Data source

The RNA sequencing data and relevant clinical data of patients with LUSC were obtained from The Cancer Genome Atlas (TCGA) database, accessible at https://portal.gdc.cancer.gov/repository. Figure 1 shows the flowchart of the study design. Furthermore, a total of 33 pyroptosis-related genes (PRGs) were selected, including ELANE, PJVK, TNF, NLRC4, NLRP3, NLRP7, GSDMA, CASP5, NLRP6, GPX4, PLCG1, PRKACA, SCAF11, CASP3, CASP4, GSDMD, NLRP2, AIM2, GSDMC, NOD2, TIRAP, GSDMB, NOD1, CASP6, CASP9, NLRP1, PYCARD, CASP1, CASP8, GSDME, IL18, IL1B, and IL6 [14,15,16].

Fig. 1

Study Design. TCGA, The Cancer Genome Atlas; LUSC, lung squamous cell carcinoma; PRlncRNAs, pyroptosis-related long-noncoding RNAs; FDR, false discovery rate; GSEA, Gene Set Enrichment Analysis; TME, tumor microenvironment

Identification of differentially expressed PRlncRNAs

To identify lncRNAs more accurately and rigorously, PRlncRNAs were classified as lncRNAs that were co-expressed with PRGs, with a Pearson's regression coefficient |r|≥ 0.3 and a p-value < 0.001 [17]. The selection of differentially expressed long non-coding RNAs (lncRNAs) involved comparing 49 normal tissues with 502 LUSC tissues using the limma package. The selection criteria were based on previous studies [18,19,20,21,22] and included the following criteria: |log fold change|> 1 and false discovery rate (FDR) < 0.05. An average was computed based on many data points collected from a single patient. Furthermore, the chi-squared test was performed to determine if the training and test cohorts were part of the larger cohort. In the training cohort, a univariate Cox analysis was performed to identify lncRNAs that had a significant prognostic value for LUSC.

Construction of a risk model

The whole data set was randomly divided into two equal cohorts, namely the training cohort and the test cohort, using the createDataPartition function from the "caret" package https://github.com/topepo/caret/) [23]. The R "survival" package was used to perform univariate and multivariate Cox regression and survival studies. The software can be found at https://github.com/therneau/survival [24]. Only patients with overall survival > 1 month were selected for further investigations. With prognostic lncRNAs in the univariate Cox analysis, the LASSO Cox regression algorithm was applied to minimize the risk of overfitting using the “glmnet” package (https://cloud.r-project.org/package=glmnet) [25]. The risk model was developed by selecting seven lncRNAs. The following formula was employed to determine the risk score of each patient: risk score = Σi coefficient (lncRNAi) × expression (lncRNAi). The median risk score equitably divided the overall, training, and test cohorts into low- and high-risk groups. Finally, the Kaplan–Meier survival analysis was conducted, and risk curves were drawn. The "rms" program was employed to generate the nomogram.

Gene set enrichment analysis

To better understand the specific biochemical pathways in the high- and low-risk groups, Gene Set Enrichment Analysis (GSEA) was performed using the KEGG gene sets and GSEA software (version 4.2.2).

Immune landscape analysis

Six immune-related algorithms were used to describe the immune landscape in the two cohorts, including XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, and CIBERSORT-ABS [26, 27]. To have a comprehensive understanding of the relationship between the risk score and immunological status, Spearman's correlation analysis was performed to determine the correlation between the risk score and the infiltration of immune cells. Single-sample GSEA was used to examine immune cell activity, function, and pathway between the high- and low-risk groups. The immunological, stromal, and estimate scores for each patient were derived based on the composition of immune and stromal cells using the ESTIMATE algorithm. Furthermore, the Wilcoxon test was conducted to compare the levels of immune checkpoint molecules between the high- and low-risk groups.

Association of the risk score with chemotherapy and immunotherapy responses

To identify the response of patients to chemotherapy drugs, the “pRRophetic” package was used to calculate the half-maximal inhibitory concentration (IC50) [28]. Higher IC50 values indicated lower sensitivity to drugs. The Wilcoxon test was used to assess differences between groups.

The Tumor Immune Dysfunction and Exclusion (TIDE) score was used as a biomarker of the efficacy of immunotherapy. Higher TIDE scores indicated poorer immunotherapy efficacy and patient prognosis [29]. The TIDE score was calculated using the TIDE database.

