Radiotherapy of Human Sarcoma Promotes an Intratumoral Immune Effector Signature

This article is featured in Highlights of This Issue, p. 4545

Sarcomas are a heterogeneous group of malignant tumors of mesenchymal origin. They can arise anywhere in the bone, cartilage, fat, muscle, blood vessels, or other connective or supportive tissue (1). Sarcomas comprise 1% of all adult cancers and about 15% of all childhood cancers there, with high mortality and metastatic potential (2). There is clear evidence from patients and preclinical models that the immune system can control the development of malignancies, a concept termed tumor immunoediting and immunosurveillance (3). Moreover, spontaneous tumor-specific immunity can be detected in cancer patients and in tumor-bearing mice (4, 5). The targets of such responses are usually tumor-associated antigens, of which the group of cancer-testis (CT) antigens is a prominent representative (6). Cancer-testis antigens are especially interesting because they are highly immunogenic and as their name suggests, their expression is restricted to germ cells and cancer cells. More than 100 cancer-testis genes are known to date (7, 8). However, when tumor-specific immunity fails to eliminate cancer, it has proven very difficult to boost this response such that tumor control is achieved. The adaptive arm of the immune response consists of T and B lymphocytes, including antibodies, CD8⁺ T cells that recognize tumor antigens presented by MHC class I (MHC-I) molecules on tumor cells (9) are thought to be major effectors. Natural killer (NK) cells, which represent the innate immune system, may also mediate antitumor effects by direct cytotoxicity toward malignant cells that express low levels of MHC-I and by producing immunostimulatory cytokines such as IFN-γ (10). Immune effector functions, however, are hampered by an immunosuppressive environment, which is created by the tumor and to which FoxP3⁺ regulatory T cells as well as myeloid cells contribute through a variety of mechanisms including TGF-β, arginase-1, and interleukin-10 (IL-10; refs. 11–13). The tumor microenvironment presumably significantly influences the outcome of conventional cancer therapies (14, 15). Human sarcomas are treated by radiotherapy, chemotherapy, and/or surgery (16). Recent evidence suggests that both radio- and chemotherapy result in the mobilization of innate and adaptive immunity (17–19), but very little is known about the impact of radiotherapy on the immune infiltrate in human sarcomas. We investigated the effect of radiotherapy on the tumor microenvironment in sarcoma patients using paired biopsies that were collected before and after radiotherapy from 38 sarcoma patients. Upon radiotherapy we found an increase of many cell types and molecules that are characteristic for protective immunity, whereas those associated with immunoregulation were often downregulated. Furthermore, we found a relatively high expression of immune effectors and low expression of immune suppressors after radiotherapy in those patients who survived for 3 years or more after radiotherapy in comparison to those who survived for less than 3 years and died. Our results justify further investigating whether a combination of radiotherapy and immune stimulation results in a better clinical outcome than either therapy alone.

Formalin-fixed, paraffin-embedded (FFPE) paired tumor samples were collected from a cohort of 38 sarcoma patients before and after radiotherapy. Tumor samples were retrieved from the archives of the Department of Pathology, University Hospital Zurich, Switzerland. The samples after radiotherapy were obtained from planned resection and the time points of collection following radiotherapy varied between 1 and 89 days (Supplementary Table S1). Patients with nonmetastatic disease and only those patients who received neo-adjuvant radiotherapy before surgery as a part of their standard treatment regimen were included in the study. The patients were treated by standard photon-radiotherapy and received a cumulative dose of 40 to 60 Gy (2 Gy per treatment). An overview of the sarcoma subtypes, cumulative radiation dose, percentage of dead cells following radiotherapy and clinical outcome is given in Table 1. The ethics committee “Ethical Committee of the Canton of Zurich” specifically approved this study (EK-2011-0224/0). For this study, all relevant data were retrieved from the computerized database of the Department of Pathology, University Hospital Zurich, and transferred into a separate anonymous database. Fifteen patient samples from our previous work overlapped in this study (17), but were specifically approved under the study (EK-2011-0224/0). All patients signed the informed consent form in accordance with the declaration of Helsinki and were given a unique code, thus protecting the patient identity.

