Sex-specific Body Composition Features Impacting Survival Outcomes in Surgically Managed Clear Cell Renal Cell Carcinoma

doi:10.21203/rs.3.rs-5313658/v1

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Sex-specific Body Composition Features Impacting Survival Outcomes in Surgically Managed Clear Cell Renal Cell Carcinoma

https://doi.org/10.21203/rs.3.rs-5313658/v1

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Purpose: Body composition phenotypes were investigated in 200 patients with clear cell renal cell carcinoma (ccRCC), focusing on muscularity, adiposity, and fat distribution. The goal was to identify prognostic body composition features in ccRCC and their clinical correlates.

Materials and Methods: A cohort of 200 patients with resected ccRCC and available CT scans annotated by The Cancer Genome Atlas was studied. Computed tomography (CT) scans were acquired from The Cancer Imaging Archive, then a single axial image landmarked at the third lumbar vertebra (L3) was analyzed for cross sectional area and radiodensity of skeletal muscle and adipose tissue. The relationships of various body composition features with other clinical factors and with overall survival (OS) were evaluated.

Results: There were sex-related differences in body composition phenotype. High subcutaneous fat density (SFD) was uncommon in females. In males, the most common features that co-existed were low subcutaneous adipose tissue (SAT) and high SFD. In females, sarcopenia and low muscle radiodensity (myosteatosis) were the most frequently co-existent features. On univariate analysis, sarcopenia, low SAT, high SFD and myosteatosis were associated with shorter OS. On multivariate analysis, sarcopenia is associated with shorter OS (HR 1.9, P=0.05), and high SFD also associated with shorter OS (HR 2.06, P=0.04). Sarcopenia was associated with more advanced disease, but high SFD was not.

Conclusions: Body composition features in males and females with ccRCC differ significantly. Sarcopenia and increased SFD are prognostic in ccRCC. Further studies are required to understand the pathogenesis of ccRCC-associated changes in body composition.

clear cell renal cell carcinoma

sarcopenia

cachexia

body composition

prognosis

Renal cell carcinoma (RCC) is the most prevalent type of kidney malignancy, affecting over 300,000 patients worldwide and leading to more than 100,000 deaths annually (1). Clear cell renal cell carcinoma (ccRCC) is the most common and clinically aggressive subtype, which comprises 75% of RCC (1). Curative intent surgery is the typical treatment for locoregional disease. However, for metastatic ccRCC and locally advanced disease, systemic therapies targeting vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR) pathways (2), and immune checkpoint inhibitors (PD-1 and CTLA-4) (1) are options. Adjuvant chemotherapy and immunotherapy have also demonstrated efficacy in reducing recurrence rates in high-risk ccRCC (3). Therefore, understanding the factors that affect recurrence rate is essential to making decisions regarding adjuvant therapy. Cachexia, characterized by involuntary weight loss, and skeletal muscle wasting, with or without a loss of fat mass, has been described by others as a paraneoplastic syndrome in the context of ccRCC (4). However, body composition phenotypes are diverse and not always encapsulated by the definition of cachexia.

Low muscle mass (sarcopenia), quantifiable on CT scans, is observed in 25–74% of patients with advanced ccRCC (5), and in locoregional disease, the prevalence ranges from 29–65% (6). Sarcopenia has been linked to worse survival outcomes across various cancer types (7). In kidney cancer, sarcopenia adversely impacts dose-limiting toxicities for chemotherapy, postoperative hospital stays, and overall survival (OS)(8).

Other cancer-related changes in body composition have also been observed on CT scans, including myosteatosis (intramuscular adiposity, manifested as low radiodensity skeletal muscle), and high fat radiodensity. Myosteatosis, manifested as low muscle radiodensity, has been reported in about half of patients with ccRCC (9). Previous studies have identified a correlation between low skeletal muscle radiodensity and increased mortality rate in ccRCC patients who received targeted therapy, chemotherapy, radiotherapy, or underwent surgical intervention (8–10). Additionally, high-radiodensity subcutaneous fat has been reported in various cancer types (11, 12), including ccRCC (13). However, the association of high subcutaneous fat density (SFD) on survival in ccRCC patients is controversial, as there have been conflicting findings in previous studies (8, 13).

