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Visceral Obesity Promotes Lung Cancer Progression—Toward Resolution of the Obesity Paradox in Lung Cancer

Open ArchivePublished:May 25, 2021DOI:https://doi.org/10.1016/j.jtho.2021.04.020

      Abstract

      Introduction

      Although obesity is associated with adverse cancer outcomes in general, most retrospective clinical studies suggest a beneficial effect of obesity in NSCLC.

      Methods

      Hypothesizing that this “obesity paradox” arises partly from the limitations of using body mass index (BMI) to measure obesity, we quantified adiposity using preoperative computed tomography images. This allowed the specific determination of central obesity as abdominal visceral fat area normalized to total fat area (visceral fat index [VFI]). In addition, owing to the previously reported salutary effect of metformin on high-BMI patients with lung cancer, metformin users were excluded. We then explored associations between visceral obesity and outcomes after surgical resection of stage I and II NSCLC. We also explored potential immunologic underpinnings of such association using complimentary analyses of tumor gene expression data from NSCLC tumors and the tumor transcriptome and immune microenvironment in an immunocompetent model of lung cancer with diet-induced obesity.

      Results

      We found that in 513 patients with stage I and II NSCLC undergoing lobectomy, a high VFI is associated with decreased recurrence-free and overall survival. VFI was also inversely related to an inflammatory transcriptomic signature in NSCLC tumors, consistent with observations made in immunocompetent murine models wherein diet-induced obesity promoted cancer progression while exacerbating elements of immune suppression in the tumor niche.

      Conclusions

      In all, this study uses multiple lines of evidence to reveal the adverse effects of visceral obesity in patients with NSCLC, which align with those found in animal models. Thus, the obesity paradox may, at least in part, be secondary to the use of BMI as a measure of obesity and the confounding effects of metformin use.

      Keywords

      Introduction

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      Thus, additional work is needed to develop and validate a method for determining obesity that is reliable and useful in retrospective applications. In our present study, we deployed a novel approach to measure VFA at the L3 level relative to the TFA at the same level to create a normalized metric useful in retrospective applications—the visceral fat index (VFI).
      On the basis of the established knowledge described above, we sought to measure central obesity in a cohort of patients with stage I and II NSCLC undergoing lobectomy at our institution and evaluate its association with oncologic outcomes. As early stage patients are typically treated with surgery alone, without other treatments that may complicate analysis, they provide a context wherein the relationship between central obesity and tumor progression can be studied without additional therapy-associated confounders. For this reason, we focused our study on this subset of the patient pool with NSCLC.
      In this study, we found that excess visceral adiposity, as defined by a relatively high VFI, was indeed associated with poor overall and recurrence-free survival in patients with early stage NSCLC. A high VFI was also inversely related to an inflammatory gene expression signature in the tumor microenvironment (TME) of patients with advanced NSCLC—observations suggestive of robust suppression of antitumor immunity in patients with excess visceral adipose tissue. Although previous retrospective studies of obesity and lung cancer patient outcomes have generated paradoxical conclusions, our present findings suggest an effect of obesity on lung cancer that is aligned with both studies of other human cancers and comparisons of obese and normal mice in numerous preclinical tumor studies, including those we herein report that were generated using two widely used murine lung cancer models. These findings clarify the truly negative relationship that exists between central obesity and lung cancer outcomes, and they present a viable alternative to the use of BMI in retrospective studies of obesity rooted in biology with clear relevance to cancer outcomes.
      Taken together, our clinical and preclinical findings suggest a common potential mechanism for the accelerating effect of obesity on the development of tumor burden in the obese—namely, an apparently multifaceted immune dysfunction prevalent in the tumors of obese mice and patients. Thus, our study provides much needed clarity to the relationship between patient survival with adiposity and NSCLC, providing firm scientific justification for the targeting of obesity’s pro-tumor impact that includes decidedly adverse effects on the antitumor immune response. Our findings also reaffirm the utility and relevance of available mouse models to study further the mechanisms of obesity’s lung cancer-promoting effects. Importantly, they also validate a refined approach for studying obesity in retrospective cancer patient data sets.

      Materials and Methods

      Clinical Data

      All data were acquired under Institutional Review Board–approved protocols. For survival analyses, all consecutive patients with pathologic stages I and II undergoing pulmonary lobectomy at the Roswell Park Comprehensive Cancer Center from October 2008 to December 2015 were included. Relevant clinical data were extracted from the institutional thoracic surgery database and the medical record. Tumor stage, tumor grade, histology, overall survival (OS), and recurrence-free survival (RFS) were extracted from the institutional tumor registry data. All confounders except for age were treated as categorical variables. For analysis, variables were categorized further as described in the Supplementary Material (Supplementary Text 1, which has additional methodological details). OS time started from the day of surgery and concluded at last contact or date of death. RFS time started from the day of surgery and ended with either the date of first recurrence (if exists) or the date of last contact or date of death (if no recurrence). For correlation with patients with immune gene expression, those with advanced-stage NSCLC undergoing molecular testing to guide therapy who had an "immune report card" generated as previously described
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      Robust detection of immune transcripts in FFPE samples using targeted RNA sequencing.
      were analyzed. Of patients with these data available, those on metformin (both past and present metformin users) were excluded.

      Image Analysis

      CT scan results obtained as part of a preoperative PET-CT were analyzed. A single image at L3 level was identified and exported as a DICOM image. In unusual cases in which a preoperative PET-CT scan was unavailable in the clinical record, images at L2 or L1 obtained from chest CT scans were used for analysis. Images at L3, L2, and L1 levels were obtained for a cohort of 46 patients to evaluate the validity of using images at these levels in lieu of L3. Image acquisition was performed by CR, EK, XW, SS, RG, and SY, and measurements were performed using NIH ImageJ (v.1.52 Java 1.8.0_112), as described in the Supplementary Data (Supplementary Text 1). The entire cross-section of the patient was selected and TFA was calculated. The VFA was then selected and measured. Central adiposity was estimated as the ratio between the VFA to the TFA and was labeled the VFI.

      Survival Analyses

      As established categories of VFI that demarcate central obesity do not exist, VFI was first analyzed as a continuous variable in these studies. Age, sex, grade, race, histology, diffusion capacity for carbon monoxide (DLCO), American Society of Anesthesiology (ASA) score, and smoking status were used as covariates in model generation. Univariate analyses (Kaplan-Meier) were performed to evaluate the association of individual variables with OS and RFS. Only variables associated with OS and RFS on univariate analysis were included in model generation by multivariable analyses (Cox proportional hazards). Given the association of VFI with age and sex, interaction variables were included in model generation. Variables were excluded at a significance greater than 0.1 at each step of model generation. In a separate analysis, patients were classified into tertiles (“Top,” “Middle,” and “Bottom”) on the basis of VFI. Univariate (Kaplan-Meier) and multivariable (Cox proportional hazards) survival analyses were performed to compare the OS and RFS of the “Top” and “Bottom” tertiles of patients. Similar analyses were also performed with disease-specific survival (DSS). All analyses were performed in SPSS version 25.

