þ Cells and Circulating HLA-DR Monocytes Correlate …...Reducer Sniper (Biocare Medical #BS966L), washed twice in wash buffer, and incubated for 60 minutes in puriﬁed rabbit anti-human

Biology of Human Tumors

Intratumoral CD14þ Cells and CirculatingCD14þHLA-DRlo/neg Monocytes Correlate withDecreased Survival in Patients with Clear CellRenal Cell CarcinomaMichael P. Gustafson1,Yi Lin2, Jonathan S. Bleeker3, Deepti Warad4, Matthew K.Tollefson5,Paul L. Crispen6, Peggy A. Bulur1, Susan M. Harrington7, Rebecca R. Laborde1,Dennis A. Gastineau1,2, Bradley C. Leibovich5, John C. Cheville8, Eugene D. Kwon5, andAllan B. Dietz1

Abstract

Purpose: Immunotherapeutic strategies to treat patients withrenal cell carcinoma (RCC) offer new opportunities for diseasemanagement. Further improvements to immunotherapy willrequire additional understanding of the host response to RCCdevelopment.

Experimental Design: Using a novel approach to understand-ing the immune status of cancer patients, we previously showedthat patients with a certain immune profile had decreased overallsurvival. Here, we examine inmore detail the phenotypic changesin peripheral blood and the potential consequences of thesechanges in RCC patients.

Results: We found that CD14þHLA-DRlo/neg monocytes werethe most predominant phenotypic change in peripheral blood ofRCC patients, elevated nearly 5-fold above the average levels

measured in healthy volunteers. Intratumoral and peritumoralpresence of CD14 cells was an independent prognostic factor fordecreased survival in a cohort of 375 RCCpatients. The amount ofperipheral blood CD14þHLA-DRlo/neg monocytes was found tocorrelatewith the intensity ofCD14 staining in tumors, suggestingthat the measurement of these cells in blood may be a suitablesurrogate for monitoring patient prognosis. The interaction ofmonocytes and tumor cells triggers changes in both cell typeswith a loss of HLA-DR expression in monocytes, increases ofmonocyte survival factors such as GM-CSF in tumors, andincreased production of angiogenic factors, including FGF2.

Conclusions:Our results suggest a model of mutually beneficialinteractions between tumor cells and monocytes that adverselyaffect patient outcome. Clin Cancer Res; 21(18); 4224–33. �2015 AACR.

IntroductionIt is estimated that approximately 70,000 new cases and 13,000

deaths occur annually from cancer of the kidney and renal pelvisin the United States (1). Recent advances have focused on target-ing receptor tyrosine kinases, angiogenesis, or mTOR pathways(2–4). Despite improvements in treatments, durable responsesremain a challenge. Immunotherapy for renal cell carcinoma

(RCC) has had mixed results. High-dose IL2 regimens have onlybeen successful in a small percentage of patients. Other immune-modulating approaches like peptide and dendritic cell vaccinesfor RCC showed promising results, but additional clinical trialsare needed to optimize treatment protocols to improve theirefficacy (5–7). With the preliminary successes of checkpointinhibitors to CTLA-4 and PD-1 (8, 9) in other cancers, there hasbeen a renewed interest for adding immunotherapy to the treat-ment repertoire for RCC.

Tumor-mediated immune suppression remains a significantbarrier to cancer treatment. RCCs can induce both local andsystemic immune suppression via multiple mechanisms(reviewed by Bedke and Stenzl; ref. 10). However, it is unclearhow immunosuppressive mechanisms counteract the compo-nents needed to generate an effective, multifactorial antitumorresponse. Thus, additional understanding of the immune status ofcancer patients is critical for both improving the outcomes of aspecific immunotherapy and identifying relevant biomarkers toguide the selection of patients most likely to benefit from specificimmunotherapy strategies.

Recently, we used quantitative whole blood flow cytometry on160 healthy volunteers and patients from four cancer types,including RCC, to identify immune profiles of cancer patientsthat were prognostic for overall survival (11). We took a com-prehensive approach by measuring all of the major leukocyte

1HumanCellular TherapyLaboratory,Divisionof TransfusionMedicine,Department of Laboratory Medicine and Pathology, Mayo Clinic,Rochester, Minnesota. 2Division of Hematology, Mayo Clinic, Roche-ster, Minnesota. 3Division of Hematology, Sanford Health, Sioux Falls,South Dakota. 4Division of Pediatric Hematology/Oncology, MayoClinic, Rochester, Minnesota. 5Department of Urology, Mayo Clinic,Rochester, Minnesota. 6Department of Urology, University of Florida,Gainesville, Florida. 7Department of Immunology, Mayo Clinic, Roche-ster, Minnesota. 8Department of Pathology, Mayo Clinic, Rochester,Minnesota.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

Corresponding Author: Allan B. Dietz, Mayo Clinic, 200 1st St. SW, Rochester,MN 55905. Phone: 507-266-4258; Fax: 507-284-1399; E-mail:[email protected]

doi: 10.1158/1078-0432.CCR-15-0260

�2015 American Association for Cancer Research.

ClinicalCancerResearch

Clin Cancer Res; 21(18) September 15, 20154224

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populations, including several immunosuppressive cell typessuch as regulatory T cells and myeloid-derived suppressor cells(MDSC). We identified a dominant leukocyte population(CD14þ HLA-DRlo/neg monocytes) within the immune profilesassociated with decreased survival. In this study, we aimed tounderstand the source and consequence of CD14þHLA-DRlo/neg

monocytes in RCC patient cell populations.

Materials and MethodsPatient selection, clinical and pathologic features, and patientoutcome

Peripheral blood samples were collected from 25 patients withmetastatic RCCbefore cytoreductive nephrectomy and 40 healthyvolunteers. Three patients had papillary histology. The clinicalcharacteristics of the RCC patients have been described elsewhere(11). All studies were performed under the approval of the MayoClinic Institutional Review Board. Informed consent wasobtained from all patients. We also identified 375 patients treatedwith radical or partial nephrectomy for unilateral, sporadic,noncystic clear cell RCC between 2000 and 2002, from the MayoClinic Nephrectomy Registry. The clinical features studied includ-ed age, gender, and symptoms at presentation. Patients with apalpable flank or abdominal mass, discomfort, gross hematuria,acute onset varicocele, or the constitutional symptoms of rash,sweats, weight loss, fatigue, early satiety, or anorexia were con-sidered symptomatic at presentation. The pathologic featuresstudied included histologic subtype classified according to theUnion Internationale Contre le Cancer, American Joint Commit-tee onCancer, andHeidelberg guidelines, the 2002primary tumorclassification, regional lymph node involvement, distant metas-tases, the 2002 TNM (tumor node metastasis) stage groupings,tumor size, nuclear grade, coagulative tumor necrosis, sarcoma-toid differentiation, and SSIGN (Stage, SIze, Grade, Necrosis)score (12). To obtain these features, a pathologist (J.C. Cheville)reviewed the microscopic slides from all specimens withoutknowledge of patient outcome. Vital status for patients in theNephrectomy Registry is updated each year. If a patient died inthe previous year, a death certificate was ordered to determine the

cause of death. A visit to our institution within 6 months of thedate of death for metastatic RCC was good documentation thatRCCwas the cause of death. If the death certificate did not supportthis, the medical history was reviewed to determine the cause ofdeath. If a death certificate could not be obtained, the cause ofdeath was verified with the patient's family or local physician.

