Project description:An experiment was performed to investigate the perservation of gene expression upon metastasis of primary head and neck squamous cell carcinomas to the cervical lymph node.
Project description:A classifier was build on 82 training samples to differentiate between lymph node negative (N0) and lymph node metastasis (N+) head and neck squamous-cell carcinomas (HNSCC). The 102 predictor genes that resulted from this classifier where then validated against a independent validation set.
Project description:We performed oligonucleotide microarray analysis to assess the genetic expression alteration wich affected on lateral neck node metastasis of thyroid papillary microcarcinoma(PTMC). We performed microarray analysis in three PTMCs without cervical lymph-node metastases (N0), and five PTMCs with lateral neck-node metastasis (N1b) at initial diagnosis, using an Illumina HumanHT-12 v4.0 Expression BeadChip.
Project description:Background. The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histological subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1,103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient’s samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina. Results. The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies. Conclusions. On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers’ tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.
Project description:To identify the lymph node (LN) metastasis-associated genes in primary ESCC tumors, gene expression profiling assay (GEP) was performed to identify the differences in gene expression profiles between primary ESCC tumors that were with LN metastases (N+) and those without LN metastases (N-).
Project description:We performed a quantitative proteome comparison on formalin-fixed paraffin embedded (FFPE) tissue of metastasized and non-metastasized primary prostate cancer (PCa) and on recurrent lymph node metastases. Comparing these three sample groups, we aimed to identify proteins, that might potentially promote/supress tumor progression or metastasis formation. Proteins were quantified label-free. Proteins with interesting biological functions were followed-up by immunohistochemistry.
Project description:Samples were taken from colorectal cancers in surgically resected specimens in 89 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133 Plus 2.0 arrays. Comparison between the sample groups allow to identify a set of discriminating genes that can be used for molecular markers for predicting lymph node metastases. Keywords: disease state analysis
Project description:Expression data from 4T1 subclones derived from mammary fat pad tumors (MFP), axillary lymph node tumors (AxLN), and axillary lymph node-derived lung metastases (AxLN-LuM). In parallel, expression data, in the same subclones, of tail vein-derived (TV) lung metastases. The mechanism of how lymph node metastases seed distant metastases is unknown. We used the 4T1 breast cancer cell line, which is an immune competent model of triple negative breast cancer and spontaneously metastasizes in balb/c mice. 4T1-GFP/fLuc cells were injected into MFP to form tumors and 4T1-mCherry/rLuc cells were injected into axillary lymph nodes to form tumors and then allowed to metastasize to lung. TV cells were allowed to metastasize in the lung. Cells were harvested at different time intervals after the injection. Tumors were extracted, dissociated, and then expanded in vitro to obtain MFP, AxLN, AxLN-LuM and TV-LuM subclones isolated after different time lags with respect to the injection.