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From phenotypical investigation to RNA-sequencing for gene expression analysis: A workflow for single and pooled rare cells.
Rossi, Tania; Angeli, Davide; Martinelli, Giovanni; Fabbri, Francesco; Gallerani, Giulia.
Afiliación
  • Rossi T; Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
  • Angeli D; Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
  • Martinelli G; Scientific Directorate, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
  • Fabbri F; Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
  • Gallerani G; Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
Front Genet ; 13: 1012191, 2022.
Article en En | MEDLINE | ID: mdl-36452152
ABSTRACT
Combining phenotypical and molecular characterization of rare cells is challenging due to their scarcity and difficult handling. In oncology, circulating tumor cells (CTCs) are considered among the most important rare cell populations. Their phenotypic and molecular characterization is necessary to define the molecular mechanisms underlying their metastatic potential. Several approaches that require cell fixation make difficult downstream molecular investigations on RNA. Conversely, the DEPArray technology allows phenotypic analysis and handling of both fixed and unfixed cells, enabling a wider range of applications. Here, we describe an experimental workflow that allows the transcriptomic investigation of single and pooled OE33 cells undergone to DEPArray analysis and recovery. In addition, cells were tested at different conditions (unfixed, CellSearch fixative (CSF)- and ethanol (EtOH)-fixed cells). In a forward-looking perspective, this workflow will pave the way for novel strategies to characterize gene expression profiles of rare cells, both single-cell and low-resolution input.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2022 Tipo del documento: Article País de afiliación: Italia