Muscle mass loss in breast cancer patients of reproductive age (≤ 45 years) undergoing neoadjuvant chemotherapy

Mechanisms, assessment, and exercise interventions for skeletal muscle dysfunction post-chemotherapy in breast cancer: from inflammation factors to clinical practice

Chemotherapy remains a central component of breast cancer treatment, significantly improving patient survival rates. However, its toxic side effects, along with cancer-related paraneoplastic syndromes, can lead to the loss of skeletal muscle mass and function, impairing physical abilities and increasing the risk of complications during treatment. Chemotherapeutic agents directly impact skeletal muscle cells by promoting protein degradation, inhibiting protein synthesis, and triggering systemic inflammation, all of which contribute to muscle atrophy. Additionally, these drugs can interfere with the proliferation and differentiation of stem cells, such as satellite cells, disrupting muscle regeneration and repair while inducing abnormal differentiation of intermuscular tissue, thereby worsening muscle wasting. These effects not only reduce the effectiveness of chemotherapy but also negatively affect patients' quality of life and disease prognosis. Recent studies have emphasized the role of exercise as an effective non-pharmacological strategy for preventing muscle loss and preserving muscle mass in cancer patients. This review examines the clinical manifestations of muscle dysfunction following breast cancer chemotherapy, the potential mechanisms underlying these changes, and the evidence supporting exercise as a therapeutic approach for improving muscle function.

Relationship Between Body Mass Index and Low Skeletal Muscle Mass in Adults Based on NHANES 2011-2018

Sarcopenia, a syndrome characterized by declining muscle mass and function, is associated with various adverse health outcomes. While body mass index (BMI) is a fundamental health indicator, its relationship with sarcopenia is complex and remains inadequately explored. Low BMI has been linked to muscle loss, but the role of other demographic and clinical factors in this relationship is unclear. This cross-sectional study analyzed data from the NHANES 2011-2018 cohort, including 7,455 adults aged ≥ 20 years. Low muscle mass was diagnosed based on appendicular skeletal muscle mass using DXA criteria. BMI was categorized into quartiles for analysis. Weighted multivariable logistic regression assessed associations between BMI and low muscle mass, adjusting for confounders such as age, gender, ethnicity, income-to-poverty ratio, and chronic diseases (e.g., diabetes and hypertension). Variance inflation factors (VIF) confirmed the absence of multicollinearity. Lower BMI was significantly associated with higher odds of low muscle mass (adjusted OR: 0.508, 95% CI: 0.483-0.533, p < 0.001), while higher BMI exhibited a protective effect. Age (OR: 1.035, 95% CI: 1.025-1.045, p < 0.001) and female gender (OR: 1.570, 95% CI: 1.267-1.949, p < 0.001) were independent risk factors. Racial disparities were noted, with non-Hispanic Black individuals at lower risk compared to non-Hispanic Whites (OR: 0.242, 95% CI: 0.152-0.384, p < 0.001). Other significant factors included diabetes and alcohol consumption, while education and smoking status were not significantly associated. BMI is inversely associated with low muscle mass prevalence, with lower BMI posing a higher odds. The findings underscore the clinical importance of monitoring BMI and addressing multifactorial risk profiles for low muscle mass management and prevention.

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.

Sarcopenia among treated cancer patients before and after neoadjuvant chemotherapy: a systematic review and meta-analysis of high-quality studies

BACKGROUND

Neoadjuvant chemotherapy, used to shrink tumors before surgery, is increasingly applied in clinical practice. However, retrospective studies indicate that it may increase sarcopenia rates and consequently result in an elevated occurrence rate of postoperative severe complications such as severe surgical incision infection, severe respiratory failure, and severe postoperative hemorrhage, especially in the elderly population. Currently, no systematic analysis examines the association between neoadjuvant chemotherapy and sarcopenia. This study aims to fill this gap with a comprehensive meta-analysis focused on this critical aspect of the field.

METHODS

A systematic literature search was conducted in the PubMed and Web of Science databases from their inception to January 2024. The included studies encompassed patients who received neoadjuvant chemotherapy and underwent computed tomography (CT) scans both before and after treatment to calculate skeletal muscle index (SMI) or categorize them for the presence of sarcopenia. The determination of sarcopenia status was based on well-established and validated threshold criteria. Data extraction was performed independently by two reviewers. A meta-analysis was employed to estimate the pooled odds ratio (OR) and its corresponding 95% confidence interval (95% CI) to assess the risk of neoadjuvant chemotherapy-induced muscle reduction.

RESULTS

In the 14 studies with complete categorical variable data, comprising 1853 patients, 773 patients were identified as having sarcopenia before neoadjuvant treatment and 941 patients had sarcopenia after neoadjuvant therapy. The OR and its 95% CI was calculated as 1.51 [1.31, 1.73]. Among these, 719 patients had digestive system cancer, with 357 patients having sarcopenia before neoadjuvant treatment and 447 patients after, resulting in an OR of 1.74 [1.40, 2.17]. In the remaining 1134 patients with non-digestive system cancers, 416 were identified as having sarcopenia before neoadjuvant treatment, and 494 patients had sarcopenia after, with an OR of 1.37 [1.15, 1.63]. Additionally, in seven studies with complete continuous variable data, including 1228 patients, the mean difference in the change of SMI before and after neoadjuvant treatment was  - 1.13 [- 1.65,  - 0.62]. After excluding low-quality small-sample studies with fewer than 50 patients, the same trend was observed in the analysis.

