Differential expression of SASS6 between tumor and normal cases

Pan-cancer analysis demonstrated that SASS6 was overexpressed in tumor samples compared to adjacent tissues in multiple types of cancer in the TCGA database (Fig. 1A). The area under the ROC curve of bladder cancer (BLCA), cervical cancer (CESC), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal cancer (ESCA), glioblastoma (GBM), head and neck squamous cancer (HNSC), liver hepatocellular carcinoma (LIHC), lung squamous cell carcinoma (LUSC), stomach adenocarcinoma (STAD), and uterine corpus endometrial carcinoma (UCEC) were all greater than 0.8, indicating that SASS6 had good diagnostic efficacy for pan-cancer (Fig. 1B–L).

Fig. 1

Differential expression and diagnostic value of SASS6 in pan-cancer. A Analysis of SASS6 expression in pan-cancer from the TCGA dataset. B–L Diagnostic ROC curves constructed in relation to SASS6 expression in BLCA, CESC, CHOL, COAD, ESCA, GBM, HNSC, LIHC, LUSC, STAD, and UCEC

Differential analysis of SASS6 expression in LUAD

Analysis of the TCGA and GEO validation datasets demonstrated that, compared with normal lung tissue, the expression of SASS6 at the RNA expression level was up-regulated in LUAD (Fig. 2A–C). Analysis results from the UALCAN and HPA databases revealed that SASS6 was overexpressed in LUAD at the protein expression level (Fig. 2D–F). SASS6 expression tended to be higher in groups with a high clinical T stage in LUAD (Fig. 2G). SASS6 expression was upregulated in patients with an advanced pathological stage (Fig. 2H).

Fig. 2

A–C Comparison of SASS6 expression differences in TCGA, GSE27262, and GSE43458 datasets. D Comparison of protein levels of SASS6 from the UALCAN database. E–F Immunohistochemical staining of SASS6 in LUAD and lung tissue from the HPA database. G Comparison of SASS6 expression in LUAD between the different T stages. H Comparison of SASS6 expression in LUAD between the different pathological stages

Comparison of SASS6 expression in multiple cell clusters

The heat map listed the top 10 marker genes for all cell clusters (Fig. 3A). The types of cell clusters were annotated separately according to the marker genes of each cell cluster, which included ciliated cell, megakaryocyte, idiopathic pulmonary fibrosis (IPF) cell, T cell, cancer stem cell, epithelial cell, type II pneumocyte, secretory cell, and mesenchymal stromal cell (MSC) (Fig. 3B). Comparison of SASS6 expression in these cell clusters revealed that SASS6 was mainly expressed in cancer stem cells and mesenchymal stromal cells (Fig. 3C).

Fig. 3

Annotation of cell types and analysis of SASS6 expression. A Heat map of expression of marker genes in multiple cell clusters from LUAD tissue. B UMAP map of dimensionality reduction and cell clustering. C Comparison of SASS6 expression in multiple cell clusters

Diagnostic value and survival analysis of SASS6 in LUAD

The expression of SASS6 was extracted to distinguish LUAD from normal samples, and ROC curves were constructed to evaluate the efficiency of discrimination. The area under ROC curves from TCGA, GSE27262 and GSE43458 were 0.8968, 0.7856 and 0.7413, respectively (Fig. 4A–C). The above results confirmed the excellent diagnostic value of SASS6 in LUAD. Survival analyses from the TCGA, GSE30219 dataset, and GEPIA database demonstrated a worse prognosis for LUAD patients with high SASS6 expression (Fig. 4D–F).

Fig. 4

Diagnostic efficiency and prognostic value of SASS6 in LUAD. A–C Diagnostic ROC curves constructed in relation to SASS6 expression in the TCGA, GSE27262, and GSE43458 datasets. D–F KM survival curve constructed by grouping according to the median expression of SASS6 from TCGA, GSE30219 dataset and GEPIA database

Identification of DEGs related to SASS6 and functional enrichment analysis based on DEGs

