RNA-sequence data of 407 patients (32 non-malignant and 375 tumor) were abstracted from the TCGA-STAD data resource. TCGA constitutes a publicly funded project whose purpose includes cataloging and discovering major cancer-pathogenesis genome changes in large data sets of over 30 human cancer types via large-scale genome sequencing along with integrated multidimensional analyses. Herein, the matching TCGA clinical data were abstracted from the cBioPortal (http://www.cbioportal.org/) (10). The matching ferroptosis-related lncRNAs were abstracted from FerrDb (11), an online consortium providing a comprehensive, as well as up-to-date data resource for ferroptosis biomarkers, their modulatory molecules along with the linked diseases.
Profiling differentially expressed ferroptosis-related lncRNAs (DEFRLs)
To determine ferroptosis-related lncRNAs, we employed to limma R tool to conduct differential analyses for the STAD samples from TCGA. The remarkable differences in expressions were determined using the FDR < 0.05 and |log2FC|≥1 threshold. Pearson correlation was adopted to determine the relationship of the lncRNAs with ferroptosis markers. A correlation coefficient of |R2|>0.45 at P < 0.05 signified remarkable relationship.
Functional enrichment analysis of DEFRLs
The clusterprofle R tool was employed to perform Gene Ontology (GO) coupled with Kyoto Encyclopedia of Genes and Genomes (KEGG) to elucidate the role of unrecovered DEFRLs (12). An adjusted P < 0.05 denoted statistical significance.
Development of the ferroptosis-related lncRNA prognostic signatures
We analyzed OS along with PFS to gain insights into the prognostic significance of DEFRLs in individuals with STAD. We defined OS as the time beginning from the first day of diagnosis to death from any cause, whilst PFS included the time from the day of diagnosis to the time of cancer progression or death. Firstly, a univariate Cox analysis was adopted to explore OS- along with PFS-related DEFRLs. Secondly, multivariate Cox regression was employed to determine the potential OS- along with PFS-related DEFRLs to create two predictive signatures, referred to as the OS signature and the PFS signature, respectively. The DEFRLs’ coefficients in the final signatures were validated simultaneously and utilized to compute the risk scores for each STAD patient. And all subjects were stratified into either low-risk group or high-risk group, as per the median score. The risk score was calculated as follows:
\(\beta i\) is the coefficient of lncRNA \(i\) in the multivariate Cox analysis; \(Gi\) is the expression value of lncRNA \(i\); and \(n\) is the number of lncRNAs in the signature.
To explore the efficiency of the signatures, the “survival ROC” tool was employed to create ROC (receiver operating characteristic) curves at one-, three-, and five-years, and the matching time-based AUCs (area under the curves) were computed. And we generated the K-M survival plots with the log-rank test to assess the differences in OS and PFS between high- and low-risk group.
The predictive nomogram integrating DEFRL signatures and clinical variables
Clinical characteristics, including gender, age, grade and stage were abstracted from the cBioPortal data resource. Univariate Cox regression integrating the signature with the clinical information was conducted for individuals with STAD, and factors harboring P < 0.05 were subjected to multivariate regression to determine the independent predictive factors. After that, two predictive nomograms were created using the R “rms” package on the basis of the independent predictive factors for estimating OS along with PFS in individuals with STAD. We employed the concordance index (C-index) to explore the discrimination efficiency of these two nomograms.
Cells and culture conditions
The AGS and MKN7 cell lines were acquired from cell bank of the Chinese Academy of Sciences and inoculated in RPMI-1640 medium (PM 150110, Procell Life Science &Technology Co,.Ltd) enriched with 10% FBS (Gibco, NY, USA) at 37°C and 5% CO2 conditions.
Reagents and antibodies
Antibodies against β-actin (#4970, Cell Signaling Technology, USA), Anti-GPX4 (ab18196) bought from Abcam (Cambridge, United States), and secondary antibodies (abs20002) acquired from Absin (Shanghai, China) were used for western blotting experiment.
We transfected the cells with small interfering RNAs (siRNAs) against LASTR (siLASTR; LncRNA-Pharma, Shanghai, China) and a negative control (siNC) with the Lipofectamine 2000 system (Invitrogen, United States) as described by the manufacturer. Cells were propagated with LASTR siRNAs for 48 h and harvested for subsequent experiments.