In most studies only one or two dimensions of body composition have been evaluated in isolation. Little is known about the relative effects of muscularity, muscle quality, fat distribution, and fat quality on long-term cancer outcomes; and few studies have described the relationship between these factors. The current study aims to assess and quantify a range of body composition features in patients who have undergone resection for ccRCC. Additionally, we seek to explore the interrelationship of these body composition features and their potential impact on survival outcomes within this patient cohort.

Data acquisition and study population

Data were collected from The Cancer Genome Atlas (TCGA) KIRC cohort, which included clinical data and outcomes data from 538 patients with ccRCC. The corresponding preoperative CT scan DICOM images from 200 of these patients were obtained from The Cancer Imaging Archive (TCIA). All patients annotated by TCGA and TCIA consented to participate, and the data are publicly available.

Radiographic measurement

Skeletal muscle area (SMA), skeletal muscle radiodensity (SMD), subcutaneous fat area (SAT), visceral adipose tissue area (VAT), and subcutaneous fat radiodensity (SFD) were analyzed using Slice-O-Matic software (v.5.0, Tomovision, Montreal, Canada) on cross-sectional CT images at the level of the 3rd lumbar vertebra (14). Tissue cross-sectional areas at L3 correlate with whole-body tissue volume (14). Therefore, a single-slice transverse CT image at the L3 vertebra was utilized to describe the body composition phenotype (15). As previously described, the volume and quality of muscle and fat in CT images were quantified by measuring the radiodensity of the image pixels with a semi-automated method using Hounsfield Unit (HU) thresholds of -29 to + 150 HU for SM, and − 190 to -30 for SAT (15). HU is standardized to water (0 HU) and air (-1000 HU) and quantifies the relative radiodensity for tissues in CT images (16). Two trained individuals analyzed the CT images to identify and quantify lumbar vertebrae, and parameters of interest. The intra-observer coefficient of variation was 1.5%. Observers were blinded to the survival status of patients.

CT scans included enhanced and nonenhanced scans; individuals annotated in TCIA rarely had both. To be sure that radiodensity measurements were comparable, we compared enhanced and nonenhanced scans (Supplementary Figure S1). There were no significant differences in measures of skeletal muscle density (SMD) or subcutaneous fat density (SFD).

Definition of body composition phenotypes for the ccRCC population

In previous studies, SMA, TAT, SAT, and VAT have been described following height correction. This has enabled authors to identify height-normalized levels of muscularity and adiposity associated with adverse survival outcomes (17, 18). However, height and weight information were not available for the TCGA cohort. Therefore, to evaluate the effects of muscularity and adiposity on survival outcomes, sex-specific distributions of SMA, SAT, and VAT area were described, and outcomes were compared between the top and lower tertiles of each parameter. Using this approach, sarcopenia was defined as SMA < 157.5 cm² for males and < 102.4 cm² for females; low subcutaneous adiposity was defined as SAT ≤ 156.9 cm² for males and SAT ≤ 177.8 cm² for females; and low visceral adiposity was defined as VAT ≤ 167.2 cm² for males and VAT ≤ 73.57 cm² for females.

Myosteatosis has been previously defined as muscle radiodensity ≤ 30 HU for both sexes in patients with metastatic or locally advanced lung or GI tumors (19), and that was the definition for this study. Relatively little is known about the clinically significant range of subcutaneous fat radiodensity. Therefore, we utilized cut-off finder software (20) to identify a threshold for high fat radiodensity that was associated with worse survivals. Using this approach, high fat radiodensity was defined as subcutaneous adipose tissue radiation attenuation ≥-94.1 HU for males and ≥-92.6 HU for females.

Statistical analysis

Categorical variables were compared using chi-square and Fisher's exact tests. The student t-test was employed to compare continuous variables with normal distribution. The Mann-Whitney U test was used to compare continuous variables which violated normal distribution. OS was analyzed from the time of surgery until the last day of survival or the last follow-up visit. The Kaplan-Meier method was used to estimate survivals, and the log-rank non-parametric test was used to compare survivals and to test for significance. Cox proportional hazard models were used to identify clinical risk factors related to OS in univariate and multivariate analyses. A p-value < 0.05 was considered significant. For the statistical analyses, IBM SPSS Statistics (Version 26.0) was utilized. Survival analysis was performed by GraphPad Prism (version 8.4.2).

