Computational insights into CRISP3 downregulation in cervical cancer and its cervical lineages pattern

Abstract

Background: Cysteine-rich secretory protein 3 (CRISP3) emerges as a potential biomarker in the study of many cancers, including cervical cancer (CC). This study aimed to analyze the expression pattern of CRISP3 in CC patients and CC cell lineages, following treatment with the epigenetic drugs: trichostatin A (TSA) and 5-aza-2'-deoxycytidine (5-aza).

Methods: The differentially expressed genes identified in GSE63514 were used to construct a protein-protein interaction network. CRISP3 was selected for subsequent analyses. We utilized data from the TCGA and GENT2 projects to evaluate the expression profile and clinical behavior of CRISP3. Additionally, we conducted cell culture experiments to analyze the expression profile of CRISP3 in cells.

Results: Low levels of CRISP3 were observed in squamous cell carcinoma (SCC) and human papillomavirus (HPV)16+, along with being associated with worse overall survival (OS). MIR-1229-3p was analyzed, and its high expression was associated with worse prognostic outcomes. In CC-derived cell lines, we observed low levels of CRISP3 in SiHa, followed by SW756, C33A, HeLa, and higher levels in CaSki. All cells were treated with TSA, 5-aza, or both. In all cell lines, treatment with TSA resulted in increased transcription of CRISP3.

Conclusion: We identified a significant downregulation of CRISP3 in CC, particularly in cases with HPV16 infection and SCC, which was associated with poorer OS. Preliminary findings suggest that epigenetic treatments with TSA and 5-aza may modulate CRISP3 expression, warranting further research to elucidate its regulatory mechanisms and potential as a prognostic biomarker.

Keywords: CRISP3; biomarkers in cancer; cervical cancer; prognosis; uterine cervical carcinoma.

Graphical Abstract

Figure 1.

CRISP3 identification and expression profile. (A) Volcano plot containing the 54 675 probes analyzed in GSE63514 from the identification group. Blue corresponds to probes with fold-change value < 0 and p.adj value < 0.05 in tumor tissue. Red corresponds to probes with fold-change value > 0 and p.adj value < 0.05 in tumor tissue. The region with the highest number of overlapping points, in black, corresponds to probes with a P-value without statistical significance. The black arrow indicates the CRISP3 probe. (B) CRISP3 expression profile in normal tissue and tumor tissue samples from the identification group. (C) CRISP3 expression profile in normal tissue, grade 1, 2 and 3 of cervical intraepithelial neoplasia (CIN), and tumor tissue. The data were tested for normality and subjected to the Mann–Whitney and Kruskal–Wallis U Test with Dunn's multiple comparison test.

Figure 2.

PPI network and pathway enrichment analysis. (A) The PPI network was constructed using the STRING database, employing the top 100 deregulated genes identified in the GSE63514 dataset. (B) A cropped and enlarged version of (A), focusing on genes closely associated with CRISP3. (C) The enrichment analysis prominently highlights the main altered pathways, providing an in-depth insight into the functional implications arising from protein interactions.

Figure 3.

CRISP3 RNA levels in CC by (A) histological subtype categorized in SCC, Adeno, and other subtypes; (B) HPV type. Kruskal–Wallis test was applied with Dunn's multiple comparison test; and (C) age. Mann–Whitney test was applied. (D) Correlation between CRISP3 RNA levels and methylation was accessed using the Spearman test. The analyses are based on TCGA Firehose Legacy CC patients. SCC: squamous cervical carcinomas. Adeno: adenocarcinomas.

Figure 4.

OS of patients with uterine CC with CRISP3 expression (A) regardless of histological subtype and (B) SCCs of the uterine cervix subtype. RFS of patients with uterine CC with CRISP3 expression (C) regardless of histological subtype and (D) only SCCs of the uterine cervix. Patients were categorized according to the best cutoff of CRISP3 mRNA expression. Data from the TCGA Firehose study.

Figure 5.

Survival analysis of patients with SCCs of the uterine cervix stratified by has-miR-1229–3p expression. (A) OS and (B) RFS. Patients were categorized according to the best cutoff of miRNA expression. Data from the TCGA Firehose study.

Figure 6.

(A) CRISP3 expression in CC cell lineages. CRISP3 expression under TSA or 5-AZA treatment in: (B) SiHa, (C) SW756, (D) C33A, (E) HeLa, and (F) CaSki. All RT-PCR experiments were conducted in triplicate.