Leveraging Cancer-Associated Mutations to Identify Synthetic Lethal Therapeutic Strategies in Endometriosis

Introduction: Endometriosis is a disease caused by abnormal growth of the inner lining of the uterus, known as the endometrium, outside the uterus. Endometriosis and endometrial carcinoma exhibit similarities in ectopic growth, which could also imply other underlying correlations. There have been studies that reveal cancer-associated mutations in endometriosis (KRAS, ARID1A, PIK3CA, PPP2R1A). Of these, KRAS mutations (p.G12D, p.G12V) are of particular interest due to their strong influence on the pathogenesis of many aggressive cancers as well as their mutant recurrence in patients with endometriosis. In cancer, genetic mutations can lead to a cell's increased reliance and activation of additional genes for its survival. Targeting these genes that become essential due to evolved dependencies is therapeutically known as Synthetic Lethality. Work by our group and others has shown that comparing the relative essentiality of genes in mutant cancers to wild-type tissue can uncover novel therapeutic strategies for targeting mutated cells. However, this approach has not been applied outside of the context of cancer, to situations where cancer-associated mutations occur in non-cancer cells, as is the case with endometriosis. The KRAS mutation is significant in endometrial lesions and its relationship with other essential genes could reveal a new application for synthetic lethality concepts as strategies to pharmacologically regress lesions in endometriosis. In this study, we combine transcriptomic data from endometriosis patients with genetic screening data from endometrial cancer cell lines to identify genes with dysregulated expression in endometriosis that exhibit increased essentiality in the presence of a KRAS mutation (Figure 1).

Materials and

Methods: Two primary datasets were utilized for this study. The endometriosis dataset included gene expression profiles from 6 healthy and 6 endometriosis samples. This data was obtained from Northwestern University and is available on the Gene Expression Omnibus database (GSE58178). The endometrial carcinoma dataset comprised CRISPR Gene Dependency probability estimates, accessed via the Dependency Map (DepMap) portal provided by the Broad Institute. These datasets were vital in conducting comparative analyses between gene expressions in healthy versus diseased states and understanding gene dependencies in endometrial carcinoma (Figure 2).

A literature review was conducted to identify cancer-associated mutations present in endometriosis before analyzing the datasets. For the endometriosis dataset, differential gene expression analysis was performed to identify distinct gene expression profiles between healthy and endometriosis samples. This involved standard preprocessing steps, normalization of expression levels, and subsequent statistical testing to highlight significantly differentially expressed genes. Endometrial carcinoma cell lines containing the formerly identified cancer-associated mutations were compared with wild-type cell lines through heatmaps (Figure 3). A Mann-Whitney test was applied to assess gene essentiality across mutants compared to wildtype, focusing on mutations impacting gene dependency. The outcome of this analysis was a list of genes found to be more essential in mutant cells relative to their wild-type counterparts.

Results, Conclusions, and Discussions: The integration of transcriptomic data from endometriosis patients with genetic screening data from endometrial cancer cell lines has led to notable findings in this study. Specifically, the genes containing KRAS mutations (e.g. p.G12D, p.G12V) in endometrial carcinoma include VISG8, YLMP1, and INPP4A. Additionally, genes like ZNF81 and NPFF were found to carry mutations not only in KRAS but also in other cancer-associated genes such as ARID1A, PIK3CA, and PPP2R1A (Figure 4). These genes exhibited significantly altered expression levels in endometriosis samples and increased essentiality in the mutant cancer cell lines, which make them potential targets for synthetic lethality.

The concept of synthetic lethality is primarily explored within the context of cancer; it appears promising when applied to endometriosis, particularly given the shared mutations such as those in the KRAS gene. The identification of these genes offers a novel approach for therapeutically targeting the ectopic growth seen in endometriosis, which is similar to strategies used in oncology. Validation of these target genes in endometriosis models could lead to breakthroughs in non-cancerous conditions where cancer-associated mutations are present. Furthermore, our study stresses the importance of cross-referencing findings with additional datasets, such as those derived from single-cell analyses, to confirm the prevalence and impact of identified mutations in endometriosis.

The preliminary findings from this study indicates a list of genes that may be dependent upon mutations in KRAS and other cancer-associated genes to keep endometriosis cells alive. This shows promise for adopting synthetic lethal therapeutic strategies in endometriosis. This research not only enhances our understanding of the molecular basis of endometriosis, but also opens new therapeutic avenues that leverage cancer biology insights in other areas of research.

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