Body Composition Variables in ccRCC

The distribution of values for each body composition measurement are summarized in Fig. 1. Sexual dimorphism was especially apparent in muscularity, fat distribution and fat radiodensity. Mann-Whitney U test was used to compare these continuous variables in males and females. We attempted to find the interplay between parameters of body composition and their reciprocal interaction. Figure 2A depicts a correlation matrix that illustrates the relationships between various body composition features in males, when considered as a continuous variable. Figure 2B depict the same relationships in females. Muscularity (SMA) was positively correlated with SAT and VAT. There were some differences in males and females in relation to muscularity: SMA was inversely proportional to SFD in males, and it was directly proportional to SMD in females. In both sexes, SAT and VAT were highly correlated, more strongly in females. In males, SAT and SMD were negatively correlated, but not in females. In both sexes, SAT and SFD were negatively correlated.

Venn diagrams for the patients with at least one feature summarize the co-existence of body composition features, in each sex (Figs. 2C, 2S). The concurrent appearance of sarcopenia, myosteatosis, low SAT and high SFD was rare, occurring in only 2% of females and none of the males. In males, 54.3% exhibited only one of these features, and 52.3% of females displayed a single body composition feature. High SFD was more common in males. In males, the most common features that co-existed were low SAT and high SFD (n = 23, 24.4%). In females, sarcopenia and myosteatosis were the most frequently co-existent features (n = 11, 22.8%). Importantly, myosteatosis and low SAT were mutually exclusive in males but not in females.

Factors associating with Overall Survival

During the follow-up period, 64 out of 200 patients (32%) died. On univariate analysis, age, sarcopenia as tertile of SMA, low SAT, TAT consists of SAT and VAT area, high SFD, T stage, metastasis stage, pathological stage, and grade, were all significant factors associated with worse overall survival (OS) (Table 1). Notably, myosteatosis was not significantly associated with OS. Kaplan-Meier curves related to each body composition variable in each sex are depicted in Fig. 3. For features analyzed by tertiles (SMA, TAT and SAT), the lowest tertile consistently had the worst survivals; survival outcomes tended to be best in patients on the upper tertile, except for SAT in males. On multivariate analysis, sarcopenia, high SFD, and pathologic stage remained significant (Table 1). There was no evidence of a synergistic impact of sarcopenia and high SFD on OS, in our cohort.

Table 1

Univariate and multivariate Cox regression analysis evaluating the association of clinical factors and body composition phenotypes with OS. Only covariates demonstrating a significant impact on survival in the univariate analysis were included in the multivariate analysis.
VARIABLE	COMPARISON	UNIVARIATE ANALYSIS				MULTIVARIATE ANALYSIS
VARIABLE	COMPARISON	P-value	HR		95% CI for HR	P-value	HR		95% CI for HR
Sex	FEMALE vs MALE	NS¹	--		--	--	--		--
Age	50 < vs > 50 (ref: 50 <)	0.02	0.4		0.2–0.9	NS	--		--
SMA	Lower vs. Middle vs. Top third (ref: Top third)	< 0.001	--		--	0.05	--		--
SAT	Lower vs. Middle vs. Top third (ref: Top third)	0.001	--		--	NS	--		--
TAT	Lower vs. Middle vs. Top third (ref: Top third)	0.01	--		--	NS	--		--
Myosteatosis	Myosteatosis vs. Normal (ref: Normal)	NS	--		--	--	--		--
SFD	High SFD vs. Normal (ref: Normal)	0.001	2.3		1.4–3.8	0.02	1.9		1.1–3.2
T-Stage	T3/4 vs. T1/2 (ref: T1/2)	< 0.001	3.3		2.0-5.5	NS	--		--
M-Stage	M1 vs. M0 (ref: M0)	< 0.001	4		2.4–6.7	NS	--		--
Pathologic Stage	stage III/IV vs. stage I/II (ref: stage I/II)	< 0.001	4		2.4-7.0	0.04	3.6		1.1–12.1
Grade	G3/4 vs. G1/2 (ref: G1/2)	0.03		2	1.1–3.3	NS		--	--
Hemoglobin	Low vs. Normal (ref: Normal)	NS	--		--	--	--		--
Platelets	Elevated vs. Normal (ref: Normal)	NS	--		--	NS	--		--
Serum Calcium	Low vs. Normal (ref: Normal)	NS	--		--	NS	--		--
WBC	Elevated vs Normal (ref: Normal)	NS	--		--	--	--		--
1. NS: not significant
2. ref: reference

Clinical Characteristics Associated with Body Composition Features

We wanted to understand what clinical features were associated with sarcopenia and high SFD, since these two body composition features were most closely associated with prognosis. While myosteatosis was not associated with OS in our cohort, we also evaluated clinical features related to myosteatosis, as this feature has been influential on outcomes in other cancer types (21, 22). The data are summarized in Table 2. Data on comorbidities and body mass index (BMI) were not available in our data set.

