PMC:4979055 / 19945-22496 JSONTXT

{"project":"2_test","denotations":[{"id":"27600345-18586686-69480504","span":{"begin":2544,"end":2546},"obj":"18586686"},{"id":"27600345-10753637-69480505","span":{"begin":2547,"end":2549},"obj":"10753637"}],"text":"3.2.4. Pathways that Are Differentially Expressed between Adenocarcinoma and Squamous Cell Carcinoma\nFrom the previous analysis it is apparent that there is considerable overlap in the pathways that are differentially expressed in adenocarcinoma and squamous cell carcinoma. There are three datasets that allow direct comparison between the transcriptomes of the two NSCLC sub-types, E-GEOD-6044, E-GEOD-40275 and E-GEOD-50081 (this dataset was specifically created to compare gene expression between cancer sub-types). Table 2 shows that there are only a small number of differentially expressed genes between the two NSCLC sub-types except in the E-GEOD-50081 dataset. It is therefore slightly surprising that after pathway analysis this large number of genes reduces to 13 pathways: unwinding DNA; type I hemidesmosome assembly; telomere maintenance; SIRTS1 negatively regulates rRNA expression; packaging of telomere ends; nucleosome assembly; metabolism of porphyrins; heme degradation; glucuronidation; DNA strand elongation; Deposition of new CENPA-containing nucleosomes at the centromere; condensation of prophase chromosomes and chromosome maintenance.\nThe E-GEOD-6044 dataset has many fewer differentially expressed genes (although more than are differentially expressed between normal-adenocarcinoma and normal-squamous cell carcinoma). This produces a much more extensive list of pathways, with novel pathways involved in extra-cellular processes, such as extracellular matrix organization, cell-cell communication, cell-cell junction organization and immune system. The data however is very noisy and there is poor overlap between the results from pathway analysis after the three different normalization methods and so these results should be considered with some caution.\nFinally the E-GEOD-40275 also shows a small number of differentially expressed pathways. These agree with the extra-cellular pathways found in the E-GEOD-6044 results lending support to those findings, and also include new pathways involved in fatty acid triacylglycerol, and ketone body metabolism, as well as the metabolism of lipids and lipoproteins. There are also two pathways highlighted that are involved in the regulation of the peroxisome proliferator-activated receptor alpha (PPARA). There is some evidence that PPARA is associated with breast cancer but this is the first time it has been identified as involved in lung cancer although the gamma receptor has previously been identified and playing a role in inhibiting lung cancer cell growth [47,48]."}