Peripheral blood immunophenotypingQuantitative whole blood flow cytometry and data analysis,

including hierarchical clustering, for the patient and healthyvolunteer samples were previously described (11). Additionalprinciple component analysis of flow data was performed inPartek Genomics Suite 6.6 (Partek Inc.). Color dot plots of flowdata were generated using the Kaluza flow analysis software(Beckman Coulter).

Immunohistochemical staining and quantitation of CD14expression

A formalin-fixed, paraffin-embedded block with representa-tive tumor tissue was selected for each patient in the cohort.Staining for CD14 was conducted as follows. Tissue sectionswere deparaffinized in xylene and rehydrated in a graded seriesof ethanols. Antigen retrieval was performed by heating tissuesections in Target Retrieval solution pH 6 (Dako #S1699) to121�C using a Digital Decloaking Chamber (Biocare Medical).Sections were cooled to 90�C and incubated for an additional 5minutes before the Decloaking Chamber was opened. Sectionswere washed in running DH2O for 5 minutes and incubated for5 minutes in Wash Buffer (Dako #S3006) before being placedon the Autostainer Plus (Dako) for the following protocol.Sections were blocked for endogenous peroxidase for 5 minutesusing Endogenous Blocking solution (Dako #S2001), washedtwice in wash buffer, incubated 5 minutes in BackgroundReducer Sniper (Biocare Medical #BS966L), washed twice inwash buffer, and incubated for 60 minutes in purified rabbitanti-human CD14 antibody (Sigma PA #HPA001882) diluted1:300 with DaVinci Green antibody diluent (Biocare Medical#PD900M). Sections were washed twice in wash buffer, incu-bated 15 minutes in the rabbit probe from the Mach 3 RabbitHRP-Polymer Kit (Biocare Medical #M3R531L), washed twicein wash buffer, and incubated 15 minutes with the rabbitpolymer from the Rabbit HRP-Polymer Kit. Sections werewashed with wash buffer and visualized by incubating BetazoidDAB (Biocare Medical #BDB2004L) for 8 minutes. Sectionswere washed with DH2O, counterstained with hematoxylin,dehydrated in ethanol, and cleared in xylene. Coverslips weremounted in permanent mounting media. All stained slideswere reviewed and quantitated by a pathologist (J.C. Cheville)without knowledge of patient outcome. Intratumoral and (ifpossible) peritumoral CD14 expression was assessed as absent,focal, moderate, or marked.

Monocyte/cell line coculture experimentsCD14þ monocytes were purified from normal donor leukor-

eduction chambers by density gradient separation (13) andselection of CD14þ monocytes from peripheral blood mononu-clear cells by immunomagnetic selection via the AutoMacs CellSeparator (Miltenyi Biotech). CD14þ cells (2 � 106/mL) wereplated into control medium (DMEM) alone, or incubated with1 � 106 cells/mL of RCC cell lines or normal renal cell epithelialcells. ACHN (CRL-1611, lot #57586991), 786-O (CRL-1932, lot

Translational Relevance

In this study, we demonstrate that the most significantimmunophenotypic change in clear cell renal cell carcinoma(RCC)patients is the inductionofCD14þHLA-DRlo/negmono-cytes. CD14þ monocytes were found to accumulate in renalcell tumors, and their abundance is strongly associated withdecreased patient survival. The correlation between peripheralblood CD14þHLA-DRlo/neg monocytes and the accumulationof CD14þmonocytes in tumors suggest that these cellsmay bea suitable prognostic marker in RCC. CD14þHLA-DRlo/neg

monocytes have been shown to counteract the efficacy ofimmunotherapeutic approaches, and our data provide evi-dence that these cells may also negate the effect of antiangio-genesis therapies through a monocyte/tumor-coordinatedinduction of other angiogenic factors, such as FGF2. Thepresence of CD14þHLA-DRlo/neg monocytes thus serves as abiomarker for patient outcome and as a therapeutic target forimproving the efficacy of immunotherapies.

CD14þ Monocytes as a Prognostic Biomarker in RCC

www.aacrjournals.org Clin Cancer Res; 21(18) September 15, 2015 4225




#7643580), and Caki-1 (HTB-46, lot #5074655) were purchasedfrom the American Type Culture Collection (ATCC) in 2009, andprimary renal epithelial cells (PCS-400-012, lot #58488854) in2010. RCC cell lines were cultured as per the ATCC instructionsless than 6months before the coculture experiments, and primarycells were cultured in Renal Cell Growth medium (Lonza) nomore than 10 passages. ATCC uses short tandem repeats (SRT)profiling to characterize most cell lines. RCC cells were alsocultured alone at 1 � 106 cells/mL in DMEM/10% FBS. Cellsand conditioned supernatants were harvested after 72 hours. Forcocultures, monocytes were reselected with CD14 microbeadswith the negative fraction containing RCC cells. Flow cytometrywas performed to assess purity of cultures.

Angiogenesis arrays and ELISAsThe Proteome Profiler Human Angiogenesis Array kits (R&D

Systems; catalog # ARY007) were used to analyze supernatantsand cell lysates according to the manufacturer's instructions.Equal volumes were used for supernatants and for lysates, andvolumes were normalized to equal cell numbers. FGF2 ELISAs(R&D Systems) were performed via manufacturer's instructions.

RNA isolation and qPCR analysisRNA was isolated from cells via the Qiagen RNeasy Plus Kit

(Qiagen) and made into cDNA with the Transcriptor First StrandcDNA Kit (Roche Diagnostics GmbH). Primers for FGF2, IL1b,GM-CSF, PTX3, and ARG-1 were designed with the Roche Uni-versal Probe Library (UPL) system. PCR reactions were performedwith the LightCycler TaqmanMasterMix, ran and analyzed on theRoche Light Cycler System. Relative transcript levels were deter-mined by assessing the crossing points (Cp) for each gene for eachexperiment. The relative transcript levels were first normalized tothe reference geneGAPDHand calculated by the log2 difference ofthe Cp (DCp) of the reference gene and the gene of interest. Geneexpression changes between samples were calculated as the log2fold change by subtracting the average of theDCp from the controlsample from the average DCp of the test sample (DDCp) and theirfold difference 2�DDCp.

