Introduction
Cancer cachexia is a multifactorial and sometimes irreversible syndrome characterized by pronounced unintentional weight loss and skeletal muscle wasting [ 1 ] impacting cardiorespiratory function, quality of life, and treatment effectiveness as well as the survival of patients with cancer [ 2 – 5 ]. Cancer cachexia affects approximately 50-80% of cancer patients (depending on the tumor type) and is thought to contribute to 22-30% of cancer-related deaths [ 6 , 7 ]. The mechanisms underlying the development of cancer cachexia have not been clearly elucidated, but are thought to involve a range of tumor-derived inflammatory and immune-related mediators that trigger inflammation, proteolysis, and lipolysis [ 8 , 9 ] leading to loss of skeletal muscle and adipose tissue mass. Although some therapeutic options have been suggested for the management of cancer cachexia (e.g., nutrition counseling, progesterone analogs, androgens, and corticosteroids among others), their effectiveness is modest [ 10 ]. More recently, inhibition of growth differentiation factor 15 (GDF-15) has been proposed as a potential therapeutic approach with encouraging results in patients with cancer cachexia [ 11 ].
Brown adipose tissue (BAT) and the “browning” of the white adipose tissue (WAT) - i.e., the emergence of brown-like adipocytes in classical WAT depots - has attracted research interest due to its high capacity for nutrient utilization to produce heat, a wasting process [ 12 ]. To this date, BAT has been mostly studied in the context of obesity and its related metabolic perturbations suggesting that increased BAT volume is associated with improved metabolic function and lower probability of having a diagnosis of type 2 diabetes, cardiovascular diseases, and hepatic steatosis [ 13 – 17 ]. However, BAT and the thermogenic adipocytes in WAT have been implicated in the pathophysiology of various wasting conditions (e.g., cancer cachexia, burn injury and pheochromocytoma) [ 18 ]. Although preclinical data support that BAT and the browning of WAT may contribute to the pathogenesis of cancer cachexia [ 19 – 23 ], results from studies in patients have reported inconsistent results [ 24 – 28 ].
The purpose of this study was to examine the interrelationships between BAT, changes in body weight, and cachexia in patients with cancer. To address this question, we conducted a retrospective cohort study in adult patients with diagnosed primary malignancies of various origins. We hypothesized that patients with detectable BAT in their diagnostic 2-deoxy-2-[ 18 F]-fluoro-glucose ( 18 F-FDG) positron emission tomography-computed tomography (PET-CT) imaging scan would exhibit more pronounced weight loss and have higher risk of developing cancer cachexia up to 12 months after diagnosis compared to patients without detectable BAT.
Material and Methods
Patient population
To identify patients with cancer and evidence of active BAT, we retrospectively queried the radiological reports database of all patients who had undergone 18 F-FDG-PET-CT for cancer diagnosis and/or staging at University of California Davis (UC Davis) from December 2004 until July 2020, for evidence of detectable BAT depots (BAT+). Subsequently, we queried the electronic medical records to identify patients with newly diagnosed cancer who also underwent staging 18 F-FDG-PET-CT with no evidence of BAT presence (BAT-) in their radiologic report. The inter-reader variability for the assessment of BAT has been previously reported to be very high using 18 F-FDG-PET-CT imaging [ 29 ]. Eligible participants had to be at least 18 years old, recorded a staging 18 F-FDG-PET-CT prior to cancer-specific treatment, and provided electronic medical records for at least 6 months following the initial cancer diagnosis. Exclusion criteria included prior cancer diagnosis/treatment within 5 years, use of medications that may affect BAT activity (i.e., alpha or beta- adrenergic blockers or agonists and steroids), incomplete medical records (missing height and weight data at diagnosis), pregnancy, and prisoners. Based on these criteria, we identified a group of BAT+ patients (n = 75) and a group of BAT- (n = 257). To minimize the effect of confounding factors on the relationship of the BAT presence or absence with weight loss and cancer cachexia, out of the previously identified BAT+ and BAT- groups, we selected a group of BAT+ patients (n = 57) who were matched with a group of BAT- patients (n = 73) with similar age, sex, body mass index (BMI), race, ethnicity, outdoor temperature during the day of the 18 F-FDG-PET-CT imaging session, cancer type and grade. This study was approved by the UC Davis Institutional Review Board in accordance with the Declaration of Helsinki.