Through the analysis of tumor cases with different SASS6 expression, the obtained DEGs included 804 up-regulated DEGs and 469 down-regulated DEGs (Fig. 5A). GO analysis showed that the biological processes were all related to the cell cycle, including “nuclear division”, “chromosome segregation”, and “nuclear chromosome segregation” (Fig. 5B). KEGG analysis enriched DEGs in multiple items, of which the most significant were “Neuroactive ligand − receptor interaction”, “Cell cycle”, “Oocyte meiosis”, “Salivary secretion”, “Nicotine addiction” (Fig. 5C). GSEA analysis enriched DEGs in these items, which were “GO_CARBOHYDRATE_BINDING”, “GO_CELL_CYCLE”, “GO_CELL_SURFACE”, “GO_DIGESTION”, “GO_DNA_BINDING_TRANSCRIPTION_FACTOR_ACTIVITY”, “GO_IMMUNE_EFFECTOR_PROCESS”, “GO_POSITIVE_REGULATION_OF_IMMUNE_RESPONSE”, “GO_REGULATION_OF_IMMUNE_RESPONSE”, “GO_REGULATION_OF_IMMUNE_SYSTEM_PROCESS”, and “GO_VACUOLE” (Fig. 5D).

Fig. 5

Acquisition and function annotation of DEGs. A A volcano map constructed from significant DEGs in the TCGA dataset. B A dot plot showing the GO analysis results. C A dot plot showing the KEGG analysis results. The size and color of the dots represent the degree of gene enrichment and significance, respectively. D Demonstration of results acquired from GSEA analysis

Analysis of immune cell infiltration in tumor cases with different SASS6 expression

Samples with increased or decreased arm-level of SASS6 in LUAD showed decreased infiltration of a variety of immune cells, including B cell, CD8+ T cell, CD4+ T cell, Macrophage, neutrophil (Fig. 6A). Samples with high SASS6 expression had 16 subtypes of immune cells that were low expressed (Activated B cell, Activated dendritic cell, CD56dim natural killer cell, Central memory CD4 T cell, Eosinophil, Immature B cell, Macrophage, Mast cell, MDSC, Monocyte, Natural killer cell, Neutrophil, Plasmacytoid dendritic cell, T follicular helper cell, Type 1 T helper cell, and Type 17 T helper cell) and 4 subtypes of immune cells that were high expressed (Fig. 6B). In addition, the samples with high SASS6 expression had lower ESTIMATE, Immune, and Stromal scores but higher tumor purity (Fig. 6C).

Fig. 6

Correlation analysis of immune infiltration associated with SASS6. A Analysis of immune cell infiltration levels between tumor cases with different SASS6 CNV in LUAD. CNV: copy number variation. B Differences in the expression of immune cells between two groups with different SASS6 expression. C Comparison of results obtained by ESTIMATE analysis

Differences in TMB and immune checkpoint expression between the two groups

Immune checkpoint and TMB had an impact on immunotherapy in tumor patients, and then we analyzed the relationship between SASS6 and them to explore the role of SASS6 in immunotherapy. As shown in the two waterfall maps of gene mutations from the two groups with different SASS6 expression, there were more TP53 mutation cases in high SASS6 expression group, and more than 70% of patients in the high SASS6 expression group had TP53 mutations, while TP53 mutations in low SASS6 expression group was only 25% (Fig. 7A, B). The expression of PDCD1, CD274, PDCD1LG2, LAG3 and the value of TMB were all higher in the samples with high SASS6 expression (Fig. 7C, D).

Fig. 7

Investigation of the association between SASS6 and immunotherapy. A Waterfall map of genetic mutations in samples with high SASS6 expression. B Waterfall map of genetic mutations in samples with low SASS6 expression. C Differences of TMB between the two groups with discrepant SASS6 expression. D Differential analysis of immune checkpoint expression

Analysis of the relationship between SASS6 and drug sensitivity

There was lower half-maximal inhibitory concentration (IC50) of afatinib, crizotinib, erlotinib, gefitinib, osimertinib, savolitinib, cisplatin, cyclophosphamide, docetaxel, paclitaxel, vincristine, and vinorelbine in the high SASS6 expression group, suggesting that LUAD patients with high SASS6 expression may be more sensitive to the drugs mentioned above (Fig. 8A–L).