Statistical analysesValues between groups of data were tested for statistical sig-

nificance using the Mann–Whitney nonparametric test forunpaired samples. Correlation analysis was performed usingPearson correlation using Prism, version 5.0 software (GraphPadSoftware). For the qPCR analysis, values were measure for statis-tical significance by using a t-test against a normalized value (1.0;representing 100%). Associations of CD14 expression with clin-ical and pathologic features were evaluated using c2 tests. Asso-ciations of CD14 expression with cancer-specific survival wereillustrated using Kaplan–Meier curves. The magnitudes of theassociations of CD14 expression with death from RCC wereevaluated using Cox proportional hazards regression models andsummarized with HRs and 95% confidence intervals (CI). Theduration of follow-up was calculated from the date of nephrec-tomy to the date of death or last follow-up. Patients who diedfrom causes other than RCC were censored at the date of death,whereas patients who were alive at the time of analysis werecensored at the date of last follow-up. Statistical analyses wereperformedusing the SAS software package (SAS Institute). All testswere two-sided, and P values <0.05 were considered statisticallysignificant. The 3� 3 Fisher exact test was used for the grouping of

intratumoral CD14 staining with peripheral blood phenotypes.The significance level was set at probability of significance set atless than 0.05 with specific calculated P values provided whenapplicable.

ResultsLoss of HLA-DR on CD14þ monocytes is the dominantphenotypic change in peripheral blood of RCC patients

By combining whole blood quantitative flow cytometry andbioinformatics analyses, we generated immune profiles from 160healthy volunteers, cancer patients, and patients with or at risk ofsepsis (11). The overall survival of patients with an abnormalimmune profile was significantly shorter than those patients withan immune profile similar to healthy volunteers. Twenty-fivepatients with RCC were included in this analysis, 9 of which wereclustered into abnormal immune profiles. Here, we further inves-tigated the immunophenotypic changes in peripheral bloodleukocytes of these patients. Because the immune profiles weregenerated from 10 immune phenotypes [granulocytes, mono-cytes, lymphocytes, T cells, B cells, natural killer (NK) cells, CD4þ

T cells, CD4þCD25þCD127lo regulatory T cells (Tregs), CD14þ

HLA-DRlo/neg monocytes, and CD86þ monocytes], we wanted toidentify the immune phenotypes in RCC patients that were mostresponsible for the variation and to determine potential relation-ships between seemingly unrelated cells. We performed a princi-pal component analysis to identify the immune phenotypes withthe largest variation in this dataset (Supplementary Fig. S1).Lymphocytes, CD14þHLA-DRlo/neg monocytes, Tregs, and B cellswere the four immune phenotypes that appeared to be respon-sible for most of the variability. In univariate analyses, 4 of the 10immune phenotypes were different in RCC patients comparedwith healthy volunteers. B cells were lower (healthy volunteer:mean ¼ 247 � 131.4 (SD) cells/mL vs. RCC: 204 � 209.6),whereas granulocytes (healthy volunteer: 4,784 � 1,620 cells/mLvs. RCC: 7,383� 5,025), monocytes (healthy volunteer: 508.9�145.9 cells/mL vs. RCC: 718.2 � 229), and CD14þHLA-DRlo/neg

monocytes (healthy volunteer: 57.7 � 36.6 cells/mL vs. RCC:249.4 � 178.6) were elevated in RCC patients (Fig. 1A).CD14þHLA-DRlo/neg monocytes showed the greatest increase ofany immunephenotype inRCCpatients at nearly 5-fold above themean of healthy volunteers. Correlative analyses identifiedexpected and novel relationships (Fig. 1B, data not shown). Forexample, the levels of B cells correlated positively with CD4þ cellsand granulocytes with CD14þHLA-DRlo/neg monocytes in bothhealthy volunteers and RCC patients; however, Tregs were corre-lated to CD4þ T cells only in RCC patients. The magnitude ofchange in the levels of CD14þHLA-DRlo/neg monocytes in RCCpatients suggests that this immune phenotype is important in thepathology of RCC.

We (14–16) and others (17–20) have demonstrated thatCD14þHLA-DRlo/neg monocytes are major mediators oftumor-induced immunosuppression. Other myeloid cells/MDSCs have been implicated in RCC-induced immunosup-pression, including CD11bþCD14�CD15þ cells (21), lineage-negative (LIN�)CD33þHLA-DR�CD11bþ (22), CD15þ

CD11bþCD14�CD66bþCD33þ (23), CD33þHLA-DR�, andCD15þCD14� cells (24). Because these reports measured cellpopulations from density-gradient–purified mononuclear cells,we wanted to assess the levels of these cells in fresh unfractio-nated whole blood. Because there is considerable diversity in

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Clin Cancer Res; 21(18) September 15, 2015 Clinical Cancer Research4226




the use of phenotypic markers for human MDSCs (25), wenarrowed the characterization of these cells to CD14þHLA-DRlo/neg monocytes, immature LIN�CD33þHLA-DR� cells, andCD33þHLA-DR� cells (gating strategies outlined in Supplemen-tary Fig. S2). Figure 2A shows the forward and side scatterproperties of each of these cell types in an RCC patient todemonstrate the forward and side scatter positioning of thesecells relative to each other. LIN�CD33þHLA-DR� cells residemainly in the lymphocyte compartment (low side scatter andforward scatter). LIN�CD33þHLA-DR� cells and CD33þHLA-DR� granulocytes are distinct populations (26). CD14þHLA-DRlo/neg cells have typical forward/side scatter properties ofmonocytes and should not be considered MDSCs as per conven-tion, but are really monocytes characterized by the single-markerCD14 that has lost HLA-DR expression. As monocytes can befurther subgrouped into classical (CD14þCD16�), intermediate(CD14þCD16þ), and nonclassical (CD14loCD16þ; ref. 27), wemeasured the distribution of these subsets in RCC patients andtheir corresponding HLA-DR expression. The distribution of thesubsets was not different in RCC patients compared with healthyvolunteers, and HLA-DR was significantly lower in each of thesubsets in RCC patients (Supplementary Fig. S3). Although therewas some overlap with monocytes, CD33þHLA-DR� cells almostentirely resided in the high forward/side scatter compartmenttypified by granulocytes. Not unexpectedly, CD15 and CD66b

also identified granulocytes. Interestingly however, as CD33þ

HLA-DR�CD15þCD11bþCD14�CD66bþ granulocytes havebeen shown to copurify with mononuclear cells in RCC patients(21, 22, 24, 28), we rarely observed CD15þCD66bþ cells in themononuclear "fraction" in staining of whole blood samples. Wedid not observe an increase in the amount of LIN�CD33þHLA-DR� cells or a difference of CD66b expression on granulocytes inRCC patients versus healthy volunteers (Fig. 2B).