Power calculation
Based on the current literature [ 30 ], patients with cancer experience (mean ± SD) 7.0% ± 6.7% body weight loss 6 months after diagnosis. Assuming the same variability, we estimated that 48 patients would be minimally needed in each group to detect a 5% difference in weight loss trajectory since cancer diagnosis (primary outcome) between the two groups (which is realistic and clinically meaningful [ 31 ]) with >95% power using two-sided tests at the α = 0.05 level of significance.
Cancer Diagnosis and Staging
Primary cancer sites were classified to one of the eight categories: 1) hematologic (all lymphoma types, multiple myeloma, large B-cell lymphoma, chronic myeloid leukemia); 2) genitourinary (endometrial, cervix, renal cell, urothelial, squamous cell carcinoma of the bladder); 3) skin (carcinomas, melanoma, squamous cell carcinoma with no primary origin noted, Merkel cell carcinoma, basosquamous carcinoma, large cell carcinoma); 4) respiratory (lung-based tumours, mucinous adenocarcinoma, adenosquamous carcinoma, small cell carcinoma of the lung, squamous cell carcinoma of the lung, clear cell carcinoma of the lung, adenocarcinoma without a tissue diagnosis, non-small cell lung carcinoma, thymoma); 5) gastrointestinal (cholangiocarcinoma, colorectal, intestine neuroendocrine); 6) breast (lobular carcinoma, any breast tissue malignancy, in situ/ invasive ductal carcinoma); 7) head and neck (squamous cell carcinoma with origin in the head or neck region, basaloid squamous cell carcinoma, adenoid cystic carcinoma); and 8) other cancer types of various origins (neurofibroma, paraganglioma, myxoid liposarcoma, leiomyosarcoma, fibromyxosarcoma, malignant neoplasm of unknown primary). The cancer stage for solid tumours was decided using the Tumour, Node, and Metastasis (TNM) staging system, categorizing it into four stages (I–IV) and was obtained from the CNEXT registry at UC Davis [ 32 ].
Definition of Cancer Cachexia
Cancer cachexia was determined in accordance with the international consensus on the definition of cachexia: i) weight loss greater than 5% or ii) weight loss greater than 2% if BMI is lower than 20 kg/m 2 [ 31 ].
Other Characteristics
Patients’ clinical and histological data (cancer type, stage, and grade), demographic (age, gender, race, and ethnicity), and anthropometric characteristics (height and weight) of the were extracted from their electronic medical records during the first year after diagnosis. The local average, minimum and maximum temperatures of the day of the scan were extracted for the historic temperature dataset available via the National Oceanic and Atmospheric Administration [ 33 ].
18 F-FDG-PET-CT imaging
18 F-FDG-PET-CT scans were performed using a Discovery ST or 690 scanners (General Electric, Boston, MA). The patient preparation protocol included fasting for 4-6 hours and avoiding strenuous exercise for at least 24 hours prior to the imaging visit. Patients received either 740 MBq (on Discovery ST) or 370 MBq (on Discovery 690) and the 18 F-FDG-PET-CT imaging was performed (mean and standard deviation (SD)) 71 ± 12 minutes later. According to the clinical imaging protocol, the patients first performed a CT scan (140 kVp, 300 mAs) followed by a PET scan (3-4 minutes per bed position depending on the patient’s size) from skull base to mid-thigh, or from vertex to toes depending on the clinical indication. The CT was reconstructed with filtered back projection into a 512 x 512 matrix resulting in voxel size of 0.98 x 0.98 x 3.75 mm. For the Discovery 690 scanner, PET images were reconstructed into a 192 x 192 matrix using an ordered subsets expectation maximization (OSEM) algorithm with two iterations and 24 subsets and incorporating time-of-flight (TOF) and all standard corrections (attenuation, scatter, randoms, deadtime, and normalization). No point spread function modeling was employed. A post-reconstruction Gaussian smoothing was applied with 6.4 mm full width at half maximum (FWHM). The resulting PET voxel size was of 3.65 x 3.65 x 3.27 mm. On Discovery ST scanner, PET images were reconstructed into 128 x 128 matrix using OSEM algorithm with 2 iterations and 30 subsets. The resulting voxel size was 5.47 x 5.47 x 3.27 mm.
