Discovery and validation of FBLN1 and ANT3 as potential biomarkers for early detection of cervical cancer

Abstract

Background To validate markers for cervical carcinoma (CC) and precancerous lesions related with HPV infections. Methods Three different cervical cancer cell lines C-33A, SiHa and Caski were used for secretome profiling by label-free quantitative proteomics. Cervical exfoliated cells and matching serum samples were collected from 284 patients with normal control (n = 75, 26.41 %), precancerous lesions (n = 88, 30.99 %) and early stage cervical squamous carcinoma (n = 121, 42.61 %). HPV subtyping and quantification was performed by PCR and hybridization. 20 candidate proteins identified in previous screening studies (tissue, plasma, cells) were quantified by ELISA. Finally, highly quantitative parallel reaction monitoring mass spectrometry was used to assess the specificities and sensitivities of candidate serum markers. Results While CC was found to be associated with high-risk HPV subtypes, serum antibodies for high risk HPV were not significantly related to the progression of cervical cancer. Significant differences between patient groups were detected for the four proteins CLU, APOA4, APOE and MLH3, but none would allow clinical application due to insufficient sensitivity and specificity and large variability. Subsequent proteomic secretome analysis of cervical cancer cell lines identified a set of 729 common proteins. Cross referencing this dataset with ELISA measurements revealed six candidate proteins of which two, FBLN1 and ANT3, showed co-occurrence with HPV infection (75.7 % and 85 %, respectively) and had promising diagnostic ability in terms of sensitivity and specificity. After the loss of E6/E7 by using CRISPR/Cas9 gene editing, the content of ANT3 and FBLN1 in KoE6/E7 SiHa were downregulated, which indicated the expression of ANT3 and FBLN1 in cervical cancer may be affected by HPV infection. Conclusions FBLN1 and ANT3 might be potential tumor- and HPV-associated serum markers.

Single-cell RNA combined with Bulk RNA analysis to explore oxidative stress and energy metabolism factors and found a new prostatic cancer oncogene MXRA8

“…Moreover, our machine learning algorithms accurately predicted Based on bioinformatics analysis and survival data of prostate cancer patients from TCGA and GEO cohorts, a prognostic model was constructed using 9 genes (MYLK, FBLN1, PTGDS, TGFB1, MXRA8, PTN, COL1A1, THBS2, and MT1E), which was validated by clinical prognosis and correlation with tumor immunity. MYLK1 gene encodes MYLK, a Ca2+/CaM-dependent enzyme that has been identified as a promoter of prostate cancer progression [15][16][17]. FBLN family genes code for ECM proteins responsible for maintaining tissue structure as a component of the basement membrane and elastic fibers [18].…”

Prognostic signature of ovarian cancer based on 14 tumor microenvironment-related genes

“…FBLN1, located on chromosome 22 (22q13), is reported to be closely associated with the migrative, adhesive, and invasive features of tumor cells, and is adopted as a signature in multiple cancers. [ 37 ] For example, the FBLN1 in serum is considered as a noninvasive biomarker in identifying colorectal cancer. [ 38 ] FRAT2 is located on human chromosome 10q24.1 and could regulate the WNT signaling pathway.…”

“…For the remaining genes, although there are no direct researches on their association with ovarian cancer, most of them are reported to be associated with other cancers. FBLN1, located on chromosome 22 (22q13), is reported to be closely associated with the migrative, adhesive, and invasive features of tumor cells, and is adopted as a signature in multiple cancers [37] . For example, the FBLN1 in serum is considered as a noninvasive biomarker in identifying colorectal cancer [38] .…”

Molecular markers for cervical cancer screening

“…To overcome the limited depth of direct MS methods, efficient isolation, separation, and fractionation techniques are required in combination with advanced MS detection. UHPLC coupled with high-resolution qTOF and Orbitrap MS or medium-resolution triple quadrupole (QqQ) MS proved to be a powerful tool for protein and metabolite analysis in cervical cancer research [69][70][71][72]. Electrophoretic separation techniques like 2D-GE [73,74], SDS-PAGE, or IPG-IEF are rarely used as primary separation techniques, as they are laborintensive and difficult to automate.…”