The assessment of peripheral blood immune phenotypes infresh unmanipulated cells allows us to build a complete picture ofthe differences between the typical peripheral blood composition(both in quantity and composition) of healthy volunteers andthat of RCCpatients. Figure 2C shows the distribution of immunemarkers from the mean of 40 healthy volunteers and 25 RCCpatients. The leukocyte compartment of RCC patients is enlargedby about a third over healthy volunteers with granulocytes andCD14þHLA-DRlo/neg monocytes significantly expanding in thispopulation.

CD14þ monocytes accumulate in human RCCs, and theirpresence is predictive of outcome

Monocytes are capable of migrating from blood to tissues.Therefore, we investigated if the increase in the periphery ofCD14þHLA-DRlo/neg cells was associated with the presence ofmonocytes in the tumor. We examined the associations of tumor

Figure 1.Multiple immunophenotypic changes are observed in RCC patients. A, comparison of four immune phenotypes quantified fromwhole blood in RCC patients versushealthy volunteers (HV). B cells, granulocytes, monocytes, and CD14þHLA-DRlo/neg monocytes were reported as cells per microliter. B, correlation of individualimmune phenotypes. RCC patient graphs are shown on top and healthy volunteer patient graphs on the bottom.






CD14 expressionwith clinical and pathologic features andpatientoutcome using a large cohort (n ¼ 375) of RCC patients. Asummary of clinical and pathologic features for the 375 ccRCCpatients studied is shown in Table 1. Mean age at surgery was 63years (median, 63; range, 26–87), mean tumor size was 6.8 cm(median, 5.8; range, 1.0–22.0), and mean SSIGN score was 3.9(median, 3; range, 0–15). Tumors from 375 RCC patients werestained by immunohistochemistry for CD14 expression. Thesesections were evaluated and divided into four groups classified ashigh (marked CD14 expression), moderate (intermediate CD14expression), and low (focal) or none (absent CD14 expression).Intratumoral, peritumoral, and maximal CD14 expressionsbetween the two are summarized in Supplementary Table S1.Associations of maximal CD14 expression with clinical andpathologic features are summarized in Table 2. The associationof maximal intratumoral and peritumoral CD14 expression withcancer-specific survival is illustrated in Fig. 3A. Themagnitudes of

the associations of CD14 expression with death from RCC aresummarized in Supplementary Table S2. At last follow-up 159patients had died, including 100who died fromRCC at amean of2.3 years following surgery (median, 1.7; range, 0–9). Among the216 patients who were still alive at last follow-up, the meanduration of follow-up was 7.1 years (median, 7.3; range, 0–10);only 5 (2.3%) patients had fewer than 2 years of follow-up.Estimated cancer-specific survival rates (95% CI, number still atrisk) at 1, 3, 5, and 7 years following surgery were 91.0% (88.1–94.0; 328), 79.0% (74.9–83.4; 268), 75.3% (70.9–80.0; 232),and 71.9% (67.3–77.0; 136), respectively. By univariate analysis,patients whose tumors contained moderate CD14 expressionwere nearly 5 times more likely to die from RCC compared withpatients whose tumors contained absent/focal CD14 expression(HR, 4.79; P < 0.001). Patients whose tumors contained markedCD14 expression were over 11 times more likely to die from RCCcompared with patients whose tumors contained absent/focal

Figure 2.Expansion of CD14þHLA-DRlo/neg monocytes and granulocytes in relation to the total leukocyte compartment in RCC patients. A, representative forward scatterand side scatter dot plots of myeloid phenotypes from an RCC patient. The first dot plot is a density dot plot, whereas the middle and right plots are gated andcolored on specific populations. Lin�CD33þHLA-DR� cells (blue), CD14þHLA-DRlo/neg monocytes (red), CD33þHLA-DR– (orange), and CD15þCD66bþ (purple) aredisplayed with ungated cells (gray). B, Lin�CD33þHLA-DR� MDSCs were quantified from whole blood in RCC patients versus healthy volunteers (HV; left graph).The geographic mean fluorescent intensity on granulocytes was measured from a subset of RCC patients and healthy volunteers. C, pie graphs representing themean of the entire leukocyte compartment of RCC patients and healthy volunteers. The mean values of immune phenotypes, including T cells, B cells, NK cells, CD14þ

HLA-DRþ monocytes, CD14þHLA-DRlo/neg monocytes, LIN�CD33þHLA-DR� MDSCs, and granulocytes, were quantified from RCC patients, and healthy volunteers incells permicroliterwere combined to represent the total leukocyte compartment. TheRCC pie graph is sized in relation to the healthy volunteer graph (140% vs. 100%).

Gustafson et al.





CD14 expression (HR, 11.51; P < 0.001). These associations werealso evaluated in a multivariable setting adjusting for the SSIGNscore. After accounting for the association between SSIGN scoreanddeath fromRCC, theHRs for the associations ofmoderate andmarked CD14 expression with death from RCC were 2.87 (P <0.001) and3.03 (P<0.001), respectively. After further adjustmentfor age at surgery, gender, symptoms at presentation, sarcomatoiddifferentiation, and the SSIGN score, the HRs were 2.53 (95% CI,1.45–4.42; P ¼ 0.001) and 2.69 (1.44–5.01; P ¼ 0.002),respectively.

We confirmed that increased fraction of CD14þHLA-DRlo/neg

cells in blood was correlated to intratumoral CD14 expression bymeasuring both in 23 RCC patients and proceeded to classifythemas high,moderate, or low/none for intratumoral expression.We performed CD14/CD15 dual labeling immunohistochemis-try on additional RCC tumors (n ¼ 6) and found that the meanfluorescent intensity of HLA-DR expression on peripheral bloodCD14þ monocytes in RCC patients inversely correlated with theintensity of CD14 staining in their corresponding tumors (Fig.3B). We also confirmed that the CD14þ cells identified in RCC

tumor tissue lack expression of granulocyte cell markers (CD15),indicating that these are not granulocytes with aberrant CD14expression (Fig. 3C). Taken together, these results confirmedpositive correlation between increased intratumoral CD14mono-cytes and increased CD14þHLA-DRlo/neg monocytes in systemiccirculation, suggesting that CD14þHLA-DRlo/neg monocytes canbe a surrogate marker for intratumoral CD14 and a predictor ofdecreased survival.

The interaction of CD14þ monocytes and tumor cells leads toloss of monocyte HLA-DR expression and release ofproangiogenic factors

Knowing that patients with high intratumoral CD14 havedecreased survival, we developed an in vitro model to examinemonocyte/tumor cell interaction. We isolated CD14þ monocytesfrom healthy volunteers and coincubated them for 72 hours withthe renal carcinoma cell line ACHN. HLA-DR expression wasreduced by more than 75% upon coculture with ACHN cellsversus monocytes in media alone (Fig. 4A, left graph; experimen-tal replicates ¼ 7; P ¼ 0.026). This result was specific for tumorcells as HLA-DR expression was not downregulated during cocul-ture with normal primary renal epithelial cells. We also observedloss ofHLA-DR expressionwhenmonocytes were coculturedwithanother RCC cell line, 786-0 (Supplementary Fig. S4). Tumor cellspromoted survival ofmonocytes in these coculture experiments asrecovery of the CD14þ monocytes was 31% compared with 5%for monocytes alone (P¼ 0.004; experimental replicates¼ 5; Fig.4A, right graph).

