Salivary Interleukin-13 and Transforming Growth Factor Beta as Potential Biomarkers of Cancer Cachexia.

Cancer cachexia is a syndrome characterized by weight and muscle loss and functional impairment, strongly influencing survival in cancer patients. In this study, we aimed to establish the role of saliva cytokine measurement in cancer cachexia investigation and define two potential independent salivary biomarkers of the condition. METHODS: serum and saliva specimens were obtained from 78 patients. Forty-six patients were non-cachectic, and 32 patients were cachectic (per SCRINIO group criteria), all with metastatic solid tumors. Commercial ELISA kits were used to determine the salivary and serum concentrations of interleukin 13 (IL-13) and transforming growth factor beta (TGF-ß) in two patient groups and healthy controls. Laboratory values were obtained from the hospital information system, and weight and height were measured at the time of sampling. RESULTS: A statistically significant difference was observed between the groups in saliva IL-13 concentrations but no difference in serum concentrations. Statistically significant differences were also observed between the groups in saliva and serum concentrations of TGF-ß. Logistic regression analysis has identified salivary IL-13 and TGF-ß as independent factors for cancer cachexia. CONCLUSIONS: We demonstrated saliva as a valuable specimen for cachexia investigation and established IL-13 and TGF-ß as potential cancer cachexia biomarkers. Further research is needed to evaluate these findings.

Efficacy and safety of pharmacotherapy for cancer cachexia: A systematic review and network meta-analysis.

BACKGROUND: Cancer cachexia affects more than half of all cancer patients, reducing survival rates. Evidence-based approaches are urgently needed to optimize treatment. METHODS: A systematic review and network meta-analysis were conducted to assess the effectiveness and safety of different pharmacotherapies for cancer cachexia. Three databases (PubMed, Cochrane Library, and Web of Science) were searched for the period from January 1, 2000, to March 20, 2024. The netmeta package in R software was used to calculate the pooled effect, employing a random effects model. RESULTS: Seven placebo-controlled randomized trials involving 1421 patients were analyzed. Pairwise analysis showed that body weight increases were 4.6 kg (95% confidence interval [CI] 0.83-8.37 kg) for olanzapine, 3.82 kg (95% CI 0.73-6.91 kg) for espindolol (20 mg), 2.36 kg (95% CI 1.84-2.89 kg) for anamorelin (100 mg), and 1.31 kg (95% CI 0.42-2.19 kg) for anamorelin (50 mg). In terms of safety profiles, olanzapine demonstrated the lowest odds ratio when compared to placebo, at 0.26 (95% CI 0.07-0.94), followed by anamorelin (50 mg) at 0.86 (95% CI 0.30-2.48), and anamorelin (100 mg) at 0.89 (95% CI 0.42-1.88). However, network meta-analysis could not confirm the superiority of olanzapine over anamorelin in terms of efficacy and safety. CONCLUSION: Both olanzapine and anamorelin are useful in improving body weight in patients with cancer cachexia. Personalization may be helpful for different patients.

Inter-organ cross-talk in human cancer cachexia revealed by spatial metabolomics.

BACKGROUND: Cancer cachexia (CCx) presents a multifaceted challenge characterized by negative protein and energy balance and systemic inflammatory response activation. While previous CCx studies predominantly focused on mouse models or human body fluids, there's an unmet need to elucidate the molecular inter-organ cross-talk underlying the pathophysiology of human CCx. METHODS: Spatial metabolomics were conducted on liver, skeletal muscle, subcutaneous and visceral adipose tissue, and serum from cachectic and control cancer patients. Organ-wise comparisons were performed using component, pathway enrichment and correlation network analyses. Inter-organ correlations in CCx altered pathways were assessed using Circos. Machine learning on tissues and serum established classifiers as potential diagnostic biomarkers for CCx. RESULTS: Distinct metabolic pathway alteration was detected in CCx, with adipose tissues and liver displaying the most significant (P ≤ 0.05) metabolic disturbances. CCx patients exhibited increased metabolic activity in visceral and subcutaneous adipose tissues and liver, contrasting with decreased activity in muscle and serum compared to control patients. Carbohydrate, lipid, amino acid, and vitamin metabolism emerged as highly interacting pathways across different organ systems in CCx. Muscle tissue showed decreased (P ≤ 0.001) energy charge in CCx patients, while liver and adipose tissues displayed increased energy charge (P ≤ 0.001). We stratified CCx patients by severity and metabolic changes, finding that visceral adipose tissue is most affected, especially in cases of severe cachexia. Morphometric analysis showed smaller (P ≤ 0.05) adipocyte size in visceral adipose tissue, indicating catabolic processes. We developed tissue-based classifiers for cancer cachexia specific to individual organs, facilitating the transfer of patient serum as minimally invasive diagnostic markers of CCx in the constitution of the organs. CONCLUSIONS: These findings support the concept of CCx as a multi-organ syndrome with diverse metabolic alterations, providing insights into the pathophysiology and organ cross-talk of human CCx. This study pioneers spatial metabolomics for CCx, demonstrating the feasibility of distinguishing cachexia status at the organ level using serum.