      FFPE Tumor Gene Expression

      RNA was extracted from each FFPE sample and processed for targeted RNA sequencing (RNA-seq), as previously described.
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      Analytical validation of a next-generation sequencing assay to monitor immune responses in solid tumors.
      Gene expression was evaluated by amplicon sequencing of 394 immune transcripts on samples that met validated quality control thresholds (Supplementary Text 1).

      Murine Lung Cancer Models

      Age-matched cohorts of obese and nonobese male C57BL/6 mice were purchased from the Jackson Laboratory, Bar Harbor, ME (stock numbers 380050 and 380056, respectively). These mice were generated by feeding them a high-fat diet (5.2 kcal/gram, 60% fat calories) beginning at 6 weeks of age and continuing for approximately 14 weeks to induce obesity. Mice fed a conventional chow diet (3.8 kcal/gram, 5%–10% fat calories) were used as normal weight (NORM) controls. Mice were weighed before and periodically after initiation of experiments to confirm obese/normal status. All mice were housed in a specific pathogen-free facility, and all procedures were approved by the Institutional Animal Care and Use Committee. The Lewis lung carcinoma (LLC) cell line and its EF1 promoter-driven firefly luciferase-expressing variant (LLC-luc) were purchased from the American Type Culture Collection (ATCC), Manassas, VA (product identifiers CRL-1642 and CRL-1642-LUC2, respectively). Both cell lines were maintained as adherent cultures in Dulbecco's Modified Eagle's medium (DMEM; Gibco) supplemented with 10% v/v fetal bovine serum (Gemini Bioproducts). For tumor challenge experiments, cells were grown to near confluency, detached with trypsin/ethylenediaminetetraacetic acid (EDTA), washed, and resuspended in sterile phosphate buffered saline. For subcutaneous (s.c.) tumor challenge, 1 × 105 tumor cells were implanted into the shaved flanks of obese and NORM mice (n = 5–7 per group). Tumor volumes were measured every 2 to 3 days using a digital caliper. Approximately 21 days postimplantation, mice were euthanized. Tumor sections were harvested and either snap frozen for RNA-seq analysis or mechanically dissociated to generate single-cell suspensions. Tumor-infiltrating leukocytes (TILs) were recovered from the latter after washing and Percoll gradient centrifugation. These and the cells of tumor-draining and tumor-distal lymph nodes as well as the spleen were analyzed by flow cytometry. For studies of pulmonary metastases, 0.25 × 106 LLC-luc cells were injected intravenously by the tail vein into obese and nonobese mice (n = 5 per group), and the development of secondary tumors in the lung was quantified by in vivo bioluminescence imagery using Xenogen IVIS Spectrum technology (PerkinElmer, Waltham, MA). Just before imaging session, mice were injected intraperitoneally with D-luciferin (150 mg/kg body weight; Gold Biotechnology) and anesthetized by isoflurane inhalation. Photonic flux (photon per s) in representative images was quantified with Living Image software (v.4.3.1.0.15880; PerkinElmer).

      Mouse Tumor Gene Expression

      Gene expression in the tumors of control and obese mice (three each) from two independent experiments was assessed by mRNA sequencing (Supplementary Text 1). Raw sequencing data were deposited in the European Nucleotide Archive under accession number PRJEB34297. Tumors of control and obese mice were compared for differential gene expression and gene set enrichment using DESeq2 and gsva Bioconductor software, with false discovery rate (FDR) cutoffs of 0.05 and 0.25, respectively, used for significance testing (Supplementary Text 1).

      Flow Cytometry Analysis

      TILs and cells from tumor-associated lymphoid tissues were recovered from the mice described above. Single-cell suspensions were generated and washed with phosphate-buffered saline containing 2% v/v fetal bovine serum before staining with fluorochrome-conjugated antibodies recognizing surface markers defining key immune cell subsets. Intracellular markers (e.g., FOXP3) were stained after fixation and permeabilized using specialized kits. For intracellular cytokine staining, cell suspensions were re-stimulated with phorbol myristate acetate (PMA) and Ionomycin (Millipore-Sigma) in the presence of Brefeldin-A (Thermo Fisher Scientific) for 4 hours at 37°C followed by washing, surface staining, and fixation/permeabilization (eBioscience) before incubation with conjugated anti-interferon-gamma (IFN-γ) antibodies. Multicolor flow cytometry data were collected using a BD LSR II analyzer and analyzed using FlowJo software (version 10.7, BD Biosciences). For specific antibodies used in this study, see Supplementary Table 1.

      Results

      On the basis of the described inclusion and exclusion criteria, 554 patients with stages I and II NSCLC undergoing lobectomy were selected for analysis. Of these, reliable fat area measurements were obtained in 513 patients—499 (97.3%) at L3, 5 (0.9%) at L2, and 9 (1.8%) at L1. Similarly, 159 patients with advanced-stage NSCLC with molecular testing had reliable fat area measurements—146 (91.8%) at L3, 10 at L2 (6.3%), and three at L1 (1.9%). Interobserver correlation of VFI measurements was good (n = 53; R2 = 0.95; Supplementary Fig. 1A). Correlation of measurements between L2 and L3 levels (n = 29; R2 = 0.92; slope = 1.05) and between L1 and L3 levels (n = 28; R2 = 0.85; slope = 1.05) was also good (Supplementary Fig. 1). Therefore, in the few cases wherein measurements at L3 were not available, measurements at L2 or L1 were used. Importantly, CT scans of these patients could be used to clearly identify individuals with distinctly predominant visceral or subcutaneous adipose tissue distributions (Supplementary Fig. 2A and B).

      Visceral Obesity Is Associated With Poor Overall and RFS in Patients With Early NSCLC Undergoing Surgical Resection

