Identification of Potential Biomarkers for Pan-Cancer Diagnosis and Prognosis Through the Integration of Large-Scale Transcriptomic Data

Upregulation of TTK expression is associated with poor prognosis and immune infiltration in endometrial cancer patients

BACKGROUND

Threonine and tyrosine kinase (TTK) is associated with invasion and metastasis in various tumors. However, the prognostic importance of TTK and its correlation with immune infiltration in endometrial cancer (EC) remain unclear.

METHODS

The expression profile of TTK was analyzed using data from The Cancer Genome Atlas (TCGA) and the Clinical Proteome Cancer Analysis Consortium (CPTAC). TTK protein and mRNA levels were verified in EC cell lines. Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of TTK to distinguish between normal and EC tissues. K-M survival analysis was also conducted to evaluate the impact of TTK on survival outcomes. Protein‒protein interaction (PPI) networks associated with TTK were explored using the STRING database. Functional enrichment analysis was performed to elucidate the biological functions of TTK. TTK mRNA expression and immune infiltration correlations were examined using the Tumor Immune Estimation Resource (TIMER) and the Tumor-Immune System Interaction Database (TISIDB).

RESULTS

TTK expression was significantly greater in EC tissues than in adjacent normal tissues. Higher TTK mRNA expression was associated with tumor metastasis and advanced TNM stage. The protein and mRNA expression of TTK was significantly greater in tumor cell lines than in normal endometrial cell lines. ROC curve analysis revealed high accuracy (94.862%), sensitivity (95.652%), and specificity (94.894%) of TTK in differentiating EC from normal tissues. K-M survival analysis demonstrated that patients with high TTK expression had worse overall survival (OS) and disease-free survival (DFS) rates. Correlation analysis revealed that TTK mRNA expression was correlated with B cells and neutrophils.

CONCLUSION

TTK upregulation is significantly associated with poor survival outcomes and immune infiltration in patients with EC. TTK can serve as a potential biomarker for poor prognosis and a promising immunotherapy target in EC. Further investigation of the role of TTK in EC may provide valuable insights for therapeutic interventions and personalized treatment strategies.

Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel

BACKGROUND

The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood.

METHODS

We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs.

RESULTS

We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs.

CONCLUSION

The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type.

Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.