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Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer
BACKGROUND: Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities. METHODS: We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4430711/ https://www.ncbi.nlm.nih.gov/pubmed/25965298 http://dx.doi.org/10.1038/bjc.2014.665 |
Sumario: | BACKGROUND: Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities. METHODS: We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We also included patient-matched non-cancerous thyroid and lymph node samples as controls to address some limits of previous studies. RESULTS: The transcriptomes of patient-matched primary tumours and metastases were more similar than those of unrelated metastases/primary pairs, as previously reported in other organ systems. This similarity partly reflected patient background. Lymphoid tissues in the metastases confounded the comparison of patient-matched primary tumours and metastases. We circumvented this with an original data adjustment, revealing a differential expression of stroma-related gene signatures also regulated in other organs. The comparison of N0 vs N+ primary tumours uncovered a signal irreproducible across independent data sets. This signal was also detectable when comparing the non-cancerous thyroid tissues adjacent to N0 and N+ tumours, suggesting a cohort-specific bias also likely present in previous similarly sized studies. Classification of N0 vs N+ yielded an accuracy of 63%, but additional statistical controls absent in previous studies revealed that this is explainable by chance alone. We used large data sets from The Cancer Genome Atlas: N0 vs N+ classification was not better than random for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers. CONCLUSIONS: The clinical potential of gene expression to predict nodal metastases seems limited for most cancers. |
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