Ovarian cancer ascites induces skeletal muscle wasting in vitro and reflects sarcopenia in patients

Muscle weakness and mitochondrial stress occur before metastasis in a novel mouse model of ovarian cancer cachexia

Objectives

A high proportion of women with advanced epithelial ovarian cancer (EOC) experience weakness and cachexia. This relationship is associated with increased morbidity and mortality. EOC is the most lethal gynecological cancer, yet no preclinical cachexia model has demonstrated the combined hallmark features of metastasis, ascites development, muscle loss and weakness in adult immunocompetent mice.

Methods

Here, we evaluated a new model of ovarian cancer-induced cachexia with the advantages of inducing cancer in adult immunocompetent C57BL/6J mice through orthotopic injections of EOC cells in the ovarian bursa. We characterized the development of metastasis, ascites, muscle atrophy, muscle weakness, markers of inflammation, and mitochondrial stress in the tibialis anterior (TA) and diaphragm ~45, ~75 and ~90 days after EOC injection.

Results

Primary ovarian tumour sizes were progressively larger at each time point while robust metastasis, ascites development, and reductions in body, fat and muscle weights occurred by 90 Days. There were no changes in certain inflammatory (TNFα), atrogene (MURF1 and Atrogin) or GDF15 markers within both muscles whereas IL-6 was increased at 45 and 90 Day groups in the diaphragm. TA weakness in 45 Day preceded atrophy and metastasis that were observed later (75 and 90 Day, respectively). The diaphragm demonstrated both weakness and atrophy in 45 Day. In both muscles, this pre-metastatic muscle weakness corresponded with considerable reprogramming of gene pathways related to mitochondrial bioenergetics as well as reduced functional measures of mitochondrial pyruvate oxidation and creatine-dependent ADP/ATP cycling as well as increased reactive oxygen species emission (hydrogen peroxide). Remarkably, muscle force per unit mass at 90 days was partially restored in the TA despite the presence of atrophy and metastasis. In contrast, the diaphragm demonstrated progressive weakness. At this advanced stage, mitochondrial pyruvate oxidation in both muscles exceeded control mice suggesting an apparent metabolic super-compensation corresponding with restored indices of creatine-dependent adenylate cycling.

Conclusion

This mouse model demonstrates the concurrent development of cachexia and metastasis that occurs in women with EOC. The model provides physiologically relevant advantages of inducing tumour development within the ovarian bursa in immunocompetent adult mice. Moreover, the model reveals that muscle weakness in both TA and diaphragm precedes metastasis while weakness also precedes atrophy in the TA. An underlying mitochondrial bioenergetic stress corresponded with this early weakness. Collectively, these discoveries can direct new research towards the development of therapies that target pre-atrophy and pre-metastatic weakness during EOC in addition to therapies targeting cachexia.

Mechanisms of Ovarian Cancer-Associated Cachexia

Cancer-associated cachexia occurs in 50% to 80% of cancer patients and is responsible for 20% to 30% of cancer-related deaths. Cachexia limits survival and treatment outcomes, and is a major contributor to morbidity and mortality during cancer. Ovarian cancer is one of the leading causes of cancer-related deaths in women, and recent studies have begun to highlight the prevalence and clinical impact of cachexia in this population. Here, we review the existing understanding of cachexia pathophysiology and summarize relevant studies assessing ovarian cancer-associated cachexia in clinical and preclinical studies. In clinical studies, there is increased evidence that reduced skeletal muscle mass and quality associate with worse outcomes in subjects with ovarian cancer. Mouse models of ovarian cancer display cachexia, often characterized by muscle and fat wasting alongside inflammation, although they remain underexplored relative to other cachexia-associated cancer types. Certain soluble factors have been identified and successfully targeted in these models, providing novel therapeutic targets for mitigating cachexia during ovarian cancer. However, given the relatively low number of studies, the translational relevance of these findings is yet to be determined and requires more research. Overall, our current understanding of ovarian cancer-associated cachexia is insufficient and this review highlights the need for future research specifically aimed at exploring mechanisms of ovarian cancer-associated cachexia by using unbiased approaches and animal models representative of the clinical landscape of ovarian cancer.

Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer

BACKGROUND

Skeletal muscle loss during treatment is associated with poor survival outcomes in patients with ovarian cancer. Although changes in muscle mass can be assessed on computed tomography (CT) scans, this labour-intensive process can impair its utility in clinical practice. This study aimed to develop a machine learning (ML) model to predict muscle loss based on clinical data and to interpret the ML model by applying SHapley Additive exPlanations (SHAP) method.

