Identification of Gene-Expression Signatures and Protein Markers for Breast Cancer Grading and Staging

Abstract

The grade of a cancer is a measure of the cancer's malignancy level, and the stage of a cancer refers to the size and the extent that the cancer has spread. Here we present a computational method for prediction of gene signatures and blood/urine protein markers for breast cancer grades and stages based on RNA-seq data, which are retrieved from the TCGA breast cancer dataset and cover 111 pairs of disease and matching adjacent noncancerous tissues with pathologists-assigned stages and grades. By applying a differential expression and an SVM-based classification approach, we found that 324 and 227 genes in cancer have their expression levels consistently up-regulated vs. their matching controls in a grade- and stage-dependent manner, respectively. By using these genes, we predicted a 9-gene panel as a gene signature for distinguishing poorly differentiated from moderately and well differentiated breast cancers, and a 19-gene panel as a gene signature for discriminating between the moderately and well differentiated breast cancers. Similarly, a 30-gene panel and a 21-gene panel are predicted as gene signatures for distinguishing advanced stage (stages III-IV) from early stage (stages I-II) cancer samples and for distinguishing stage II from stage I samples, respectively. We expect these gene panels can be used as gene-expression signatures for cancer grade and stage classification. In addition, of the 324 grade-dependent genes, 188 and 66 encode proteins that are predicted to be blood-secretory and urine-excretory, respectively; and of the 227 stage-dependent genes, 123 and 51 encode proteins predicted to be blood-secretory and urine-excretory, respectively. We anticipate that some combinations of these blood and urine proteins could serve as markers for monitoring breast cancer at specific grades and stages through blood and urine tests.

CTCs‐derived xenograft development in a triple negative breast cancer case

“…However, its role in vivo , the regulation of genes or cellular function, have still to be discerned. PCDHA8 is also involved in WNT pathway and has been suggested as a potential marker for the prediction of BC classification and staging of since it was part of a set of genes identified in a computational analysis of tissue‐based gene expression data to identify possible gene signatures and markers of blood or urine proteins . We found this gene expressed in CTCs isolated from TNBC patient's blood samples, however, little is known about its involvement in tumor development or metastasis.…”

An efficient biomarker panel for diagnosis of breast cancer using surface-enhanced laser desorption ionization time-of-flight mass spectrometry

“…Serum SELDI-TOF-MS protein profiling is a powerful method used for biomarker discovery and can be used to distinguish patients with BC from NCI with high sensitivity and specificity (18). It has previously been reported that monitoring protein-based markers in blood and urine samples may be used for cancer staging (19). In the past decade, a number of studies have utilized SELDI-TOF to identify proteomic patterns in biological fluids, including serum, urine and nipple aspirates (20)(21)(22).…”

Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI‐based approach

“…The association between the somatic mutation and the gene expression profile is directly linked with the health of the cancer patients and are highly important factors that decide their grade and overall survival. Various studies have predicted the grade and survival of the cancer patients by scrutinizing the somatic alteration and expression profiles of cancer-specific significant genes (An, Yang, Cheng, Wang, & Zhang, 2015;Mercatelli, Ray, & Giorgi, 2019;Yao, Zhang, Du, Liu, & Xu, 2015). The accurate and robust prediction of grade and survival are essential for better prognostic and selection of treatment strategies especially for the cancer with high incidence and low survival rate, such as gliomas.…”