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1.
Int J Mol Sci ; 22(13)2021 Jun 29.
Article in English | MEDLINE | ID: mdl-34209696

ABSTRACT

Up to 40% of advance lung, melanoma and breast cancer patients suffer from brain metastases (BM) with increasing incidence. Here, we assessed whether circulating tumor cells (CTCs) in peripheral blood can serve as a disease surrogate, focusing on CD44 and CD74 expression as prognostic markers for BM. We show that a size-based microfluidic approach in combination with a semi-automated cell recognition system are well suited for CTC detection in BM patients and allow further characterization of tumor cells potentially derived from BM. CTCs were found in 50% (7/14) of breast cancer, 50% (9/18) of non-small cell lung cancer (NSCLC) and 36% (4/11) of melanoma patients. The next-generation sequencing (NGS) analysis of nine single CTCs from one breast cancer patient revealed three different CNV profile groups as well as a resistance causing ERS1 mutation. CD44 and CD74 were expressed on most CTCs and their expression was strongly correlated, whereas matched breast cancer BM tissues were much less frequently expressing CD44 and CD74 (negative in 46% and 54%, respectively). Thus, plasticity of CD44 and CD74 expression during trafficking of CTCs in the circulation might be the result of adaptation strategies.


Subject(s)
Antigens, Differentiation, B-Lymphocyte/genetics , Brain Neoplasms/genetics , Brain Neoplasms/secondary , Histocompatibility Antigens Class II/genetics , Hyaluronan Receptors/genetics , Neoplastic Cells, Circulating/metabolism , Antigens, Differentiation, B-Lymphocyte/metabolism , Biomarkers, Tumor , Brain Neoplasms/diagnosis , Breast Neoplasms/pathology , Carcinoma, Non-Small-Cell Lung/pathology , Cell Line, Tumor , Female , Histocompatibility Antigens Class II/metabolism , Humans , Hyaluronan Receptors/metabolism , Immunohistochemistry , Male , Mutation , Whole Genome Sequencing
2.
BMC Genomics ; 15: 675, 2014 Aug 11.
Article in English | MEDLINE | ID: mdl-25113896

ABSTRACT

BACKGROUND: Gene expression analysis by RNA sequencing is now widely used in a number of applications surveying the whole transcriptomes of cells and tissues. The recent introduction of ribosomal RNA depletion protocols, such as RiboZero, has extended the view of the polyadenylated transcriptome to the poly(A)- fraction of the RNA. However, substantial amounts of intronic transcriptional activity has been reported in RiboZero protocols, raising issues regarding their potential nuclear origin and the impact on the actual sequence depth in exonic regions. RESULTS: Using HEK293 human cells as source material, we assessed here the impact of the two commonly used RNA extraction methods and of the library construction protocols (rRNA depletion versus mRNA) on 1) the relative abundance of intronic reads and 2) on the estimation of gene expression values. We benchmarked the rRNA depletion-based sequencing with a specific analysis of the cytoplasmic and nuclear transcriptome fractions, suggesting that the large majority of the intronic reads correspond to unprocessed nuclear transcripts rather than to independent transcriptional units. We show that Qiagen or TRIzol extraction methods retain differentially nuclear RNA species, and that consequently, rRNA depletion-based RNA sequencing protocols are particularly sensitive to the extraction methods. CONCLUSIONS: We could show that the combination of Trizol-based RNA extraction with rRNA depletion sequencing protocols led to the largest fraction of intronic reads, after the sequencing of the nuclear transcriptome. We discuss here the impact of the various strategies on gene expression and alternative splicing estimation measures. Further, we propose guidelines and a double selection strategy for minimizing the expression biases, without loss of information.


Subject(s)
RNA, Messenger/isolation & purification , Gene Expression Profiling , Gene Library , HEK293 Cells , Humans , Proto-Oncogene Proteins B-raf/genetics , RNA Splicing , RNA, Long Noncoding/genetics , RNA, Long Noncoding/isolation & purification , RNA, Messenger/genetics , Sequence Analysis, RNA , Transcriptome
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