METHODS

This study included the data of 617 patients with ovarian cancer who underwent primary debulking surgery and platinum-based chemotherapy at a tertiary centre between 2010 and 2019. The cohort data were split into training and test sets based on the treatment time. External validation was performed using 140 patients from a different tertiary centre. The skeletal muscle index (SMI) was measured from pre- and post-treatment CT scans, and a decrease in SMI ≥ 5% was defined as muscle loss. We evaluated five ML models to predict muscle loss, and their performance was determined using the area under the receiver operating characteristic curve (AUC) and F1 score. The features for analysis included demographic and disease-specific characteristics and relative changes in body mass index (BMI), albumin, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). The SHAP method was applied to determine the importance of the features and interpret the ML models.

RESULTS

The median (inter-quartile range) age of the cohort was 52 (46-59) years. After treatment, 204 patients (33.1%) experienced muscle loss in the training and test datasets, while 44 (31.4%) patients experienced muscle loss in the external validation dataset. Among the five evaluated ML models, the random forest model achieved the highest AUC (0.856, 95% confidence interval: 0.854-0.859) and F1 score (0.726, 95% confidence interval: 0.722-0.730). In the external validation, the random forest model outperformed all ML models with an AUC of 0.874 and an F1 score of 0.741. The results of the SHAP method showed that the albumin change, BMI change, malignant ascites, NLR change, and PLR change were the most important factors in muscle loss. At the patient level, SHAP force plots demonstrated insightful interpretation of our random forest model to predict muscle loss.

CONCLUSIONS

Explainable ML model was developed using clinical data to identify patients experiencing muscle loss after treatment and provide information of feature contribution. Using the SHAP method, clinicians may better understand the contributors to muscle loss and target interventions to counteract muscle loss.

Association of malignant ascites with systemic inflammation and muscle loss after treatment in advanced-stage ovarian cancer

BACKGROUND

Malignant ascites is prevalent in advanced-stage ovarian cancer and may facilitate identification of the drivers of muscle loss. This study aimed to evaluate the association of ascites with changes in systemic inflammation and muscle after treatment of advanced-stage ovarian cancer.

METHODS

We evaluated 307 patients with advanced-stage (III/IVA) ovarian cancer who underwent primary debulking surgery and adjuvant platinum-based chemotherapy between 2010 and 2019. The changes in skeletal muscle index (SMI) and radiodensity (SMD) were measured using pre-surgery and post-chemotherapy portal-venous phase contrast-enhanced computed tomography scans at L3. Systemic inflammation was measured using albumin levels, prognostic nutritional index (PNI), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR). Primary endpoint was the changes in SMI and SMD after treatment. Linear regression analysis was used to test associations between muscle change and other covariates. Mediation analysis was used to determine the mediator.

RESULTS

The median (range) age was 53 (23-83) years. The median duration (range) of follow-up was 5.2 (1.1-11.3) years. Overall, 187 (60.9%) patients had ascites. The changes in muscle and systemic inflammatory markers after treatment were significantly different between patients with and without ascites (SMI: -3.9% vs. 2.2%, P < 0.001; SMD: -4.0% vs. -0.4%, P < 0.001; albumin: -4.4% vs. 2.1%, P < 0.001; PNI: -8.4% vs. -0.1%, P < 0.001; NLR: 20.6% vs. -29.4%, P < 0.001; and PLR: 1.7% vs. -19.4%, P < 0.001). The changes in SMI and SMD were correlated with the changes in albumin, PNI, NLR, and PLR (all P < 0.001). In multiple linear regression, ascites and NLR changes were negatively while albumin change was positively correlated with SMI change (ascites: β = -3.19, P < 0.001; NLR change: β = -0.02, P = 0.003; albumin change: β = 0.37, P < 0.001). Ascites and NLR changes were negatively while PNI change was positively correlated with SMD change (ascites: β = -1.28, P = 0.02; NLR change: β = -0.02, P < 0.001; PNI change: β = 0.11, P = 0.04). In mediation analysis, ascites had a direct effect on SMI change (P < 0.001) and an indirect effect mediated by NLR change (indirect effects = -1.61, 95% confidence interval [CI]: -2.22 to -1.08) and albumin change (indirect effects = -2.92, 95% CI: -4.01 to -1.94). Ascites had a direct effect on SMD change (P < 0.001) and an indirect effect mediated by NLR change (indirect effects = -1.76, 95% CI: -2.34 to -1.22) and PNI change (indirect effects = -2.00, 95% CI: -2.79 to -1.36).

CONCLUSIONS

Malignant ascites was associated with enhanced systemic inflammation and muscle loss after primary debulking surgery and adjuvant chemotherapy in advanced-stage ovarian cancer. The association between ascites and muscle loss may be mediated by systemic inflammation.

Whole-Body Composition Features by Computed Tomography in Ovarian Cancer: Pilot Data on Survival Correlations

BACKGROUND

The primary objective of this study was to assess the associations of computed tomography (CT)-based whole-body composition values with overall survival (OS) and progression-free survival (PFS) in epithelial ovarian cancer (EOC) patients. The secondary objective was the association of body composition with chemotherapy-related toxicity.