      We initially sought to establish the relationship between visceral obesity, as measured by VFI, and several clinically relevant metrics. We found that VFI was not associated with BMI (Pearson correlation coefficient = −0.006, p = 0.9, Supplementary Fig. 2C). Nevertheless, VFI was associated with sex and age. Specifically, the mean VFI of males was higher than females (0.56 versus 0.37; p < 0.01). VFI also tended to be elevated with increasing age (Pearson’s correlation coefficient = 0.32, p < 0.01).
      Univariate analyses revealed a statistically significant association of sex, ASA score, tumor grade, histology, age, DLCO, and VFI with OS. Similarly, sex, tumor grade, tumor stage, ASA score, and VFI were associated with RFS. Multivariable analysis resulted in a final model of OS that retained age, sex, DLCO, ASA score, VFI, tumor grade, and the interaction term between VFI and age. Similar analysis resulted in a final model of RFS that retained only tumor grade, tumor stage, and VFI as predictive variables. These results are summarized in Table 1.
      Table 1Univariate Associations and Multivariable Models of Overall and Recurrence-Free Survival in Patients With Stages I and II NSCLC Undergoing Lobectomy
      VariablesMeasureUnivariateMultivariable
      Overall Survival HR (95% CI)Recurrence-Free SurvivalOverall Survival HR (95% CI)Recurrence-Free Survival
      Age67 ± 10.41.05 (1.03–1.06)1.01 (0.99–1.03)1.04 (1.02–1.06)
      Sex (female vs. male)305 (59.5%) Female0.57 (0.41–0.80)0.65 (0.43–1.00)0.64 (0.44–0.92)
      Race (white vs. others)462 (90.1%) White0.70 (0.36–1.31)0.40 (0.15–1.10)
      DLCO77.3 ± 21.20.99 (0.98–1.00)0.99 (0.98–1.00)0.99 (0.98–1.00)
      ASA score (high vs. low)248 (48.3%) high2.07 (1.47–2.90)1.49 (0.97–2.28)1.55 (1.07–2.24)
      BMI27.2 ± 5.61.01 (0.98–1.04)1.01 (0.97–1.05)
      VFI0.45 ± 0.147.30 (3.18–24.08)5.19 (1.14–23.69)4.51 (0.93–21.76)
      Tumor grade (high vs. low)181 (35.3%) High1.62 (1.16–2.26)1.95 (1.28–2.98)1.64 (1.16–2.32)1.88 (1.22–2.88)
      Tumor stage (II vs. I)140 (27.3%) Stage II1.21 (0.84–1.74)2.19 (1.43–3.36)1.97 (1.28–3.04)
      HistologyAdeno 317 (61.8%)
      Adeno vs. otherSqCC 139 (27.1%)0.81 (0.64–1.03)1.04 (0.76–1.42)
      SqCC vs. otherOther 57 (11.1%)1.33 (1.02–1.72)1.02 (0.71–1.47)
      Smoking statusNever—52 (10.1%)
      Current vs. neverFormer—175 (34.1%)0.79 (0.53–1.17)0.94 (0.59–1.49)
      Former vs. neverCurrent—286 (55.8%)1.03 (0.78–1.37)1.01 (0.72–1.42)
      Note: Variables associated with survival on univariate analysis (p < 0.1; in bold) were included in multivariable analyses. Only variables included in the final multivariable models are found.
      Adeno, adenocarcinoma; ASA, American Society of Anesthesiology; BMI, body mass index; CI, confidence interval; DLCO, diffusion capacity for carbon monoxide; HR, hazard ratio; SqCC, squamous cell carcinoma; VFI, visceral fat index.
      To observe the potential relationship between VFI and lung cancer survival outcomes, patients were stratified by VFI for Kaplan-Meier and Cox proportional hazards analyses. Comparison of the top and bottom VFI tertiles (VFIterts) revealed an association between high VFI and worse OS and RFS (Fig. 1A and B). Multivariable modeling confirmed these results with high VFI group associated with RFS (hazard ratio [HR] = 1.79, 95% confidence interval: 1.04–3.08; Fig. 1C). The model of OS retained VFItert and the interaction terms between VFI and age and VFI and sex (Supplementary Table 2). These results suggest that in contrast to high-BMI, visceral obesity as defined by elevated VFI is negatively associated with survival in patients with early stage lung cancer.
      Figure thumbnail gr1
      Figure 1Overall and recurrence-free survival of patients with high and low VFI. (A) Overall survival curves generated for 513 patients separated categorized as having high (top tertile; N = 171) and low (bottom tertile; N = 171) visceral adiposity as defined by VFI score revealed decreased survival with high visceral adiposity (HR = 1.84, 95% CI: 1.21–2.81). (B) Recurrence-free survival curves revealed decreased survival with high visceral adiposity (HR = 1.82, 95% CI: 1.06–3.11). (C) Expected recurrence-free survival curves using the Cox proportional hazards model for revealed decreased survival with high visceral adiposity (HR = 1.79, 95% CI: 1.04–3.08). CI, confidence interval; HR, hazard ratio; VFI, visceral fat index.
      Of the 513 patients, cause of death was unknown in 41 patients. Therefore, DSS was analyzed in 472 patients. Similar to OS and RFS, VFItert (top tertile versus bottom tertile) was associated with DSS on Kaplan-Meier analysis (HR = 2.1, p = 0.025). VFI as a continuous variable did not reach statistical significance, however (p = 0.1). On multivariate analysis, VFItert (top tertile versus bottom tertile) was associated with worse DSS (HR = 2.25, 95% CI: 1.16–4.37, p = 0.016; Supplementary Fig. 3) and was the only variable retained in the model. When VFI was analyzed as a continuous variable, age (0.006), VFI (p = 0.001), tumor grade (p = 0.003), and the interaction variable between VFI and age (p < 0.001) were associated with DSS.

      Visceral Obesity Is Associated With Alterations in the Immune TME in Patients With Late-Stage NSCLC

