The expression level of the TTN gene in different types of cancers was analyzed in the Oncomine database (23) (https://www.oncomine.org/resource/login.html) and TIMER (24) (http://timer.cistrome.org/). The threshold was determined according to the following values: P-value of 0.0001, fold change of 2, gene ranking of top 10% and data type of all.

The overall survival and progress-free survival curves correlated to TTN expression in LUAD were plotted by Kaplan-Meier plotter (25, 26) (http://kmplot.com/analysis/). The correlation between TTN expression and survival in various cancer types was investigated in the PrognoScan database (27) (http://www.abren.net/PrognoScan/). The threshold was adjusted by a log-rank p-value of <0.05. Hazard ratio (HR) with 95% confidence intervals (CI) was also calculated.

Clinicopathological characteristics and the mutation information of TTN of LUAD patients were explored in the cBioPortal database (28) (https://www.cbioportal.org). CBioPortal database contains somatic mutation and copy number variation data from the cancer genome atlas (TCGA) database (29) (https://www.cancer.gov/aboutnci/organization/ccg/research/structuralgenomics/tcga). The data of alteration frequency (mutation, fusion, amplification, deep deletion) of TTN was also visualized and downloaded from the official website. Besides, we excluded samples that are not profiled for all queried genes in all queried profiles.

TTN mRNA expression and other related cell type markers in each cell type cluster of lung tissue were visualized by Uniform Manifold Approximation and Projection (UMAP) in the Human protein atlas (30, 31) (HPA; www.proteinatlas.org). Specificity and distribution classification were performed to determine the number of genes elevated in different cell types. The genes expressed in each of the cell types were explored in interactive UMAP plots and bar charts. Color-coding is based on groups of cells, and each cell type has common functional features. The functional state of TTN in various cancer types was analyzed by CancerSEA (32) (http://biocc.hrbmu.edu.cn/CancerSEA/). Correlations between the gene of interest and functional state in different single-cell datasets were filtered by correlation strength > 0.3 and P-value < 0.05.

The relevance of TTN expression to tumor immune infiltration was analyzed via TIMER (http://timer.cistrome.org/). The gene expression level was displayed with log2 RSEM. The significantly correlated genes in TIMER were validated in GEPIA (33) (http://gepia.cancer-pku.cn/index.html). The Spearman method was used to analyze the correlation coefficient. TTN was used for the x-axis, and other genes of interest are represented on the y-axis. The tumor and normal tissue datasets were used for analysis.

One independent cohort (GSE116959) was downloaded from the GEO database. GSE116959 contains transcriptome profiling information of 57 LUAD samples and 11 peritumoral normal lung tissues, with gene expression measured by Agilent-039494 SurePrint G3 Human GE v2 8x60K Microarray 039381 in GPL17077. The TTN expression of each sample was analyzed using an unpaired t-test.

Two tumor tissue samples and paired tumor-adjacent tissues, five human lung tumor cell lines and one human pulmonary alveolar epithelial cell line (HPAEpiC) were used to detect transcriptional expression of TTN. A549, HCC827, H3255 and H1975 cell samples belong to lung adenocarcinoma cell lines, H1703 belongs to lung squamous cell line and HPAEpiC belongs to human pulmonary alveolar epithelial cell line. The mRNA expression of TTN was detected by real-time PCR, and GAPDH was the internal control gene. Real‐time PCR was performed with TB Green qPCR Master Mix (RR920A, Takara, Beijing, China) using the QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA). The expression values were analyzed by using 2−ΔΔCt relative quantitative methods. Primer sequences for the real-time PCR were listed as follows:

TTN forward: 5′- ACCCTTCTTTGACATCCGT -3′, reverse: 5′- TACTTTCCGCCACTTCGT -3′;

GAPDH forward: 5′- ACAACTTTGGTATCGTGGAAGG -3′, reverse: 5′- GCCATCACGCCACAGTTTC -3′.

Clinical samples were obtained from 1 patient with LUAD who was surgically treated at shanghai pulmonary hospital. The LUAD tissue and the paired adjacent tissues were prepared into 5 μm paraffin sections and incubated with mouse polyclonal antibodies of titin (1:150, Sigma, USA) at 4° overnight in a refrigerator. The sections were coupled with the secondary antibody labeled with horseradish peroxidase (1:400, Abcam, USA) at room temperature for 1.5 h, then each section was stained with DAB reagent, and counterstained with hematoxylin. IHC sections were independently reviewed by two pathologists (JC, HS).

Protein from five lung cancer cell samples and one normal epithelial cell sample were extracted for used in the following western blotting (WB) experiments. WB experiments were performed according to the detailed protocol previously reported (34), with antibody against titin N-terminal (mouse;1:1000; Sigma SAB1400284).

Survival curves were generated by the PrognoScan and Kaplan Meier plots. The results generated in PrognoScan were performed with the hazard ratio (HR), 95% confidence interval (CI), and Cox P-values. The results generated in Oncomine are displayed with P-values, fold changes, and ranks. The results of Kaplan Meier plots and GEPIA are displayed with HR and P or Cox P-values from a log-rank test. The correlation of gene expression was evaluated by Spearman’s correlation and statistical significance, and the strength of the correlation was determined using the following criteria: 0.00–0.19 “very weak,” 0.20–0.39 “weak,” 0.40–0.59 “moderate,” 0.60–0.79 “strong,” 0.80–1.0 “very strong.” P -value<0.05 was considered statistically significant.