Table 2

Clinical characteristics of ccRCC patients as a function of low muscle mass, low muscle radiodensity (myosteatosis), and high subcutaneous adipose tissue.
Variable	Sarcopenia¹ N = 63	No Sarcopenia² N = 63	P-value	Myosteatosis³ N = 44	No Myosteatosis N = 156	P-value	High SFD N = 58	Normal SFD N = 142	P-value
AGE (years)	66.5 ± 12.4	53.3 ± 9.2	5.6*10^− 10	68.6 ± 10.3	58 ± 12.2	< 0.001	64.4 ± 12.7	58.7 ± 12.2	0.005
SEX			1.00			0.007			0.003
Male	42 (75%)	42 (75%)		21 (47.7%)	110 (70.5%)		47 (81%)	84 (59%)
Female	21 (25%)	21 (25%)		23 (52.3%)	46 (29.5%)		11 (19%)	58 (41%)
T stage			0.06			0.3			0.9
T1	28 (44.4%)	35 (55.5%)		26 (59.1%)	80 (51.3%)		28 (48.3%)	78 (55%)
T2	3 (4.8%)	9 (14.3%)		5 (11.4%)	17 (10. 9%)		7 (12.1%)	15 (10.6%)
T3	29 (46%)	18 (28.6%)		11 (25%)	57 (36.5%)		22 (37.9%)	46 (32.4%)
T4	3 (4.8%)	1 (1.6%)		2 (4.5%)	2 (1.3%)		1 (1.7%)	3 (2%)
N stage			0.3			1.00			1.00
N0	20 (87%)	25 (96.1%)		27 (96.4%)	54 (94.7%)		21 (95.5%)	60 (95.2%)
N1	3 (13%)	1 (3.9%)		1 (3.6%)	3 (5.3%)		1 (4.5%)	3 (4.8%)
M stage			0.4			0.3			0.08
M0	47 (77%)	51 (85%)		36 (90%)	127 (83%)		43 (76.8%)	120 (87.6%)
M1	14 (23%)	9 (15%)		4 (10%)	26 (17%)		13 (23.2%)	17 (12.4%)
Clinical stage			< 0.001			0.6			0.1
Stage I	26 (41.2%)	35 (60.3%)		26 (59.1%)	77 (49.3%)		26 (44.8%)	77 (54.2%)
Stage II	3 (4.8%)	7 (12%)		4 (9.1%)	13 (8.3%)		5 (8.6%)	12 (8.5%)
Stage III	18 (28.6%)	12 (20.7%)		9 (20.4%)	38 (24.4%)		12 (20.7%)	35 (24.6%)
Stage IV	16 (25.4%)	4 (7%)		5 (11.4%)	28 (18%)		15 (25.9%)	18 (12.7%)
Hemoglobin Levels			0.01			0.6			0.7
Low	40 (69%)	26 (45.6%)		26 (65%)	82 (57.3%)		33 (62.3%)	75 (57.7%)
Normal	18 (31%)	31 (54.4%)		14 (35%)	61 (42.7%)		20 (37.7%)	55 (42.3%)
1: Least muscular tertile
2: Most muscular tertile
3: SMD < 30 HU

Myosteatosis was more prevalent in females. Conversely, high SFD was more frequently observed in males. Sexual predilection for sarcopenia could not be evaluated, as we defined sarcopenia by tertiles in each sex. Sarcopenia in particular was more prevalent in patients with more advanced disease stages, and low hemoglobin was also a characteristic feature. In contrast, myosteatosis and high SFD were not at all related to cancer stage. This was particularly notable given the adverse effects of high SFD on prognosis.

Cancer cachexia is a well described phenomenon, and it has been associated with more advanced ccRCC (23). In recent years, more subtle body composition features have been identified using CT scans. Some of these features, such as high SFD and myosteatosis, are externally invisible. Their relationship to cachexia and their impact on clinical outcomes is poorly understood. We sought to investigate in a more granular fashion how various body composition features inter-relate in a cohort of ccRCC patients. In addition, we explored their relationship with survival outcomes in surgically managed patients.

