Dataset Information

ComBat HarmonizR enables the integrated analysis of independently generated proteomic datasets through data harmonization with appropriate handling of missing values

ABSTRACT: The integration of proteomic datasets, generated by non-cooperating laboratories using different LC-MS/MS setups can overcome limitations in statistically underpowered sample cohorts but has not been demonstrated to this day. In proteomics, differences in sample preservation and preparation strategies, chromatography and mass spectrometry approaches and the used quantification strategy distort protein abundance distributions in integrated datasets. The Removal of these technical batch effects requires setup-specific normalization and strategies that can deal with missing at random (MAR) and missing not at random (MNAR) type values at a time. Algorithms for batch effect removal, such as the ComBat-algorithm, commonly used for other omics types, disregard proteins with MNAR missing values and reduce the informational yield and the effect size for combined datasets significantly. Here, we present a strategy for data harmonization across different tissue preservation techniques, LC-MS/MS instrumentation setups and quantification approaches. To enable batch effect removal without the need for data reduction or error-prone imputation we developed an extension to the ComBat algorithm, ´ComBat HarmonizR, that performs data harmonization with appropriate handling of MAR and MNAR missing values by matrix dissection The ComBat HarmonizR based strategy enables the combined analysis of independently generated proteomic datasets for the first time. Furthermore, we found ComBat HarmonizR to be superior for removing batch effects between different Tandem Mass Tag (TMT)-plexes, compared to commonly used internal reference scaling (iRS). Due to the matrix dissection approach without the need of data imputation, the HarmonizR algorithm can be applied to any type of -omics data while assuring minimal data loss

INSTRUMENT(S): TripleTOF 6600, Orbitrap Fusion, Q Exactive

ORGANISM(S): Homo Sapiens (human) Escherichia Coli Saccharomyces Cerevisiae (baker's Yeast) Mus Musculus (mouse)

TISSUE(S): Brain, Cell Culture

DISEASE(S): Medulloblastoma

SUBMITTER: Hannah Voß

LAB HEAD: Prof. Dr. Hartmut Schlüter

PROVIDER: PXD027467 | Pride | 2022-05-23

REPOSITORIES: Pride

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Project description:Cultured cancer cells exhibit substantial phenotypic heterogeneity when measured in a variety of ways such as sensitivity to drugs or the capacity to grow under various conditions. Among these, the ability to exhibit anchorage-independent cell growth (colony forming capacity in semisolid media), has been considered to be fundamental in cancer biology, because it has been connected with tumor cell aggressiveness in vivo such as tumorigenic and metastatic potentials, and also utilized as a marker for in vitro transformation. Although multiple genetic factors for anchorage-independence have been identified, the molecular basis for this capacity is still largely unknown. To investigate the molecular mechanisms underlying anchorage independent cell growth, we have used genome-wide DNA microarray studies to develop an expression signature associated with this phenotype. Using this signature, we identify a program of activated mitochondrial biogenesis associated with the phenotype of anchorage-independent growth and importantly, we demonstrate that this phenotype predicts potential for metastasis in primary breast and lung tumors. Keywords: Breast cancer cell lines with various colony-forming ability To develop an expression signature reflecting the capacity for anchorage-independent cell growth, we first carried out colony formation assays with 19 breast cancer cell lines in suspension culture dish with methyl-cellulose containing media. Starting with 20,000 plated cells, five cell lines (MDA-MB-361, HCC38, ZR75, Hs578T and BT483) gave rise to less than 20 colonies, while 8 cell lines (MCF7, MDA-MB-231, BT20, SKBR3, MDA-MB-435s, T47D and BT474) showed formation of more than 500 colonies. The rest of the cell lines showed an intermediate phenotype in colony forming ability (20-200 colonies; HCC1143, HCC1806, HCC1428, MDA-MB-453, CAMA1, BT549 and MDA-MB-157). Among 19 cell lines, 11 cell lines have duplicates of expression data in a different batch. We removed the batch effect of this Affymetrix expression data using ComBat according to the instruction of http://statistics.byu.edu/johnson/ComBat/Abstract.html. Therefore, this dataset is a combined and standardized data that are originally RMA formatted.

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ComBat HarmonizR enables the integrated analysis of independently generated proteomic datasets through data harmonization with appropriate handling of missing values

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