Three punches (0.6-mm diameter) were randomly taken from each of the FFPE blocks using a tissue arrayer MTA-1 (Beecher Instruments). Deparaffinization was conducted in 300 μL elution buffer [1 M Tris pH 8, 0.5 M EDTA pH 8, 20% SDS (all Ambion), ultrapure water (Sigma)] at 95°C for 10 minutes on a shaker followed by centrifugation at 4°C, 14,000 rpm for 10 minutes, followed by digestion with 3 μL of Proteinase K (18 ± 4 mg/mL; Roche) at 55°C for 72 hours. The samples were then centrifuged at 4°C, 14,000 rpm for 2 minutes. The supernatants (250 μL) were transferred into fresh tubes and 750 μL TriZol LS reagent (Invitrogen) was added to each sample while vortexing followed by homogenization by centrifugation at 4°C, 14,000 rpm for 2 minutes using QIA-shredder columns. This was followed by RNA purification using phenol and chloroform. Two hundred microliters of chloroform was added to each flow-through with mild vortexing, followed by incubation at room temperature for 5 minutes until the 2 phases separated, followed by centrifugation at 4°C, 14,000 rpm for 15 minutes. The upper aqueous phase containing the RNA was transferred into a new tube, 20 μg glycogen (Invitrogen) was added followed by the precipitation of RNA by adding 0.5 mL isopropanol [99.9% (v/v); Kantonsapotheke Zürich]. Samples were incubated at room temperature for 15 minutes and then centrifuged at 4°C, 14,000 rpm for 20 minutes. The supernatant was removed and the pellet was washed with 1 mL 75% ethanol (Merck), air-dried, dissolved in Rnase-free water (Sigma), and digested with 80 U/mL DNAse I (New England Biolabs) at room temperature for 15 minutes, followed by inactivation using 2 mmol/L EDTA (Ambion) at 65°C for 10 minutes. The concentration and purity was evaluated using the NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies). Three hundred nanograms of RNA was reverse transcribed using the high-capacity cDNA Reverse Transcription Kit (Applied Biosciences). The cDNA was either used immediately for quantitative reverse transcription PCR (qRT-PCR) reactions or stored at −20°C until use. Because of limited material availability the cDNA was preamplified. Preamplification was conducted for 14 cycles using TaqMan PreAmp Master Mix Kit (Applied Biosystems). All kits were used according to the manufacturer's instructions.

The expression of target genes was analyzed using TaqMan gene expression assays containing commercially available predeveloped TaqMan reagents with optimized primer and probe concentrations and TaqMan 1× universal master mix (Applied Biosystems; Supplementary Table S2), on a RotoGene Q real-time PCR cycler (Qiagen). The reaction mixture (10 μL) consisted of 1 μL cDNA, 3.5 μL water, 0.5 μL primer, and 5 μL TaqMan 1× universal master mix. The following cycle conditions were used: initial hold for 2 minutes at 50°C and 10 minutes at 95°C, the probes were cycled 45 times at 95°C for 15 seconds and at 60°C for 1 minute. All reactions were conducted in at least triplicates. Threshold cycle (Ct) values were determined using the Rotor-Gene Q Series software 1.7. ΔCt levels of the transcripts were calculated by normalization to the endogenous control (β-actin). The change in expression (ΔΔCt) levels of the target genes following radiotherapy is given as the fold change in expression (2^{− (ΔΔCt)}) and is determined as (ΔCt _{before radiotherapy} − ΔCt _{after radiotherapy}). Ct values >38 cycles were interpreted as negative for gene expression. Fold changes in the range of a fold increase of >0.5 and <2 was considered as not significant. This range is marked as shaded area in the figures.