      Despite the reported survival advantage found in patients with high-BMI lung cancer,
      • Dahlberg S.E.
      • Schiller J.H.
      • Bonomi P.B.
      • et al.
      Body mass index and its association with clinical outcomes for advanced nonsmall-cell lung cancer patients enrolled on Eastern Cooperative Oncology Group clinical trials.
      • Leung C.C.
      • Lam T.H.
      • Yew W.W.
      • Chan W.M.
      • Law W.S.
      • Tam C.M.
      Lower lung cancer mortality in obesity.
      • Lam V.K.
      • Bentzen S.M.
      • Mohindra P.
      • et al.
      Obesity is associated with long-term improved survival in definitively treated locally advanced non-small cell lung cancer (NSCLC).
      a preponderance of data, including that obtained from a number of preclinical mouse tumor models, has revealed a profoundly negative effect of obesity on the cells of the antitumor immune response.
      • Wang Z.
      • Aguilar E.G.
      • Luna J.I.
      • et al.
      Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade.
      ,
      • Algire C.
      • Amrein L.
      • Bazile M.
      • David S.
      • Zakikhani M.
      • Pollak M.
      Diet and tumor LKB1 expression interact to determine sensitivity to anti-neoplastic effects of metformin in vivo.
      • Nimri L.
      • Saadi J.
      • Peri I.
      • Yehuda-Shnaidman E.
      • Schwartz B.
      Mechanisms linking obesity to altered metabolism in mice colon carcinogenesis.
      • Ringel A.E.
      • Drijvers J.M.
      • Baker G.J.
      • et al.
      Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity.
      To evaluate the potential association of VFI with tumor immune gene expression, we analyzed existing data from patients with advanced-stage NSCLC that underwent molecular testing to guide their therapy. In these patients, a targeted transcriptome (an “immune report card”) analysis was carried out as described in the Methods section. Thus, the expression of 395 immune genes was evaluated for 159 patient lung tumors (Supplementary Table 3 for a summary of patient characteristics).
      Unsupervised clustering analysis led to the discovery of three major inflammation clusters, namely, inflamed, borderline, and noninflamed tumors (Fig. 2A). The inflammatory status of the tumors was significantly associated with both VFI as a continuous variable (Fig. 2B) and VFItert as well (Fig. 2C). Specifically, cases in the top VFItert were significantly over-represented in the noninflamed tumor cluster (p = 0.04), whereas those in the bottom VFItert were over-represented among the inflamed tumors to a considerably significant degree (p = 0.0085) (Fig. 2C). Within noninflamed tumors (n = 38), a significantly higher proportion of moderately proliferative TMEs were found in patients in the bottom tertile (p = 0.015) compared with those in the top tertile, wherein a larger proportion of highly proliferative TMEs was found, indicating low visceral obesity may confer improved OS in NSCLC (Supplementary Fig. 4).
      • Pabla S.
      • Conroy J.M.
      • Nesline M.K.
      • et al.
      Proliferative potential and resistance to immune checkpoint blockade in lung cancer patients.
      Further gene-wise differential gene expression analysis confirmed the significant (p < 0.05) down-regulation of inflammation-associated genes in the top VFItert. Notably, tumors from high-VFI patients displayed enhanced expression of CDKN3 (a driver of cell proliferation linked to poor prognosis when over-expressed in lung cancer
      • Fan C.
      • Chen L.
      • Huang Q.
      • et al.
      Overexpression of major CDKN3 transcripts is associated with poor survival in lung adenocarcinoma.
      ), and BCL6, a promoter of tumor growth and survival in NSCLC
      • Deb D.
      • Rajaram S.
      • Larsen J.E.
      • et al.
      Combination therapy targeting BCL6 and phospho-STAT3 defeats intratumor heterogeneity in a subset of non-small cell lung cancers.
      and CD44, a marker of cancer stemness and poor prognoses in multiple cancers. Among the transcripts significantly under-represented in the tumors of high-VFI patients were those encoding chemokines or their receptors (including those associated with T helper 1 [Th1]-type antitumor immune responses), the Th1 transcription factor Tbet, T cell lineage markers (e.g., CD4 and CD8), components of the T cell receptor and co-stimulatory signaling cascades (e.g., CD3, CD86), and the machinery of antigen presentation (Supplementary Table 4). These results strongly link central obesity (defined by high VFI) to a diminished immune activity in the lung TME that may stem from impaired T cell recruitment or expansion in this niche—conditions likely permissive to the growth and progression of lung cancers.
      Figure thumbnail gr2
      Figure 2Changes in the tumor immune microenvironment with visceral obesity in advanced-stage NSCLC. (A) Heatmap of unsupervised clustering of immune response GEX (rank: columns) and 159 samples (rows) annotated by VFI tertiles, BMI thresholds, and cell proliferation groups. (B) Boxplot of inflammation cluster groups for VFI as a continuous variable with Wilcoxon test p values found for all pairwise comparisons. (C) Bar chart revealing distribution of inflammation clusters within top and bottom VFI tertiles with chi-square proportion test p values found. BMI, body mass index; GEX, gene expression rank; N.S., not significant; VFI, visceral fat index.
      We further explored the potential association of VFI with covariates, such as BMI, race, gender, primary histology, and staging. As expected, BMI category was inversely associated with VFI (p = 0.00652), and pathologic stage was significantly associated with VFItert (p = 0.0024). In addition, male gender was highly associated with high VFI status (p = 1.54E-11) (Supplementary Table 5). These findings are in line with the generally accepted notion that males are more susceptible to visceral adiposity than females.
      • Nauli A.M.
      • Matin S.
      Why do men accumulate abdominal visceral fat?.
      They also merit further investigation into the role of gender in visceral versus subcutaneous fat distribution within the sexes and the potential implications for long-term lung cancer patient outcomes and the antitumor immune response.
      Interestingly, examining the correlation between traditional obesity status (as defined by a BMI of 30 or greater) with patient VFItert revealed that a significantly higher proportion of obese cases was found in bottom VFItert than in the top tertile (p = 0.009) (Supplementary Fig. 5B). This surprising result suggests that only 15% of the VFI high cases would be classified as obese using the prevailing method of identifying patients with obesity in retrospective studies. In addition, no association was found between standard BMI categories and tumor inflammation state (Supplementary Fig. 5A). These results link visceral adiposity in patients with lung cancer to potential immune dysfunction expected in the obese host, and they further highlight the markedly different relationships that exist between VFI and BMI and lung cancer biology.

      Obesity Exacerbates Lung Cancer Progression in Mice While Altering TME Gene Expression