Because myeloid cells have been implicated in the process ofangiogenesis (reviewed by Schmid and colleagues; ref. 29), wehypothesized that the interaction between the tumor and mono-cytes highlighted by the loss of DRmay also represent the increaseof an angiogenesis program bymonocytes. We used a proteomicsapproach to test supernatants and cell lysates from CD14þ andACHN cells following coculture for the simultaneous expressionof 55 proteins involved in angiogenesis (Fig. 4B). We detectedspecific increases in a number of secreted proteins in the super-natant following monocyte/tumor cell coculture including IL1b,FGF2, and CSF2/GM-CSF. We also found other angiogenic fac-tors, PTX3 and VEGF, that were secreted by monocytes and/ortumor cells but were not changed upon coculture (Fig. 4B). Byexamining the cell lysates, we could further determine the celltypes (CD14þ or ACHN cells) that were producing the proteinsdetected in the supernatant. For example, IL1b and FGF2 werespecifically induced in monocytes when cocultured with tumorcells, whereas GM-CSF and PTX3 were induced in tumor cellswhen cocultured with monocytes. Again, there were other angio-genic factors, like VEGF, that were detected in the cell lysates butdid not change upon coculture. These proteins were not inducedin cocultures of monocytes with primary renal epithelial cells(Supplementary Fig. S4). To further verify these changes, werepeated these experiments with up to 6 other normal donormonocyte preparations but assessed changes by quantitative RT-PCR (Fig. 4C). The RNA transcript levels of GM-CSF and PTX3were significantly induced in tumor cells, whereas IL1b and FGF2were induced in monocytes. Interestingly, FGF2 levels were notdetectable in monocytes cultured in control media, but weregreatly induced upon coculture with tumor cells. Since FGF2expression in tumors has been implicated as a prognostic factorin RCC (30), wemeasured the plasma levels of FGF2 in our cohortof RCC patients. Although we failed to see a significant difference

Table 1. Clinical and pathologic features for 375 ccRCC patients

Feature N (%)

Age at surgery (years)<65 204 (54.4)�65 171 (45.6)

GenderFemale 113 (30.1)Male 262 (69.9)

Symptoms 192 (51.2)Constitutional symptoms 50 (13.3)2002 Primary tumor classificationpT1a 114 (30.4)pT1b 94 (25.1)pT2 71 (18.9)pT3a 40 (10.7)pT3b 50 (13.3)pT3c 3 (0.8)pT4 3 (0.8)

Regional lymph node involvementpNX and pN0 349 (93.1)pN1 and pN2 26 (6.9)

Distant metastasesM0 324 (86.4)M1 51 (13.6)

2002 TNM stage groupingsI 203 (54.1)II 54 (14.4)III 62 (16.5)IV 56 (14.9)

Tumor size (cm)<5 144 (38.4)5 to <7 73 (19.5)7 to <10 75 (20.0)�10 83 (22.1)

Nuclear grade1 24 (6.4)2 136 (36.3)3 183 (48.8)4 32 (8.5)

Coagulative tumor necrosis 97 (25.9)Sarcomatoid differentiation 17 (4.5)SSIGN scoreLow (0–2) 175 (46.7)Intermediate (3–6) 111 (29.6)High (�7) 89 (23.7)






between healthy volunteer and RCC patient plasma FGF2 levels,we found that FGF2 levels inversely correlatedwith the expressionofHLA-DR onCD14þmonocytes (Fig. 4D). Taken together, thesedata demonstrate that monocytes and tumor cells are undergoingreciprocity of inductionwheremonocytes are changing the tumormicroenvironment and the tumor environment is changing themonocytes leading to monocytic survival, increased immunesuppression, and increased angiogenesis.

DiscussionThe relationship between the power of the immune system to

eliminate tumors and the tumors' ability to stifle that power hasbeen a source of intense investigation. Most models of tumor/immune system interaction consist of the tumor actively andunilaterally inhibiting an antitumor response through therelease of tumor-suppressing growth factors, or by specificantigen escape. The data we have presented here provide analternative and powerful model. Our data suggest that tumorsinteract with monocytes resulting in altered monocytes withboth immunosuppressive and immune-independent function-al characteristics. This model also provides a framework to

describe systemic immune suppression as the monocytes havethe capacity to leave the tumor environment and move to theperiphery.

CD14þHLA-DRlo/negmonocytes have known immunosuppres-sive properties via multiple mechanisms, including effector T-cellinhibition, decreased antigen presentation, and defective dendrit-ic cell maturation (14, 15, 18, 19, 31). The degree by which thesecells were increased in RCC patients suggests a dominant role inmediating tumor progression. Other myeloid cells, includingCD33þHLA-DR�CD15þCD66bþ granulocytes, were also elevat-ed in RCC patients. This observation is generally consistent withprevious findings that granulocytic MDSCs are elevated in RCCpatients in the mononuclear fraction of density gradient centri-fugation–purified cells (21–24). However, these results are notdirectly comparable because we performed our flow assays onunfractionated whole blood. In our experience, flow cytometryperformed on whole blood is more amenable to standardizationand direct inter-laboratory comparisons than flow cytometryperformed on fractionated samples (32). The correlation betweenthe levels of CD14þHLA-DRlo/neg monocytes and granulocytes isquite interesting. We do not have any data suggesting that thesecells influence each other; however, it is possible that tumor-

Table 2. Associations of CD14 expression with clinical and pathologic features for 375 ccRCC patients

Maximal intratumoral and peritumoral CD14Absent/focalN ¼ 184

ModerateN ¼ 142

MarkedN ¼ 49

Feature N (%) P value

Age at surgery (years)<65 109 (59.2) 73 (51.4) 22 (44.9) 0.133�65 75 (40.8) 69 (48.6) 27 (55.1)

GenderFemale 64 (34.8) 35 (24.7) 14 (28.6) 0.137Male 120 (65.2) 107 (75.4) 35 (71.4)

Symptoms 74 (40.2) 88 (62.0) 30 (61.2) <0.001Constitutional symptoms 13 (7.1) 20 (14.1) 17 (34.7) <0.0012002 Primary tumor classificationpT1a and pT1b 138 (75.0) 60 (42.3) 10 (20.4) <0.001pT2 27 (14.7) 30 (21.1) 14 (28.6)pT3a, pT3b, pT3c, and pT4 19 (10.3) 52 (36.6) 25 (51.0)

Regional lymph node involvementpNX and pN0 179 (97.3) 128 (90.1) 42 (85.7) 0.004pN1 and pN2 5 (2.7) 14 (9.9) 7 (14.3)

