Project description:Background: The molecular determinants of carcinogenesis, tumor progression and patient prognosis can be deduced from simultaneous comparison of thousands of genes by microarray analysis. However, the presence of stroma cells in surgically excised carcinoma tissues might obscure the tumor cell-specific gene expression profiles of these samples. To circumvent this complication, laser microdissection can be performed to separate tumor epithelium from the surrounding stroma and healthy tissue. In this report, we compared RNAs isolated from macrodissected, of which only surrounding healthy tissue had been removed, and microdissected rectal carcinoma samples by microarray analysis in order to determine the most reliable approach to detect the expression of tumor cell-derived genes by microarray analysis. Results: As microdissection yielded low tissue and RNA quantities, extra rounds of mRNA amplification were necessary to obtain sufficient RNA for microarray experiments. These second rounds of amplification influenced the gene expression profiles. Moreover, the presence of stroma cells in macrodissected samples had a minor contribution to the tumor cell gene expression profiles, which can be explained by the observation that more RNA is extracted from tumor epithelial cells than from stroma. Conclusion: These data demonstrate that the more convenient procedure of macrodissection can be adequately used and yields reliable data regarding the identification of tumor cell-specific gene expression profiles. Keywords: macrodissection, microdissection, RNA amplification, stroma, rectal carcinoma
Project description:Ductal carcinoma in situ (DCIS) is a precursor lesion that can give rise to invasive breast cancer (IBC). It has been proposed that both the nature of the lesion and the tumor microenvironment play key roles in progression to IBC. Here, laser capture microdissected tissue samples from epithelium and stroma in normal breast, pure DCIS, and pure IBC were employed to define key gene expression profiles associated with disease progression. Tumor and matching stroma were profiled for 9 DCIS patients, 10 IBC patients, and 3 normal breast. Differential gene expression was evaluated for paired normal stroma versus normal epitelium samples, paired DCIS stroma versus DCIS epitelium samples, paired IBC stroma versus IBC epitelium, IBC stroma versus DCIS stroma, and IBC epithelium versus DCIS epithelium.
Project description:Tumor stroma strongly influences behaviour of cancer cells. Here, we study influence of the tumor stroma on transcription activity of head and neck squamous cell carcinoma cells. In particular, we compare transcription activity of the cancer cells in relation to expression of a putative prognostic marker tenascin in the tumor stroma.
Project description:The aim of this work is to compare the expression profiles of the microenvironment of various morphological structures of luminal breast cancer obtained by laser microdissection. For this, sections of primary breast carcinoma were stained according to the RNA-preserving protocol, fragments of the stroma around alveolar, trabecular, solid structures and single tumor cells were isolated using a laser capture microdissection, and then RNA-sequencing was performed using Illumina NextSeq500. Our study presents the first analysis of DEGs and activated signaling pathways of the microenvironment of various morphological structures of breast cancer.
Project description:Tumor stroma strongly influences behaviour of cancer cells. Here, we study influence of the tumor stroma on transcription activity of head and neck squamous cell carcinoma cells. In particular, we compare transcription activity of the cancer cells in relation to expression of a putative prognostic marker tenascin in the surrogate of the tumor stroma, margin of surgical resecate.
Project description:We employed laser microdissection to selectively harvest tumor cells and stroma from the microenvironment of formalin-fixed, paraffin-embedded head and neck squamous cell carcinoma (HNSCC) tissues. The captured HNSCC tissue fractions were analyzed by quantitative mass spectrometry-based proteomics using a data independent analysis approach. In paired samples, we achieved excellent proteome coverage having quantified 6,668 proteins with a median quantitative coefficient of variation under 10%. We observed significant differences in relevant functional pathways between the spatially resolved tumor and stroma regions. Our results identified extracellular matrix (ECM) as a major component enriched in the stroma, including many cancer associated fibroblast signature proteins in this compartment. We demonstrate the potential for comparative deep proteome analysis from very low starting input in a scalable format that is useful to decipher the alterations in tumor and the stromal microenvironment. Correlating such results with clinical features or disease progression will likely enable identification of novel targets for disease classification and interventions.