METHODS

Thirty-four patients (median age 64.9 years; interquartile range 55.4-75.4) with EOC and thorax and abdomen CT scans were included. Clinical data recorded: age; weight; height; stage; chemotherapy-related toxicity; and date of last contact, progression and death. Automatic extraction of body composition values was performed by dedicated software. Sarcopenia was defined according to predefined cutoffs. Statistical analysis included univariate tests to investigate associations of sarcopenia and body composition with chemotoxicity. Association of body composition parameters and OS/PFS was evaluated by log-rank test and Cox proportional hazard model. Multivariate models were adjusted for FIGO stage and/or age at diagnosis.

RESULTS

We found significant associations of skeletal muscle volume with OS (p = 0.04) and PFS (p = 0.04); intramuscular fat volume with PFS (p = 0.03); and visceral adipose tissue, epicardial and paracardial fat with PFS (p = 0.04, 0.01 and 0.02, respectively). We found no significant associations between body composition parameters and chemotherapy-related toxicity.

CONCLUSIONS

In this exploratory study, we found significant associations of whole-body composition parameters with OS and PFS. These results open a window to the possibility to perform body composition profiling without approximate estimations.

Association of prognostic nutritional index with muscle loss and survival in patients with ovarian cancer treated with primary debulking surgery and chemotherapy

PURPOSE

Sarcopenia is prevalent in ovarian cancer and contributes to poor survival. This study is aimed at investigating the association of prognostic nutritional index (PNI) with muscle loss and survival outcomes in patients with ovarian cancer.

METHODS

This retrospective study analyzed 650 patients with ovarian cancer treated with primary debulking surgery and adjuvant platinum-based chemotherapy at a tertiary center from 2010 to 2019. PNI-low was defined as a pretreatment PNI of < 47.2. Skeletal muscle index (SMI) was measured on pre- and posttreatment computed tomography (CT) at L3. The cut-off for the SMI loss associated with all-cause mortality was calculated using maximally selected rank statistics.

RESULTS

The median follow-up was 4.2 years, and 226 deaths (34.8%) were observed. With a median duration of 176 days (interquartile range: 166-187) between CT scans, patients experienced an average decrease in SMI of 1.7% (P < 0.001). The cut-off for SMI loss as a predictor of mortality was - 4.2%. PNI-low was independently associated with SMI loss (odds ratio: 1.97, P = 0.001). On multivariable analysis of all-cause mortality, PNI-low and SMI loss were independently associated with all-cause mortality (hazard ratio: 1.43, P = 0.017; hazard ratio: 2.27, P < 0.001, respectively). Patients with both SMI loss and PNI-low (vs. neither) had triple the risk of all-cause mortality (hazard ratio: 3.10, P < 0.001).

CONCLUSIONS

PNI is a predictor of muscle loss during treatment for ovarian cancer. PNI and muscle loss are additively associated with poor survival. PNI can help clinicians guide multimodal interventions to preserve muscle and optimize survival outcomes.

DUSP1 promotes muscle atrophy by inhibiting myocyte differentiation in cachectic patients

BACKGROUND

Skeletal muscle atrophy is the major hallmark of cancer cachexia. The mechanisms underlying muscle wasting remain elusive in cachectic patients. Our research seeks to identify differentially expressed genes (DEGs) between non-cachectic and cachectic cancer patients and elucidate their functions.

METHODS

We screened the DEGs of skeletal muscle between patients with and without cachexia from microarray data. Biological function of DEGs is analyzed through gene enrichment analysis, while an interaction network is constructed to visualize how genes are related. A Spearman's correlation analysis demonstrated the clinical significance of DUSP1 related to cancer cachexia. Skeletal muscle samples were collected and histomorphology studies were conducted. Function of DUSP1 on myogenesis was clarified by qPCR, western blotting, and immunofluorescence.

RESULTS

We screened 324 DEGs in skeletal muscle from patients with and without cachexia. The results of the gene enrichment analysis indicated that inflammatory cytokines and immune responses contribute significantly to the pathological condition of cachexia. DUSP1 was one of the key genes in the regulating network. DUSP1 protein and mRNA levels were increased significantly in skeletal muscle tissues from patients with cancer cachexia. DUSP1 expression in cachectic group was found to have negative correlation with SMA, prealbumin and BMI and positive correlation with TNFα, IL6 and weight loss. Significant changes of myogenesis related genes were observed in myocyte after DUSP1 was overexpressed and knocked down.

CONCLUSION

In skeletal muscle of cachectic patients, DUSP1 expression was observed to be higher and thus DUSP1 promote muscle atrophy by inhibiting myogenesis. DUSP1 is expected to be a specific target in cancer cachexia for preventing and treating muscle atrophy.