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Aichi M, Hasegawa S, Shinoda S, Suzuki Y, Kamiya N, Ishidera Y, Imai Y, Miyagi E, Mizushima T. Sarcopenia shortens overall survival of patients with platinum-resistant recurrent ovarian cancer: inverse probability of treatment-weighting analysis. Int J Gynecol Cancer 2024:ijgc-2024-005323. [PMID: 39107046 DOI: 10.1136/ijgc-2024-005323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2024] Open
Abstract
OBJECTIVE The association between sarcopenia and prognosis in patients with platinum-resistant recurrent ovarian cancer remains unclear. This study investigated whether sarcopenia is a prognostic factor in patients with platinum-resistant recurrent ovarian cancer. METHODS A total of 52 patients diagnosed with platinum-resistant recurrent ovarian cancer who had undergone non-platinum chemotherapy at our institution formed our study population. Body composition and clinicopathological data of these patients were collected retrospectively. Abdominal computed tomography (CT) scans obtained at the time of platinum-resistant recurrent ovarian cancer diagnosis were used to measure the cross-sectional area of skeletal muscles at L3 level. These values were corrected for height to calculate the skeletal muscle index, and accordingly sarcopenia was defined. Overall survival was defined as the primary outcome of the study. The impact of sarcopenia on overall survival was assessed using Cox proportional hazards regression models with inverse probability weighting of treatment based on propensity scores and log-rank tests. RESULTS The median patient age was 63 years (IQR: 53-71). The most common International Federation of Gynecology and Obstetrics (FIGO) 2018 stage was stage III (50%) and the most common histology was serous or adenocarcinoma (67.3%). The optimal cut-off value of skeletal muscle index was 35.6 cm2/m2, which was calculated using the data of 21 patients with sarcopenia and 31 without sarcopenia. Sarcopenia was significantly associated with shorter overall survival (HR 1.93; 95% CI 1.06-3.49; p=0.03). Subgroup analysis based on patient attributes and prognostic factors suggested a consistent prognostic impact of sarcopenia. Sarcopenia was identified as a significant risk factor, particularly in patients who had higher CA125 levels (HR, 2.47; 95% CI, 1.07 to 5.69; p=0.034) and a higher neutrophil-to-lymphocyte ratio (HR, 2.92; 95% CI, 1.02 to 8.31; p=0.045). CONCLUSION Sarcopenia significantly shortened the overall survival of patients with platinum-resistant recurrent ovarian cancer.
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Affiliation(s)
- Masahiro Aichi
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Sho Hasegawa
- Gastroenterology and Hepatology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Satoru Shinoda
- Department of Biostatistics, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Yukio Suzuki
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Natsuko Kamiya
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Yumi Ishidera
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Yuichi Imai
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Etsuko Miyagi
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
| | - Taichi Mizushima
- Department of Obstetrics and Gynecology, Yokohama City University School of Medicine Graduate School of Medicine, Yokohama, Japan
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Lin WC, Weng CS, Ko AT, Jan YT, Lin JB, Wu KP, Lee J. Interpretable machine learning model based on clinical factors for predicting muscle radiodensity loss after treatment in ovarian cancer. Support Care Cancer 2024; 32:544. [PMID: 39046568 DOI: 10.1007/s00520-024-08757-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 07/21/2024] [Indexed: 07/25/2024]
Abstract
PURPOSE Muscle radiodensity loss after surgery and adjuvant chemotherapy is associated with poor outcomes in ovarian cancer. Assessing muscle radiodensity is a real-world clinical challenge owing to the requirement for computed tomography (CT) with consistent protocols and labor-intensive processes. This study aimed to use interpretable machine learning (ML) to predict muscle radiodensity loss. METHODS This study included 723 patients with ovarian cancer who underwent primary debulking surgery and platinum-based chemotherapy between 2010 and 2019 at two tertiary centers (579 in cohort 1 and 144 in cohort 2). Muscle radiodensity was assessed from pre- and post-treatment CT acquired with consistent protocols, and a decrease in radiodensity ≥ 5% was defined as loss. Six ML models were trained, and their performances were evaluated using the area under the curve (AUC) and F1-score. The SHapley Additive exPlanations (SHAP) method was applied to interpret the ML models. RESULTS The CatBoost model achieved the highest AUC of 0.871 (95% confidence interval, 0.870-0.874) and F1-score of 0.688 (95% confidence interval, 0.685-0.691) among the models in the training set and outperformed in the external validation set, with an AUC of 0.839 and F1-score of 0.673. Albumin change, ascites, and residual disease were the most important features associated with a higher likelihood of muscle radiodensity loss. The SHAP force plot provided an individualized interpretation of model predictions. CONCLUSION An interpretable ML model can assist clinicians in identifying ovarian cancer patients at risk of muscle radiodensity loss after treatment and understanding the contributors of muscle radiodensity loss.