In this cohort, sarcopenia was associated with higher mortality. This has been previously reported in ccRCC (24) as well as other cancer types (25). Myosteatosis, characterized by low radiodensity skeletal muscle (19), was identified in a significant portion of ccRCC patients in our study. Surprisingly, we did not find a significant correlation between myosteatosis and OS in ccRCC. Myosteatosis is associated with a worse prognosis for some other cancer types (9), and a previous study demonstrated that low SMD was associated with worse survival in stage I-III resected ccRCC, as well as in stage IV patients treated with immunotherapy (10). Antoun et al. similarly highlighted low SMD as a predictor of shorter OS in European patients with metastatic ccRCC receiving targeted therapy (26). In contrast, a study of Chinese patients on targeted therapies for ccRCC did not demonstrate a relationship of low SMD and survival (13). Additionally, a study involving 96 localized RCC patients with overweight or obesity reported no significant association between SMD and OS (6). Our study does not discount the potential clinical relevance of myosteatosis but highlights the need for further research to elucidate its prognostic value and the underlying mechanisms specific to ccRCC, especially given the inconsistencies in the literature.

Interestingly, in our series, high SFD was prognostic, but it was not related to tumor stage, unlike sarcopenia. There are limited studies on fat radiodensity in cancer. High intermuscular fat radiodensity and high SFD are associated with a worse prognosis in breast cancer (12). High SFD is associated with shorter survival in hepatocellular carcinoma (27), a high rate of biochemical recurrence in prostate cancer (11) as well as a worse prognosis in ovarian cancer (28), pancreatic cancer (29), and colorectal cancer (30). A study of metastatic ccRCC patients treated with targeted therapy did not demonstrate an association of high SFD and survival (13). The cause of high SFD is not known, but one study suggested that it may be related to the adipose tissue fibrosis, perhaps mediated by TGFb (31). Further studies are needed to clarify the clinical implications of high SFD as well as the underlying mechanisms responsible for these features.

It is essential to acknowledge the limitations of our study, including the sample size and the lack of height data to precisely define sarcopenia. Further research is needed to validate our results and to uncover the underlying mechanisms and clinical significance of the observed body composition features in ccRCC. Additionally, larger studies should explore the potential synergistic effects of these body composition parameters and their interactions with other clinical variables to refine risk stratification. Importantly, it is impossible to determine whether preoperative CT scans reflect the effects of the cancer on body composition, or whether these body composition features are constitutive.

There is growing evidence of a close association between body composition and outcome in patients with ccRCC. In this study, the most impactful body composition features on prognosis were sarcopenia and high SFD. Additional studies will be required to explore this further. Understanding the impact of tumor features and genetic predisposition will also be important, to better understand how this information affects clinical decision making.

Clinical trial number

Not applicable.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Conflict of Interest

I.T, J.L and O.F.B. were employees of Pfizer when the study was conducted. E.P. is an employee and shareholder of Pfizer.

Funding

This study was funded by Pfizer.

Author Contribution

R.H.J. and O.F.B. conceived the project. R.H.J., O.F.B., C.S., V.E.B., I.T., E.P., J.L., and O.B. performed experimental design. R.H.J., V.A., and M.T.B. performed body composition analyses. R.H.J. performed clinical and genomic analyses. All authors participated in data interpretation. R.H.J and O.F.B wrote the manuscript. All authors reviewed and approved the final manuscript.

Acknowledgements

We are grateful for comments and critiques provided by Dr. Jason de Koning and Dr. Eric Hyndman.

Availability of data and material

The clinical data analyzed in this study can be downloaded from the GDC (https://gdc.cancer.gov) and TCIA (https://www.cancerimagingarchive.net/collection/tcga-kirc/).

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Sex-specific Body Composition Features Impacting Survival Outcomes in Surgically Managed Clear Cell Renal Cell Carcinoma

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Abstract

Figures

INTRODUCTION

MATERIALS AND METHODS

Data acquisition and study population

Radiographic measurement

Definition of body composition phenotypes for the ccRCC population

Statistical analysis

RESULTS

Body Composition Variables in ccRCC

Factors associating with Overall Survival

Clinical Characteristics Associated with Body Composition Features

DISCUSSION

CONCLUSION

Declarations

Clinical trial number

Competing interests

Conflict of Interest

Funding

Author Contribution

Acknowledgements

Availability of data and material

References

Additional Declarations

Supplementary Files

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