      In parallel, we observed the effects of obesity on tumor progression and antitumor immunity in widely used preclinical models of lung cancer. For this, the in vivo conditions present in overweight and obese lung cancer patients were recreated using a well-characterized approach for diet-induced obesity (DIO) in mice. Prolonged administration of high-fat diet (e.g., one containing 60% calories from fat) to mice of an obesity-susceptible genetic background, such as C57BL/6, results in progressive weight gain and an accumulation of visceral fat
      • Magnuson A.M.
      • Regan D.P.
      • Fouts J.K.
      • Booth A.D.
      • Dow S.W.
      • Foster M.T.
      Diet-induced obesity causes visceral, but not subcutaneous, lymph node hyperplasia via increases in specific immune cell populations.
      compared with normal diet-fed control mice (NORM). Cohorts of obese and NORM mice were injected s.c. with LLC cells, and subsequent tumor development was monitored. As generally found in implantable mouse tumor models,
      • Wang Z.
      • Aguilar E.G.
      • Luna J.I.
      • et al.
      Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade.
      ,
      • Ringel A.E.
      • Drijvers J.M.
      • Baker G.J.
      • et al.
      Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity.
      obese mice supported more robust tumor growth compared with nonobese controls in this model (Fig. 3A). In a complementary model of pulmonary metastatic disease, obese mice challenged intravenously with a modest number of LLC-luc cells developed markedly enhanced lung tumor burden compared with NORM controls within 26 days postinjection (Fig. 3B and C). These results reveal the decidedly protumor effects associated with obesity in mouse models that align closely with the relationship between lung cancer outcomes and central obesity brought to light by the use of VFI in our clinical studies.
      Figure thumbnail gr3
      Figure 3Obesity-mediated effects on progression of LLC tumors in mice. (A) C57BL/6 mice were fed a high-fat (to induce obesity) or normal diet for approximately 14 weeks before s.c. implantation of 1 × 105 cells by s.c. injection into the shaved flanks. Mean tumor volumes were calculated using the following formula: volume = 0.5 × length × width
      • Lauby-Secretan B.
      • Scoccianti C.
      • Loomis D.
      • et al.
      Body fatness and cancer--viewpoint of the IARC working group.
      . (B, C) Obese and normal mice were challenged with intravenous tail vein injection of 0.25 × 106 LLC-luc cells. After 26 days from injection, tumor burden (pulmonary metastases) was visualized by BLI after i.p. injection of d-luciferin (150 mg/kg) using IVIS technology. p < 0.05 (∗), < 0.02 (∗∗), and < 0.001 (∗∗∗) in standard t test. Error bars depict the SEM. Revealed are a representative image (B) and mean tumor burden measurements (A and C) from three to five independent experiments. BLI, bioluminescence imagery; DIO, diet-induced obesity; i.p., intraperitoneal; LLC, Lewis lung carcinoma; LLC-luc, Lewis lung carcinoma luciferase-expressing variant; NORM, normal weight; s.c., subcutaneous.
      To gain insight into the potential mechanisms underlying the effects of obesity on tumor progression, we set out to document the transcriptomic changes in the TME associated with excess adiposity. RNA was harvested from s.c. tumor sections (n = 6 each) generated in the experiments described in Figure 3A, and RNA-seq analysis was carried out. Expression of 187 and 217 genes was respectively up-regulated and down-regulated by greater than 1.2× in tumors of obese compared with normal with adjusted Wald’s test p value of less than 0.05 in analysis with DESeq2.
      • Love M.I.
      • Huber W.
      • Anders S.
      Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
      Single-sample gene set enrichment analysis using the gene set variation analysis method
      • Hänzelmann S.
      • Castelo R.
      • Guinney J.
      GSVA: gene set variation analysis for microarray and RNA-seq data.
      revealed significant divergences of multiple gene sets related to metabolism and cancer biology (Bayes-moderated t test p < 0.05 with FDR < 0.20).
      Of the 18,025 genes expressed in these tumors, expression of only 33 differed by greater than or equal to 1.5-fold between obese and control mice at a FDR less than 0.05 (Supplementary Table 6). The five genes that were most up-regulated in obese tumors compared with controls were all found to either encode proteins involved in fat metabolism (i.e., pyruvate dehydrogenase kinase 4, lipase K, fatty acid-binding protein 4) and lipid oxidation in particular
      • Pettersen I.K.N.
      • Tusubira D.
      • Ashrafi H.
      • et al.
      Upregulated PDK4 expression is a sensitive marker of increased fatty acid oxidation.
      or to have been previously associated with adiposity (i.e., angiotensin II receptor 2,
      • Xue Q.
      • Chen P.
      • Li X.
      • Zhang G.
      • Patterson A.J.
      • Luo J.
      Maternal high-fat diet causes a sex-dependent increase in AGTR2 expression and cardiac dysfunction in adult male rat offspring.
      bone morphogenetic protein 5
      • Shao G.C.
      • Luo L.F.
      • Jiang S.W.
      • Deng C.Y.
      • Xiong Y.Z.
      • Li F.E.
      A C/T mutation in microRNA target sites in BMP5 gene is potentially associated with fatness in pigs.
      ). Examination of gene expression at the level of biological processes revealed a 1.2- to 1.3-fold enrichment of the gene sets involved in adipogenesis and oxidative phosphorylation in the tumors of obese mice. As might be expected, given the robust tumor growth in the obese mice, genes involved in angiogenesis, epithelial-mesenchymal transition, hypoxia, and glycolysis were also up-regulated in obese tumors. In contrast, expression of genes associated with the immunologically relevant IL6-JAK-STAT3 signaling pathway was significantly reduced in the tumors of obese compared with control mice. In addition, expression of Stat4, a central driver of Th1 immunity and Areg, a gene known to be up-regulated by regulatory T cells (Treg) in peripheral tissues (including lungs), was nominally down-regulated and up-modulated in obese tumors, respectively (Supplementary Fig. 5 and Supplementary Table 6).
      These findings suggest that obesity’s still poorly understood impact on the TME and its potential fueling of tumor progression may be multifaceted in nature, involving processes capable of aiding tumors directly and by opposing the activity of immune cells in the TME. Indications of reduced interleukin-6/STAT3 signaling were surprising, however, because elevated serum levels of interleukin-6 have been reported in the obese,
      • Weisberg S.P.
      • McCann D.
      • Desai M.
      • Rosenbaum M.
      • Leibel R.L.
      • Ferrante A.W.J.R.
      Obesity is associated with macrophage accumulation in adipose tissue.
      and this cascade is generally thought to have multiple protumor effects in cancer cells themselves, including expression of genes that promote cell proliferation, survival, angiogenesis, invasiveness, metastasis, and stemness.
      • Taniguchi K.
      • Karin M.
      IL-6 and related cytokines as the critical lynchpins between inflammation and cancer.
      Interestingly though, an inverse relationship has been reported between STAT3 expression and commitment to oxidative metabolism/tricarboxylic acid (TCA) cycle in other cancers (i.e., prostate cancer).
      • Oberhuber M.
      • Pecoraro M.
      • Rusz M.
      • et al.
      STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer.
      Also, given the known involvement of STAT3 signaling in glycolytic metabolism,
      • Valle-Mendiola A.
      • Soto-Cruz I.
      Energy metabolism in cancer: the roles of STAT3 and STAT5 in the regulation of metabolism-related genes.
      a reduced engagement of this cascade could also reflect a favoring of oxidative metabolism in the obese TME. Indeed, metabolic pathways that consume the available oxygen and enforce hypoxia in the TME were recently found to be an obstacle for the mounting of effective immune cell activity,
      • Scharping N.E.
      • Menk A.V.
      • Whetstone R.D.
      • Zeng X.
      • Delgoffe G.M.
      Efficacy of PD-1 blockade is potentiated by metformin-induced reduction of tumor hypoxia.
      and altered lipid transport and metabolism that can alter the availability of free fatty acids may also modify immune function in the TME.
      • Ringel A.E.
      • Drijvers J.M.
      • Baker G.J.
      • et al.
      Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity.
      A relative up-regulation of genes involved in transforming growth factor (TGF)-beta-signaling suggests that along with these more recently described mechanisms, obesity may enhance the notoriously anti-inflammatory cytokine, contributing to a staunchly immune-suppressive TME under obese conditions.

