High TSTA3 Expression as a Candidate Biomarker for Poor Prognosis of Patients With ESCC

Biomarkers of lymph node metastasis in esophageal cancer

Esophageal cancer (EC) is among the most aggressive malignancies, ranking as the seventh most prevalent malignant tumor worldwide. Lymph node metastasis (LNM) indicates localized spread of cancer and often correlates with a poorer prognosis, emphasizing the necessity for neoadjuvant systemic therapy before surgery. However, accurate identification of LNM in EC presents challenges due to the lack of satisfactory diagnostic techniques. Imaging techniques, including ultrasound and computerized tomography scans, have low sensitivity and accuracy in assessing LNM. Additionally, the existing serological detection lacks precise biomarkers. The intricate and not fully understood molecular processes involved in LNM of EC contribute to current detective limitations. Recent research has shown potential in using various molecules, circulating tumor cells (CTCs), and changes in the microbiota to identify LNM in individuals with EC. Through summarizing potential biomarkers associated with LNM in EC and organizing the underlying mechanisms involved, this review aims to provide insights that facilitate biomarker development, enhance our understanding of the underlying mechanisms, and ultimately address the diagnostic challenges of LNM in clinical practice.

TSTA3 overexpression promotes malignant characteristics in LUSC by regulating LAMP2-mediated autophagy and tumor microenvironment

BACKGROUND

TSTA3 gene encoding GDP-L-fucose synthase has recently been proved to be closely related to the prognosis of patients with various tumors. However, its role in lung cancer is still unclear. The purpose of this study is to explore the expression level, prognostic effect, potential function and mechanism of TSTA3 in lung cancer.

METHODS

Based on TCGA database, Kaplan-Meier and COX regression was used to analyze the relationship between TSTA3 expression and prognosis of lung cancer patients. Immunohistochemistry was used to determine the TSTA3 protein expression in lung cancer and normal tissues. The function of TSTA3 in lung squamous cell carcinoma (LUSC) cell was determined by CCK8, colony formation, transwell assay in vitro and subcutaneous xenografts in vivo. Transcriptome analysis, Lyso-Tracker Red staining and rescue experiment were used to explore the possible underlying mechanism.

RESULTS

The expression of TSTA3 was significantly increased in lung cancer, especially in LUSC, and was significantly correlated with the malignant characteristics of LUSC. COX regression analysis showed that the high expression of TSTA3 was an independent prognostic factor in LUSC patients. This was also confirmed by immunohistochemical staining. Compared with the control group, the proliferation, colony formation, invasion and migration ability of LUSC cells with TSTA3 overexpression was enhanced. Similarly, the ability of cell proliferation, colony formation, invasion and migration were weakened after transient knockdown of TSTA3. In vivo experiment showed that compared with control group, TSTA3 overexpression significantly promoted the growth of tumor and shortened survival time. In addition, transcriptome sequencing analysis showed that the differentially expressed genes between TSTA3 overexpression and control group was mainly concentrated in the lysosome pathway. Further study found that TSTA3 might affect the proliferation, invasion and migration of LUSC by regulating the expression of lysosome-associated membrane protein 2 (LAMP2) in LUSC.

CONCLUSION

The expression level of TSTA3 in LUSC is significantly higher than that in normal tissues. High expression of TSTA3 is associated with poor prognosis of LUSC patients. TSTA3 may affect the proliferation, invasion and migration of LUSC by regulating LAMP2.

A glycolysis-related two-gene risk model that can effectively predict the prognosis of patients with rectal cancer

Background

Aerobic glycolysis is an emerging hallmark of cancer. Although some studies have constructed glycolysis-related prognostic models of colon adenocarcinoma (COAD) based on The Cancer Genome Atlas (TCGA) database, whether the COAD glycolysis-related prognostic model is appropriate for distinguishing the prognosis of rectal adenocarcinoma (READ) patients remains unknown. Exploring critical and specific glycolytic genes related to READ prognosis may help us discover new potential therapeutic targets for READ patients.