Towards a fully automatic workflow for investigating the dynamics of lung cancer cachexia during radiotherapy using cone beam computed tomography.

OBJECTIVE: Cachexia is a devastating condition, characterized by involuntary loss of muscle mass with or without loss of adipose tissue mass. It affects more than half of patients with lung cancer, diminishing treatment effects and increasing mortality. Cone-beam computed tomography (CBCT) images, routinely acquired during radiotherapy treatment, might contain valuable anatomical information for monitoring body composition changes associated with cachexia. For this purpose, we propose an automatic artificial intelligence (AI)-based workflow, consisting of CBCT to CT conversion, followed by segmentation of pectoralis muscles. Approach. Data from 140 stage III non-small cell lung cancer patients was used. Two deep learning models, cycle-consistent generative adversarial network (CycleGAN) and contrastive unpaired translation (CUT), were used for unpaired training of CBCT to CT conversion, to generate synthetic CT (sCT) images. The no-new U-Net (nnU-Net) model was used for automatic pectoralis muscle segmentation. To evaluate tissue segmentation performance in the absence of ground truth labels, an uncertainty metric (UM) based on Monte Carlo dropout was developed and validated. Main results. Both CycleGAN and CUT restored the Hounsfield unit fidelity of the CBCT images compared to the planning CT (pCT) images and visually reduced streaking artefacts. The nnU-Net model achieved a Dice Similarity Coefficient (DSC) of 0.93, 0.94, 0.92 for the CT, sCT and CBCT images, respectively, on an independent test set. The UM showed a high correlation with DSC with a correlation coefficient of -0.84 for the pCT dataset and -0.89 for the sCT dataset. Significance. This paper shows a proof-of-concept for automatic AI-based monitoring of the pectoralis muscle area of lung cancer patients during radiotherapy treatment based on CBCT images, which provides an unprecedented time resolution of muscle mass loss during cachexia progression. Ultimately, the proposed workflow could provide valuable information for early intervention of cachexia, ideally resulting in improved cancer treatment outcome.

A comprehensive review of animal models for cancer cachexia: Implications for translational research.

Cancer cachexia is a multifactorial syndrome characterized by progressive weight loss and a disease process that nutritional support cannot reverse. Although progress has been made in preclinical research, there is still a long way to go in translating research findings into clinical practice. One of the main reasons for this is that existing preclinical models do not fully replicate the conditions seen in clinical patients. Therefore, it is important to understand the characteristics of existing preclinical models of cancer cachexia and pay close attention to the latest developments in preclinical models. The main models of cancer cachexia used in current research are allogeneic and xenograft models, genetically engineered mouse models, chemotherapy drug-induced models, Chinese medicine spleen deficiency models, zebrafish and Drosophila models, and cellular models. This review aims to revisit and summarize the commonly used animal models of cancer cachexia by evaluating existing preclinical models, to provide tools and support for translational medicine research.

Machine learning to identify precachexia and cachexia: a multicenter, retrospective cohort study.

BACKGROUND: Detection of precachexia is important for the prevention and treatment of cachexia. However, how to identify precachexia is still a challenge. OBJECTIVE: This study aimed to detect cancer precachexia using a simple method and distinguish the different characteristics of precachexia and cachexia. METHODS: We included 3896 participants in this study. We used all baseline characteristics as input variables and trained machine learning (ML) models to calculate the importance of the variables. After filtering the variables based on their importance, the models were retrained. The best model was selected based on the receiver operating characteristic value. Subsequently, we used the same method and process to identify patients with precachexia in a noncachexia population using the same method and process. RESULTS: Participants in this study included 2228 men (57.2%) and 1668 women (42.8%), of whom 471 were diagnosed with precachexia, 1178 with cachexia, and the remainder with noncachexia. The most important characteristics of cachexia were eating changes, arm circumference, high-density lipoprotein (HDL) level, and C-reactive protein albumin ratio (CAR). The most important features distinguishing precachexia were eating changes, serum creatinine, HDL, handgrip strength, and CAR. The two logistic regression models for screening for cachexia and diagnosing precachexia had the highest area under the curve values of 0.830 and 0.701, respectively. Calibration and decision curves showed that the models had good accuracy. CONCLUSION: We developed two models for identifying precachexia and cachexia, which will help clinicians detect and diagnose precachexia.

