Identification of Prognostic Dosage-Sensitive Genes in Colorectal Cancer Based on Multi-Omics

Abstract

Several studies have already identified the prognostic markers in colorectal cancer (CRC) based on somatic copy number alteration (SCNA). However, very little information is available regarding their value as a prognostic marker. Gene dosage effect is one important mechanism of copy number and dosage-sensitive genes are more likely to behave like driver genes. In this work, we propose a new pipeline to identify the dosagesensitive prognostic genes in CRC. The RNAseq data, the somatic copy number of CRC from TCGA were assayed to screen out the SCNAs. Wilcoxon rank-sum test was used to identify the differentially expressed genes in alteration samples with |SCNA| > 0.3. Coxregression was used to find the candidate prognostic genes. An iterative algorithm was built to identify the stable prognostic genes. Finally, the Pearson correlation coefficient was calculated between gene expression and SCNA as the dosage effect score. The cell line data from CCLE was used to test the consistency of the dosage effect. The differential coexpression network was built to discover their function in CRC. A total of six amplified genes (NDUFB4, WDR5B, IQCB1, KPNA1, GTF2E1, and SEC22A) were found to be associated with poor prognosis. They demonstrate a stable prognostic classification in more than 50% threshold of SCNA. The average dosage effect score was 0.5918 ± 0.066, 0.5978 ± 0.082 in TCGA and CCLE, respectively. They also show great stability in different data sets. In the differential co-expression network, these six genes have the top degree and are connected to the driver and tumor suppressor genes. Function enrichment analysis revealed that gene NDUFB4 and GTF2E1 affect cancer-related functions such as transmembrane transport and transformation factors. In conclusion, the pipeline for identifying the prognostic dosagesensitive genes in CRC was proved to be stable and reliable.

Study on the regulatory mechanism of EAF2 in the microenvironment of cervical cancer

“…Among the positively correlated genes analyzed in the LinkedOmics database, IQCB1 expression was most highly co-altered along with EAF2 expression, followed by ILDR1 and ASTE1, respectively. IQCB1 was found to be associated with poor prognosis in colorectal cancer [24]. Overlapping ASTE1 and ATP2C1 genes in human genome implicate for SPCA1, for affecting cytosolic Ca 2+ -signaling, and in turn perturbing cell division, leading to cell death or to neoplastic transformation [25].…”

Multi-Omics Analysis to Identify Driving Factors in Colorectal Cancer

“…Recent studies have revealed that multi-omics analysis, which focuses on biological changes at the genomic, epigenomic and transcriptomic levels, can provide insights for tumorigenesis [36]. For example, Chang et al [37] integrated and analyzed RNA sequence and somatic CNV data to demonstrate dosage-sensitive genes in CRC, which provided a new reference for cancer therapy. In this study, we investigated genes associated with CRC incidence and prognosis.…”

Therapeutic targeting of nuclear export and import receptors in cancer and their potential in combination chemotherapy

“…Many of the karyopherin family members are dysregulated in cancer, most frequently in the form of elevated expression evident from studies comparing tumour samples to normal adjacent tissues 4,24–28 . Upregulation of karyopherin proteins has been associated with enhanced transport efficiency, which is thought to benefit tumour cells via promoting oncogenic signalling and sustaining the high metabolic and proliferative demands of the cancer phenotype 29 .…”