Results

Three gene sets, HALLMARK_GLYCOLYSIS, REACTOME_GLYCOLYSIS and REACTOME_REGULATION_OF_GLYCOLYSIS_BY_FRUCTOSE_2_6_BISPHOSPHATE_METABOLISM, were both significantly enriched in both COAD and READ through glycolysis-related gene set enrichment analysis (GSEA). We found that six genes (ANKZF1, STC2, SUCLG2P2, P4HA1, GPC1 and PCK1) were independent prognostic genes in COAD, while TSTA3 and PKP2 were independent prognostic genes in READ. Glycolysis-related prognostic model of COAD and READ was, respectively, constructed and assessed in COAD and READ. We found that the glycolysis-related prognostic model of COAD was not appropriate for READ, while glycolysis-related prognostic model of READ was more appropriate for READ than for COAD. PCA and t-SNE analysis confirmed that READ patients in two groups (high and low risk score groups) were distributed in discrete directions based on the glycolysis-related prognostic model of READ. We found that this model was an independent prognostic indicator through multivariate Cox analysis, and it still showed robust effectiveness in different age, gender, M stage, and TNM stage. A nomogram combining the risk model of READ with clinicopathological characteristics was established to provide oncologists with a practical tool to evaluate the rectal cancer outcomes. GO enrichment and KEGG analyses confirmed that differentially expressed genes (DEGs) were enriched in several glycolysis-related molecular functions or pathways based on glycolysis-related prognostic model of READ.

Conclusions

We found that a glycolysis-related prognostic model of COAD was not appropriate for READ, and we established a novel glycolysis-related two-gene risk model to effectively predict the prognosis of rectal cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-022-00377-0.

Identification of hub genes with prognostic values in multiple myeloma by bioinformatics analysis

PURPOSE

Multiple myeloma (MM) is a malignant disease with abnormal proliferation of clonal plasma cells. Hypoxia is an important factor in the pathogenesis and development of MM. However, the underlying mechanisms are not fully understood.

MATERIAL & METHODS

To determine hub genes related to hypoxia in MM, this study took integrated bioinformatics analysis with two expression datasets (GSE80140 and GSE80545) downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were filtrated under the condition of both p-value < 0.05 and [log2FoldChange (log2FC)] > 1. Then, gene ontology (GO) and Kyoto encyclopedia of genes and genomes enrichment (KEGG) analysis, and protein-protein interaction (PPI) network construction were utilized to further explore these DEGs. PrognoScan evaluated all the candidate hub genes for survival analysis.

RESULTS

In total, three hub genes, including FH, TSTA3, and POLR3G, were screened out to be related to hypoxia in MM. Patients with the lower expression level of FH, TSTA3, and POLR3G have statistically significantly longer disease- specific survival (Cox p < 0.05).

CONCLUSION

We identified FH, TSTA3, and POLR3G as hub genes which can affect MM patients'outcome and new biomarkers for diagnosis and prognosis of MM. Further functional and mechanistic studies are need to develop in order to make them as potential target for clinical treatment.

Tissue-specific transplantation antigen P35B functions as an oncogene and is regulated by microRNA-125a-5p in lung cancer

Tissue‑specific transplantation antigen P35B (TSTA3) expression is upregulated in esophageal squamous cell carcinoma and breast cancer, and functions as an oncogene in breast cancer. However, the roles and underlying mechanisms of TSTA3 in lung cancer have not been fully elucidated. The current study aimed to reveal the role of TSTA3 in lung cancer and explore whether TSTA3 may be modulated by microRNA (miR)‑125a‑5p to activate β‑catenin signaling. Immunohistochemical staining and western blotting were used to analyze TSTA3 expression in lung cancer tissues and cells. Cell functions were assessed via Cell Counting Kit‑8, flow cytometry, wound‑healing, Transwell and in vivo tumor formation assays. The effect of TSTA3 on the activation of β‑catenin signaling was determined using western blot and immunofluorescence analyses. The association between miR‑125a‑5p and TSTA3 was determined by western blotting and luciferase gene reporter assay. The present study revealed that, compared with normal tissues and cells, TSTA3 expression was significantly increased in lung cancer tissues and cell lines, and high TSTA3 expression predicted a poor prognosis and more malignant clinical features in patients with lung cancer. TSTA3 upregulation significantly enhanced β‑catenin expression and promoted its nuclear accumulation. In addition, TSTA3 expression was negatively regulated by miR‑125a‑5p, which was downregulated in lung cancer. Furthermore, TSTA3 overexpression markedly promoted cell proliferation, migration, invasion and tumorigenesis, and suppressed cell apoptosis. TSTA3 downregulation abolished the effects of miR‑125a‑5p downregulation on promoting lung cancer cell malignant transformation. Overall, the current study demonstrates that TSTA3 is regulated by miR‑125a‑5p and functions as an oncogene in lung cancer via promoting the activation of β‑catenin signaling.

A systematic analysis of a potential metabolism-related prognostic signature for breast cancer patients

Background

Metabolic pathways play an essential role in breast cancer. However, the role of metabolism-related genes in the early diagnosis of breast cancer remains unknown.