Frequency of weight and body composition increases in advanced non-small cell lung cancer patients during first line therapy.

BACKGROUND: The primary objective of this study was to assess the frequency of body composition increases and their relationships to changes in body weight in two cohorts of real world, treatment-naïve, advanced non-small cell lung cancer (NSCLC) patients. One cohort received the current standard of care (CSOC), which consisted of immunotherapy and newer chemotherapy regimens, and the other cohort was treated with the former standard of care (FSOC), consisting only of older platinum-containing regimens. METHODS: CSOC (n = 106) and FSOC (n = 88) cohorts of advanced NSCLC patients were included in this study. Weights were collected at each clinical visit, and body composition analysis from routine chest computed tomography via automated segmentation software assessed at baseline and at 6 and 12 weeks. Standard statistical methods were used to calculate relationships between changes in weight and in body composition. RESULTS: The CSOC cohort contained 106 stage IV NSCLC patients treated between 16/12/2014 and 22/10/2020 while the FSOC cohort contained 88 stage III/IV NSCLC patients treated between 16/6/2006 and 18/11/2014. While each cohort exhibited decreases in median weight, body mass index (BMI), mean skeletal muscle index (SMI) and subcutaneous adipose tissue index (SATI) at the 6 and 12 week time points, a subset of patients experienced increases in these parameters. Using a threshold of ≥2.5% increase for weight, BMI, SMI, and SATI at the 12 week time point, both cohorts showed similar (20.5% and 27.3%) increases in these parameters. With a cut point of ≥5% increase at 12 weeks follow-up, 8.0% to 25.0% of the patients gained ≥5% in weight, BMI, SMI and SATI. Comparing these results in each cohort showed no significant differences. Pearson coefficients for weight change related to changes in SMI and SATI at 6 and 12 weeks ranged from 0.31 to 0.58 with all P values <0.02. Pearson coefficients for weight change at 12 weeks related to changes in VATI and IMATI ranged from 0.26 to 0.47 with all P values <0.05. Comparison of Pearson coefficients for each cohort showed no significant differences. CONCLUSIONS: Although decreases in median weight, BMI, SMI and SATI were observed in both cohorts, similar percentage of patients in each cohort experienced increases in these parameters. These findings, plus the positive correlations between longitudinal measurements of weight, muscle mass and adipose tissue, indicate that weight gain in these patients involves increases in both muscle mass and adipose tissue. Upon validation, these findings could have implications for clinical trial design and for translational research in cancer cachexia.

Prevalence of and Survival with Cachexia among Patients with Cancer: A Systematic Review and Meta-Analysis.

Cachexia is associated with lower overall survival (OS) in patients with cancer; however, the relationship between the two is reported to differ according to the definitive criteria for diagnosing cachexia. We aimed to investigate 1) the difference in the prevalence of cachexia in patients with cancer and 2) the association between cachexia and OS, depending on the definitive criteria for diagnosing cachexia in patients with cancer. We searched PubMed and Web of Science from their inception until July 31, 2023, to identify eligible studies. We conducted a systematic review of the prevalence of cachexia in patients with cancer and performed a meta-analysis to investigate its relationship with OS. A total of 125 articles comprising 137,960 patients were included in the systematic review, and 26 articles consisting of 11,118 patients underwent meta-analysis. The overall prevalence of cachexia in patients with cancer was 33.0% (95% confidence interval [CI]: 32.8, 33.3); however, it varied according to the definitive criteria for diagnosing cachexia (13.9%-56.5%). According to the Fearon 2011 criteria, the prevalence of cachexia was associated with a high hazard ratio (HR) for OS compared with that of noncachexia [HR: 1.58 (95% CI: 1.45, 1.73)]; according to the other criteria, the HR was 2.78 (95% CI: 1.88, 4.11), indicating significant subgroup differences (P = 0.006). The dose-response curve indicated that the HR for OS plateaued at a cachexia prevalence range of 40%-50% (l-shaped relationship). The prevalence of cachexia in patients with cancer may vary depending on the definitive criteria used to diagnose cachexia. The HR for OS was higher for low cachexia prevalence. The definitive criteria should be carefully considered when assessing cachexia in patients with cancer. This trial was registered at the PROSPERO as CRD42023435474.