Distant metastasesM0 172 (93.5) 118 (83.1) 34 (69.4) <0.001M1 12 (6.5) 24 (16.9) 15 (30.6)

2002 TNM stage groupingsI 136 (73.9) 58 (40.9) 9 (18.4) <0.001II 25 (13.6) 22 (15.5) 7 (14.3)III 10 (5.4) 34 (23.9) 18 (36.7)IV 13 (7.1) 28 (19.7) 15 (30.6)

Tumor size (cm)<5 100 (54.4) 37 (26.1) 7 (14.3) <0.0015 to <7 35 (19.0) 28 (19.7) 10 (20.4)7 to <10 31 (16.9) 32 (22.5) 12 (24.5)�10 18 (9.8) 45 (31.7) 20 (40.8)

Nuclear grade1 17 (9.2) 7 (4.9) 0 <0.0012 99 (53.8) 34 (23.9) 3 (6.1)3 66 (35.9) 87 (61.3) 30 (61.2)4 2 (1.1) 14 (9.9) 16 (32.7)

Coagulative tumor necrosis 12 (6.5) 53 (37.3) 32 (65.3) <0.001Sarcomatoid differentiation 1 (0.5) 7 (4.9) 9 (18.4) <0.001SSIGN scoreLow (0–2) 128 (69.6) 44 (31.0) 3 (6.1) <0.001Intermediate (3–6) 42 (22.8) 53 (37.3) 16 (32.7)High (�7) 14 (7.6) 45 (31.7) 30 (61.2)

Gustafson et al.





derived factors that promote the survival, mobilization, and/orproliferation of monocytes also influence granulocytes. Our invitro monocyte/coculture system supports this observation withincreased GM-CSF induced during cocultures. It is likely that thisobservation is an indication of increased program of survival forcertain classes of leukocytes.

We found considerable variability in the amount of CD14staining in RCC samples but found a strong adverse correlationto the amount of intratumoral CD14 staining and survival.Sections of the highest grade from the tumor blocks were selectedfor staining and were generally consistent. Multiple blocks werenot assessed; therefore, little is known regarding whole tumorinfiltration ofmonocytes. In addition, it is not known if the tumorheterogeneity or specific oncogene expression influences therecruitment of monocytes differently at primary sites as opposedto metastatic sites.

Our in vitro coculturemodel of CD14þmonocytes and RCC celllines demonstrated that the interaction between monocytes andtumor cells leads to the upregulation of factors that favor tumorprogression.Monocytes inducedGM-CSFproduction from tumorcells, a known potent survival factor for monocytes. Tumor cellscaused the downregulation of HLA-DR on monocytes andinduced expression of the angiogenic factors FGF2 and IL1b (RNAtranscript and protein levels). IL1b is a potent inducer of angio-genesis and has been reported to contribute to tumor invasive-

ness, metastasis, and immune suppression (33). In the RCCsetting, Chittezhath and colleagues recently identified the IL1-IL1R pathway via transcriptomic and molecular profiling as animportant mechanism for the tumor-promoting role of mono-cytes (34). They found that peripheral blood monocytes fromRCC patients displayed elevated expression of genes involved inangiogenesis and invasion. Blockade of the IL-1IL1R pathway intumor/monocyte cocultures inhibited the induction of thesegenes. Through their analysis of tumor-gene expression datafrom 34 RCC patients, they found that IL1b expression corre-lated with myelomonocytic markers, including CD14. Weidentified that IL1b protein levels were induced in monocytescocultured and assessed CD14 accumulation in tumors byimmunohistochemistry. Taken together, our results combinedwith those of Chittezhath and colleagues independently con-firm the role of tumor-promoting effects of monocytes andtheir impact on patient survival. FGF2 has been shown to bea prognostic factor in RCC (35). The high levels of intratumoralCD14þ cells combined with the observation that FGF2 waspredominantly induced in monocytes may provide a mecha-nistic explanation to the failure of anti-VEGF therapies insome RCC patients. In many respects, the actions of tumor-infiltrating monocytes mimic the natural phenomena of tissuerepair. Circulating monocytes are very efficient at homingto sites of injury, whereby they initiate proinflammatory

Figure 3.The presence of intratumoral CD14 isprognostic for survival in RCC andcorrelates with the frequency ofperipheral blood CD14þHLA-DRlo/neg

monocytes. A, cancer-specific survivalfollowing surgery determined bymaximal intratumoral and peritumoralCD14 immunohistochemistry for 375RCC patients based on no staining(blue), focal staining (green),moderatestaining (red), and marked staining(yellow; P < 0.001). Estimated cancer-specific survival rates at 5 years(involvement; 95% CI; number still atrisk) following surgery were 100% (nostaining; 100–100; n ¼ 6), 92.2% (focalstaining; 88.2–96.4; n ¼ 134), 64.1%(moderate staining; 56.4–73.0; n¼ 75),and 41.8% (marked staining; 29.6–58.9;n ¼ 17) for patients with tumors withabsent, focal, moderate, and markedCD14 expression, respectively. B,seventeen patients with correspondingblood and tumor tissue were analyzedfor the frequency of CD14þHLA-DRneg

in peripheral blood and CD14 stainingby immunohistochemistry in theirtumor. Intensity of tumor tissue CD14positivitywas related to loss of HLA-DRexpression on peripheral blood CD14þ

monocytes (P < 0.01). C, tumor CD14þ

cells are CD15 and CD66b negative.Representative tissue costaining CD14(brown) with CD15 or CD66b (pink) atlow and high magnifications.






responses as part of the innate immune response. The mono-cytes/macrophages then switch to an antiinflammatoryresponse that is required for efficient tissue regeneration.Angiogenesis and fibroblast recruitment, mediated in part byFGF2, are additional functions that these cells provide. Thisprocess certainly demonstrates the remarkable plasticity of thefunctions of monocytes (36, 37).

Our data additionally suggest that CD14þHLA-DRlo/neg mono-cytes are both an important therapeutic target and a strongprognostic biomarker for outcome in RCC patients. Perhaps by

targeting these cells through elimination or blocking their migra-tion to tumors, the efficacy of conventional therapies will likelyimprove. For example, we have recently shown that in a similar invitro model with non-Hodgkin lymphomas, the presence ofmonocytes protected the tumor from direct killing with doxoru-bicin by altering the expression patterns of proapoptotic andantiapoptotic proteins (38). This study identifies an additionalmechanism, protection fromchemotherapy-induced cytotoxicity,inwhich the interaction ofmonocytes and tumor cells reduces theefficacy of anticancer treatments.

