Synthetic lethality between TP53 and ENDOD1

Promising predictive molecular biomarkers for cervical cancer (Review)

Cervical cancer (CC) constitutes a serious public health problem. Vaccination and screening programs have notably reduced the incidence of CC worldwide by >80%; however, the mortality rate in low‑income countries remains high. The staging of CC is a determining factor in therapeutic strategies: The clinical management of early stages of CC includes surgery and/or radiotherapy, whereas radiotherapy and/or concurrent chemotherapy are the recommended therapeutic strategies for locally advanced CC. The histopathological characteristics of tumors can effectively serve as prognostic markers of radiotherapy response; however, the efficacy rate of radiotherapy may significantly differ among cancer patients. Failure of radiotherapy is commonly associated with a higher risk of recurrence, persistence and metastasis; therefore, radioresistance remains the most important and unresolved clinical problem. This condition highlights the importance of precision medicine in searching for possible predictive biomarkers to timely identify patients at risk of treatment response failure and provide tailored therapeutic strategies according to genetic and epigenetic characteristics. The present review aimed to summarize the evidence that supports the role of several proteins, methylation markers and non‑coding RNAs as potential predictive biomarkers for CC.

Predicting therapeutic responses in head and neck squamous cell carcinoma from TP53 mutation detected by cell-free DNA

Background

Head and neck squamous cell carcinoma (HNSCC) is an epithelial malignant tumor originating from the oral cavity, oropharynx, nasal cavity, sinuses, nasopharynx, hypopharynx, or larynx. Mutations in TP53 are the most common of all somatic genomic changes in HNSCC, and TP53 mutations are associated with the response to immunotherapy and chemotherapy. Tumor-derived circulating cell-free DNA (cfDNA) is a minimally invasive method to determining genetic alterations in cancer. This study aimed to explore the therapeutic responses of patients with HNSCC with TP53 mutation and the accuracy of cfDNA for detecting TP53 mutation.

Methods

Information on TP53 mutations, patient survival time, and clinical data in HNSCC were downloaded from The Cancer Genome Atlas database. The difference in immune infiltration between the TP53-mutant group and the wild-type group was compared. We applied the single-sample gene set enrichment analysis method on the transcriptome of HNSCC samples to assess the distribution of immune cell types between the two groups. The chemotherapy response was constructed using the R software package, "pRRophetic". Gene set enrichment analysis was performed based on the TP53 mutation. The next-generation sequencing was executed on cfDNA from nine patients with HNSCC to detect genetic alterations. Tumor biopsy (n=9) was sequenced using the same technique.

Results

TP53 was the most frequently mutated gene in HNSCC. The TP53 mutation was related to immune cells and the expression of immune-associated genes. The TP53 mutation group showed lower response to immunotherapy but high sensitivity to some chemotherapies compared with the wild-type group. TP53 was the most frequently mutated gene (6/9; 66.67%) in cfDNA. Only 27.27% of TP53 mutations in tumor tissue were detected outside of cfDNA.

Conclusions

TP53 mutation could be used as a specific predictor of treatment response in patients with HNSCC. Using cfDNA to detect the TP53 mutations in patients with HSNCC is a feasible method. The results suggested that the therapeutic response in patients could be predicted by detecting TP53 mutations in cfDNA, and large-scale and prospective studies are needed to validate this hypothesis.

Systematic analysis of cancer-specific synthetic lethal interactions provides insight into personalized anticancer therapy

The concept of synthetic lethality has great potential for anticancer therapy as a new strategy to specifically kill cancer cells while sparing normal cells. To further understand the potential molecular interactions and gene characteristics involved in synthetic lethality, we performed a comprehensive analysis of predicted cancer-specific genetic interactions. Many genes were identified as cancer-associated genes that contributed to multiple biological processes and pathways, and the gene features were not random, indicating their potential roles in human carcinogenesis. Some relevant genes detected in multiple cancers were prone to be enriched in specific biological progresses and pathways, especially processes associated with DNA damage, chromosome-related functions and cancer pathways. These findings strongly implicated potential roles for these genes in cancer pathophysiology and functional relationships, as well as applications for future anticancer drug discovery. Further experimental validation indicated that the synthetic lethal interaction of APC and GFER may provide a potential anticancer strategy for patients with APC-mutant colon cancer. These results will contribute to further exploration of synthetic lethal interactions and broader application of the concept of synthetic lethality in anticancer therapeutics.