CONCLUSION

The risk of muscle reduction significantly increases in cancer patients after neoadjuvant chemotherapy and digestive system cancers tend to have a higher risk of developing sarcopenia post-treatment compared to non-digestive system cancers.

The Relationship of Pathological Response and Visceral Muscle and Fat Volume in Women With Breast Cancer Who Received Neoadjuvant Chemotherapy

Objective

Differences in individual muscle/fat volumes may change the effectiveness of chemotherapy. In this study, the relationship between trunkal muscle and fat volume and body mass index (BMI) obtained before receiving neoadjuvant chemotherapy (NCT) in patients with breast cancer and complete pathological response (pCR) was investigated.

Materials and Methods

The volumes of psoas, abdominal and paraspinal muscles, and trunkal subcutaneous and visceral fat were calculated using CoreSlicer AI 2.0 opensource program from the F-18 fluorodeoxyglucose positron emission tomography/computed tomography (CT) and CT images before NCT and postoperative pCR rates to NCT were recorded. Muscle/fat volumes and BMI prior to NCT were compared in terms of pathological pCR rates. Patients were followed up regularly for recurrence and survival.

Results

Ninety-three patients were included with median (range) values for age, BMI, and body weights of 48 (28-72) years, 27 (16.8-51.6) kg/m2, and 71.94 (43-137) kg, respectively. The median follow-up time was 18.6 (6.7-59.6) months. No significant correlation was found between total muscle or fat volumes of patients with and without pCR. BMI [26.2 (16.8-51.6) kg/m2 vs. 24.6 (20.3-34.3) kg/m2, p = 0.03] and pCR rates in patients with low right-psoas muscle volume [11.74 (7.03-18.51) vs. 10.2 (6.71-13.36), p = 0.025] were significantly greater. A significant relationship was found between right psoas muscle volume and disease-free survival (DFS) (11.74 cm3 (7.03-18.51) vs. 10.2 cm3 (6.71-13.36), p = 0.025). However, no significant relationship was detected between total muscle-fat volume, BMI and overall survival and DFS (p>0.05).

Conclusion

This is the first published study investigating the relationship between the pCR ratio and body muscle and fat volume measured by CoreSlicer AI 2.0 in patients with breast cancer who received NCT. No correlation was found between the pCR ratio and total muscle plus fat volume. However, these results need to be validated with larger patient series.

Significance of skeletal muscle index-to-body mass index ratio as a predictor of post-surgical bleeding after mastectomy in patients with breast cancer

BACKGROUND

Post-surgical bleeding is a major complication of mastectomy in patients with breast cancer. However, the risk factors for post-surgical bleeding have not been well studied. Although obesity or reduced skeletal muscle mass is an indicator of cancer surgery complications, its impact on post-surgical bleeding after mastectomy remains unknown.

METHODS

In total, 563 patients with breast cancer who underwent mastectomy were included in this study. We evaluated the preoperative body mass index (BMI), skeletal muscle index (SMI), and SMI-to-BMI ratio and analyzed the association between these values and the incidence of post-surgical bleeding.

RESULTS

Post-surgical bleeding occurred in 33 (5.6%) patients. Mean BMI was significantly higher in the bleeding group (26.3 ± 4.7) than in the no-bleeding group (23.0 ± 4.1) (p < 0.001), whereas mean SMI was lower in the former group (45.0 ± 8.5) than in the latter group (48.0 ± 8.5) (p = 0.08). The bleeding group had significantly lower SMI-to-BMI ratio (1.71 ± 0.16) than the no-bleeding group (2.10 ± 0.23) (p < 0.001). Among these three parameters, SMI-to-BMI ratio had the highest area under the curve value in their receiver operating characteristic curves (0.73 for BMI, 0.59 for SMI, 0.92 for SMI-to-BMI ratio). Furthermore, on multivariate analysis, SMI-to-BMI ratio was an independent risk factor for post-surgical bleeding (hazard ratio, 38.4; 95% confidence interval, 13.9-136.2; p < 0.001).

CONCLUSIONS

SMI-to-BMI ratio is a superior predictive factor of post-surgical bleeding after mastectomy to either BMI or SMI alone.

Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice

Breast ultrasound (US) has undergone dramatic technological improvement through recent decades, moving from a low spatial resolution, grayscale-limited technique to a highly performing, multiparametric modality. In this review, we first focus on the spectrum of technical tools that have become commercially available, including new microvasculature imaging modalities, high-frequency transducers, extended field-of-view scanning, elastography, contrast-enhanced US, MicroPure, 3D US, automated US, S-Detect, nomograms, images fusion, and virtual navigation. In the subsequent section, we discuss the broadened current application of US in breast clinical scenarios, distinguishing among primary US, complementary US, and second-look US. Finally, we mention the still ongoing limitations and the challenging aspects of breast US.