Identification of Prognostic Markers and Potential Therapeutic Targets in Gastric Adenocarcinoma by Machine Learning Based on mRNAsi Index

KIF18B: an important role in signaling pathways and a potential resistant target in tumor development

KIF18B is a key member of the kinesin-8 family, involved in regulating various physiological processes such as microtubule length, spindle assembly, and chromosome alignment. This article briefly introduces the structure and physiological functions of KIF18B, examines its role in malignant tumors, and the associated carcinogenic signaling pathways such as PI3K/AKT, Wnt/β-catenin, and mTOR pathways. Research indicates that the upregulation of KIF18B enhances tumor malignancy and resistance to radiotherapy and chemotherapy. KIF18B could become a new target for anticancer drugs, offering significant potential for the treatment of malignant tumors and reducing chemotherapy resistance.

The emerging role of FAM46C as a biomarker and therapeutic target in gastric adenocarcinoma

On a global scale, gastric adenocarcinoma (GCa) accounts for a large burden of death from cancer. Despite advances in systemic therapy and surgical technique, the fatality rate for GCa remains unacceptably high in Europe and North America, where diagnosis is typically made at an advanced stage. Biomarkers that can accurately predict response to new therapies and provide novel therapeutic strategies are urgently sought. FAM46C, a putative noncanonical nucleotidyltransferase, has garnered interest for its tumor suppressor function in multiple myeloma. A frequent and profound depletion of FAM46C has been described in GCa patients from China, Japan and now Canada. Furthermore, the degree of FAM46C depletion meaningfully portends cancer recurrence following resection, and death from GCa. In this review, we provide an updated summary of the literature regarding FAM46C as a biomarker in GCa and explore the potential mechanism(s) through which FAM46C depletion promotes GCa progression, including dis-inhibition of oncogenic Plk4 kinase activity. We highlight the potential for restoration of FAM46C levels as a therapeutic strategy. Norcantharidin, a synthetic analogue of the traditional Chinese medicine cantharidin derived from the blister beetle, is the only bio-available compound presently known to upregulate FAM46C expression and is under investigation in phase one trials in cancer patients.

Important role and underlying mechanism of non‑SMC condensin I complex subunit G in tumours (Review)

At present, the incidence of tumours is increasing on a yearly basis, and tumourigenesis is usually associated with chromosomal instability and cell cycle dysregulation. Moreover, abnormalities in the chromosomal structure often lead to DNA damage, further exacerbating gene mutations and chromosomal rearrangements. However, the non‑SMC condensin I complex subunit G (NCAPG) of the structural maintenance of chromosomes family is known to exert a key role in tumour development. It has been shown that high expression of NCAPG is closely associated with tumour development and progression. Overexpression of NCAPG variously affects chromosome condensation and segregation during cell mitosis, influences cell cycle regulation, promotes tumour cell proliferation and invasion, and inhibits apoptosis. In addition, NCAPG has been associated with tumour cell stemness, tumour resistance and recurrence. The aim of the present review was to explore the underlying mechanisms of NCAPG during tumour development, with a view towards providing novel targets and strategies for tumour therapy, and through the elucidation of the mechanisms involved, to lay the foundation for future developments in health.

An individualized stemness-related signature to predict prognosis and immunotherapy responses for gastric cancer using single-cell and bulk tissue transcriptomes

BACKGROUND

Currently, many stemness-related signatures have been developed for gastric cancer (GC) to predict prognosis and immunotherapy outcomes. However, due to batch effects, these signatures cannot accurately analyze patients one by one, rendering them impractical in real clinical scenarios. Therefore, we aimed to develop an individualized and clinically applicable signature based on GC stemness.

METHODS

Malignant epithelial cells from single-cell RNA-Seq data of GC were used to identify stemness-related signature genes based on the CytoTRACE score. Using two bulk tissue datasets as training data, the enrichment scores of the signature genes were applied to classify samples into two subtypes. Then, using the identified subtypes as criteria, we developed an individualized stemness-related signature based on the within-sample relative expression orderings of genes.

RESULTS

We identified 175 stemness-related signature genes, which exhibited significantly higher AUCell scores in poorly differentiated GCs compared to differentiated GCs. In training datasets, GC samples were classified into two subtypes with significantly different survival times and genomic characteristics. Utilizing the two subtypes, an individualized signature was constructed containing 47 gene pairs. In four independent testing datasets, GC samples classified as high risk exhibited significantly shorter survival times, higher infiltration of M2 macrophages, and lower immune responses compared to low-risk samples. Moreover, the potential therapeutic targets and corresponding drugs were identified for the high-risk group, such as CD248 targeted by ontuxizumab.

CONCLUSIONS

We developed an individualized stemness-related signature, which can accurately predict the prognosis and efficacy of immunotherapy for each GC sample.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.