RNA isolation and real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR)

Total RNA was extracted using the RNAfast200 reagent kits (Fastagen, Thermo Fisher Scientific) from the H226, SKMES1, H520 LUSC cell lines, and the Beas-2B lung epithelial cell line. The PrimeScript™ RT reagent kit (TaKaRa) was used for reverse transcription. Table 1 presents the primer sequences for the seven lncRNAs. The expression levels of the lncRNAs MIR193BHG, MIR3945HG, C10orf55, AC004069.1, LINC01956, AC008734.1, and AC090001.1 were normalized using GAPDH.

Table 1 Primer sequences of the seven lncRNAsCell culture and transfection

The human LUSC cell lines SKEMS, H226, and H520 were obtained from CoBier Bioscience Company (http://www.cobier.com). The SK-MES-1 cells were cultured in Minimum Essential Medium (MEM) containing 10% fetal bovine serum (FBS), 1% non-essential amino acids, and 1 mM sodium pyruvate. H226 and H520 cells were cultured in RPMI-1640 medium (Gibco, Thermo Fisher Scientific) and enriched with 10% FBS (Gibco, Thermo Fisher Scientific) and 1% penicillin–streptomycin antibiotic solution. The cells were incubated at 37 °C in a 5% CO2 humidified incubator.

H226 and H520 cell lines were transfected with MIR193BHG-specific and negative-control siRNA oligonucleotides, which were manufactured by Ribobio Company (www.ribobio.com), using the Lipofectamine RNAimax reagent (Invitrogen, Thermo Fisher Scientific). SiRNA oligonucleotides specific to MIR193BHG were synthesized based on the target sequence 5'-GGCTGGATCTGTAATGAAA-3'. The siRNA was used at a final concentration of 10 μM.

After transfection for 48 h, the cells were collected for further experiment. The overexpression of MIR193BHG was performed using plasmids synthesized by Shanghai GeneChem Company (www.genechem.com.cn) and the Lipofectamine 3000 Transfection Kit (Invitrogen, Thermo Fisher Scientific).

Proliferation assay

Cells were seeded at a density of 5 × 103 cells/well with five replicates per group in 96-well plates and cultured in a complete medium. For each well, 10 μL of CCK-8 solution and 100 μL of fresh culture medium were added on days 1, 2, and 3, followed by a 2 h incubation at 37 °C. Absorbance was read against 450 nm in a microplate reader (Bio-Rad).

Wound Healing, migration and invasion assay

For the wound healing assay, 2 × 105 cells/well (three replicates per group) were plated into a six-well plate and cultured to reach confluence. After confluency, the monolayer of the cells was scratched with a sterile tip and washed with RPMI-1640 to remove the detached cells. The cells were incubated in RPMI-1640 and photographed at 0 h and 18 h post-wounding. The closure area of the wound was calculated as follows: migration area (%) = (A0 – A18)/A0 × 100%. Where A0 represents the area of the initial wound area, and A18 represents the wound area at 18 h.

For the transwell migration assay, LUSC cells were resuspended in serum-free RPMI-1640 medium, and 1 × 105 cells were introduced into the upper chamber of the transwell inserts (8‑µm pore size; 6.5 mm diameter; Corning) with 100 μL RPMI-1640. Next, 600 μL RPMI-1640 containing 10% FBS was added to the lower chamber. Following a 24 h incubation, the cells in the upper chamber were fixed with pure methanol at room temperature for 30 min (min). The cells on the upper surface of the chamber were then removed by swabbing, and the migrated cells, which adhered to the lower surface of the membrane, were stained with 0.1% crystal violet (Sigma‑Aldrich) for 30 min.

The number of migrating cells was quantified using an inverted light microscope at a magnification of 100 × . The experiments were performed in triplicates. The protocol for the transwell invasion assay was similar to that of the migration assay, with the exception that the membrane was pre-coated with Matrigel (Corning) before the addition of the cell suspension.

Statistical analysis

The hazard ratio (HR) was calculated using both univariable and multivariable Cox regression analysis. The FDR was employed to assess the statistical significance of multivariate variables. Each group had three independent in vitro experiment replications. The unpaired t-test was used to compare groups in terms of in vitro experiments. All P-values are calculated using a two-tailed test. A P-value less than 0.05 and an FDR q-value less than 0.05 were considered as statistical significance. This study made use of R version 4.1.2.