Introduction: Uterine cancer (UC) remains one of the most predominant gynaecological malignancies in Asia and is often associated with high mortality owing to the unavailability of reliable precision markers and targeted therapy. Also, the option of hysterectomy renders a woman infertile as part of its current treatment course. Therefore, it is the need of the hour to develop new drug targets to efficiently formulate a new treatment regimen.

Methods: With recent advances in the field of multi-omics studies, it is now possible to mine data from several publicly available data repositories, thereby accelerating the search for a suitable biomarker and drug target. Thus, bioinformatic analyses were performed using various web applications like UALCAN, Gepia2, OncoDB, and cBioPortal to understand the impact of HMG-CoA reductase (HMGCR) and its effects on both subtypes of uterine cancer by extracting data from TCGA and GTEx.

Results: TCGA data accessed through cBioPortal revealed a higher percentage of mutational anomalies in the UCEC (6%) patients compared to UCS (1.75%). By accessing the transcriptomics data, it was found that the UCEC type, the most abundant form of UC, showed significantly higher expression of HMGCR (TPM) compared to the normal tissues (p<0.05). However, the changes in mRNA level expression in the case of UCS and its normal counterparts were found to be non-significant (p>0.05). Subsequent studies also reconfirm the claim in pre-menopausal women, where preserving fertility is a major concern.

Conclusion: HMGCR catalyses an important step in the cholesterol biosynthetic pathway. Often, statins are prescribed for managing LDL levels, which are inhibitors of this enzyme. HMGCR is significantly increased at transcript levels in the UCEC samples but not in the UCS samples. Therefore, statins might serve as an alternative medication to harness UC in pre- and perimenopausal women and are yet to be confirmed through in vitro studies.