PET-CT image analysis
BAT volume and activity were quantified in the BAT+ group according to BARCIST recommendations [ 34 ]. The analysis of PET-CT imaging was conducted using Life X software version 6.2 [ 35 ]. 18 F-FDG uptake was quantified as a standardized uptake value (SUV) normalized to the individual’s estimated lean body mass (LBM) which was calculated using the Janmahasatian formula [ 36 ]. BAT volume and activity were quantified using a threshold corrected for LBM, SUV LBM = (1.2 g/mL)/(LBM%) [ 34 ]. After ensuring adequate registration between the CT and PET components of each scan, a threshold-based method was applied to quantify BAT metrics. Specifically, a large initial volume of interest (VOI) was placed on CT slices between C3 and T3 vertebrae; to capture the neck and paravertebral brown fat depots. Then, a CT-based contour that included radiodensity within the -190 to -10 Hounsfield Units was defined [ 34 ]. A new threshold was added on the PET component based on the SUV above the individually determined SUV LBM cut-off. The intersected contour that fulfilled the two threshold conditions (on CT and PET) was used to derive BAT metrics including active BAT volume. Before deriving any metrics, the contour was reviewed slice-by-slice to avoid including other tissues with high 18 F-FDG uptake either pathologic (e.g., tumour foci) or physiologic (e.g. soft palate, esophagus, bone marrow, muscles, or myocardium) ( Figure 2 ).
Statistical analysis
Analyses were performed using the following software SPSS (IBM Corp. Version 26.0, Armonk, NY), Stata Statistical Software version 17.0 (College Station, TX: StataCorp LLC) and Prism (GraphPad, Boston, MA). Data are presented as mean ± SD or 95% confidence interval (CI) for normally distributed variables or median (interquartile range, IQR) for non-normally distributed parameters. Categorical variables are presented as absolute number of observations and percentages (%). Crude differences between BAT+ and BAT- groups in patient characteristics were assessed using Students t-test for normally distributed data and the Mann-Whitney U test for skewed data. Chi-squared or Fisher’s Exact test was used to analyze differences in categorical variables (such as sex, race, ethnicity) between the study groups. For hypothesis testing, a mixed-effects analysis was employed to examine the between-group differences for changes in body weight over time, with a subsequent post-hoc Sidak’s procedure for pairwise-comparisons across different study time points. For the association of the BAT status with the risk of developing cancer cachexia, a repeated-measures Poisson regression was fitted to estimate the relative risk (RR) and 95% CI with statistical adjustments for potential covariates. The level of statistical significance was set at 0.05 for all analyses.
Results
Patient population
Table 1 contains the demographic, clinical, anthropometric, and other relevant information of the patients included in the BAT+ and BAT- groups. By study design, there were no significant differences between groups in any matching factors: demographic, anthropometric, clinical, or cancer-related characteristics (all comparisons: p > 0.05). Similarly, we observed no statistically significant differences in the temperature (minimum, maximum, and average) on the day of the scan and season that PET-CT scans took place. For the BAT+ group, the median BAT volume was 38.0 mL (IQR: 16.9 to 83.1 mL) with median SUV mean of 2.4 g/mL (IQR: 2.2 to 2.8 g/mL) and median SUV max 5.9 g/mL (IQR: 4.2 to 8.5 g/mL). The mean BAT radiodensity was -57.2 ± 10.2 Hounsfield units. The BAT- group had no detectable BAT according to relevant radiological report and after visual inspection by our research team.
Changes in body weight after cancer diagnosis in patients with and without detectable BAT
We found a significant interaction between BAT group and time for body weight (p-value for interaction = 0.014, Figure 3A ), absolute weight change (p-value for interaction = 0.012, Figure 3B ) and relative weight change from cancer diagnosis (p-value for interaction = 0.051, Figure 3C ) between the two groups and across the study timepoints. The BAT+ group exhibited a relatively stable body average weight (change in weight at 6 months: -0.2 kg; 95% CI: -1.5 to 1.1 kg or 0.2%; 95% CI: -1.8 to 1.9%) up to 6 months after diagnosis with a trend for small weight gain at 12 months (change in weight at 12 months: 1.8 kg; 95% CI: -0.3 to 3.9 kg or 1.8%; 95% CI: -0.3 to 3.9%) after diagnosis. Conversely, the BAT- group demonstrated progressive weight loss (change in weight at 6 months: -2.4; 95% CI: -3.9 to -0.8 kg or -2.5%; 95% CI: -4.7 to -0.3% and 12 months: -1.7 kg; 95% CI: -4.2 to 0.7 kg or -1.8%; 95% CI: -4.3 to 0.8%) with significant post-hoc difference between groups at 12 months (p<0.05 for both absolute weight and weight change, Figure 3B-C ).