Methods

In our study, RNA sequencing (RNA-seq) expression data and clinicopathological information from The Cancer Genome Atlas (TCGA) and GSE20685 were obtained. Univariate cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed on the differentially expressed metabolism-related genes. Then, the formula of the metabolism-related risk model was composed, and the risk score of each patient was calculated. The breast cancer patients were divided into high-risk and low-risk groups with a cutoff of the median expression value of the risk score, and the prognostic analysis was also used to analyze the survival time between these two groups. In the end, we also analyzed the expression, interaction, and correlation among genes in the metabolism-related gene risk model.

Results

The results from the prognostic analysis indicated that the survival was significantly poorer in the high-risk group than in the low-risk group in both TCGA and GSE20685 datasets. In addition, after adjusting for different clinicopathological features in multivariate analysis, the metabolism-related risk model remained an independent prognostic indicator in TCGA dataset.

Conclusions

In summary, we systematically developed a potential metabolism-related gene risk model for predicting prognosis in breast cancer patients.

Proteomic analysis of hypopharyngeal and laryngeal squamous cell carcinoma sheds light on differences in survival

The link between differences in molecular expression and survival among advanced laryngeal (LSCC) and hypopharyngeal squamous carcinoma (HPSCC) remains unclear. Here, we applied the Surveillance, Epidemiology, and End Results (SEER) program, Isobaric tag for relative and absolute quantitation (iTRAQ) with Liquid chromatography-mass spectrometry (LC–MS/MS) proteomics data and The Cancer Genome Atlas (TCGA) related data to discover the possible disparities between HPSCC and LSCC. Our results showed a significantly worse 5-year overall-survival in HPSCC compared with LSCC before and after adjusting for clinical parameters. 240 differentially expressed proteins were enriched in molecular networks of cytoskeleton remodeling and antigen presentation. Moreover, HPSCC consisted of less T-central-memory cells, T-follicular-helper cells, TGF-β response, and CD4⁺  T memory resting cells, but more wound healing than LSCC. Furthermore, 9 mRNAs expression were  significantly and independently correlated to overall survival in 126 HPSCC and LSCC patients, which was further validated in another cohort of head and neck cancers. These findings support that Immunity signatures as well as pathway networks that include cytoskeleton remodeling and antigen presentation may contribute to the observed differences in survival between HPSCC and LSCC.

TSTA3 facilitates esophageal squamous cell carcinoma progression through regulating fucosylation of LAMP2 and ERBB2

Background: TSTA3 gene encodes an enzyme responsible for synthesis of GDP-L-fucose as the only donor in fucosylation. This study was designed to explore clinical value, function and underlying mechanism of TSTA3 in the development of esophageal squamous cell carcinoma (ESCC). Methods: Whole genomic sequencing data from 663 ESCC patients and RNA sequencing data from 155 ESCC patients were used to analyze the copy number variation and mRNA expression of TSTA3 respectively. Immunohistochemistry based or not based on the tissue microarrays was used to detect its protein expression. Transwell assay and in vivo metastasis assay were used to study the effect of TSTA3 on invasion and metastasis of ESCC. Immunofluorescence was used to analyze fucosylation level. N-glycoproteomics and proteomics analysis, Lens Culinaris Agglutinin (LCA) and Ulex Europaeus Agglutinin I (UEA-I) affinity chromatography, immunoprecipitation, glycosyltransferase activity kit and rescue assay were used to explore the mechanism of TSTA3. Results: TSTA3 was frequently amplified and overexpressed in ESCC. TSTA3 amplification and protein overexpression were significantly associated with malignant progression and poor prognosis of ESCC patients. TSTA3 knockdown significantly suppressed ESCC cells invasion and tumor dissemination by decreasing fucosylation level. Conversely, exogenous overexpression of TSTA3 led to increased invasion and tumor metastasis in vitro and in vivo by increasing fucosylation level. Moreover, core fucosylated LAMP2 and terminal fucosylated ERBB2 might be mediators of TSTA3-induced pro-invasion in ESCC and had a synergistic effect on the process. Peracetylated 2-F-Fuc, a fucosyltransferase activity inhibitor, reduced TSTA3 expression and fucosylation modification of LAMP2 and ERBB2, thereby inhibiting ESCC cell invasion. Conclusion: Our results indicate that TSTA3 may be a driver of ESCC metastasis through regulating fucosylation of LAMP2 and ERBB2. Fucosylation inhibitor may have prospect to suppress ESCC metastasis by blocking aberrant fucosylation.