Two distinct mechanisms underlie estrogen-receptor-negative breast cancer susceptibility at the 2p23.2 locus

WD repeat domain 43 as a new predictive indicator and its connection with tumor immune cell infiltration in pan-cancer

BACKGROUND

WD repeat domain 43 (WDR43) is a protein component that encodes WD-repeats and is involved in ribosome biogenesis. However, little is known about the role of WDR43 in cancer prognosis and immune modulation.

METHODS

In this study, we analyzed the expression and prognostic significance of WDR43 in pan-cancer using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas. We also examined the differential expression of WDR43 in liver hepatocellular carcinoma (LIHC) and adjacent tissues of 48 patients using immunohistochemistry. Additionally, we investigated the correlation between WDR43 and clinical characteristics, gene alterations, tumor mutation burden, microsatellite instability, mismatch repair, tumor microenvironment, immune infiltrating cells, and immune-related genes using bioinformatics methods. Gene set enrichment analysis was conducted, and potential biological mechanisms were identified.

RESULTS

Immunohistochemistry staining showed that WDR43 was overexpressed in LIHC among 48 patients. Upregulation of WDR43 was associated with unfavorable prognosis, including overall survival in various types of cancer such as LIHC, uterine corpus endometrial cancer, head and neck squamous cell carcinoma, and pancreatic adenocarcinoma. Differential expression of WDR43 was significantly correlated with microsatellite instability, mismatch repair, and immune cell infiltration. Gene ontology annotation analysis revealed that these genes were significantly enriched in immune-related functions, including immune response, immune regulation, and signaling pathways.

CONCLUSION

We conducted a thorough investigation of the clinical features, phases of tumor development, immune infiltration, gene mutation, and functional enrichment analysis of WDR43 in various types of cancer. This research offers valuable insight into the significance and function of WDR43 in clinical therapy.

TAaCGH Suite for Detecting Cancer-Specific Copy Number Changes Using Topological Signatures

Copy number changes play an important role in the development of cancer and are commonly associated with changes in gene expression. Persistence curves, such as Betti curves, have been used to detect copy number changes; however, it is known these curves are unstable with respect to small perturbations in the data. We address the stability of lifespan and Betti curves by providing bounds on the distance between persistence curves of Vietoris–Rips filtrations built on data and slightly perturbed data in terms of the bottleneck distance. Next, we perform simulations to compare the predictive ability of Betti curves, lifespan curves (conditionally stable) and stable persistent landscapes to detect copy number aberrations. We use these methods to identify significant chromosome regions associated with the four major molecular subtypes of breast cancer: Luminal A, Luminal B, Basal and HER2 positive. Identified segments are then used as predictor variables to build machine learning models which classify patients as one of the four subtypes. We find that no single persistence curve outperforms the others and instead suggest a complementary approach using a suite of persistence curves. In this study, we identified new cytobands associated with three of the subtypes: 1q21.1-q25.2, 2p23.2-p16.3, 23q26.2-q28 with the Basal subtype, 8p22-p11.1 with Luminal B and 2q12.1-q21.1 and 5p14.3-p12 with Luminal A. These segments are validated by the TCGA BRCA cohort dataset except for those found for Luminal A.