Determination of anamorelin concentration in human plasma using a simple high-performance liquid chromatography-ultraviolet detection method.

Anamorelin, a non-peptide ghrelin analog and growth hormone secretagogue, is a novel oral drug used to treat cancer cachexia. Patients with cancer cachexia frequently use several drugs and anamorelin is a substrate of cytochrome P450 (CYP) 3A4; therefore, drug-drug interactions with CYP3A4 inhibitors and inducers pose a clinical problem. In this study, we aimed to determine the concentration of anamorelin in human plasma using a simple high-performance liquid chromatography-ultraviolet (HPLC-UV)-based method. The analysis involved extracting a 200-µL plasma sample and protein precipitation using solid-phase extraction. Anamorelin was isocratically separated using a mobile phase consisting of 0.5% potassium dihydrogen phosphate (pH 4.5) and acetonitrile (61:39, v/v) on a Capcell Pack C18 MG II column (250 mm × 4.6 mm) at a flow rate of 1.0 mL/min and monitored at a detection wavelength of 220 nm. The calibration curve was linear within a plasma concentration range of 12.5-1,500 ng/mL, with a coefficient of determination of 0.9999. The intra- and inter-day coefficients of variation were 0.37-6.71% and 2.05-4.77%, respectively. The accuracy of the assay and recovery were 85.25-112.94% and > 86.58%, respectively. This proposed HPLC-UV method is simple and can be applied in clinical settings.

Family Members' Explanatory Models of Cancer Anorexia-Cachexia.

The experience of bearing witness to the lack of appetite and involuntary weight loss that characterizes cancer anorexia-cachexia syndrome (CACS) is reported to be stressful for family members. Research identifies that family members engage in a wide range of behaviors in response to a relative who shows minimal interest in eating and is literally 'wasting away' before their eyes. Some families, though concerned about the symptoms of CACS, do not dwell excessively on the patient's nutritional intake while others continually harass the patient to eat and petition health care providers for aggressive nutritional interventions to eat in an attempt to stave off further physical deterioration. While studies have detailed how family members respond to a terminally ill relative with CACS, empirical work explicating the explanatory models of CACS that they hold is lacking. Explanatory models (EMs) reflect the beliefs and ideas that families have about why illness and symptoms occur, the extent to which they can be controlled, how they should be treated, and how interventions should be evaluated. To address this gap in the literature, a grounded theory study guided by Kleinman's Explanatory Model questions was conducted with 25 family members of advanced cancer patients. The core category of 'Wayfaring' integrates the key categories of the model and maps onto Kleinman's questions about CACS onset, etiology, natural course, physiological processes/anatomical structures involved, treatment, and the impacts of disease on patient and family. Findings suggest that a divergence between some biomedical constructions of CACS and explanatory models held by family members may fuel the family-health care provider conflict, thereby providing direction for communication with families about care of the patient with anorexia-cachexia.

AWGC2023 cachexia consensus as a valuable tool for predicting prognosis and burden in Chinese patients with cancer.