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Affiliation(s)
- Wan-Chun Lin
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Li-Nong St., Beitou District, Taipei, 112304, Taiwan
| | - Chia-Sui Weng
- Department of Obstetrics and Gynecology, MacKay Memorial Hospital, Taipei, Taiwan
- Department of Medicine, MacKay Medical College, New Taipei City, Taiwan
| | - Ai-Tung Ko
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Li-Nong St., Beitou District, Taipei, 112304, Taiwan
| | - Ya-Ting Jan
- Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan
| | - Jhen-Bin Lin
- Department of Radiation Oncology, Changhua Christian Hospital, Changhua, Taiwan
| | - Kun-Pin Wu
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Li-Nong St., Beitou District, Taipei, 112304, Taiwan.
| | - Jie Lee
- Department of Medicine, MacKay Medical College, New Taipei City, Taiwan.
- Department of Radiation Oncology, MacKay Memorial Hospital, 92, Section 2, Chung Shan North Road, Taipei, 104217, Taiwan.
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Delfinis LJ, Ogilvie LM, Khajehzadehshoushtar S, Gandhi S, Garibotti MC, Thuhan AK, Matuszewska K, Pereira M, Jones RG, Cheng AJ, Hawke TJ, Greene NP, Murach KA, Simpson JA, Petrik J, Perry CG. Muscle weakness and mitochondrial stress occur before metastasis in a novel mouse model of ovarian cancer cachexia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.08.588639. [PMID: 38645227 PMCID: PMC11030380 DOI: 10.1101/2024.04.08.588639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
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.
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Affiliation(s)
- Luca J. Delfinis
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
| | - Leslie M. Ogilvie
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada
| | | | - Shivam Gandhi
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
| | - Madison C. Garibotti
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
| | - Arshdeep K. Thuhan
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
| | - Kathy Matuszewska
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada
| | - Madison Pereira
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada
| | - Ronald G. Jones
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, USA
| | - Arthur J. Cheng
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
| | - Thomas J. Hawke
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Nicholas P. Greene
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, USA
| | - Kevin A. Murach
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, USA
| | - Jeremy A. Simpson
- Department of Human Health and Nutritional Sciences, University of Guelph, Guelph, ON, Canada
| | - Jim Petrik
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada
| | - Christopher G.R. Perry
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, ON, Canada
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Callaway CS, Mouchantat LM, Bitler BG, Bonetto A. Mechanisms of Ovarian Cancer-Associated Cachexia. Endocrinology 2023; 165:bqad176. [PMID: 37980602 PMCID: PMC10699881 DOI: 10.1210/endocr/bqad176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/02/2023] [Accepted: 11/15/2023] [Indexed: 11/21/2023]
Abstract
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.
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Affiliation(s)
- Chandler S Callaway
- Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Lila M Mouchantat
- Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Benjamin G Bitler
- Department of Obstetrics & Gynecology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Comprehensive Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Andrea Bonetto
- Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Comprehensive Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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Hsu W, Ko A, Weng C, Chang C, Jan Y, Lin J, Chien H, Lin W, Sun F, Wu K, Lee J. Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer. J Cachexia Sarcopenia Muscle 2023; 14:2044-2053. [PMID: 37435785 PMCID: PMC10570082 DOI: 10.1002/jcsm.13282] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 03/30/2023] [Accepted: 05/22/2023] [Indexed: 07/13/2023] Open
Abstract
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.
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Affiliation(s)
- Wen‐Han Hsu
- Institute of Biomedical InformaticsNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
| | - Ai‐Tung Ko
- Institute of Biomedical InformaticsNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
| | - Chia‐Sui Weng
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
| | - Chih‐Long Chang
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
| | - Ya‐Ting Jan
- Department of RadiologyMacKay Memorial HospitalTaipeiTaiwan
| | - Jhen‐Bin Lin
- Department of Radiation OncologyChanghua Christian HospitalChanghuaTaiwan
| | - Hung‐Ju Chien
- Department of Obstetrics and GynecologyChanghua Christian HospitalTaipeiTaiwan
| | - Wan‐Chun Lin
- Institute of Biomedical InformaticsNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
| | - Fang‐Ju Sun
- Institute of Biomedical InformaticsNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
- Department of Medical ResearchMacKay Memorial HospitalTaipeiTaiwan
| | - Kun‐Pin Wu
- Institute of Biomedical InformaticsNational Yang Ming Chiao Tung UniversityTaipeiTaiwan
| | - Jie Lee
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
- Department of Radiation OncologyMacKay Memorial HospitalTaipeiTaiwan
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Weng C, Huang W, Chang C, Jan Y, Chen T, Lee J. Association of malignant ascites with systemic inflammation and muscle loss after treatment in advanced-stage ovarian cancer. J Cachexia Sarcopenia Muscle 2023; 14:2114-2125. [PMID: 37503876 PMCID: PMC10570096 DOI: 10.1002/jcsm.13289] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 04/23/2023] [Accepted: 05/22/2023] [Indexed: 07/29/2023] Open
Abstract
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.
