Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay.
Berggrund Malin,Enroth Stefan,Lundberg Martin,Assarsson Erika,Stålberg Karin,Lindquist David,Hallmans Göran,Grankvist Kjell,Olovsson Matts,Gyllensten Ulf
Molecular & cellular proteomics : MCP
Human papillomavirus (HPV) is recommended as the primary test in cervical cancer screening, with co-testing by cytology for HPV-positive women to identify cervical lesions. Cytology has low sensitivity and there is a need to identify biomarkers that could identify dysplasia that are likely to progress to cancer. We searched for plasma proteins that could identify women with cervical cancer using the multiplex proximity extension assay (PEA). The abundance of 100 proteins were measured in plasma collected at the time of diagnosis of patients with invasive cervical cancer and in population controls using the Olink Multiplex panels CVD II, INF I, and ONC II. Eighty proteins showed increased levels in cases compared with controls. We identified a signature of 11 proteins (PTX3, ITGB1BP2, AXIN1, STAMPB, SRC, SIRT2, 4E-BP1, PAPPA, HB-EGF, NEMO and IL27) that distinguished cases and controls with a sensitivity of 0.96 at a specificity of 1.0. This signature was evaluated in a prospective replication cohort with samples collected before, at or after diagnosis and achieved a sensitivity of 0.78 and a specificity 0.56 separating samples collected at the time of diagnosis of invasive cancer from samples collected prior to diagnosis. No difference in abundance was seen between samples collected prior to diagnosis or after treatment as compared with population controls, indicating that this protein signature is mainly informative close to time of diagnosis. Further studies are needed to determine the optimal window in time prior to diagnosis for these biomarker candidates.
Identification of miRNA-mRNA Regulatory Network and Construction of Prognostic Signature in Cervical Cancer.
Mei Yong,Jiang Pinping,Shen Ningmei,Fu Shilong,Zhang Jinsong
DNA and cell biology
Cervical cancer (CC) remains a most prevalent female cancer worldwide, but there are few biomarkers used in diagnosis and prognosis of CC. The aim of this study is to find reliable and effective biomarkers regarding CC development. Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to search potential miRNA-mRNA in CC. The gene ontology term enrichment and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were conducted to reveal the underlying functions and pathways of differently expressed genes (DEGs). Univariate Cox, multivariate Cox, and risk scoring methods were performed to identify a prognostic model. A total of 209 DEGs of CC were identified. In the protein-protein interaction network, hub module, and hub genes were recognized. Based on DEGs, three small molecules (thioguanosine, apigenin, and trichostatin A) were screened out as potential drugs. Two miRNAs (hsa-mir-101-3p and hsa-mir-6507-5p) and some transcription factors were found to be associated with prognosis of CC. A five-candidate gene signature (, , , , and ) was constructed to stratify risk subgroups for patients with CC. The risk score of the prognostic model was also found to be associated with immune cells infiltration, including mast cell activation, natural killer cells resting, dendritic cells resting, T cells regulatory (Tregs), and T cells follicular helper. The miRNA-mRNA regulatory network and the prognostic model are of great clinical significance in promoting prognosis prediction and treatment of CC.
Systematic profiling of alternative splicing signature reveals prognostic predictor for cervical cancer.
Hu Yue-Xin,Zheng Ming-Jun,Zhang Wen-Chao,Li Xiao,Gou Rui,Nie Xin,Liu Qing,Hao Ying-Ying,Liu Juan-Juan,Lin Bei
Journal of translational medicine
AIM:Cervical cancer is a common malignant carcinoma of the gynecological tract with high morbidity and mortality. Therefore, it is crucial to elucidate the pathogenesis, prevention, diagnosis and prognosis of cervical cancer by searching for the involved key genes. METHOD:In this study, the alternative splicing (AS) events of 253 patients with cervical cancer were analyzed, and 41,766 AS events were detected in 9961 genes. Univariate analysis was performed to screen prognostic AS events. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to identify the pathways in which these AS events were involved. RESULTS:We found that exon skip (ES) is the main AS event in patients with cervical cancer. There was pronounced consistency between the genes involved in overall survival and those involved in recurrence. At the same time, we found that a gene may exhibit several different types of AS events, and these different AS events may be related to prognosis. Four characteristic genes, HSPA14, SDHAF2, CAMKK2 and TM9SF1, that can be used as prognostic markers for cervical cancer were selected. CONCLUSION:The importance of AS events in the development of cervical cancer and prediction of prognosis was revealed by a large amount of data at the whole genome level, which may provide a potential target for cervical cancer treatment. We also provide a new method for exploring the pathogenesis of cervical cancer to determine clinical treatment and prognosis more accurately.