BACKGROUND: The Asian Working Group for Cachexia (AWGC) proposed the first consensus report on diagnostic criteria for cachexia in Asians in 2023. However, the current consensus lacks cohort evidence to validate its effectiveness and practicality. We aimed to explore the value of the AWGC2023 criteria for predicting the prognosis and medical burden of patients with cancer through a retrospective post hoc cross-sectional analysis of the Investigation on Nutrition Status and its Clinical Outcome of Common Cancers (INSCOC) project in China. METHODS: Cox regression analyses were performed to assess the independent association between cachexia and long-term survival. We utilized C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), inflammatory burden index (IBI), albumin (ALB) and Glasgow prognostic score (GPS) as diagnostic markers for cachexia, designating them as CRP-based cachexia, NLR-based cachexia, IBI-based cachexia, ALB-based cachexia and GPS-based cachexia, respectively. Additionally, we diagnosed cachexia using body mass index (BMI) cutoff values of 18.5, 20, 21 and 22 kg/m2, respectively, and subsequently compared their prognostic predictive value through Harrell's concordance index (C-index). Logistic regression models were used to assess the association between cachexia and medical burden. RESULTS: A total of 5426 patients with cancer were enrolled in this study. Cox regression analysis confirmed that cachexia based on the AWGC2023 criteria was an independent predictor of long-term survival in patients with cancer. Patients with cachexia had significantly poorer long-term survival than patients without cachexia (66.4% vs. 49.7%, P < 0.001). Inflammatory biomarker-based cachexia was as an independent predictor of prognosis in patients with cancer, with inflammatory burden index (IBI)-based cachexia demonstrating the optimal prognostic discriminatory ability. The C-index indicated that cachexia based on BMI cutoff values of 18.5, 20, and 22 kg/m2 did not perform as well as a BMI cutoff value of 21 kg/m2. Logistic regression models revealed that using the AWGC2023 criteria, patients with cachexia had a 16.6% higher risk of prolonged hospitalization and a 16.0% higher risk of high medical expenses than patients without cachexia. CONCLUSION: The AWGC2023 criteria represent a valuable tool for predicting survival and medical burden among Chinese patients with cancer. Encouragement for further validation in other Asian populations is warranted for the AWGC2023 criteria.

Understanding cachexia and its impact on lung cancer and beyond.

Cancer cachexia is a multifactorial syndrome characterized by loss of body weight secondary to skeletal muscle atrophy and adipose tissue wasting. It not only has a significant impact on patients' quality of life but also reduces the effectiveness and tolerability of anticancer therapy, leading to poor clinical outcomes. Lung cancer is a prominent global health concern, and the prevalence of cachexia is high among patients with lung cancer. In this review, we integrate findings from studies of lung cancer and other types of cancer to provide an overview of recent advances in cancer cachexia. Our focus includes topics such as the clinical criteria for diagnosis and staging, the function and mechanism of selected mediators, and potential therapeutic strategies for clinical application. A comprehensive summary of current studies will improve our understanding of the mechanisms underlying cachexia and contribute to the identification of high-risk patients, the development of effective treatment strategies, and the design of appropriate therapeutic regimens for patients at different disease stages.

Role of the sympathetic nervous system in cancer-associated cachexia and tumor progression in tumor-bearing BALB/c mice.

BACKGROUND: Adipose and muscle tissue wasting outlines the cachectic process during tumor progression. The sympathetic nervous system (SNS) is known to promote tumor progression and research suggests that it might also contribute to cancer-associated cachexia (CAC) energetic expenditure through fat wasting. METHODS: We sympathectomized L5178Y-R tumor-bearing male BALB/c mice by intraperitoneally administering 6-hydroxydopamine to evaluate morphometric, inflammatory, and molecular indicators of CAC and tumor progression. RESULTS: Tumor burden was associated with cachexia indicators, including a 10.5% body mass index (BMI) decrease, 40.19% interscapular, 54% inguinal, and 37.17% visceral adipose tissue loss, a 12% food intake decrease, and significant (p = 0.038 and p = 0.0037) increases in the plasmatic inflammatory cytokines IL-6 and IFN-γ respectively. Sympathectomy of tumor-bearing mice was associated with attenuated BMI and visceral adipose tissue loss, decreased interscapular Ucp-1 gene expression to basal levels, and 2.6-fold reduction in Mmp-9 relative gene expression, as compared with the unsympathectomized mice control group. CONCLUSION: The SNS contributes to CAC-associated morphometric and adipose tissue alterations and promotes tumor progression in a murine model.

l-Carnitine relieves cachexia-related skeletal muscle fibrosis by inducing deltex E3 ubiquitin ligase 3L to negatively regulate the Runx2/COL1A1 axis.

