biological replicates were dye swaps.

2010-08-27 | E-GEOD-23811 | biostudies-arrayexpress

From mouse to humans: detecting preventing vaccination targets associated to breast cancer stem cells. Exon-level analysis

Project description:TuBo cell line (E) was compared to passage 1 (P1), 2 (P2) and 3 (P3) mammospheres to detect specific transcription isoforms associated to cancer stem cell. TuBo cell line (E) was compared to passage 1 (P1), 2 (P2) and 3 (P3) mammospheres. Exon-level transcription profiling was done using Affimetrix GeneChip Exon 1.0 ST. Exon-level analysis is more complex than gene-level analysis. The number of probesets to be investigated is at least 10 times larger in number than gene-level probesets. Thus results, upon statistical analysis, are massively contaminated by type I statistical errors, i.e. false positive [Della Beffa et al. 2008]. Furthermore, exon-level probesets are based only on four probes, which makes exon-level signal summarization more noisy than gene-level, where signal summarization is based on the overall probes encompassed by all exons of a gene. To moderate these issues we have expanded the number of experimental replications: six for TuBo and passage 1 mammosphere, four for passage 3 mammosphere and three for passage 2 mammosphere. Furthermore, after data summarization with RMA and normalization with sketch quantile method, alternative splicing detection between epithelial and mammospheres passages, was assessed using MiDAS, a two way anova developed by Affymetrix for the detection of alternative splicing events. We considered suitable for further investigations the splicing events in common between the sets of exons detected as spliced in each of the following comparisons: E vs P1, E vs P2 and E vs P3.

2013-11-30 | E-GEOD-21475 | biostudies-arrayexpress

Evaluation Of Wharton's Jelly Mesenchymal Stem Cells Secretome Profiling Derived In Time And Passage Dependent Manner

Project description:The data provided is from LCMS run of Wharton's Jelly Mesenchymal Stem Cells (WJMSC) derived secretomes. The samples consist of secretomes harvested at different time points (24, 48, and 72 hours) and passage numbers (P3, P5, and P10). The samples used were taken from 3 donors, with 3 technical runs for each sample. Thus, a total of 81 samples of data were collected. The research aims to understand how the composition of the secretome changes over time and with different cell passages. Advanced proteomic techniques are used to analyze the bioactive molecules secreted by WJMSCs, highlighting the impact of time and cell passage number on the therapeutic potential of these cells. This research seeks to enhance the clinical efficiency of WJMSCs for regenerative medicine applications by revealing the dynamic nature of their secretome.

2024-11-09 | MSV000096363 | MassIVE

Single Cell Sequencing Reveals Gene Expression Signatures Associated with Bone Marrow Stromal Cell Subpopulations and Time in Culture [microarray]

Project description:Background Bone marrow stromal cells (BMSCs) are a heterogeneous population that participates in wound healing, immune modulation and tissue regeneration. Next generation sequencing was used to analyze transcripts from single BMSCs in order to better characterize BMSC subpopulations. Methods Cryopreserved passage 2 BMSCs from one healthy subject were cultured through passage 10. The transcriptomes of bulk BMSCs from designated passages were analyzed with microarrays and RNA sequencing (RNA-Seq). For some passages, single BMSCs were separated using microfluidics and their transcriptomes were analyzed by RNA-Seq. Results Transcriptome analysis microarray and RNA-Seq of unseparated BMSCs from passages 2, 4, 6, 8, 9 and 10 yielded similar results; both data sets grouped passages 4 and 6 and passages 9 and 10 together and genes differentially expressed among these early and late passage BMSCs were similar. 3D Diffusion map visualization of single BMSCs from passages 3, 4, 6, 8 and 9 clustered passage 3 and 9 into two distinct groups, but there was considerable overlap for passage 4, 6 and 8 cells. Markers for early passage, FGFR2, and late passage BMSCs, PLAT, were able to identify three subpopulations within passage 3 BMSCs; one that expressed high levels of FGFR2 and low levels of PLAT; one that expressed low levels of FGFR2 and high levels of PLAT and one that expressed intermediate levels of FGFR2 and low levels of PLAT. Conclusions Single BMSCs can be separated by microfluidics and their transcriptome analyzed by next generation sequencing. Single cell analysis of early passage BMSCs identified a subpopulation of cells expressing high levels of FGFR2 that might include skeletal stem cells.

2019-01-10 | GSE124860 | GEO

Single Cell Sequencing Reveals Gene Expression Signatures Associated with Bone Marrow Stromal Cell Subpopulations and Time in Culture [NGS_bulk cell RNA-seq]

2019-01-10 | GSE124859 | GEO

Single Cell Sequencing Reveals Gene Expression Signatures Associated with Bone Marrow Stromal Cell Subpopulations and Time in Culture [scRNA-seq]

2019-01-10 | GSE124858 | GEO