Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA97219 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Using gene expression microarrays, we tested whether lung SCCs that have metastasised to loco-regional lymph nodes (N1/2m) are different to those that directly invade and involve local nodes (N1d). Using 22,323 element microarrays, a non-parametric test identified 126 genes/transcripts that discriminated between N0 (n=35) and N1/2m (n=16) tumours (Wilcoxon-Mann-Whitney U test, P<0.01). Hiearchical clustering of all 59 tumours (including 8 N1d tumours) demonstrated the N1d tumours clustered with the N0 tumours rather than the N1/2m tumours. Next, we built class prediction models from the 35 N0 tumours and 16 N1/2m tumours to predict the class of N1d tumours. All models consistently classified N1d tumours as similar to N0 tumours. This could explain some of the variable response of some N1 tumours to adjuvant chemotherapy, and suggest refinement of the TNM "N" stage nomenclature to adjust for this biological observation to ensure appropriate patients benefit from treatment. Keywords: non-small cell lung carcinoma, squamous cell, nodal metastasis, TNM staging, expression profiling Expression profiling using 22K element microarrays of 59 primary lung squamous cell carcinomas.
2007-05-01 | E-GEOD-5828 | biostudies-arrayexpress
Project description:Using gene expression microarrays, we tested whether lung SCCs that have metastasised to loco-regional lymph nodes (N1/2m) are different to those that directly invade and involve local nodes (N1d). Using 22,323 element microarrays, a non-parametric test identified 126 genes/transcripts that discriminated between N0 (n=35) and N1/2m (n=16) tumours (Wilcoxon-Mann-Whitney U test, P<0.01). Hiearchical clustering of all 59 tumours (including 8 N1d tumours) demonstrated the N1d tumours clustered with the N0 tumours rather than the N1/2m tumours. Next, we built class prediction models from the 35 N0 tumours and 16 N1/2m tumours to predict the class of N1d tumours. All models consistently classified N1d tumours as similar to N0 tumours. This could explain some of the variable response of some N1 tumours to adjuvant chemotherapy, and suggest refinement of the TNM "N" stage nomenclature to adjust for this biological observation to ensure appropriate patients benefit from treatment. Keywords: non-small cell lung carcinoma, squamous cell, nodal metastasis, TNM staging, expression profiling
2007-05-01 | GSE5828 | GEO
Project description:Gene expression profiling comparing biological mechanisms for lymphatic metastases in lung adenocarcinoma and squamous cell carcinoma Two-condition comparison: primary invasive tumors (TN+), without lymph node metastasis (TN-), matched tumor cells in metastatic lymph nodes (MT) in ADC and SCC separately
2011-08-30 | E-GEOD-29827 | biostudies-arrayexpress
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.
2017-03-27 | MSV000080685 | MassIVE
Project description:Cancer-associated fibroblasts (CAFs) play a pivotal role in the tumor microenvironment. We conducted an analysis using RNA sequencing to identify specific markers for CAFs compared to normal fibroblasts (NFs) in non-small cell carcinoma (NSCLC) under various condition. We analyzed 22 CAF samples and 11 NF samples. The 22 CAF samples consisted of 12 adenocarcinomas and 10 squamous cell carcinomas (SqCC), with 16 samples from the lungs and 6 samples from the lymph nodes. Notably, COL11A1, GREM1, CD36, and GAS6 showed higher expression in CAFs than in NFs, whereas TNC and CXCL2 were more highly expressed in NFs. CD36 levels were elevated in CAFs from lymph nodes (LN-CAFs) compared with those from lung specimens (Lung-CAFs) and NFs. COL11A1 levels in Lung-CAFs surpassed those in LN-CAFs and NFs. Both GREM1 and GAS6 showed strong expression in Lung-CAFs and LN-CAFs relative to NFs. CAFs exhibited features of the myofibroblast CAF subpopulation, whereas NFs displayed traits of the antigen-presenting CAF subtype. In NSCLC, GREM1 and GAS6 can be valuable diagnostic and therapeutic targets for CAFs from primary tumors and metastatic sites; they warrant further study.
2025-09-17 | GSE300983 | GEO
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.
2024-03-04 | GSE256413 | GEO
Project description:To identify gene expression biomarkers associate with asbestos-related lung squamous cell carcinoma, we analyzed gene expression profiles for a total of 56 lung squamous cell carcinomas using 44K Illumina Gene Expression microarrays. Twenty-six cases had lung asbestos body counts above levels associated with urban dwelling (ARLC-SCC: asbestos-related lung cancer-squamous cell carcinoma) and 30 cases had no lung asbestos bodies (NARLC-SCC: non-asbestos related lung cancer- squamous cell carcinoma). Genes differentially expressed between ARLC-SCC and NARLC-SCC were identified on fold change and P-value, and then prioritised using gene ontology. Total RNA was obtained from fresh frozen lung tumour tissue and stratified by asbestos phenotype. Gene expression profiling was performed to identify differences in the gene profiles of asbestos-related and non-asbestos related lung squamous cell carcinomas.
2012-01-30 | E-GEOD-23822 | biostudies-arrayexpress
Project description:We performed an expression profiling study of 168 primary breast tumors, lymph node metastases, and autopsy samples of primary breast tumours and metastases to liver, chest wall, lymph node, lung, and spleen, as well as positive and negative RNA controls, with technical replicates, to assess quality control methodology and probe-level reproducibility of the Illumina DASL microarray assay. The experiment included both Illumina DASL HumanRef-v3 and DASL HT-12; this series includes only the 120 HumanRef-v3 samples . This series includes 120 samples in total: 19 autopsy tissues of the chest wall, liver, lymph nodes, lung, spleen, liver, and breast, 5 negative controls, 6 positive controls, and 90 lymph node metastases.
2012-10-02 | E-GEOD-32489 | biostudies-arrayexpress
Project description:Protein Co-expression Network-based Profiles Revealed from Laser-microdissected Cancerous Cells of Lung Squamous-Cell Carcinomas
2021-07-19 | PXD027381 | JPOST Repository
Project description:NUT carcinoma (NC) is a highly aggressive subtype of squamous carcinoma driven by the BRD4-NUT fusion oncoprotein. Closely resembling human NC (hNC), GEMM tumors (mNC) are poorly differentiated squamous carcinomas that express high levels of MYC and metastasize to organs (liver, lung) and regional lymph nodes. Two GEMM-derived cell lines were developed whose transcriptomic and epigenetic landscapes, characterized by RNAseq and CUT&RUN, show striking overlap with those of primary GEMM tumors. As in hNC, BRD4-NUT functions to block differentiation and maintain growth of mNC, as evidenced by BRD4-NUT knockdown and treatment of mNC cell lines with BET bromodomain inhibitors (BETi). Mechanistically, GEMM primary tumor and cell lines form very large H3K27ac-enriched super-enhancers that are unique to hNC, termed megadomains, that are invariably associated with key hNC-defining transcriptional oncogenic targets, Myc and Trp63.
2023-10-04 | GSE241474 | GEO