BACKGROUND: Cancer cachexia-induced skeletal muscle fibrosis (SMF) impairs muscle regeneration, alters the muscle structure and function, reduces the efficacy of anticancer drugs, diminishes the patient's quality of life and shortens overall survival. RUNX family transcription factor 2 (Runx2), a transcription factor, and collagen type I alpha 1 chain (COL1A1), the principal constituent of SMF, have been linked previously, with Runx2 shown to directly modulate COL1A1 mRNA levels. l-Carnitine, a marker of cancer cachexia, can alleviate fibrosis in liver and kidney models; however, its role in cancer cachexia-associated fibrosis and the involvement of Runx2 in the process remain unexplored. METHODS: Female C57 mice (48 weeks old) were inoculated subcutaneously with MC38 cells to establish a cancer cachexia model. A 5 mg/kg dose of l-carnitine or an equivalent volume of water was administered for 14 days via oral gavage, followed by assessments of muscle function (grip strength) and fibrosis. To elucidate the interplay between the deltex E3 ubiquitin ligase 3L(DTX3L)/Runx2/COL1A1 axis and fibrosis in transforming growth factor beta 1-stimulated NIH/3T3 cells, a suite of molecular techniques, including quantitative real-time PCR, western blot analysis, co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays, were used. The relevance of the DTX3L/Runx2/COL1A1 axis in the gastrocnemius was also explored in the in vivo model. RESULTS: l-Carnitine supplementation reduced cancer cachexia-induced declines in grip strength (>88.2%, P < 0.05) and the collagen fibre area within the gastrocnemius (>57.9%, P < 0.05). At the 5 mg/kg dose, l-carnitine also suppressed COL1A1 and alpha-smooth muscle actin (α-SMA) protein expression, which are markers of SMF and myofibroblasts. Analyses of the TRRUST database indicated that Runx2 regulates both COL1A1 and COL1A2. In vitro, l-carnitine diminished Runx2 protein levels and promoted its ubiquitination. Overexpression of Runx2 abolished the effects of l-carnitine on COL1A1 and α-SMA. Co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays confirmed an interaction between DTX3L and Runx2, with l-carnitine enhancing this interaction to promote Runx2 ubiquitination. l-Carnitine supplementation restored DTX3L levels to those observed under non-cachectic conditions, both in vitro and in vivo. Knockdown of DTX3L abolished the effects of l-carnitine on Runx2, COL1A1 and α-SMA in vitro. The expression of DTX3L was negatively correlated with the levels of Runx2 and COL1A1 in untreated NIH/3T3 cells. CONCLUSIONS: This study revealed a previously unrecognized link between Runx2 and DTX3L in SMF and demonstrated that l-carnitine exerted a significant therapeutic impact on cancer cachexia-associated SMF, potentially through the upregulation of DTX3L.

Metabolic Effects of Ketogenic Diets: Exploring Whole-Body Metabolism in Connection with Adipose Tissue and Other Metabolic Organs.

The ketogenic diet (KD) is characterized by minimal carbohydrate, moderate protein, and high fat intake, leading to ketosis. It is recognized for its efficiency in weight loss, metabolic health improvement, and various therapeutic interventions. The KD enhances glucose and lipid metabolism, reducing triglycerides and total cholesterol while increasing high-density lipoprotein levels and alleviating dyslipidemia. It significantly influences adipose tissue hormones, key contributors to systemic metabolism. Brown adipose tissue, essential for thermogenesis and lipid combustion, encounters modified UCP1 levels due to dietary factors, including the KD. UCP1 generates heat by uncoupling electron transport during ATP synthesis. Browning of the white adipose tissue elevates UCP1 levels in both white and brown adipose tissues, a phenomenon encouraged by the KD. Ketone oxidation depletes intermediates in the Krebs cycle, requiring anaplerotic substances, including glucose, glycogen, or amino acids, for metabolic efficiency. Methylation is essential in adipogenesis and the body's dietary responses, with DNA methylation of several genes linked to weight loss and ketosis. The KD stimulates FGF21, influencing metabolic stability via the UCP1 pathways. The KD induces a reduction in muscle mass, potentially involving anti-lipolytic effects and attenuating proteolysis in skeletal muscles. Additionally, the KD contributes to neuroprotection, possesses anti-inflammatory properties, and alters epigenetics. This review encapsulates the metabolic effects and signaling induced by the KD in adipose tissue and major metabolic organs.

Healthcare professionals' knowledge of and compliance with the ASCO/ESMO/GLIM guidelines for the diagnosis and management of cancer cachexia (CC): the ASSIST-CC baseline findings in Uganda.