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Affiliation(s)
- Chia‐Sui Weng
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
| | - Wan‐Chun Huang
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
| | - Chih‐Long Chang
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
| | - Ya‐Ting Jan
- Department of RadiologyMacKay Memorial HospitalTaipeiTaiwan
| | - Tze‐Chien Chen
- Department of Obstetrics and GynecologyMacKay Memorial HospitalTaipeiTaiwan
| | - Jie Lee
- Department of MedicineMacKay Medical CollegeNew Taipei CityTaiwan
- Department of Radiation OncologyMacKay Memorial HospitalTaipeiTaiwan
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Raia G, Del Grande M, Colombo I, Nerone M, Manganaro L, Gasparri ML, Papadia A, Del Grande F, Rizzo S. Whole-Body Composition Features by Computed Tomography in Ovarian Cancer: Pilot Data on Survival Correlations. Cancers (Basel) 2023; 15:2602. [PMID: 37174067 PMCID: PMC10177066 DOI: 10.3390/cancers15092602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
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.
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Affiliation(s)
- Giorgio Raia
- Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland; (G.R.); (F.D.G.)
| | - Maria Del Grande
- Service of Medical Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6500 Bellinzona, Switzerland; (M.D.G.); (I.C.); (M.N.)
| | - Ilaria Colombo
- Service of Medical Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6500 Bellinzona, Switzerland; (M.D.G.); (I.C.); (M.N.)
| | - Marta Nerone
- Service of Medical Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale (EOC), 6500 Bellinzona, Switzerland; (M.D.G.); (I.C.); (M.N.)
| | - Lucia Manganaro
- Department of Radiological, Oncological and Pathological Sciences, University of Rome Sapienza (IT), 00185 Roma, Italy;
| | - Maria Luisa Gasparri
- Department of Gynecology and Obstetrics, Ente Ospedaliero Cantonale of Lugano (EOC), 6900 Lugano, Switzerland; (M.L.G.); (A.P.)
| | - Andrea Papadia
- Department of Gynecology and Obstetrics, Ente Ospedaliero Cantonale of Lugano (EOC), 6900 Lugano, Switzerland; (M.L.G.); (A.P.)
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana, 6900 Lugano, Switzerland
| | - Filippo Del Grande
- Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland; (G.R.); (F.D.G.)
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana, 6900 Lugano, Switzerland
| | - Stefania Rizzo
- Istituto di Imaging della Svizzera Italiana (IIMSI), Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland; (G.R.); (F.D.G.)
- Facoltà di Scienze Biomediche, Università della Svizzera Italiana, 6900 Lugano, Switzerland
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8
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Lee J, Weng CS, Chang CL, Hsu WH, Jan YT, Wu KP. Association of prognostic nutritional index with muscle loss and survival in patients with ovarian cancer treated with primary debulking surgery and chemotherapy. Support Care Cancer 2023; 31:267. [PMID: 37058264 DOI: 10.1007/s00520-023-07719-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 03/31/2023] [Indexed: 04/15/2023]
Abstract
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.
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Affiliation(s)
- Jie Lee
- Department of Radiation Oncology, MacKay Memorial Hospital, Taipei, Taiwan.
- Department of Medicine, MacKay Medical College, New Taipei City, Taiwan.
| | - Chia-Sui Weng
- Department of Medicine, MacKay Medical College, New Taipei City, Taiwan
- Department of Obstetrics and Gynecology, MacKay Memorial Hospital, Taipei, Taiwan
| | - Chih-Long Chang
- Department of Medicine, MacKay Medical College, New Taipei City, Taiwan
- Department of Obstetrics and Gynecology, MacKay Memorial Hospital, Taipei, Taiwan
| | - Wen-Han Hsu
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ya-Ting Jan
- Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan
| | - Kun-Pin Wu
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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Sui X, Mao X, Wu G, Meng Q. DUSP1 promotes muscle atrophy by inhibiting myocyte differentiation in cachectic patients. Front Oncol 2022; 12:1040112. [PMID: 36387242 PMCID: PMC9663480 DOI: 10.3389/fonc.2022.1040112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/03/2022] [Indexed: 01/07/2024] Open
Abstract
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.
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Affiliation(s)
| | - Xiangyu Mao
- Department of General Surgery, Zhongshan Hospital of Fudan University, Shanghai, China
| | - Guohao Wu
- Department of General Surgery, Zhongshan Hospital of Fudan University, Shanghai, China
| | - Qingyang Meng
- Department of General Surgery, Zhongshan Hospital of Fudan University, Shanghai, China
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