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Peripheral blood transcriptome in breast cancer patients as a source of less invasive immune biomarkers for personalized medicine, and implications for triple negative breast cancer
Helena Sabina Čelešnik, Uroš Potočnik, 2022, review article

Abstract: Transcriptome studies of peripheral blood cells can advance our understanding of the systemic immune response to the presence of cancer and the mechanisms underlying cancer onset and progression. This enables the identification of novel minimally invasive immune biomarkers for early cancer detection and personalized cancer management and may bring forward new immunotherapy options. Recent blood gene expression analyses in breast cancer (BC) identified distinct patient subtypes that differed in the immune reaction to cancer and were distinct from the clinical BC subtypes, which are categorized based on expression of specific receptors on tumor cells. Introducing new BC subtypes based on peripheral blood gene expression profiles may be appropriate, since it may assist in BC prognosis, the identification of patients likely to benefit from immunotherapy, and treatment efficacy monitoring. Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous, and difficult-to-treat disease, and identification of novel biomarkers for this BC is crucial for clinical decision-making. A few studies have reported TNBC-enriched blood transcriptional signatures, mostly related to strong inflammation and augmentation of altered immune signaling, that can differentiate TNBC from other classical BC subtypes and facilitate diagnosis. Future research is geared toward transitioning from expression signatures in unfractionated blood cells to those in immune cell subpopulations.
Keywords: triple negative breast cancer, transcriptome, peripheral blood, PBMC, gene expression, immune biomarker
Published in DKUM: 23.08.2023; Views: 227; Downloads: 18
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Isolation and characterization of human articular chondrocytes from surgical waste after total knee arthroplasty (TKA)
Jakob Naranđa, Lidija Gradišnik, Mario Gorenjak, Matjaž Vogrin, Uroš Maver, 2017, original scientific article

Abstract: BACKGROUND: Cartilage tissue engineering is a fast-evolving field of biomedical engineering, in which the chondrocytes represent the most commonly used cell type. Since research in tissue engineering always consumes a lot of cells, simple and cheap isolation methods could form a powerful basis to boost such studies and enable their faster progress to the clinics. Isolated chondrocytes can be used for autologous chondrocyte implantation in cartilage repair, and are the base for valuable models to investigate cartilage phenotype preservation, as well as enable studies of molecular features, nature and scales of cellular responses to alterations in the cartilage tissue. METHODS: Isolation and consequent cultivation of primary human adult articular chondrocytes from the surgical waste obtained during total knee arthroplasty (TKA) was performed. To evaluate the chondrogenic potential of the isolated cells, gene expression of collagen type 2 (COL2), collagen 1 (COL1) and aggrecan (ACAN) was evaluated. Immunocytochemical staining of all mentioned proteins was performed to evaluate chondrocyte specific production. RESULTS: Cartilage specific gene expression of COL2 and ACAN has been shown that the proposed protocol leads to isolation of cells with a high chondrogenic potential, possibly even specific phenotype preservation up to the second passage. COL1 expression has confirmed the tendency of the isolated cells dedifferentiation into a fibroblast-like phenotype already in the second passage, which confirms previous findings that higher passages should be used with care in cartilage tissue engineering. To evaluate the effectiveness of our approach, immunocytochemical staining of the evaluated chondrocyte specific products was performed as well. DISCUSSION: In this study, we developed a protocol for isolation and consequent cultivation of primary human adult articular chondrocytes with the desired phenotype from the surgical waste obtained during TKA. TKA is a common and very frequently performed orthopaedic surgery during which both femoral condyles are removed. The latter present the ideal source for a simple and relatively cheap isolation of chondrocytes as was confirmed in our study.
Keywords: aggrecan, collagen 2, gene expression, human articular chondrocytes, isolation protocol, phenotype preservation, TKA, total knee arthroplasty
Published in DKUM: 02.08.2017; Views: 1535; Downloads: 609
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Gene set enrichment meta-learning analysis: next-generation sequencing versus microarrays
Gregor Štiglic, Mateja Bajgot, Peter Kokol, 2010, original scientific article

Abstract: Background Reproducibility of results can have a significant impact on the acceptance of new technologies in gene expression analysis. With the recent introduction of the so-called next-generation sequencing (NGS) technology and established microarrays, one is able to choose between two completely different platforms for gene expression measurements. This study introduces a novel methodology for gene-ranking stability analysis that is applied to the evaluation of gene-ranking reproducibility on NGS and microarray data. Results The same data used in a well-known MicroArray Quality Control (MAQC) study was also used in this study to compare ranked lists of genes from MAQC samples A and B, obtained from Affymetrix HG-U133 Plus 2.0 and Roche 454 Genome Sequencer FLX platforms. An initial evaluation, where the percentage ofoverlapping genes was observed, demonstrates higher reproducibility on microarray data in 10 out of 11 gene-ranking methods. A gene set enrichment analysis shows similar enrichment of top gene sets when NGS is compared with microarrays on a pathway level. Our novel approach demonstrates high accuracy of decision trees when used for knowledge extraction from multiple bootstrapped gene set enrichment analysis runs. A comparison of the two approaches in sample preparation for high-throughput sequencing shows that alternating decision trees represent the optimal knowledge representation method in comparison with classical decision trees. Conclusions Usual reproducibility measurements are mostly based on statistical techniques that offer very limited biological insights into the studied gene expression data sets. This paper introduces the meta-learning-based gene set enrichment analysis that can be used to complement the analysis of gene-ranking stabilityestimation techniques such as percentage of overlapping genes or classic gene set enrichment analysis. It is useful and practical when reproducibility of gene ranking results or different gene selection techniquesis observed. The proposed method reveals very accurate descriptive models that capture the co-enrichment of gene sets which are differently enriched in the compared data sets.
Keywords: meta-learning, microarray, gene expression analysis
Published in DKUM: 05.06.2012; Views: 3392; Downloads: 329
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