Background: More than 50% of people with advanced cancer suffer from cancer-related cachexia (CC) - a major contributor to morbidity and mortality. Despite the lack of local guidelines on CC diagnosis and management in Uganda, the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO) and the Global Leadership Initiative on Malnutrition (GLIM) developed guidelines on CC screening and management. However, the level of knowledge on CC and compliance with the available guidelines among Ugandan oncology health professionals is unknown. This study aimed to assess the level of awareness and knowledge of CC diagnosis and management and compliance with the ASCO/ESMO/GLIM guidelines on CC among healthcare professionals (HCPs) involved in the care of cancer patients. Methods: In this phase one, a self-administered structured questionnaire developed using the ASCO/ESMO and GLIM guidelines on diagnosis and management of CC was used to assess the level of awareness, and knowledge of 200 health professionals from three hospital settings on CC, and compliance with the ASCO/ESMO/GLIM guidelines on CC related core communication, barriers to communication, clinician training in communication, discussing goals of care, treatment options and meeting the needs of the underserved populations. The data were entered into Research Electronic Data Capture software analysed using STATA version 18.0 software. Results: The overall objectively correct knowledge score of CC diagnosis criteria was 67.5% (n = 135), yet there was a much lower level of awareness about ASCO/ESMO/GLIM guidelines on CC at 30% (n = 60) and only 21% (n = 42) of the HCPs have ever assessed Quality of life of CC patients. The compliance with ASCO/ESMO/GLIM guidelines on nutritional interventions for patients with CC varied across the variables markedly, ranging from 25.1% (n = 50) to 81% (n = 162) for the specific ASCO/ESMO/GLIM guidelines' recommendations. Whereas compliance with the guidelines on discussing goals of care, prognosis, treatment options and end-of-life care scored the highest in most variables, most HCPs exhibited low compliance with the discussion about patients' end-of-life preferences early in the course of incurable illness (49.8%, n = 99). There were statistically significant differences between the mean scores of only two variables among the three hospitals in compliance with ASCO/ESMO/GLIM guidelines on the provision. Conclusion: This study indicated that the overall objectively correct knowledge of CC diagnosis criteria was inadequate, with a much lower level of awareness about the ASCO/ESMO/GLIM guidelines on CC and a handful of the HCPs have ever assessed the quality of life of CC patients. Quality improvement interventions on CC diagnosis and management should prioritize improving the level of knowledge on CC, diagnostic criteria and patient-clinician communication, including discussion about patients' end-of-life care using standardised tools such as ASCO/ESMO or GLIM guidelines on CC using a multidisciplinary team approach.

Physical performance and plasma metabolic profile as potential prognostic factors in metastatic lung cancer patients.

BACKGROUND: Low physical performance is associated with higher mortality rate in multiple pathological conditions. Here, we aimed to determine whether body composition and physical performance could be prognostic factors in non-small cell lung cancer (NSCLC) patients. Moreover, we performed an exploratory approach to determine whether plasma samples from NSCLC patients could directly affect metabolic and structural phenotypes in primary muscle cells. METHODS: This prospective cohort study included 55 metastatic NSCLC patients and seven age-matched control subjects. Assessments included physical performance, body composition, quality of life and overall survival rate. Plasma samples from a sub cohort of 18 patients were collected for exploratory studies in cell culture and metabolomic analysis. RESULTS: We observed a higher survival rate in NSCLC patients with high performance in the timed up-and-go (+320%; p = .007), sit-to-stand (+256%; p = .01) and six-minute walking (+323%; p = .002) tests when compared to NSCLC patients with low physical performance. There was no significant association for similar analysis with body composition measurements (p > .05). Primary human myotubes incubated with plasma from NSCLC patients with low physical performance had impaired oxygen consumption rate (-54.2%; p < .0001) and cell proliferation (-44.9%; p = .007). An unbiased metabolomic analysis revealed a list of specific metabolites differentially expressed in the plasma of NSCLC patients with low physical performance. CONCLUSION: These novel findings indicate that physical performance is a prognostic factor for overall survival in NSCLC patients and provide novel insights into circulating factors that could impair skeletal muscle metabolism.

Dose optimization of pancreatic enzyme replacement therapy is essential to mitigate muscle loss in patients with advanced pancreatic cancer and exocrine pancreatic insufficiency.

