Low Muscularity Research Articles

Low muscle mass in lung cancer is associated with an inflammatory and immunosuppressive tumor microenvironment

BackgroundComputed tomographies (CT) are useful for identifying muscle loss in non-small lung cancer (NSCLC) cachectic patients. However, we lack consensus on the best cutoff point for pectoralis muscle loss. We aimed to characterize NSCLC patients based on muscularity, clinical data, and the transcriptional profile from the tumor microenvironment to build a cachexia classification model.MethodsWe used machine learning to generate a muscle loss prediction model, and the tumor's cellular and transcriptional profile was characterized in patients with low muscularity. First, we measured the pectoralis muscle area (PMA) of 211 treatment-naive NSCLC patients using CT available in The Cancer Imaging Archive. The cutoffs were established using machine learning algorithms (CART and Cutoff Finder) on PMA, clinical, and survival data. We evaluated the prediction model in a validation set (36 NSCLC). Tumor RNA-Seq (GSE103584) was used to profile the transcriptome and cellular composition based on digital cytometry.ResultsCART demonstrated that a lower PMA was associated with a high risk of death (HR = 1.99). Cutoff Finder selected PMA cutoffs separating low-muscularity (LM) patients based on the risk of death (P-value = 0.003; discovery set). The cutoff presented 84% of success in classifying low muscle mass. The high risk of LM patients was also found in the validation set. Tumor RNA-Seq revealed 90 upregulated secretory genes in LM that potentially interact with muscle cell receptors. The LM upregulated genes enriched inflammatory biological processes. Digital cytometry revealed that LM patients presented high proportions of cytotoxic and exhausted CD8+ T cells.ConclusionsOur prediction model identified cutoffs that distinguished patients with lower PMA and survival with an inflammatory and immunosuppressive TME enriched with inflammatory factors and CD8+ T cells.

Low Muscularity as Assessed by Abdominal Computed Tomography on Intensive Care Unit Admission Is Associated With Mortality in a Critically Ill Asian Population.

Low muscularity (LM) is associated with high mortality in the Caucasian critically ill population. Muscularity can be accurately measured by the skeletal muscle index (SMI; cm2 /m2 ) generated by computed tomography (CT). This study aimed to establish the overall and sex-specific cutoff values that predict hospital mortality in an Asian critically ill population. This single-center, retrospective, observational study included patients aged ≥18 years with an abdominal CT conducted within 72 hours of admission to the intensive care unit. SMI generated from CT images at the level of the mid-third lumbar vertebra were extracted from the medical records. Area under the receiver operating characteristic curves (AUC) was generated to determine the SMI cutoff values for hospital mortality. Association between LM (defined by SMI cutoff value) and hospital mortality was further evaluated by multivariable logistic regression. In a sample of 228 patients, the overall SMI cutoff value (cm2 /m2 ) for hospital mortality was 42.0 (AUC: 0.637; sensitivity: 66.7%, specificity: 56.8%), whereas it was 46.5 in males and 35.3 in females. More males than females had LM (51.4% vs 37.5%), and >40% of overweight/obese patients had LM. Patients with LM were older and had a longer duration of mechanical ventilation and hospitalization. After adjusting for known confounders, LM independently predicted hospital mortality in the overall sample (adjusted odds ratio: 2.42; 95% CI 1.16-5.03; P = 0.003) and in both sexes. This study established a set of SMI cutoff values that predict hospital mortality. LM is independently associated with hospital mortality.

Clinical Classification of Cancer Cachexia: Phenotypic Correlates in Human Skeletal Muscle

BackgroundCachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system.Methods41 patients with resectable upper gastrointestinal (GI) or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL) and/or low muscularity (LM). Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation.FindingsCompared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively). No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022) and with >10%WL, beclin (p = 0.05) and ATG5 (p = 0.01) protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups.ConclusionMuscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more homogeneous patient cohort, reduce the sample size required and enhance the time scale within which trials can be conducted.