Immunohistochemistry (IHC) was conducted on FFPE-paired tissue sections obtained from a cohort of 37 to 38 sarcoma patients. Sections were stained with mouse antihuman monoclonal antibodies against CD4 (clone 1F6, 1:30; ZYMED Laboratories Inc.), CD8 (clone C8/114B, 1:100; DAKO A/S), MHC-I (clone C21, 1:1000; RDI Research Diagnostics, Inc.), CD3 (clone F7.2.38, 1:50; Dako), CT7 (clone CT7-33, 1:80; DAKO A/S), NY-ESO-1 (clone E978, 1:50; ZYMED). Sections were counterstained with hematoxylin, dehydrated, and mounted. All sections were processed with the Ventana Benchmark automated staining system (Ventana Medical Systems) using Ventana reagents for NY-ESO-1, CT7, CD4, CD8, and CD3 and the BondMax (Vison BioSystems) for MHC-I. UView (Ventana) or Refine DAB (Vision BioSystems) were used as chromogens against the primary antibodies. The slides were scanned on a NDP.view2 software (Hamamatsu), and analyzed using the IHC analysis software (NDP.analyze; Hamamatsu). The fields were observed at a magnification of 200× (field of view = 493.1 × 368.5 μm⁻¹). The IHC analysis was conducted by counting 10 random fields. The staining was scored on a scale of 0 to 5 for the expression of NY-ESO-1 and MAGE-C1/CT7 as a percentage, based on the number of positive cells expressing the antigen to the total number of cells in a high-power field (HPF). The tumor infiltrates were calculated as the number of cells expressing CD3, CD4, and CD8 per HPF. The MHC-I sections were acquired on Zeiss-Axiovert 200M (Carl Zeiss Light Microscopy) inverse microscope using Carl Zeiss Axiovision CD28 imaging system. The scoring for MHC-I expression was done based on the intensity of staining (details in Supplementary Table S3). Two individuals conducted the scoring blindly and independently for MHC-I and 1 individual conducted the scoring blindly for the other stainings. The IHC staining was interpreted in conjunction with a single hematoxylin and eosin (H&E) stained slide by a pathologist (B. Bode). The malignant nature of the tumors for the IHC evaluation and qRT-PCR analysis was apparent from the H&E-stained slides.

Correlations between the different immune response related transcripts was assessed using the Spearman's rho correlation coefficient (ρ) and the significance two-tailed analysis (P value) was used to analyze the statistical significance (IBM SPSS statistics software). The dot plots for all significant correlations were generated using the Graphpad-Prism software. Statistical significance was defined as P < 0.05.

For visualizing the gene expression profile in the sarcoma patients following radiotherapy, heatmaps were generated using software: R, Bioconductor library “gplots,” heatmap.2 software. Subtracting the mean expression value across patients centered the values for each transcript. No gene-specific scaling (standardization) was done, so that the information about the relative signal strength between probes remained intact. The color tone in the heatmaps was calibrated, so that saturated red (upregulation) and saturated green (downregulation) were reached at values equal to 3 times the standard deviation of the expression values of the entire matrix. Heatmaps were created for all the patients using the ΔΔCt values (ΔCt _{before radiotherapy} − ΔCt _{after radiotherapy}). For the purpose of clustering the genes, the de novo expression was assigned a ΔΔCt value of −10 and the loss of expression was assigned a ΔΔCt value of +10. A hierarchical clustering method using software: R, Bioconductor library “gplots,” heatmap.2 software was used to group genes on the basis of similar expression patterns, in relation to their survival status (green indicates similar behavior of genes and red indicates the reverse). Statistical analysis was conducted for each transcript between the cohort before and after radiotherapy using the two-tailed bivariate analysis (P value; Graphpad-Prism) on the ΔCt values after normalization to β-actin.