BACKGROUND & AIMS: Exocrine pancreatic insufficiency (EPI) contributes to malnutrition, marked by muscle loss during chemotherapy for advanced pancreatic cancer (aPC). Pancreatic enzyme replacement therapy (PERT) is recommended for patients with EPI; however, it's efficacy for attenuating muscle loss has not been demonstrated. We aimed to delineate the impact of PERT dose on muscle loss using a 7-year population-based cohort with aPC who were provided PERT at the discretion of their oncologist or dietitian according to clinical indications of EPI. METHODS: All patients treated with chemotherapy for aPC from 2013 to 2019 in Alberta, Canada (population ∼4.3 million) were included if they had computed tomography (CT) scans both prior to and 12 ± 4 weeks after chemotherapy initiation. Change in muscle area (cm2) was measured at 3rd lumbar level on repeated CT scans. Muscle loss was defined by measurement error (loss >2.3 cm2). Clinical and pharmaceutical data were retrieved from provincial registries. For patients who were dispensed PERT -8 to +6 weeks from chemo start (PERT users), estimated dose consumed per day was calculated as: (total dose dispensed) / (days, first to last dispensation). PERT users were categorized as high dose or low dose users according to the median estimated dose consumed. Non-users were classified as No PERT. Association between PERT use and muscle loss was analyzed with multivariable logistic regression. RESULTS: Among 210 patients, 81 (39%) were PERT users. Median estimated dose consumed per day of 75 000 USP lipase units defined the cutoff between low dose and high dose uses. There were no significant differences in baseline characteristics between high dose and low dose groups. Muscle loss was more prevalent among low dose compared to both high dose and No PERT groups (88% vs. 58% and 67%, p < 0.05). In the multivariable model predicting muscle loss, low dose PERT was independently associated with greater odds of muscle loss (OR 5.4, p = 0.004) vs. high dose, independent of tumour response, disease stage, and chemotherapy regimen. CONCLUSION: In patients with clinical indications of EPI during chemotherapy for aPC, low doses of PERT were insufficient to prevent muscle loss. Patients with EPI consuming higher doses of PERT had similar odds of muscle maintenance to patients without clinical indications of EPI. Provider education for optimal PERT dosing in patients with EPI should be prioritized, and resources must be allocated to support dose titration.

Cachexia Index Is a Prognostic Indicator in Patients With Metastatic Urothelial Carcinoma Treated With Systemic Chemotherapy.

Background/Aim: Cancer cachexia is associated with poor prognosis in patients with metastatic urothelial carcinoma (mUC). The objective of the study was to assess the cachexia index (CXI), which is a new indicator assessing the status of cancer cachexia, as a prognostic indicator for mUC patients treated with gemcitabine plus cisplatin (GC) chemotherapy. Patients and Methods: The study included 55 patients with mUC who underwent GC chemotherapy between 2008 and 2022 as first-line chemotherapy. The CXI at the start of chemotherapy was determined as follows: CXI=(serum albumin × skeletal muscle mass index)/ (neutrophil count/lymphocyte count). Patients were categorized into two groups based on a median CXI value (CXI-high and CXI low). We used Kaplan-Meier curves and multivariate Cox proportional hazards regression models to assess the association between the CXI and overall survival (OS). Results: At the start of GC chemotherapy, significant differences were not found in patients' characteristics. The median OS was significantly shorter in the CXI-low group [10.0 months (95% confidence interval (CI)=5.1-12.8)] than in the CXI-high group [22.3 months (95% CI=13.6-NA), p<0.05]. Multivariate analysis revealed that low CXI was a predictor of a poor prognosis [hazard ratio (HR)=2.25, 95% CI=1.12-4.52, p<0.05]. Conclusion: CXI might be useful as a prognostic indicator for patients with mUC undergoing first-line GC chemotherapy.

Skeletal Muscle Proteome Modifications following Antibiotic-Induced Microbial Disturbances in Cancer Cachexia.

Cancer cachexia is an involuntary loss of body weight, mostly of skeletal muscle. Previous research favors the existence of a microbiota-muscle crosstalk, so the aim of the study was to evaluate the impact of microbiota alterations induced by antibiotics on skeletal muscle proteins expression. Skeletal muscle proteome changes were investigated in control (CT) or C26 cachectic mice (C26) with or without antibiotic treatment (CT-ATB or C26-ATB, n = 8 per group). Muscle protein extracts were divided into a sarcoplasmic and myofibrillar fraction and then underwent label-free liquid chromatography separation, mass spectrometry analysis, Mascot protein identification, and METASCAPE platform data analysis. In C26 mice, the atrogen mafbx expression was 353% higher than CT mice and 42.3% higher than C26-ATB mice. No effect on the muscle protein synthesis was observed. Proteomic analyses revealed a strong effect of antibiotics on skeletal muscle proteome outside of cachexia, with adaptative processes involved in protein folding, growth, energy metabolism, and muscle contraction. In C26-ATB mice, proteome adaptations observed in CT-ATB mice were blunted. Differentially expressed proteins were involved in other processes like glucose metabolism, oxidative stress response, and proteolysis. This study confirms the existence of a microbiota-muscle axis, with a muscle response after antibiotics that varies depending on whether cachexia is present.