Identification and validation of a novel signature as a diagnostic and prognostic biomarker in colorectal cancer

Molecular subtyping and the construction of a predictive model of colorectal cancer based on ion channel genes

PURPOSE

Colorectal cancer (CRC) is a highly heterogeneous malignancy with an unfavorable prognosis. The purpose of this study was to address the heterogeneity of CRC by categorizing it into ion channel subtypes, and to develop a predictive modeling based on ion channel genes to predict the survival and immunological states of patients with CRC. The model will provide guidance for personalized immunotherapy and drug treatment.

METHODS

A consistent clustering method was used to classify 619 CRC samples based on the expression of 279 ion channel genes. Such a method was allowed to investigate the relationship between molecular subtypes, prognosis, and immune infiltration. Furthermore, a predictive modeling was constructed for ion channels to evaluate the ion channel properties of individual tumors using the least absolute shrinkage and selection operator. The expression patterns of the characteristic genes were validated through molecular biology experiments. The effect of potassium channel tetramerization domain containing 9 (KCTD9) on CRC was verified by cellular functional experiments.

RESULTS

Four distinct ion channel subtypes were identified in CRC, each characterized by unique prognosis and immune infiltration patterns. Notably, Ion Cluster3 exhibited high levels of immune infiltration and a favorable prognosis, while Ion Cluster4 showed relatively lower levels of immune infiltration and a poorer prognosis. The ion channel score could predict overall survival, with lower scores correlated with longer survival. This score served as an independent prognostic factor and presented an excellent predictive efficacy in the nomogram. In addition, the score was closely related to immune infiltration, immunotherapy response, and chemotherapy sensitivity. Experimental evidence further confirmed that low expression of KCTD9 in tumor tissues was associated with an unfavorable prognosis in patients with CRC. The cellular functional experiments demonstrated that KCTD9 inhibited the proliferation, migration and invasion capabilities of LOVO cells.

CONCLUSIONS

Ion channel subtyping and scoring can effectively predict the prognosis and evaluate the immune microenvironment, immunotherapy response, and drug sensitivity in patients with CRC.

Potentials of ribosomopathy gene as pharmaceutical targets for cancer treatment

Ribosomopathies encompass a spectrum of disorders arising from impaired ribosome biogenesis and reduced functionality. Mutation or dysexpression of the genes that disturb any finely regulated steps of ribosome biogenesis can result in different types of ribosomopathies in clinic, collectively known as ribosomopathy genes. Emerging data suggest that ribosomopathy patients exhibit a significantly heightened susceptibility to cancer. Abnormal ribosome biogenesis and dysregulation of some ribosomopathy genes have also been found to be intimately associated with cancer development. The correlation between ribosome biogenesis or ribosomopathy and the development of malignancies has been well established. This work aims to review the recent advances in the research of ribosomopathy genes among human cancers and meanwhile, to excavate the potential role of these genes, which have not or rarely been reported in cancer, in the disease development across cancers. We plan to establish a theoretical framework between the ribosomopathy gene and cancer development, to further facilitate the potential of these genes as diagnostic biomarker as well as pharmaceutical targets for cancer treatment.

A novel prognostic signature and potential therapeutic drugs based on tumor immune microenvironment characterization in breast cancer

Tumor microenvironment (TME) is closely correlated to the occurrence and progression of breast cancer, however its potentiality in assisting diagnosis and therapeutic decision remains unclear. Therefore, the major aim of this study is to explore the prognostic value of TME related gene in breast cancer. Expression matrices and clinical data of breast cancer obtained from public databases were divided into TME relevant clusters according to immune characterization. A 12-gene molecular classifier was generated through the utilization of differentially expressed genes identified between distinct Tumor Microenvironment (TME) clusters, coupled with correlative regression analysis. The performance of this TME-driven prognostic signature (TPS) were examined across both the training and validation cohorts. Furthermore, our study revealed that breast cancer cases classified as high-risk based on the TPS exhibited the phenotype with elevated immune cell infiltration, higher tumor mutational burden, and a notably worse overall prognostic outcome. To conclude, the novel TME-based TPS was able to serve as a superior prognosis indicator for breast cancer, alone or jointly with other clinical factors. Also, breast cancer patients belong to different risk subgroups of TPS were found potentially suitable for distinguished therapeutic agents, which might improve personalized treatment for breast cancer in the future.

ZNF750: A Novel Prognostic Biomarker in Metastatic Prostate Cancer

Prostate cancer is the most frequently diagnosed cancer and the fifth leading cause of cancer death among men in 2020. The clinical decision making for prostate cancer patients is based on the stratification of the patients according to both clinical and pathological parameters such as Gleason score and prostate-specific antigen levels. However, these tools still do not adequately predict patient outcome. The aim of this study was to investigate whether ZNF750 could have a role in better stratifying patients, identifying those with a higher risk of metastasis and with the poorest prognosis. The data reported here revealed that ZNF750 protein levels are reduced in human prostate cancer samples, and this reduction is even higher in metastatic samples. Interestingly, nuclear positivity is significantly reduced in patients with metastatic prostate cancer, regardless of both Gleason score and grade group. More importantly, the bioinformatics analysis indicates that ZNF750 expression is positively correlated with better prognosis. Overall, our findings suggest that nuclear expression of ZNF750 may be a reliable prognostic biomarker for metastatic prostate cancer, which lays the foundation for the development of new biological therapies.

Gene expression in organoids: an expanding horizon

Recent development of human three-dimensional organoid cultures has opened new doors and opportunities ranging from modelling human development in vitro to personalised cancer therapies. These new in vitro systems are opening new horizons to the classic understanding of human development and disease. However, the complexity and heterogeneity of these models requires cutting-edge techniques to capture and trace global changes in gene expression to enable identification of key players and uncover the underlying molecular mechanisms. Rapid development of sequencing approaches made possible global transcriptome analyses and epigenetic profiling. Despite challenges in organoid culture and handling, these techniques are now being adapted to embrace organoids derived from a wide range of human tissues. Here, we review current state-of-the-art multi-omics technologies, such as single-cell transcriptomics and chromatin accessibility assays, employed to study organoids as a model for development and a platform for precision medicine.