Fig. 8

Study on drug sensitivity in LUAD. A Analysis of difference in sensitivity of afatinib between high and low SASS6 expression groups. B Analysis of difference in sensitivity of crizotinib between two groups. C Analysis of difference in sensitivity of erlotinib between two groups. D Analysis of difference in sensitivity of gefitinib between two groups. E Analysis of difference in sensitivity of osimertinib between two groups. F Analysis of difference in sensitivity of savolitinib between two groups. G Analysis of difference in sensitivity of cisplatin between two groups. H Analysis of difference in sensitivity of cyclophosphamide between two groups. I Analysis of difference in sensitivity of docetaxel between two groups. J Analysis of difference in sensitivity of paclitaxel between two groups. K Analysis of difference in sensitivity of vincristine between two groups. L Analysis of difference in sensitivity of vinorelbine between two groups

Construction of ceRNA network targeting SASS6

The predicted miRNA was hsa–let–7b–5p, which was negatively correlated with SASS6 (Fig. 9A). The lncRNAs predicted by hsa–let–7b–5p were CYP4F26P, AC087741.1, AC074117.1, and AC109460.3, which were negatively correlated with hsa–let–7b–5p (Fig. 9B–E). Through the construction of ceRNA network, the relationship between SASS6, hsa–let–7b–5p and lncRNAs (CYP4F26P, AC087741.1, AC074117.1, and AC109460.3) was shown (Fig. 9F). Compared with the normal group, hsa–let–7b–5p was highly expressed in the LUAD group (Fig. 9G), and its up-regulation suggested a better prognosis of LUAD (Fig. 9I). CYP4F26P was overexpressed in the LUAD group (Fig. 9H), and its up-regulation suggested a worse prognosis of LUAD (Fig. 9J). Both hsa–let–7b–5p and CYP4F26P were differentially expressed between LUAD and normal cases, and they contributed to the survival of tumor cases, so they were identified as core miRNA and core lncRNA, respectively.

Fig. 9

Study on upstream gene of SASS6. A Correlation analysis between SASS6 and miRNA (hsa–let–7b–5p) predicted by SASS6. B Correlation analysis between hsa–let–7b–5p and lncRNA (CYP4F26P) predicted by hsa–let–7b–5p. C Analysis of correlation between hsa–let–7b–5p and lncRNA (AC087741.1) predicted by hsa–let–7b–5p. D Analysis of correlation between hsa–let–7b–5p and lncRNA (AC074117.1) predicted by hsa–let–7b–5p. E Analysis of correlation between hsa–let–7b–5p and lncRNA (AC109460.3) predicted by hsa–let–7b–5p. F CeRNA networks associated with SASS6. G Difference analysis of hsa–let–7b–5p between LUAD group and normal group. H Difference analysis of CYP4F26P between LUAD group and normal group. I KM survival analysis of hsa−let–7b–5p in LUAD cases. J KM survival analysis of CYP4F26P in LUAD cases

Experimental validation of differential expression of SASS6 in LUAD

Immunohistochemistry results showed deeper staining in LUAD tumor tissues, confirming that SASS6 is overexpressed in LUAD (Fig. 10).

Fig. 10

The expression of SASS6 was up-regulated in LUAD. Immunohistochemical images of the tumor and adjacent lung tissue from 4 patients with LUAD

Biological function of SASS6 in lung cancer cells

The results of WB showed that SASS6 was highly expressed in lung cancer cells (Fig. 11A), and the expression of SASS6 was successfully knocked down for subsequent cell function experiments (Fig. 11B). CCK8 and EDU assays confirmed that SASS6 knockdown attenuated proliferation of lung cancer (Fig. 11C, D). Knockdown of SASS6 inhibited the migration and invasion of lung cancer through Transwell assay (Fig. 11E), and wound healing assay further confirmed that SASS6 knockdown reduced the migration ability of cancer cells (Fig. 11F).

Fig. 11

SASS6 promoted tumor progression. A SASS6 protein was detected by WB in A549 and H1299 cells before RNA interference. B SASS6 protein was detected by WB in A549 and H1299 cells after RNA interference. The proliferation of tumor was detected by CCK8 (C) and EDU (D) assay in si-NC group and si-SASS6 group. E Transwell assay was implemented to verify the migration and invasion ability of A549 and H1299 cells. F Wound healing assay in tumor cells