      Obesity Attenuates Antilung Cancer Immune Responses in Mice

      It is well appreciated that metabolic factors play a nontrivial part in regulating the phenotypic differentiation, fitness, and activity of immune cells.
      • Beckermann K.E.
      • Dudzinski S.O.
      • Rathmell J.C.
      Dysfunctional T cell metabolism in the tumor microenvironment.
      ,
      • Zhang L.
      • Romero P.
      Metabolic control of CD8+ T cell fate decisions and antitumor immunity.
      Obesity is also known to have a profound effect on metabolism at an organismal or systemic level that is accompanied by immune dysfunction and smoldering inflammation.
      • Deng T.
      • Lyon C.J.
      • Bergin S.
      • Caligiuri M.A.
      • Hsueh W.A.
      Obesity, inflammation, and cancer.
      Yet, the precise effects of obesity on critical participants in the cellular response to lung cancer in mice and patients are just beginning to be understood. We therefore set out to dissect the impact of the obese state on the immune cell constituents of the TME in the mice described in Figure 3A using a multicolor flow cytometry-based approach. Our findings revealed multiple indications that obesity has a deleterious effect on the potency of the antitumor response.
      Leukocyte infiltration of s.c. LLC tumors was markedly suppressed in obese mice relative to NORM control tumors. This reduced intratumoral cellularity reflected a relative dearth of CD4+ and CD8+ T cells in the obese TME (Fig. 4A). The potentially tumoricidal CD8+ T cell compartment of obese mice was further observed to express considerably elevated levels of the immune checkpoint/exhaustion markers LAG3 and PD-1 on their surface relative to their NORM counterparts (Fig. 4B) in line with previous assessments of T cell phenotypes in obese tumor-bearing mice.
      • Wang Z.
      • Aguilar E.G.
      • Luna J.I.
      • et al.
      Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade.
      ,
      • Kado T.
      • Nawaz A.
      • Takikawa A.
      • Usui I.
      • Tobe K.
      Linkage of CD8+ T cell exhaustion with high-fat diet-induced tumorigenesis.
      Similarly, enhanced checkpoint expression levels were found on conventional Th CD4+ T cells from DIO tumors (data not shown), and the CD8+ T cells recovered from obese mouse tumors stained more prominently with the dead cell-identifying dye LD Aqua (Fig. 4C), indicative of an obesity-related defect in the fitness and the antitumor potential of intratumoral T cells. Further suggesting an obesity-associated suppression of antitumor responses, the numbers of TILs capable of producing the tumoricidal Th1 cytokine IFN-γ were much lower in the TILs recovered from DIO mice (Fig. 4D).
      Figure thumbnail gr4
      Figure 4Obesity-mediated effects on the antitumor immune response to s.c. LLC tumors. C57BL/6 mice were fed a high-fat (to induce obesity) or normal diet for 14-16 weeks before implantation of 1 × 105 cells by injection in shaved flanks (n = 5–7 per group). (A) The density of TILs was found, and flow cytometry analysis of tumor cell suspensions obtained in the experiment presented in revealed the frequencies of CD4+ and CD8+ T cells among the TILs. (B, C) The proportions of CD8+ T cells expressing the checkpoint molecules LAG3 and PD-1 and the viable fraction of CD8+ T cells were found and quantified. (D) The levels of IFN-γ–producing TILs in obese and nonobese mice were also found. (E) The relative proportions of Tregs among the TILs were found and (F) the levels of activated Treg markers. (G) The frequencies of Foxp3+ Tregs expressing the checkpoint molecules LAG3 and PD-1. p < 0.05 (∗), < 0.02 (∗∗), and (∗∗∗∗) < 0.001 in standard t test. Error bars depict the SEM. Revealed are representative flow plots and the mean quantification of replicates from one of two to three independent experiments. DIO, diet-induced obesity; IFN, interferon; LLC, Lewis lung carcinoma; NORM, normal weight; PD-1, programmed cell death protein-1; s.c., subcutaneous; TIL, tumor-infiltrating leukocyte; Treg, regulatory T cell.
      In addition to effector cell deficits, enhanced suppressive cell phenotypes were also found in the tumors of obese mice. Foxp3+ Treg cells were modestly yet consistently enriched in the tumors of obese mice (Fig. 4E). Moreover, these obese tumor-infiltrating Tregs displayed considerable up-regulated markers of an activated phenotype (CD44, ICOS) (Fig. 4F). Because the activated or effector-like Treg phenotype is associated with both robust suppressive potency and a tendency to accumulate in murine and human tumors,
      • Chao J.L.
      • Savage P.A.
      Unlocking the complexities of tumor-associated regulatory T cells.
      ,
      • Plitas G.
      • Konopacki C.
      • Wu K.
      • et al.
      Regulatory T cells exhibit distinct features in human breast cancer.
      this observation suggests that obesity may bolster this subpopulation of suppressor cell known to be responsible for pathologic immune suppression in the cancer setting. Concordantly, the levels of immune checkpoint molecules LAG3 and PD-1 expected to be highly expressed on the surface of intratumoral Tregs
      • Chao J.L.
      • Savage P.A.
      Unlocking the complexities of tumor-associated regulatory T cells.
      were enhanced in DIO Tregs compared with those recovered from controls (Fig. 4G). We also observed a marked elevation in the abundance of tumor CD11b+GR1(Ly6C/G)+ MDSCs in obese mice—an observation in agreement with previous studies
      • Ostrand-Rosenberg S.
      Myeloid derived-suppressor cells: their role in cancer and obesity.
      —and these cells displayed higher levels of programmed death-ligand 1 (PD-L1) on their surface in the obese setting compared with NORM controls (Fig. 5A and B). Obesity also seemed to bolster proportions of potentially suppressive tumor-associated macrophages (CD11b+/F480+) and expression of the immune checkpoint molecule PD-L1 on these cells (Fig. 5C and D). In general, these differences in T and myeloid cell phenotypes were muted in other tissues surveyed including tumor-draining and distal lymph nodes and the spleens compared with the tumors of obese and control mice (data not show) suggesting the immune cells of the TME may be particularly susceptible to obesity-related modulation. Interestingly, our findings suggest that, in contrast to the known ability of obesity to down-regulate Treg abundance in visceral fat
      • Feuerer M.
      • Herrero L.
      • Cipolletta D.
      • et al.
      Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters.
      and blood, obesity can actually enhance Treg presence and activation in the TME and tumor-associated tissues. This previously unappreciated effect, potentially in concert with the potentiation of several other notoriously suppressive elements of the immune response (i.e., MDSCs, PD-L1:PD-1 signaling, exhausted CD8 T cells) may contribute to the enhanced tumor progression found in obese mice.
      Figure thumbnail gr5
      Figure 5Obesity-mediated effects on MDSCs in s.c. LLC tumors. C57BL/6 mice were fed a high-fat (to induce obesity) or normal diet before implantation of 1 × 105 cells by injection in shaved flanks (n = 5–7 per group). Flow cytometry analysis of tumor cell suspensions obtained from . (A) The frequencies of MDSC (GR1+/CD11b+) among the TILs were found by flow cytometry as were (B) levels of PD-L1 expression on these suppressor cells. (C, D) Similarly, we determined the frequencies of tumor-associated macrophages (CD11b+/F480+) and the surface levels of PD-L1 on these cells. p < 0.05 (∗) and < 0.02 (∗∗) in standard t test. Error bars depict the SEM. Revealed are representative flow plots and the mean quantification of replicates from one of two independent experiments. DIO, diet-induced obesity; LLC, Lewis lung carcinoma; MDSC, myeloid-derived suppressor cell; MFI, mean fluorescence intensity; NORM, normal weight; PD-L1, programmed death-ligand 1; s.c., subcutaneous; TIL, tumor-infiltrating leukocyte.