Comparison of the risk for developing cancer cachexia in patients with and without detectable BAT
Applying the definition of cachexia [ 31 ] to patients’ weight status, we found that in the BAT- group, eight patients developed cancer cachexia at 3 months (11%), 33 patients (46%) at six months and 16 patients (41%) at 12 months ( Figure 4 ). In the BAT+ group, cachexia was present in five patients (10%) at 3 months, 13 patients (24%) at six months and 11 patients (25%) at 12 months, respectively. The overall incidence of cancer cachexia anytime in the first 12 months after diagnosis was 46.6% and 66.1% in the BAT+ and BAT- groups (p = 0.03), respectively. In the unadjusted model, the average risk over the 1-year follow-up was lower by 43% (RR 0.57, 95% CI: 0.36 to 0.85) in patients of the BAT+ group compared to the BAT- group. Adjustment for age, sex, mean outdoor temperature on the day of the PET/CT, and cancer site and stage did not materially affect these results indicating that the average risk over the 1-year follow-up was lower by 44% (RR: 0.56, 95% CI: 0.32 to 0.97) in patients of the BAT+ group compared to the BAT- group.
Discussion
Cachexia is a wasting syndrome affecting a large proportion of patients with cancer as well as impacting their quality of life and survival [ 2 – 5 ]. The mechanisms underlying the development of cancer cachexia have not been clearly elucidated and no approved effective treatment approaches are currently available against it. Studies in preclinical models have implicated BAT and the browning of WAT in the pathogenesis of cancer cachexia. However, results from studies in people have elicited mixed results. Using a retrospective cohort study design, we found that treatment-naive patients with evidence of BAT on 18 F-FDG-PET-CT imaging at cancer diagnosis experienced lower weight loss and risk for cachexia compared to a matched group of patients without evidence of BAT at diagnosis.
The reported protective relationship between BAT at diagnosis and risk of developing cancer cachexia contrasts our initial hypothesis that was based on the published preclinical and preliminary clinical data on the role of the thermogenic adipocytes in cancer cachexia. Specifically, BAT thermogenesis and the browning of WAT have been thought to contribute to the hypermetabolic state of cancer cachexia in rodents [ 19 – 23 ]. Further, pharmacologic and genetic manipulations affecting inflammation and the sympathetic nervous system have been reported to inhibit the browning of WAT and to ameliorate cancer cachexia in mice [ 21 , 23 ]. Conversely, cold-induced BAT activation in rodents has been reported to inhibit tumor growth by lowering glucose availability in the tumor microenvironment [ 37 ]. To this date, only a small number of observational studies have explored the potential role of BAT in cancer-related outcomes yielding mixed results. The first report on the link between BAT and cancer cachexia in humans was a necropsy study suggesting higher prevalence of multilocular adipocytes - resembling brown adipocytes - in the perirenal adipose tissue depot of patients who died from cancer compared to patients with other cause of death [ 24 ]. However, the two groups were matched for age but not for sex and anthropometric characteristics. More recently, a larger retrospective study including two separate cohorts (n 1 = 460 patients with active BAT and n 2 = 283 patients with active BAT and at least two scans) suggested that BAT activity is not associated with any changes in the calculated cancer burden, used as a marker of disease activity and grading system, between consecutive scans [ 26 ]. However, in the latter study changes in body weight and/or weight loss as well as BAT volume were not quantified. Moreover, Eljalby et al. reported a trend for lower prevalence of cancer cachexia (defined similarly to the present study, in accordance with validated international consensus criteria [ 31 ]) in patients with detectable BAT than those without, after adjusting for potential confounders, but their results did not reach statistical significance [ 27 ]. Our study suggests that evidence of detectable BAT at cancer diagnosis may be protective for developing cachexia and thus this needs to be tested with prospective and mechanistic studies in the future.
The adipose tissue is now recognized as a heterogeneous endocrine organ involved in the metabolic regulation of several (patho)physiological processes [ 38 ]. Adiposity and its related metabolic complications (i.e., insulin resistance, type 2 diabetes) have been associated with adverse cancer-related outcomes including mortality, cancer recurrence and cachexia [ 39 – 42 ] and treatment of obesity and its associated conditions could be an effective approach to improve cancer incidence and cancer-related outcomes [ 43 – 45 ]. An increased BAT volume/activity in people has been linked to improved metabolic function and lower odds of type 2 diabetes, coronary heart disease, congestive heart failure and dyslipidemia among others [ 13 – 17 ], likely due to its increased capacity for substrate oxidation and/or its potential secretory role affecting metabolic function in other tissues [ 18 , 46 ]. Considering the current knowledge in human BAT and its role in metabolism, the results of the current study suggest that individuals with detectable BAT, who are also likely to be metabolically healthier compared to those with no detectable BAT, can endure the clinical sequelae of cancer without developing cancer cachexia. Alternatively, it is possible that increased BAT activity in people with detectable BAT may decrease substrate availability to the tumour microenvironment leading to decreased tumor growth and that could potentially translate to other improved cancer related outcomes including cancer cachexia and/or there is a direct anti-cachectic, endocrine signal derived from BAT tissue.
