Homologous recombination repair capacity in peripheral blood lymphocytes and breast cancer risk

The interaction between systemic inflammatory markers and polygenic risk score in breast cancer risk: A cohort study in the UK Biobank

BACKGROUND

Systemic inflammatory markers have been widely used in cancer prognosis prediction recently. However, there is limited knowledge regarding their impact on breast cancer risk and their interaction with polygenic risk scores.

METHODS

A cohort study of 202,403 female participants from the UK Biobank were analyzed to estimate the hazard ratio (HR) for the incidence and mortality of breast cancer based on inflammatory markers using Cox regression models. Additionally, we stratified the analysis by polygenic risk scores (PRS) for breast cancer, and examined the interaction between these markers and PRS through likelihood ratio tests and relative excess risk due to interaction (RERI).

RESULTS

Women in the highest tertile of neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and C-reactive protein (CRP) showed an increased risk of breast cancer [HR (95 %CI) = 1.10 (1.02-1.18), 1.09 (1.01-1.17) and 1.15 (1.05-1.25), respectively], as compared to those in the lowest tertile. Regarding breast cancer mortality, only NLR and CRP exhibited consistent results in the univariate model [HR (95 %CI) = 1.25 (0.99-1.58) and 1.39 (1.10-1.77), respectively]. When stratified by PRS, stronger associations between inflammatory markers and breast cancer risk were observed in the high PRS group. Furthermore, there was a significant additive interaction between CRP and PRS [RERI (95 % CI) = 0.30 (0.06-0.53)].

CONCLUSION

NLR and CRP are associated with breast cancer risk and mortality, and the effect of CRP is influenced by PRS. Systematic inflammatory markers, together with PRS, might be applied in combined screening for breast cancer.

Identifying liver metastasis-related hub genes in breast cancer and characterizing SPARCL1 as a potential prognostic biomarker

Background

The liver is the third most common metastatic site for advanced breast cancer (BC), and liver metastases predict poor prognoses. However, the characteristic biomarkers of BC liver metastases and the biological role of secreted protein acidic and rich in cysteine-like 1 (SPARCL1) in BC remain unclear. The present study aimed to identify potential biomarkers for liver metastasis of BC and to investigate the effect of SPARCL1 on BC.

Methods

The publicly available GSE124648 dataset was used to identify differentially expressed genes (DEGs) between BC and liver metastases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to annotate these DEGs and understand the biological functions in which they are involved. A protein-protein interaction (PPI) network was constructed to identify metastasis-related hub genes and further validated in a second independent dataset (GSE58708). Clinicopathological correlation of hub gene expression in patients with BC was determined. Gene set enrichment analysis (GSEA) was performed to explore DEG-related signaling pathways. SPARCL1 expression in BC tissues and cell lines was verified by RT-qPCR. Further in vitro experiments were performed to investigate the biological functions of SPARCL1 in BC cells.

Results

We identified 332 liver metastasis-related DEGs from GSE124648 and 30 hub genes, including SPARCL1, from the PPI network. GO and KEGG enrichment analyses of liver-metastasis-related DEGs revealed several enriched terms associated with the extracellular matrix and pathways in cancer. Clinicopathological correlation analysis of SPARCL1 revealed that its expression in BC was associated with age, TNM stage, estrogen receptor status, progesterone receptor status, histological type, molecular type, and living status of patients. GSEA results suggested that low SPARCL1 expression in BC was related to the cell cycle, DNA replication, oxidative phosphorylation, and homologous recombination. Lower expression levels of SPARCL1 were detected in BC tissues compared to adjacent tissues. The in vitro experiments showed that SPARCL1 knockdown significantly increased the proliferation and migration of BC cells, whereas the proliferation and migration were suppressed after elevating the expression of SPARCL1.

Conclusion

We identified SPARCL1 as a tumor suppressor in BC, which shows potential as a target for BC and liver metastasis therapy and diagnosis.

DNA repair phenotype and cancer risk: a systematic review and meta-analysis of 55 case-control studies

DNA repair phenotype can be measured in blood and may be a potential biomarker of cancer risk. We conducted a systematic review and meta-analysis of epidemiological studies of DNA repair phenotype and cancer through March 2021. We used random-effects models to calculate pooled odds ratios (ORs) of cancer risk for those with the lowest DNA repair capacity compared with those with the highest capacity. We included 55 case–control studies that evaluated 12 different cancers using 10 different DNA repair assays. The pooled OR of cancer risk (all cancer types combined) was 2.92 (95% Confidence Interval (CI) 2.49, 3.43) for the lowest DNA repair. Lower DNA repair was associated with all studied cancer types, and pooled ORs (95% CI) ranged from 2.02 (1.43, 2.85) for skin cancer to 7.60 (3.26, 17.72) for liver cancer. All assays, except the homologous recombination repair assay, showed statistically significant associations with cancer. The effect size ranged from 1.90 (1.00, 3.60) for the etoposide-induced double-strand break assay to 5.06 (3.67, 6.99) for the γ-H2AX assay. The consistency and strength of the associations support the use of these phenotypic biomarkers; however large-scale prospective studies will be important for understanding their use related to age and screening initiation.