Identification of differential DNA methylation alterations of ovarian cancer in peripheral whole blood based on within-sample relative methylation orderings

Integration of miRNA expression analysis of purified leukocytes and whole blood reveals blood-borne candidate biomarkers for lung cancer

Changes in leukocyte populations may confound the disease-associated miRNA signals in the blood of cancer patients. We aimed to develop a method to detect differentially expressed miRNAs from lung cancer whole blood samples that are not influenced by variations in leukocyte proportions. The Ref-miREO method identifies differential miRNAs unaffected by changes in leukocyte populations by comparing the within-sample relative expression orderings (REOs) of miRNAs from healthy leukocyte subtypes and those from lung cancer blood samples. Over 77% of the differential miRNAs observed between lung cancer and healthy blood samples overlapped with those between myeloid-derived and lymphoid-derived leukocytes, suggesting the potential impact of changes in leukocyte populations on miRNA profile. Ref-miREO identified 16 differential miRNAs that target 19 lung adenocarcinoma-related genes previously linked to leukocytes. These miRNAs showed enrichment in cancer-related pathways and demonstrated high potential as diagnostic biomarkers, with the LASSO regression models effectively distinguishing between healthy and lung cancer blood or serum samples (all AUC > 0.85). Additionally, 12 of these miRNAs exhibited significant prognostic correlations. The Ref-miREO method offers valuable candidates for circulating biomarker detection in cancer that are not affected by changes in leukocyte populations.

Integrated analysis of diverse cancer types reveals a breast cancer-specific serum miRNA biomarker through relative expression orderings analysis

PURPOSE

Serum microRNA (miRNA) holds great potential as a non-invasive biomarker for diagnosing breast cancer (BrC). However, most diagnostic models rely on the absolute expression levels of miRNAs, which are susceptible to batch effects and challenging for clinical transformation. Furthermore, current studies on liquid biopsy diagnostic biomarkers for BrC mainly focus on distinguishing BrC patients from healthy controls, needing more specificity assessment.

METHODS

We collected a large number of miRNA expression data involving 8465 samples from GEO, including 13 different cancer types and non-cancer controls. Based on the relative expression orderings (REOs) of miRNAs within each sample, we applied the greedy, LASSO multiple linear regression, and random forest algorithms to identify a qualitative biomarker specific to BrC by comparing BrC samples to samples of other cancers as controls.

RESULTS

We developed a BrC-specific biomarker called 7-miRPairs, consisting of seven miRNA pairs. It demonstrated comparable classification performance in our analyzed machine learning algorithms while requiring fewer miRNA pairs, accurately distinguishing BrC from 12 other cancer types. The diagnostic performance of 7-miRPairs was favorable in the training set (accuracy = 98.47%, specificity = 98.14%, sensitivity = 99.25%), and similar results were obtained in the test set (accuracy = 97.22%, specificity = 96.87%, sensitivity = 98.02%). KEGG pathway enrichment analysis of the 11 miRNAs within the 7-miRPairs revealed significant enrichment of target mRNAs in pathways associated with BrC.

CONCLUSION

Our study provides evidence that utilizing serum miRNA pairs can offer significant advantages for BrC-specific diagnosis in clinical practice by directly comparing serum samples with BrC to other cancer types.

Knockdown of ARHGAP30 inhibits ovarian cancer cell proliferation, migration, and invasiveness by suppressing the PI3K/AKT/mTOR signaling pathway

The mortality and morbidity rates of ovarian cancer (OC) are high, but the underlying mechanisms of OC have not been characterized. In this study, we determined the role of Rho GTPase Activating Protein 30 (ARHGAP30) in OC progression. We measured ARHGAP30 abundance in OC tissue samples and cells using immunohistochemistry (IHC) and RT-qPCR. EdU, transwell, and annexin V/PI apoptosis assays were used to evaluate proliferation, invasiveness, and apoptosis of OC cells, respectively. The results showed that ARHGAP30 was overexpressed in OC tissue samples and cells. Inhibition of ARHGAP30 suppressed growth and metastasis of OC cells, and enhanced apoptosis. Knockdown of ARHGAP30 in OC cells significantly inhibited the PI3K/AKT/mTOR pathway. Treatment with the PI3K/AKT/mTOR pathway inhibitor buparlisib simulated the effects of ARHGAP30 knockdown on growth, invasiveness, and apoptosis of OC cells. Following buparlisib treatment, the expression levels of p-PI3K, p-AKT, and p-mTOR were significantly decreased. Furthermore, buparlisib inhibited the effects of ARHGAP30 upregulation on OC cell growth and invasiveness. In conclusion, ARHGAP30 regulated the PI3K/AKT/mTOR pathway to promote progression of OC.