Association of Sarcopenia With Toxicity-Related Discontinuation of Adjuvant Endocrine Therapy in Women With Early-Stage Hormone Receptor-Positive Breast Cancer

The association between sarcopenia and clinical outcomes among Chinese patients with triple-negative breast cancer: a retrospective study

Purpose

This study efforts to explore the association between sarcopenia, an age-related decline in muscle mass and physical function, and clinical outcomes in women with triple-negative breast cancer (TNBC).

Methods and materials

This retrospective study included women diagnosed with TNBC who received breast surgery from December 2012 to December 2018. Skeletal muscle mass index (SMI) is utilized to evaluate sarcopenia, which was quantified by the cross-sectional area of muscle at the twelfth thoracic vertebra (T12). Disease-free survival (DFS) and overall survival (OS) are the endpoints. The association of sarcopenia with DFS and OS was statistically analyzed.

Results

The study included 130 women in all, with a median age of 55 years (median follow-up, 53 months). Among them, 78 (58.5%) women had sarcopenia (SMI <28.01). 38 patients (29.2%) died and 49 patients (37.7%) experienced a recurrence of breast cancer throughout the follow-up period. Sarcopenia was demonstrated to be a significant predictive factor for both OS (HR,2.885; 95% CI, 1.349-6.169; p = 0.006) and DFS (HR,3.121; 95% CI, 1.578-6.175; p = 0.001) in the multivariate Cox proportional hazard model. There was no significant correlation seen between body mass index and either DFS (p = 0.156) or OS (P = 0.264). Logistic regression model further revealed that sarcopenia was a prognostic factor that was independently associated with both DFS (p = 0.001) and OS (p = 0.006).

Conclusions

Among women with TNBC, sarcopenia is associated with worse clinical outcomes. These patients with high risk might be candidates for individual programmed exercise and diet interventions to optimize survival outcomes.

Genetic overlap between breast cancer and sarcopenia: exploring the prognostic implications of SLC38A1 gene expression

BACKGROUND

Sarcopenia, an age-related syndrome characterized by a decline in muscle mass, not only affects patients' quality of life but may also increase the risk of breast cancer recurrence and reduce survival rates. Therefore, investigating the genetic mechanisms shared between breast cancer and sarcopenia is significant for the prevention, diagnosis, and treatment of breast cancer.

METHODS

This study downloaded gene expression datasets and clinical data related to breast cancer and skeletal muscle aging from the GEO database. Data preprocessing, integration, differential gene identification, functional enrichment analysis, and construction of protein-protein interaction networks were performed using R language. Subsequently, COX proportional hazards model analysis and survival analysis were conducted, and survival curves and nomograms were generated. The expression levels of genes in tissues were detected using qRT-PCR, and the Radiant DICOM viewer software was used to delineate the pectoralis major muscle area in CT images.

RESULTS

We identified 152 differentially expressed genes (P < .05) and 226 sarcopenia-related genes (r > .4) associated with skeletal muscle aging. The TCGA-BRCA dataset revealed 106 genes associated with breast cancer (P < .05, logFC = 1). Functional enrichment analysis indicated significant enrichment in cell proliferation and growth pathways. The PPI network identified critical molecules involved in muscle aging and tumor progression. After dimensionality reduction, a strong correlation was observed between the expression of the muscle aging-related gene set and the prognosis of breast cancer patients (P < .01). The expression of SLC38A1 identified through multivariate COX analysis was significantly associated with poor prognosis in breast cancer patients (P = .03). Incorporating SLC38A1 expression, the prognostic model precisely forecasted breast cancer survival (P < .01). External validation confirmed the higher expression of the SLC38A1 gene in breast cancer tissues compared to adjacent non-cancerous tissues (P < .01). The SLC38A1 index, calculated in combination with the patient's age and BMI, can optimize the prognostic prediction model, providing a powerful tool for personalized treatment of breast cancer.

CONCLUSION

High SLC38A1 gene expression was significantly associated with poor prognosis in breast cancer patients. The combination of SLC38A1 expression and the pectoralis major muscle area provided an optimized prognostic prediction model, offering a potential tool for personalized breast cancer treatment.

Anthropometric equation has sufficient diagnostic capacity to identify sarcopenia in women with breast cancer

BACKGROUND

Sarcopenia is a common condition in women with breast cancer, however still presents limitations for an effective diagnosis. This study aimed to evaluate the agreement and diagnostic accuracy of an anthropometric equation in diagnosing sarcopenia in women with breast cancer based on different constructs.

METHODS

Cross-sectional study carried out with women with breast cancer aged ≥ 20 years. Sarcopenia was identified according to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Muscle strength was obtained by the handgrip strength test (HGS) and muscle mass (MM) by dual-energy x-ray absorptiometry (DXA) and by the anthropometric predictive equation. For the diagnosis of sarcopenia, eight constructs were proposed based on the MM assessment method (equation or DXA) and different cutoff points. Agreement analyses using Cohen's Kappa test and diagnostic performance measures were performed. The significance level for all tests was 5%.

RESULTS

A total of 122 women, with a mean age of 55.3 ± 11.4 years, were evaluated. There was a predominance of brown participants (50.8%), insufficiently active (57.4%), with diagnosis time ≤ 3 months (54.1%), and with invasive breast carcinoma (69.7%). The prevalence of sarcopenia ranged from 3.3 to 8.2%, depending on the construct used. The constructs determined from the cutoff points < 16.0 kg/< 7.58 m² and < 23.0 kg/< 7.58 m² were the ones that showed the best ability to detect sarcopenia.

CONCLUSION

The anthropometric equation showed sufficient diagnostic capacity to be used as an alternative in identifying sarcopenia in women with breast cancer.