Because CD14þHLA-DRlo/neg monocytes have multiple immu-nosuppressive functions, they will likely negatively impact immu-notherapeutic approaches. There is emerging evidence that thisphenomenon is already happening in RCC patients. These cellshavebeen shown toadversely affect survivalofRCCpatients treatedwith a multipeptide cancer vaccine (6) and impede the differen-tiation into fullymaturedendritic cells (31). Circulatingmonocytesand granulocytes havepreviously been independently associated asprognostic factors for poor clinical responses to IL2 immunother-apy (39, 40). Therefore, the synergistic interaction between tumorand monocytes may explain the ineffectiveness of many immunetherapies by shutting down both local and systemic antitumorimmunity. Taken together, our results reveal why the presence ofCD14þ cells may reflect the aggressiveness of RCC tumors and thefailure of these tumors to respond to current treatments.

Disclosure of Potential Conflicts of InterestE.D. Kwon has ownership interest (including patents) in Bristol-Myers

Squibb and MedImmune. No potential conflicts of interest were disclosed bythe other authors.

Authors' ContributionsConception and design: M.P. Gustafson, Y. Lin, D. Warad, M.K. Tollefson,P.L. Crispen, B.C. Leibovich, E.D. Kwon, A.B. DietzDevelopment of methodology: M.P. Gustafson, Y. Lin, D. Warad, M.K. Tol-lefson, P.A. Bulur, E.D. KwonAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): M.P. Gustafson, Y. Lin, J.S. Bleeker, D. Warad,M.K. Tollefson, P.L. Crispen, P.A. Bulur, S.M. Harrington, B.C. Leibovich,J.C. Cheville, E.D. Kwon, A.B. DietzAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): M.P. Gustafson, Y. Lin, J.S. Bleeker, D. Warad,R.R. Laborde, J.C. Cheville, E.D. Kwon, A.B. DietzWriting, review, and/or revision of the manuscript: M.P. Gustafson, Y. Lin,J.S. Bleeker, D. Warad, M.K. Tollefson, P.L. Crispen, P.A. Bulur, R.R.Laborde, D.A. Gastineau, B.C. Leibovich, J.C. Cheville, E.D. Kwon,A.B. DietzAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): J.S. Bleeker, J.C. ChevilleStudy supervision: Y. Lin, A.B. Dietz

AcknowledgmentsThe authors thank Debra Head for the assistance with the collection of

samples.

Grant SupportThis study was funded in part by grants from the Department of Laboratory

Medicine and Pathology, Mayo Clinic.The costs of publication of this articlewere defrayed inpart by the payment of

page charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received January 31, 2015; revised April 17, 2015; accepted May 4, 2015;published OnlineFirst May 21, 2015.

Figure 4.Functional and phenotypic consequences of the interaction of CD14þ

monocytes and tumor cells. CD14þ monocytes from healthy volunteers werecultured with an RCC cell line (ACHN) for 72 hours. CD14þ monocytes werereisolated and analyzed for flow cytometric, protein, and gene expressionanalysis. A, representative histogram plot showing HLA-DR levels onCD14þ monocytes in control media (black line), mixed with ACHN cells (grayline), and primary normal renal epithelial cells (dotted line); representativeresults from seven similar experiments (left). Coincubation of CD14þ

monocytes with tumor increased monocyte recovery (gray) compared withCD14þmonoculture (black; n¼ 6; right). B, angiogenesis array blots showingselected proteins after coculture of CD14þ monocytes with ACHN cells fromculture medium supernatants and separated cell lysates. C, quantitativeRT-PCR results from the change in gene expression inCD14þmonocytes (left)and ACHN (right) after coincubation and reseparation as in B. D,measurements of FGF2 plasma levels and correlation between plasma FGF2and corresponding HLA-DR expression on circulating CD14þ cells in RCCpatients. Dotted line represents the mean HLA-DR MFI of healthy volunteers.

Gustafson et al.





References1. HowladerN,Noone A, KrapchoM,Garshell J, NeymanN, Altekruse S, et al.

SEER Cancer statistics review, 1975–2012. Bethesda, MD: National CancerInstitute; 2015.

2. Finke JH, Rini B, Ireland J, Rayman P, Richmond A, Golshayan A, et al.Sunitinib reverses type-1 immune suppression and decreases T-regula-tory cells in renal cell carcinoma patients. Clin Cancer Res 2008;14:6674–82.

3. Luan FL, Hojo M, Maluccio M, Yamaji K, Suthanthiran M. Rapamycinblocks tumor progression: unlinking immunosuppression from antitumorefficacy1. Transplantation 2002;73:1565–72.

4. Michaelson M, Zhu A, Ryan D, McDermott D, Shapiro G, Tye L, et al.Sunitinib in combination with gemcitabine for advanced solid tumours: aphase I dose-finding study. Br J Cancer 2013;108:1393–401.

5. Tatsugami K, Eto M, Harano M, Hamaguchi M, Miyamoto T, MorisakiT, et al. Dendritic cell therapy in combination with interferon-alphafor the treatment of metastatic renal cell carcinoma. Int J Urol 2008;15:694–8.

6. Walter S,Weinschenk T, Stenzl A, ZdrojowyR, Pluzanska A, Szczylik C, et al.Multipeptide immune response to cancer vaccine IMA901 after single-dosecyclophosphamide associates with longer patient survival. Nat Med2012;18:1254–61.

7. Zhou J,WengD, ZhouF, PanK, SongH,WangQ, et al. Patient-derived renalcell carcinoma cells fused with allogeneic dendritic cells elicit anti-tumoractivity: in vitro results and clinical responses. Cancer Immunol Immun-other 2009;58:1587–97.

8. Pardoll DM. The blockade of immune checkpoints in cancer immuno-therapy. Nat Rev Cancer 2012;12:252–64.

9. Ribas A. Tumor immunotherapy directed at PD-1. N Engl J Med 2012;366:2517–9.

10. Bedke J, Stenzl A. Immunologic mechanisms in RCC and allogeneic renaltransplant rejection. Nat Rev Urol 2010;7:339–47.

11. Gustafson MP, Lin Y, LaPlant B, Liwski CJ, Maas ML, League SC, et al.Immune monitoring using the predictive power of immune profiles.J Immunother Cancer 2013;1:7.

12. Frank I, Blute ML, Cheville JC, Lohse CM, Weaver AL, Zincke H. Anoutcome prediction model for patients with clear cell renal cell carcinomatreated with radical nephrectomy based on tumor stage, size, grade andnecrosis: the SSIGN score. J Urol 2002;168:2395–400.

13. Dietz AB, Bulur PA, Emery RL,Winters JL, EppsDE, Zubair AC, et al. A novelsource of viable peripheral blood mononuclear cells from leukoreductionsystem chambers. Transfusion 2006;46:2083–9.

14. Gustafson MP, Lin Y, New KC, Bulur PA, O'Neill BP, Dietz AB. Systemicimmune suppression in glioblastoma: the interplay between CD14þHLA-DRlo/neg monocytes, tumor factors, and dexamethasone. Neuro Oncol2010;12:631–44.