RNA isolation and RT-qPCR
The TRIZOL reagent was employed to purify total RNA from cells (TaKaRa, Beijing, China). After that, cDNA was generated from the RNA via reverse transcription with the Prime Script RT Master Mix reagent (TaKaRa, China), per the instructions of the manufacturer. Afterwards, RT-qPCR was run on the ABI 7500HT Fast Real-Time PCR Platform (Applied Biosystems, CA, USA). The 2−ΔΔCt approach was adopted to determine relative lncRNA expression with GAPDH serving as the normalization control. The oligonucleotide primers for RT-qPCR included: LASTR forward, 5'- GAGAAGACAGTGGGTGAAGTCC-3' and reverse, 5'-GACTCTAGGCACCAGCTGAC-3' and GAPDH forward, 5'-GGAAGCTTGTCATCAATGGAAATC-3', and reverse, 5'-TGATG ACCCTTTTGGCTCCC-3'.
Western blotting assay
We inoculated the GC cells onto 6-cm plates for 48 hours and the harvested them via scrapping. Thereafter, lysis RIPA lysis buffer enriched with protease along with phosphatase inhibitors (Solarbio, Beijing, China was employed lyse the cells for 30 minutes. Thereafter, the cells were span at 12,000 g for 20 minutes at 4°C, and the protein quantitated with the BCA protein assay kit (Beyotime, China). Afterwards, 20µg of the proteins were fractionated on an SDS-PAGE gel and transfer-embedded onto PVDF membranes. Blocking of the membranes was done for two hours using 5% skimmed milk dispersed in TBST. Afterwards, the membranes were inoculated overnight with the indicated primary antibody (1:1000). Next, the membranes were rinsed in TBST for ten minutes, and then inoculated at room temperature with the secondary HRP-conjugated antibodies (1:8000) for two hours. Thereafter, the membranes were rinsed with TBST and the bound antibodies visualized with a chemiluminescence kit (Life Technologies, China) on a Bio-Rad gel imager infrared imaging Platform (ChemiDoc XRS+).
5-ethynyl-2’-deoxyuridine (EdU) incorporation assay
1×105 GC cells/well were planted onto 24-well plates, allowed to grow for 48 hours, and inoculated with medium enriched with 50µM EdU (Beyotime, Shanghai, China) for two hours. Thereafter, we fixed the cells (in 4% PFA; Beyotime, Shanghai, China) followed by permeabilization, and then introduced a click reaction mixture (200µL/well) for 30 minutes. Nuclei staining (in Hoechst 33342; 200µL/well) was done for 30 minutes, and a fluorescence microscope employed to visualize the cells.
Colony formation assay
We infected cells with siRNA for two days, and the inoculated 300 cells/well into 6-well dishes and allowed to grow for 10 days. Next, the cells were fixed for 30–60 minutes (in 4% PFA), followed by staining for 20 minutes (in crystal violet). After numerous washes in ddH2O, the colonies were photographed and their numbers determined.
Transwell migration assay
Cell migration was evaluated using a BD (Franklin Lakes, United States) transwell compartment without Matrigel. Following transfection, we introduced 2x105 cells in serum-free medium onto the upper compartment of the transwell, then medium enriched with 20% FBS was introduced to the lower compartment and allowed to grow for one day. Thereafter, the cells were fixed for 30 minutes with 4% PFA, followed by staining for 20 minutes (in crystal violet) and the rinsed with PBS. We counted the cells in five fields (top, bottom, center, left, and right) under a microscope.
Wound healing assay
The GC cells were planted into 6-well plates and a sterile pipette tip employed to make a scratch. Next, the cells were rinsed with PBS, and then inoculated in medium enriched with 2% FBS. We acquired images at 0 and 24 h with a phase contrast microscope. The fraction of wound healing was determined follows: [1 - (empty area 24 h/empty area 0 h)] × 100%.
All data analyzes were implemented in Bioconductor packages in R software, version 4.1.0 and GraphPad Prism 8.0 Software. Unpaired Student’s t-test, the Wilcoxon rank-sum test, ANOVA, and the Kruskal–Wallis test were adopted to compare continuous variables. Pearson analysis was implemented for the correlation analyses. P < 0.05 denoted statistical significance.