      Perturbance by Obesity of Immune Pathways in Mouse Tumors Can Be Discerned in Tumor Transcriptome

      To obtain insights into the molecular mechanisms by which obesity may influence tumor biology, we compared mRNA sequencing-based transcriptomes of LLC tumors from obese and normal mice (n = 6 each). Expression of 187 and 217 genes was respectively up-regulated and down-regulated by greater than ×1.2 in tumors of obese compared with normal controls with adjusted Wald’s test p value less than 0.05 in analysis with DESeq2.
      • Love M.I.
      • Huber W.
      • Anders S.
      Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
      Single-sample gene set enrichment analysis using the gene set variation analysis method
      • Hänzelmann S.
      • Castelo R.
      • Guinney J.
      GSVA: gene set variation analysis for microarray and RNA-seq data.
      revealed significantly increased expression of multiple gene sets related to metabolism in tumors of obese mice (Bayes-moderated t test p < 0.05 with FDR < 0.20) (Supplementary Fig. 6) and cancer biology (such as angiogenesis and epithelial-mesenchymal transition; data not shown). In contrast, tumors of obese mice had significantly diminished expression of many immune-related gene sets (Supplementary Fig. 5). These results suggest that obesity triggers marked alterations in the TME.
      In all, these results illustrate the multifaceted nature of the immune dysfunction associated with obesity across varied mouse tumor models. These effects, which include enhanced suppressor cell presence and function and effector cell deficiencies, resonate with our transcriptomic characterization of high-VFI patient tumors as harboring a low degree of immunologic/inflammatory activity. When taken together, these preclinical and clinical findings strongly suggest that the poor outcomes found in both centrally obese mice and patients are rooted in common biological underpinning, that is, obesity-mediated effects on the antitumor immune response. Although further work will be necessary to pinpoint the precise mechanisms at play in the subversion of antitumor immunity in the obese, and indeed several potential mechanisms have been proposed to date, our results suggest that at least some of the key elements (e.g., obesity-altered tumor metabolism and immune suppression) may be explored in mouse tumor models for in-depth, mechanistic studies.

