CHD5 gene variant predicts leptomeningeal metastasis after surgical resection of brain metastases of breast cancer

Otani, Ryohei; Sadato, Daichi; Yamada, Ryoji; Yajima, Hirohisa; Kawamura, Shinji; Shimizu, Sakura; Tanaka, Shota; Takayanagi, Shunsaku; Takami, Hirokazu; Yamaguchi, Tatsuro

doi:10.1007/s11060-023-04381-9

Cited by 1 publication

(1 citation statement)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The blood-brain barrier can severely hamper the ability of chemotherapeutic drugs to achieve satisfactory efficacy within the brain, and the benefits of immunotherapy when seeking to treat metastases within the brain are also limited given the poorly characterized immunological characteristics of this compartment ( 33 ). Surgical resection can only be successfully performed in a limited subset of patients, including those with relatively stable primary lesions, intracranial oligometastatic tumors, and tumors affecting non-important functional areas ( 34 ). During surgery, BMs in BRCA patients are often found to be closely adherent to the dura matter with leptomeningeal infiltration in some cases.…”

Section: Discussionmentioning

confidence: 99%

A model for predicting clinical prognosis based on brain metastasis-related genes in patients with breast cancer

Yuan,

Li,

Zhao

2023

Transl Cancer Res

View full text Add to dashboard Cite

Background Brain metastasis (BM) is a clinically relevant cause of death in patients with breast cancer (BRCA). This study was designed to develop a clinical model capable of predicting BRCA patients’ prognostic outcomes according to the expression of BM-related genes (BMRGs). Methods The public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases served as data sources. BMRGs of BRCA were selected from previous literature. Differences among BRCA molecular subtypes were compared using R ‘limma’ package. The impact of BM-related differentially expressed genes (BM_DEGs) on BRCA patients’ outcomes was explored with a risk score model, after which the relationship between these risk scores and immune cell infiltration was examined. Risk scores were also used to judge the predicted efficacy of immunotherapeutic interventions. The utility of risk scores in combination with clinicopathological characteristics was evaluated as a predictor of patient’s survival through univariate and multivariate analyses. Results The R limma package was used to explore differential gene expression, after which 12 BM_DEGs were incorporated into a risk scoring model. The resultant risk scores were able to predict immunotherapeutic treatment efficacy. In addition, a nomogram incorporating risk scores, stage, and age was established. The nomogram was able to reliably predict the overall survival (OS) of BRCA patients, yielding predictive outcomes that aligned well with actual observations. Conclusions In summary, a predictive clinical model for BRCA patients was successfully established in this study, providing a valuable tool that may be particularly helpful for the assessment of patients facing a risk of BM development.

show abstract

Section: Discussionmentioning

confidence: 99%