Our study has strengths and limitations that need to be considered when interpreting its results. We have collected and analyzed longitudinal data at different timepoints for up to a year post cancer diagnosis and were able to show the trajectory in body weight and weight loss over time. The detailed characterization of our patients as well as the matched groups of patients with and without detectable BAT for several variables, including cancer related parameters and the outdoor temperature on the day of the imaging should be listed among its strengths. Although the two groups were matched for cancer site and stage, small, non-statistically significant differences in these variables may have introduced residual confounding in the relationship between BAT status and study outcomes. Nevertheless, the association between BAT and the risk of developing cancer cachexia remained largely unaffected after adjusting for cancer site, stage, and other potential confounders. Additional limitations of the study include its retrospective nature and the small sample size; nevertheless, the sample size was adequately powered to address the primary outcome of this investigation. Although loss of muscle mass constitutes one of the three diagnostic criteria for cancer cachexia [ 31 ], information on patients’ muscle mass was not available in the electronic medical records. We appreciate that depending on the histology of the cancer, the TNM staging system alone may not provide sufficient information for correct staging and that various other staging systems are utilized to classify different types of cancer. Additionally, the potential influence of cancer related treatments on body composition and/or weight loss was not directly accounted for, although our patient groups were matched for cancer type and/or stage and therefore likely to have had similar treatments. Further, causation cannot be established due to the observational nature of our study. We acknowledge that larger, longitudinal, prospective cohorts are needed to expand upon our observations, but our study meaningfully contributes as hypothesis generating. Studies with extended follow-up may be able to fully elucidate the weight loss trajectory and long-term survival after cancer diagnosis.
Conclusion
In conclusion, we report that presence of detectable BAT on 18 F-FDG-PET-CT in treatment-naïve patients with cancer is associated with reduced weight loss (∼3.6%) and may lower the risk for developing cancer cachexia by 44% for up to a year after cancer diagnosis. These results support that detectable levels of BAT at diagnosis may result in a clinically significant reduction in the risk for developing cancer cachexia. The mechanism underlying the reported relationship is unclear. Further research is needed to clarify whether BAT is causally involved in the pathophysiology of cancer cachexia or whether it functions as a biomarker of improved cardiometabolic health or other (patho)physiological processes conferring an advantage in patients diagnosed with malignancies of various origins.
Acknowledgments
The authors thank Dr. Heejung Bang and Dr. Sandra Taylor at the University of California Davis for consulting in the statistical aspects of the study design; Shengjie Zhu for assisting with the temperature date extraction and Rakesh Kuvar for assisting with the data management of this study; the personnel of the Explorer Molecular Imaging Center and the Innovation Technology Health Informatics at the University of California Davis for their help with the establishing the patient cohorts and extracting the electronic medical record data.
Funding
This study was supported by grants from the National Institute of Food and Agriculture (Hatch project number CA-D-NTR-2618-H), the Wellcome Trust (208363/A/17/Z), the National Institute for Health Research (NIHR) (BRC4) and Health Education England (HEE). GP is funded by the HEE/NIHR (CL-2022-14-004). FI and NGF acknowledge funding from the Medical Research Council Epidemiology Unit (MC_UU_00006/3). NGF acknowledges support from NIHR Cambridge Biomedical Research Centre (NIHR203312) and NGF is an NIHR Senior Investigator (NIHR202397). The views expressed in this publication are those of the authors and not necessarily those of the NIHR, NHS or the UK Department of Health and Social Care.
Conflict of interest
The authors declare no conflict of interest.
Author Contributions
MC designed the research study assisted by YGA and RB. YGA and DM performed the analysis of the imaging data. MC, RB, and AC supervised the extraction and analysis of the imaging data. SA, YGA, and JMC assisted with data extraction. GP, SA, and ARS assisted with the clinical evaluation of the patients included in the study. DB organized the data and evaluated the patients for presence of cancer cachexia. GP and MC performed the statistical analysis of the data. FI and NGF assisted with designing the statistical analysis and interpretation of the results. MC, GP, and DB wrote the first draft of the manuscript. MC is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors critically reviewed and edited the manuscript.
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