Functional analysis and validation of oncodrive gene AP3S1 in ovarian cancer through filtering of mutation data from whole-exome sequencing

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC) is the most aggressive and prevalent subtype of ovarian cancer and accounts for a significant portion of ovarian cancer-related deaths worldwide. Despite advancements in cancer treatment, the overall survival rate for HGSOC patients remains low, thus highlighting the urgent need for a deeper understanding of the molecular mechanisms driving tumorigenesis and for identifying potential therapeutic targets. Whole-exome sequencing (WES) has emerged as a powerful tool for identifying somatic mutations and alterations across the entire exome, thus providing valuable insights into the genetic drivers and molecular pathways underlying cancer development and progression.

METHODS

Via the analysis of whole-exome sequencing results of tumor samples from 90 ovarian cancer patients, we compared the mutational landscape of ovarian cancer patients with that of TCGA patients to identify similarities and differences. The sequencing data were subjected to bioinformatics analysis to explore tumor driver genes and their functional roles. Furthermore, we conducted basic medical experiments to validate the results obtained from the bioinformatics analysis.

RESULTS

Whole-exome sequencing revealed the mutational profile of HGSOC, including BRCA1, BRCA2 and TP53 mutations. AP3S1 emerged as the most weighted tumor driver gene. Further analysis of AP3S1 mutations and expression demonstrated their associations with patient survival and the tumor immune response. AP3S1 knockdown experiments in ovarian cancer cells demonstrated its regulatory role in tumor cell migration and invasion through the TGF-β/SMAD pathway.

CONCLUSION

This comprehensive analysis of somatic mutations in HGSOC provides insight into potential therapeutic targets and molecular pathways for targeted interventions. AP3S1 was identified as being a key player in tumor immunity and prognosis, thus providing new perspectives for personalized treatment strategies. The findings of this study contribute to the understanding of HGSOC pathogenesis and provide a foundation for improved outcomes in patients with this aggressive disease.

High-Content Analysis of the Golgi Complex by Correlative Screening Microscopy

The Golgi complex plays a central role in a number of diverse cellular processes, and numerous regulators that control these functions and/or morphology of the Golgi complex are known by now. Many of them were identified by large-scale experiments, such as RNAi-based screening. However, high-throughput experiments frequently provide only initial information that a particular protein might play a role in regulating structure and function of the Golgi complex. Multiple follow-up experiments are necessary to functionally characterize the selected hits. In order to speed up the discovery, we have established a system for correlative screening microscopy that combines rapid data collection and high-resolution imaging in one experiment. We describe here a combination of wide-field microscopy and dual-color direct stochastical optical reconstruction microscopy (dSTORM). We apply the technique to simultaneously capture and differentiate alterations of the cis- and trans-Golgi network when depleting several proteins in a singular and combinatorial manner.