Human genome u133 plus 2.0 array hg u133 plus 2

Raw microarray data of CC (GSE9750, GSE7803, GSE63514) and EC (GSE17025, GSE115810, GSE36389) were downloaded from the GEO database (Table 1). In the six datasets of our study, GSE9750, GSE7803, GSE115810, and GSE36389 were processed using the GPL96 platform (Affymetrix Human Genome U133A Array, HG-U133A, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL96, accessed on 3 July 2021), while GSE63514 and GSE17025 were based on GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array, HG-U133_Plus_2, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL570, accessed on 3 July 2021). The detailed information of datasets is as follows: GSE9750 included 33 cervical tumor and 24 normal tissue samples. GSE7803 covered 21 cervical tumor and 10 normal tissue samples. GSE63514 included data from 28 cervical tumor and 24 normal samples. GSE17025 covered 91 endometrial tumor and 12 normal tissue samples. GSE115810 comprised 24 endometrial tumor and 3 normal samples. GSE36389 consisted of 13 endometrial tumor and 7 normal samples.

The microarray gene expression dataset of GSE121248, which comprises 70 hepatocellular carcinoma samples and 37 normal liver samples, was obtained from the GEO website and exploited as discovery dataset to identify DEGs. The included dataset met the following criteria: (1) dataset included human HCC samples and normal liver samples. (2) they contained at least ten samples. (3) dataset was obtained from the Affymetrix Human Genome U133 Plus 2.0 Array [HG-U133_Plus_2] microarray platform. The raw RNA sequencing data, which comprises 374 HCC samples and 50 normal liver tissue samples, was selected from the TCGA liver hepatocellular carcinoma (TCGA-LIHC) dataset and used as a validation dataset.

The expression data and corresponding clinical characteristics for 406 patients with endometrial adenocarcinoma and 19 controls were downloaded from TCGA dataset (http://cancergenome.nih.gov/). We screened suitable clinical samples from the TCGA database with the terms “corpus uteri”, “adenocarcinoma”, and “TCGA” as the inclusion criteria; thereby 406 patients and 19 controls from studies meeting the database requirements were included in our further analysis. Controls were from tumor adjacent normal endometrium or women without endometrial cancer. The only common information for these enrolled patients were age, International Federation of Gynecology and Obstetrics (FIGO) grade, and survival information, so all patients' ages and tumor FIGO grades were sorted and listed in Table S1.
For further validation, the expression data from 64 endometrial adenocarcinoma and 33 endometrial hyperplasia tissues was downloaded from GSE 106191 of the GEO database (https://www.ncbi.nlm.nih.gov/geo/). All 33 endometrial hyperplasia tissues were adjacent to endometrial adenocarcinoma. The clinical parameters of these endometrial adenocarcinoma and hyperplasia patients have been presented previously 19 (link). Gene expression dataset was downloaded from the Affymetrix Human Genome U133 Plus 2.0 Array (HG-U133_Plus_2).

Normalized data of gene expression and related clinical data were downloaded from Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). Dataset GSE14520 was used as a training set to construct expression network and identify hub genes in this study. This dataset was based on the microarray platform of Affymetrix HT Human Genome U133A Array (HT_HG-U133A), and included 225 samples of hepatocellular carcinoma (HCC) and 220 samples of non-tumor tissues. Another independent dataset of GSE6764 was downloaded from GEO database and used as a test set to verify our results. This dataset was based on the platform of Affymetrix Human Genome U133 Plus 2.0 Array (HG-U133_Plus_2) and included 35 HCC samples covering four stepwise pathological stages of HCC progression (including very early HCC, early HCC, advanced HCC and very advanced HCC). Moreover, RNA-sequencing data of 423 HCC samples were also downloaded from The Cancer Genome Atlas (TCGA) database (https://genome-cancer.ucsc.edu/) to further verify our results. The gene expression data were based on the RNA-sequencing technology of IlluminaHiseq.