Oncomine database was used to determine the expression of TTN in various types of cancer and normal tissues. mRNA expression of TTN was significantly lower in lung cancer (Figure 1A). The panel shows the numbers of datasets with statistically significant mRNA upregulated expression (red) or downregulated expression (blue) of TTN. The threshold was designed with the following parameters: fold change of 1.5 and P-value of 0.05.

Furthermore, we evaluated the expression of TTN in different types of cancer using the RNA-seq data of multiple malignancies in TCGA. The results manifested that tumor tissues had a significantly decreased TTN expression compared with that in normal tissues in LUAD (Figure 1B). In addition, it revealed the same tendency both in the microarray and RNA-seq data.

Since TTN expression was significantly changed in various tumor tissues, especially in LUAD, we investigated the Prognostic value of TTN expression in LUAD patients (Figure 2). Kaplan-Meier analysis revealed that higher expression of TTN predicted better overall survival (OS) and progress-free survival (PFS). (OS HR= 0.7, 95% CI = 0.55 to 0.9, P=0.0044; PFS HR=0.7, 95% CI = 0.51 to 0.97, P=0.032) (OS HR= 0.46, 95% CI = 0.34 to 0.61, P = 9.1e-8; PFS HR = 0.43, 95% CI = 0.28 to 0.68, P = 0.00015) (Figures 2A–D). Therefore, lower expression level of TTN may serve as a poor prognostic factor in LUAD patients.

We investigated the relationship between TTN expression level with several clinicopathological features and prognosis in LUAD patients in the Kaplan-Meier plotter database (Table 1). Besides, the correlation between TTN expression and various characteristics in LUAD patients was visualized by the cBioPortal online tool (Figure 3). TTN mutation frequently occurs in LUAD patients with a rate of 49%. TTN missense mutation was the most common type of mutation which caused decreased mRNA expression (Figure S1). Moreover, high expression of TTN in female patients can benefit in PFS (n = 221, HR = 0.51, 95% CI = 0.32 to 0.83, P = 0.0055) and OS (n = 286, HR = 0.59, 95% CI = 0.4 to 0.89, P = 0.01) while male patients with high TTN expression level can benefit in OS (n = 328, HR = 0.62, 95% CI = 0.44 to 0.86, P = 0.0041). Thus, these results provided a theoretical basis for the poor prognosis of patients with TTN mutations.

We investigated the transcriptomic expression level in diverse cell clusters of lung tissue (Figure 4). The results showed each value in different cluster, and we found that TTN had a higher expression level in alveolar cells type 2 c-1(n=750, 228.9pTPM), c-6 (n=275, 168.4pTPM) and endothelial cells c-9 (n=182, 154.2pTPM). Consequently, TTN function in tumorigenesis was investigated in nine organs or tissues at a single-cell level, including LUAD and other tumors (Figure 5). The results showed that TTN had a negative correlation with DNA repair function, and it also significantly related to differentiation in LUAD (ρ=0.37, p<0.01).

We investigated the association between TTN expression and infiltration level of immune cells in the tumor microenvironment (Figure 6). TTN expression level was positively correlated with the infiltration of CD8+ T cells (Rho = 0.144, P = 1.32e-03), CD4+ T cells (Rho = 0.269, P = 1.31e-09), B cells (Rho = 0.191, P = 1.88e-05), neutrophils (Rho = 0.101, P = 2.54e-02), T cell regulatory (Rho = 0.016, P = 7.23e-01), macrophages (Rho = 0.046, P = 3.13e-01), monocytes (Rho = 0.173, P = 1.12e-04), myeloid dendritic cells (Rho = 0.115, P = 1.09e-02) and mast cell activated (Rho = 0.251, P = 1.54e-08). The results showed that TTN and different tumor-infiltrating immune cell subsets were weakly to moderately correlated. Biomarker sets of immune cells were significantly associated with TTN in LUAD (Table S1). Markers of monocyte and macrophage were significantly correlated with the expression level of TTN in TIMER and GEPIA databases. (Figure 7 and Table 2). Moreover, TTN had the highest correlation with T cells and its markers implicated the potential of TTN to recruit and activate T cells. Above all, these results indicated that TTN played a potentially important role in modulating the immune microenvironment of LUAD.

We investigated the Prognostic value of TTN Expression in LUAD in the PrognoScan database. The cohort (GSE31210), including 204 samples, showed that a lower TTN expression level was significantly associated with poor prognosis (Figures 8B, D–F). However, the cohort (240793_at and 1557994_at) showed no significant association between TTN expression and OS in LUAD (Figures 8A, C). In an independent (GSE116959), we found that TTN had a lower expression level, comparing to normal tissues (Figure 8G). In order to validate our findings, we also extracted RNA from 4 paired samples from 2 LUAD patients, 6 samples from five lung cancer cell lines and one normal cell line, and a similar result was also observed (Figures 8H, I). Immunohistochemical analysis confirmed that TTN expression was lower in LUAD than in normal lung tissue (Figure 8J). Western blotting analysis demonstrated that five lung cancer cell samples had significantly decreased expression of titin, compared with normal alveolar epithelial cell sample (Figure 8K).