      Discussion

      Obesity is an established risk factor in the development of multiple cancer types and a negative prognostic factor for many as well.
      • Lauby-Secretan B.
      • Scoccianti C.
      • Loomis D.
      • et al.
      Body fatness and cancer--viewpoint of the IARC working group.
      ,
      • Sung H.
      • Siegel R.L.
      • Torre L.A.
      • et al.
      Global patterns in excess body weight and the associated cancer burden.
      ,
      • Siegel R.L.
      • Miller K.D.
      • Jemal A.
      Cancer statistics, 2019.
      Nevertheless, the relationship between obesity and lung cancer outcomes is less clear. Although obese mice generally display accelerated tumor development and growth compared with normal weight controls in preclinical models of lung cancer and other malignancies, analysis of clinical data has suggested a survival benefit and better responses to therapies among patients with obesity (particularly when obesity is defined by BMI)—giving rise to a so-called “obesity paradox.” Nevertheless, a number of potential confounding factors may account for this surprising association.
      One potential confounder in clinical studies of obesity and lung cancer outcomes is the relationship between smoking and obesity. It is possible that patients with obesity smoke less, and this may be misinterpreted as a beneficial effect of obesity. For example, Lam et al.
      • Lam T.K.
      • Moore S.C.
      • Brinton L.A.
      • et al.
      Anthropometric measures and physical activity and the risk of lung cancer in never-smokers: a prospective cohort study.
      revealed that obesity is not associated with increased lung cancer in never smokers. Nevertheless, a large study of approximately 450,000 patients evaluated this in detail, and after adjusting for smoking, the relationship of obesity (measured by BMI) to lung cancer incidence still held,
      • Smith L.
      • Brinton L.A.
      • Spitz M.R.
      • et al.
      Body mass index and risk of lung cancer among never, former, and current smokers.
      suggesting the possible confounding issue of smoking is not causatively important, but nevertheless essential to consider to avoid erroneous interpretations. Another pitfall in the interpretation of clinical results concerning obesity’s effects on lung cancer survival seems to involve the widespread use of metformin to treat type II diabetes—a common comorbidity in patients with overweight and obesity. This drug has long been studied for its potential anticancer effects in preclinical models and clinical data sets with varying degrees of potency reported in the literature, and it has been revealed to have immunomodulatory effects.
      • Scharping N.E.
      • Menk A.V.
      • Whetstone R.D.
      • Zeng X.
      • Delgoffe G.M.
      Efficacy of PD-1 blockade is potentiated by metformin-induced reduction of tumor hypoxia.
      ,
      • Eikawa S.
      • Nishida M.
      • Mizukami S.
      • Yamazaki C.
      • Nakayama E.
      • Udono H.
      Immune-mediated antitumor effect by type 2 diabetes drug, metformin.
      ,
      • Zhang Z.
      • Li F.
      • Tian Y.
      • et al.
      Metformin enhances the antitumor activity of CD8+ T lymphocytes via the AMPK-miR-107-Eomes-PD-1 pathway.
      We recently linked metformin use to significantly better survival outcomes specifically in obese patients with early stage lung cancer.
      • Yendamuri S.
      • Barbi J.
      • Pabla S.
      • et al.
      Body mass index influences the salutary effects of metformin on survival after lobectomy for stage I NSCLC.
      It is possible that the context-specific benefit of this drug may account at least partially for the better lung cancer outcomes found in patients with high BMI.
      Our present findings and those of others suggest that a major contributor to the obesity paradox arises from the manner in which obesity is typically measured. Most retrospective studies evaluating the association between obesity and lung cancer use revealed BMI as an anthropomorphic measure of obesity. There is growing evidence that the use of BMI has serious limitations in the study of obesity and its effects on human health and disease outcome. Although different anatomical distribution patterns of adipose tissue accumulation (i.e., different body compositions) have major implications for human health, BMI measurements are not capable of differentiating between these patterns.
      • Cespedes Feliciano E.M.
      • Kroenke C.H.
      • Caan B.J.
      The obesity paradox in cancer: how important is muscle?.
      As such, BMI is a poor measure of visceral obesity, and this is particularly limiting in studies of obesity's effects in diverse patient demographics. Specifically, central obesity is known to occur in Asian Americans and East Asians at a lower BMI than Caucasians.
      WHO Expert Consultation
      Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies.
      Also, germane to the study of the obesity-lung cancer connection, recent studies suggest that an ability to discern between visceral and s.c. obesity is critically important for defining obesity in a meaningful way and for exploring the interaction of obesity and processes determining lung cancer outcomes.
      It is important to note that others have used WC, WHR, or imaging to explore the relationship between lung cancer outcomes and central obesity, specifically, with findings in agreement with our own. Leitzmann et al.
      • Leitzmann M.F.
      • Moore S.C.
      • Koster A.
      • et al.
      Waist circumference as compared with body-mass index in predicting mortality from specific causes.
      analyzed the NIH—American Association of Retired Persons study data set consisting of 225,712 individuals and found that patients with a higher WC had a higher lung cancer-specific mortality. This was again revealed in a pooled analysis of 1.6 million patients with 23,732 incident lung cancer cases in which WC was associated with a higher risk of lung cancer.
      • Yu D.
      • Zheng W.
      • Johansson M.
      • et al.
      Overall and central obesity and risk of lung cancer: a pooled analysis.
      These findings are in agreement with those of Ardesch et al.
      • Ardesch F.H.
      • Ruiter R.
      • Mulder M.
      • Lahousse L.
      • Stricker B.H.C.
      • Kiefte-de Jong J.C.
      The obesity paradox in lung cancer: associations with body size versus body shape.
      that implicated a positive association between lung cancer risk and an obese body shape (as determined by WC, WHR, and Body Shape Index). Similarly, measurement of visceral adipose tissue was also associated with poor lung cancer prognosis in patients undergoing chemotherapy.
      • Nattenmuller J.
      • Wochner R.
      • Muley T.
      • et al.
      Prognostic impact of CT-quantified muscle and fat distribution before and after first-line-chemotherapy in lung cancer patients.
      The findings of these studies and those of our own clearly illustrate the vital need for accurate measures of central obesity in studies of lung cancer.
      Our clinical findings are not only in line with the effects of obesity and tumor progression found in many murine lung cancer models but they also reflect the logical outcome of the roundly pro-tumor alterations that obesity triggers in human and murine gene expression (Fig. 2 and Supplementary Tables 4 and 6) and its effects on the immune cell composition of the TME reported by us
      • Yendamuri S.
      • Barbi J.
      • Pabla S.
      • et al.
      Body mass index influences the salutary effects of metformin on survival after lobectomy for stage I NSCLC.
      (Fig. 3) and others.
      Deploying a novel CT-based approach for the retrospective quantification of visceral and s.c. adipose tissues, we here report definitely that central or visceral adiposity (i.e., high VFI status) is negatively associated with both OS and RFS in patients with early stage NSCLC. This finding contrasts starkly with previous observations made using BMI that have, in part, given rise to the obesity paradox. Also, unlike the disease outcomes found in patients with high BMI, high VFI status corresponded, at least in a general sense, with the course of disease revealed in obese tumor-bearing mice. Indeed, in both mice and human, central obesity seems linked to worse outcomes, such as accelerated tumor growth (Fig. 3) and shorter survival times (Fig. 1), respectively.
      Our parallel observations of human lung TME gene expression and the cellular analysis of murine tumors clearly suggest that obesity undercuts key elements of the T cell and inflammatory response in the tumor niche while enhancing known mediators of immune suppression, which include environmental stresses, immune-dampening signaling pathways, and pro-tumor phenotypes in notorious cellular antagonists of antitumor immunity. In particular, side-by-side evaluation of human and murine lung tumors reveal common indications of a suppressed immune presence in the TME of obese hosts, albeit through distinct approaches in some cases. Perhaps most notably, in both human and mouse tumors, transcripts encoding elements of Th1 immunity were reduced by central obesity. In our comparison of immune-relevant transcripts among top and bottom VFItert patient tumors, Th1 chemokines CXCL10, CXCL11, and CXCL9 and Th1 transcription factors STAT1 and Txb21/Tbet were found to be underrepresented in the high-VFI samples as were IFIT1 and IFIT3, which are reported to be induced by IFNgamma signaling
      • Zeng W.
      • Miyazato A.
      • Chen G.
      • Kajigaya S.
      • Young N.S.
      • Maciejewski J.P.
      Interferon-gamma-induced gene expression in CD34 cells: identification of pathologic cytokine-specific signature profiles.
      (comparison p < 0.05; Supplemental Table 4). Meanwhile, in our analysis of mouse tumor gene expression, STAT4, which plays an important role in the generation of Th1 immunity, was among the genes down-regulated by obesity (Supplementary Table 6), and both these observations are very much in line with our cellular analysis of the mouse tumors in the s.c. LLC model revealing a lower density of IFN-γ–producing TILs in obese tumors (Fig. 4D). It is interesting to note that although our flow cytometric characterization of mouse tumors revealed enhancements in Tregs and PD-L1 expression by myeloid cells, general levels of CD274 (PD-L1) and Foxp3 transcript were found to be underrepresented in high-VFI tumors. This apparent incongruity could reflect, in the case of PD-L1, a low level of IFNgamma signaling
      • Cerezo M.
      • Guemiri R.
      • Druillennec S.
      • et al.
      Translational control of tumor immune escape via the eIF4F-STAT1-PD-L1 axis in melanoma.
      implicated by our other observations to be active in the obese TME or the expression of these factors by a number of tumor residents,
      • Dimitrakopoulos F.I.
      • Papadaki H.
      • Antonacopoulou A.G.
      • et al.
      Association of FOXP3 expression with nonsmall cell lung cancer.
      including tumor cells themselves.
      Across species, we observed a stymied T cell presence in the tumors of high-VFI patients and DIO mice indicated by reduced pan-T cell and lineage-defining transcripts (CD2, CD3, CD4, CD8, CD247) and the scarcity of CD4+ and CD8+ TILs in our flow cytometry analysis, respectively (Fig. 4 and Supplementary Table 4). Also, among the transcripts relatively down-regulated in high-VFI tumors were several involved in the process of antigen presentation (CIITA and several HLA transcripts; Supplementary Table 4). This observation is both compatible with a more immunologically quiet TME in the obese and potentially explanative as defective stimulation of effector T cell immunity by antigen-presenting cells in the obese TME may in part contribute to the aforementioned defects in the tumor T cell presence owing to poor expansion. The compromised viability of CD8 T cells suggested by our mouse model experiments (Fig. 4C) presents another possible explanation for both a lack of cells with antitumor potential and the enhancement of tumor growth found in the obese context—namely that the already inhospitable TME is made even less conducive to T cell infiltration by factors stemming from a state of obesity. In addition, the obesity-enhanced suppressor cell phenotypes seen among the myeloid compartment of the murine TILs (i.e., elevated MDSCs and tumor-associated macrophages marked by high PD-L1 expression; Fig. 5) are also in line with defective immune priming (in favor of immune suppression). Also, because a number of chemokine genes are relatively under-expressed in high-VFI patient tumors (Supplementary Table 4), deficient recruitment of effector T cells is another potential mechanism at play. As the previously unappreciated obesity-associated enhancement of the TILTreg phenotype that we observe in our mouse studies (Fig. 4EG) remains to be explored in depth, further study is needed to define the relative importance of this and the other potential mechanisms of obese-related immune dysfunction to overall disease outcome. Nevertheless, our present findings implicate the soundly predicted, likely multifaceted, but incompletely delineated suppressive effects of obesity on the immune TME of lung tumors as probable contributors to obesity’s protumor effects in lung cancer.
      This study marks an important step in fostering a better understanding of the so-called obesity paradox, and its findings clarify the impact of distinct body fat distribution patterns on lung cancer outcomes. Our findings results may inform continued efforts to better predict lung cancer outcomes and management, apply treatments, and develop novel therapeutic approaches to prevent or control early stage lung cancers across a patient pool that is increasingly overweight and obese.

      Acknowledgments

      This work was supported by intramural research support from RPCCC to Drs. Yendamuri and Barbi, American Lung Association Lung Cancer Discovery Award to Dr. Barbi, and National Cancer Institute, USA grant P30-CA016056 to RPCCC. We thank the Genomics Shared Resource facility of Roswell Park Comprehensive Cancer Center for performing the RNA sequencing experiments.

      Supplementary Data

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