Materials and Methods
In recent years, the rapid development of 4D-label free quantitative proteomics technology has brought a new breakthrough for the study of biopharmaceutical mass spectrometry. The technique quantifies protein expression levels by analyzing ionized peptides or protein fragments in a protein sample. It is based on mass spectrometry and allows for highly sensitive Quantitative analysis, which uses high-resolution mass spectrometry instruments and advanced data processing algorithms to detect and quantify trace amounts of proteins in samples, providing more accurate and reliable quantitative results. 4D-label free technology combines efficient sample preparation method with automated mass spectrometry platform, which can analyze a large number of samples quickly and improve the analysis efficiency and sample processing ability.

The specimens were collected from five pairs of cervical squamous cell carcinoma and corresponding paracervical normal tissues from Renmin Hospital of Wuhan University. All samples were stored at −80 °C and a preliminary histopathological diagnosis was made. Cancerous tissues and normal cervical tissues were used for proteomic analysis. This study was approved by the Ethics Committee of Wuhan University Renmin Hospital (WDRY2022-K173). We have obtained written informed consent from study participants.

An appropriate amount of SDT lysate was added into the tissue or microbial body precipitation, which was then transferred to Lysing Matrix A tube and homogenized by MP homogenizer (24 × 2, 6.0 M/S, 30 s, twice). After ultrasound, it was placed in a boiling water bath for 10 min. A total of 14,000 g was placed in a centrifuge for 15 min, and the supernatant was filtered with a 0.22 μm centrifuge tube to collect filtrate. The protein was quantified by the BCA method. Samples were stored at −80 °C.

A total of 20 μg protein from each sample was added to 6X loading buffer, placed in a boiling water bath for 5 min, 12% SDS-PAGE electrophoresis (constant pressure 250 V, 40 min), and Coomasil bright blue staining.

A total of 100 ug protein solution was taken for each sample, and DTT was added to the final concentration of 100 mM, boil water for 5 min, and cool to room temperature. A total of 200 μL UA buffer was added and mixed well, then transfered to a 30 kD ultrafiltration centrifuge tube to be centrifuged 12,500 g for 15 min, then the filtrate was discarded (this step was repeated once). Then, a total of 100 μL IAA buffer (100 mm IAA in UA) was added and shaken at 600 rpm for 1 min, react at room temperature without light for 30 min, centrifuge 12,500 g for 15 min. A total of 100 μL UA buffer should be added and 12,500 g should be centrifuged for 15 min. This step was repeated twice. A total of 100 μL 50 mM NH4HCO3 solution was added 12,500 g was centrifuged for 15 min, and this step was repeated twice. The collection tube was replaced, 40 μL Trypsin buffer (4 μg Trypsin in 40 μL 50 mM NH4HCO3 solution) was added, and oscillated at 600 rpm for 1 min, and placed at 37 °C for 16–18 h. A total of 12,500 g was centrifuged for 15 min; then, 40 μL 50 mM NH4HCO3 solution was added, 12,500 g from the center for 15 min, and the filtrate was collected. The peptide was desorted using C18 Cartridge, lyophilized, redissolved in 40 μL 0.1% formic acid solution, and quantified (OD280).

Each sample was separated using the nanoliter flow rate Easy nLC system. Buffer solution A is 0.1% formic acid aqueous solution, and solution B is 0.1% formic acid acetonitrile aqueous solution (80% acetonitrile). The chromatographic column was balanced with 100% liquid A, and the samples were separated by automatic injector into analytical column (Acclaim PepMap RSLC 50 um × 15 cm, nano viper, P/N164943; Thermo Fisher Scientiific, Waltham, MA, USA). The flow rate was 300 nL/min.

The samples were separated by chromatography and analyzed by Orbitrap Exploris 480 mass spectrometer. The analysis time was 90 min (according to the specific experimental method), the detection method is positive ion, the scanning range of parent ion is 350–1,200 m/z, the primary mass spectrometry resolution is 120,000, the AGC target is 300%, and the primary Maximum IT is 50 ms. The mass charge ratio of peptides and peptide fragments was collected according to the following methods: Data Dependent Mode was set to Cycle Time, Cycle Time was set to 1.5 s, MS2 Activation Type was set to HCD. The Isolation window is 1.6 m/z, the AGC target is 75%, the secondary mass spectrometry resolution is 15,000, the Microscans are 1, the secondary Maximum IT is 35 ms, and the ion dynamic exclusion time is 30 s. Normalized Collision Energy is 33%.

Maxquant is a leading qualitative and quantitative algorithm for proteomics and has gradually become one of the standard solutions in the field of proteomics in recent years. In proteomics research, high-resolution mass spectrometers can acquire raw data in two ways: data-dependent acquisition (DDA) and data-independent acquisition (DIA). The protein quantitative analysis based on label-free technology generally adopts the DDA method to collect the original data, which is the shotgun method in a common sense. In the DDA mode acquisition mode, the mass spectrometer first collects MS1 data, and then collects several MS2 data. In this experiment, the non-label quantitative method based on MS1 data integration is adopted. Since MS1 has a very high data density, the peptide feature of the original data needs to be intelligently identified before the data integration is calculated. The working process of Maxquant software is to identify the peptide feature first, and then calculate the strength value by graphically integrating.

Maxquant has undergone several upgrades and is now highly integrated and intelligent. In the data analysis stage of label-free experiment, the intelligent one-click operation is fully realized. After the mass spectrometry of the original document collection, only need to set the grouping, database and post-translation modification type, you can directly operate. Maxquant not only provides non-label quantitative strength data, but also automatically performs database matching to obtain qualitative results for proteins. In Maxquant’s qualitative matching, the algorithm uses FDR principle to filter the data and obtain highly reliable qualitative results. In addition, qualitative sequence information and quantitative information can be automatically correlated in the software to form a unified tabular file, which is convenient for subsequent analysis. Protein abundance was calculated based on normalized spectral protein intensity (LFQ intensity).

Gene ontology (GO) function annotation analysis was performed on all identified proteins, and the GO function of cell components, biological processes, and molecular functions corresponding to all proteins were analyzed. see http://www.geneontology.org for more information. Genomic (KEGG) pathway analysis was performed on the selected DEPs using the online analysis software Omicsbean ( http://www.omicsbean.cn/ ). The data is normalized based on Z-Score and then clustered. The cluster analysis was drawn using R script (Complex-Heatmap 2.4.3).

Gene set enrichment analysis (GSEA) was performed using GSEA v.4.2.3 (Broad Institute, Cambridge, MA, USA, https://www.gsea-msigdb.org/gsea/ ). We set parameters and run enrichment tests on a gene-set database to obtain permutation number (1,000) and permutation type (phenotype).

We analysed the protein expression of three molecules (DSP, PPP1R13L and ANXA8) by immunohistochemistry and western blotting in normal and cervical cancer tissue.

Statistical analysis was performed with Statistical Program for Social Sciences (SPSS) (SPSS, version 22.0; SPSS Inc., Armonk, NY, USA). The significant difference was analyzed with a t-test between two groups, P -value < 0.05 was considered statistically significant. Proteins with P -value < 0.05 and fold changes (FC) >1.5 were considered as differentially expressed proteins.

GEPIA is an online website for analyzing the RNA sequencing expression data of tumor and normal tissue data from the TCGA and the GTEx databases ( http://gepia.cancer-pku.cn/ ) ( Tang et al., 2017 ). We used the GEPIA database to validate the expression of DSP, PPP1R13L and ANXA8 in human cancers and normal cervix.