15. Lin Y, Gustafson MP, Bulur PA, Gastineau DA, Witzig TE, Dietz AB.Immunosuppressive CD14þHLA-DR(low)/� monocytes in B-cell non-Hodgkin lymphoma. Blood 2011;117:872–81.

16. Vuk-Pavlovic S, Bulur PA, Lin Y, Qin R, Szumlanski CL, Zhao X, et al.Immunosuppressive CD14þHLA-DRlow/�monocytes in prostate cancer.Prostate 2010;70:443–55.

17. Filipazzi P, Valenti R,Huber V, Pilla L, Canese P, IeroM, et al. Identificationof a new subset of myeloid suppressor cells in pheripheral blood ofmelanoma patients with modulation by a granulocyte-macrophage colo-ny-stimulation factor-based antitumor vaccine. J Clin Oncol 2007;25:2546–53.

18. Hoechst B, Ormandy LA, BallmaierM, Lehner F, Kruger C,MannsMP, et al.A new population of myeloid-derived suppressor cells in hepatocellularcarcinoma patients induces CD4þCD25þFoxp3þ T cells. Gastroenterol-ogy 2008;135:234–43.

19. Jitschin R, Braun M, Buttner M, Dettmer-Wilde K, Bricks J, Berger J, et al.CLL-cells induce IDOhi CD14þHLA-DRlo myeloid-derived suppressorcells that inhibit T-cell responses and promote TRegs. Blood 2014;124:750–60.

20. Poschke I, Mougiakakos D, Hansson J, Masucci GV, Kiessling R. Immatureimmunosuppressive CD14þHLA-DR-/low cells in melanoma patients are

Stat3hi and overexpress CD80, CD83, and DC-sign. Cancer Res 2010;70:4335–45.

21. Zea AH, Rodriguez PC, Atkins MB, Hernandez C, Signoretti S, Zabaleta J,et al. Arginase-producing myeloid suppressor cells in renal cell carcinomapatients: a mechanism of tumor evasion. Cancer Res 2005;65:3044–8.

22. Kusmartsev S, Eruslanov E, K€ubler H, Tseng T, Sakai Y, Su Z, et al. Oxidativestress regulates expression of VEGFR1 in myeloid cells: link to tumor-induced immune suppression in renal cell carcinoma. J Immunol 2008;181:346–53.

23. Rodriguez PC, Ernstoff MS, Hernandez C, Atkins M, Zabaleta J, Sierra R,et al. Arginase I-producing myeloid-derived suppressor cells in renal cellcarcinoma are a subpopulation of activated granulocytes. Cancer Res2009;69:1553–60.

24. Ko JS, ZeaAH,Rini BI, Ireland JL, ElsonP,CohenP, et al. Sunitinibmediatesreversal of myeloid-derived suppressor cell accumulation in renal cellcarcinoma patients. Clin Cancer Res 2009;15:2148–57.

25. Poschke I, Kiessling R. On the armament and appearances of humanmyeloid-derived suppressor cells. Clin Immunol 2012;144:250–68.

26. GustafsonMP, Lin Y,MaasML, VanKeulenVP, Johnson P, Peikert T, et al. Amethod for identification and analysis of non-overlappingmyeloid immu-nophenotypes in humans. PLoS One 2015;10:e0121546.

27. Ziegler-Heitbrock L, Ancuta P, Crowe S, Dalod M, Grau V, Hart DN, et al.Nomenclature ofmonocytes and dendritic cells in blood. Blood 2010;116:e74-e80.

28. Ochoa AC, Zea AH,Hernandez C, Rodriguez PC. Arginase, prostaglandins,and myeloid-derived suppressor cells in renal cell carcinoma. Clin CancerRes 2007;13:721s–6s.

29. Schmid MC, Varner JA. Myeloid cells in the tumor microenvironment:modulation of tumor angiogenesis and tumor inflammation. J Oncol2010;2010:201026.

30. Slaton JW, Inoue K, Perrotte P, El-Naggar AK, Swanson DA, Fidler IJ, et al.Expression levels of genes that regulate metastasis and angiogenesis cor-relatewith advanced pathological stage of renal cell carcinoma.Am JPathol2001;158:735–43.

31. Laborde RR, Lin Y, GustafsonMP, Bulur P, Dietz AB. Cancer vaccines in theworld of immune suppressive monocytes (CD14þHLA-DRlo/neg cells):the gateway to improved responses. Front Immunol 2014;5:147.

32. Gustafson MP, Lin Y, Ryder M, Dietz AB. Strategies for improving thereporting of human immunophenotypes by flow cytometry. J Immun-oTher Cancer 2014;2:18.

33. Apte RN, Voronov E. Is interleukin-1 a good or bad `guy'in tumorimmunobiology and immunotherapy? Immunol Rev 2008;222:222–41.

34. Chittezhath M, Dhillon MK, Lim JY, Laoui D, Shalova IN, Teo YL, et al.Molecular profiling reveals a tumor-promoting phenotype of mono-cytes and macrophages in human cancer progression. Immunity2014;41:815–29.

35. Horstmann M, Merseburger A, von der Heyde E, Serth J, Wegener G,Mengel M, et al. Correlation of bFGF expression in renal cell cancer withclinical and histopathological features by tissue microarray analysis andmeasurement of serum levels. J Cancer Res and Clin Oncol 2005;131:715–22.

36. MokarramN, Bellamkonda RV. A perspective on immunomodulation andtissue repair. Ann Biomed Eng 2014;42:338–51.

37. Doukas J, Blease K, Craig D, Ma CL, Chandler LA, Sosnowski BA, et al.Delivery of FGF genes to wound repair cells enhances arteriogenesis andmyogenesis in skeletal muscle. Mol Ther 2002;5:517–27.

38. Zhang Z, Bulur PA, Dogen A, Gastineau DA, Dietz AB. Immune indepen-dent crosstalk between lymphoma and myeloid suppressor CD14þHLA-DRlow/neg monocytes mediates chemotherapy resistance. Oncoimmunol2015;4:e996470.

39. Donskov F. Interleukin-2 based immunotherapy in patients with meta-static renal cell carcinoma. Dan Med Bull 2007;54:249–65.

40. HermannGG,GeertsenPF, vonderMaaseH, Zeuthen J. Interleukin-2dose,blood monocyte and CD25þ lymphocyte counts as predictors of clinicalresponse to interleukin-2 therapy in patients with renal cell carcinoma.Cancer Immunol Immunother 1991;34:111–4.






2015;21:4224-4233. Published OnlineFirst May 21, 2015.Clin Cancer Res Michael P. Gustafson, Yi Lin, Jonathan S. Bleeker, et al. Cell Renal Cell Carcinoma

ClearMonocytes Correlate with Decreased Survival in Patients with lo/negHLA-DR+ Cells and Circulating CD14+Intratumoral CD14

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