To understand the immunomodulatory effects of radiotherapy in sarcomas, we retrospectively analyzed the expression of several immune response-related transcripts and CT-antigens (Supplementary Table S2) by qRT-PCR analysis on paired FFPE tumor tissues from 37 sarcoma patients before and after radiotherapy (Table 1). We observed that radiotherapy resulted in upregulated transcripts specific for several immune effector cells or proteins including CD45, CD3, CD4, CD8, MHC-I, MHC-II, perforin, granzyme B, IFN-γ, IL-12, and NKG2D in most patients. In addition, we observed de novo expression of perforin, NKG2D, and iNOS in 2 or more patients. TNF-α transcripts were upregulated in several patients but downregulated in others. Concomitantly, the expression of various transcripts related to immune suppression (FoxP3, CD68, CD163, CTLA-4, arginase-1, IDO, PD-1, PD-L1, IL-10, TGF-β, and BTLA) was downregulated in some patients but upregulated or unchanged in others. At least in one of the patients the expression of FoxP3, PD-1, CTLA-4, BTLA, or IL-10 was lost following radiotherapy (Fig. 1A and B, Table 2). In addition, radiotherapy resulted in a substantial upregulation or de novo expression of one or more CT-antigens (CT7, LAGE-A1, MAGE-A9, and NY-ESO-1; Fig. 1C, Table 2). As the fold change in expression in terms of de novo or loss of gene expression cannot be computed, the grand mean was calculated excluding these values. Our data suggest that radiotherapy results in a favorable upregulation of transcripts associated with effector function when compared to those associated with immune suppression, therefore indicating that radiotherapy may presumably promotes protective immunity in the tumor (Table 2 and Supplementary Fig. S4).

To validate our findings at the protein level we compared the expression of CT-antigens, MHC-I as well as the infiltration of lymphocytes by immunohistochemistry in 37 to 38 paired FFPE sections obtained from sarcoma patients before and after radiotherapy. Radiotherapy upregulated the expression of MHC-I in 30 of 38 patients (Fig. 2D) and resulted in an increased infiltration by CD4⁺ and CD8⁺ T lymphocytes (Fig. 2A–C, Table 3). Furthermore, radiotherapy resulted in a substantial upregulation or de novo expression of the CT-antigens NY-ESO-1 in 13 of 38 patients (Fig. 2E, Table 3) and of CT7 in 17 of 38 patients (Fig. 2F, Table 3). Interestingly, most of the patients with an upregulated expression of one or more CT-antigens had a concomitant upregulation of MHC-I and/or increased infiltration of T cells (patient number: 2, 3, 5, 7, 8, 9,10, 11, 15, 17,19, 20, 22, 23 25, 27, 31, 33, 34, 35, and 36), which approximately comprises 55.3% of the patients. Those changes following radiotherapy were significant when compared to the untreated samples (Supplementary Fig. S5). Because of limited availability of material, we could not conduct staining for additional CT-antigens. We know from our previous work, that the expression of CT-antigens is upregulated upon irradiation in different tumor types (17). Representative sections (Fig. 2G) illustrate that there is a difference in the degree of radiotherapy-induced changes between individual sarcoma patients. A particular gene may be homogeneously expressed after radiotherapy (lower panels), whereas its expression may be upregulated, but still heterogeneous in others (upper panels). The concomitant upregulated expression of MHC-I and CT-antigens upon radiotherapy may increase the visibility of the tumor for CD8⁺ T cells.

To investigate whether the changes we observed upon radiotherapy are part of a coordinated program, we plotted our data as a heatmap by computing the ΔΔCt values of each of the transcripts against the ΔΔCt value of the other transcripts. Transcripts associated with immune suppression including IDO, BTLA, FoxP3, PD-L1, IL-10, TGF-β, STAT-3, CT10, TNF-α, and iNOS seem to follow a similar pattern of downregulated expression after radiotherapy. Furthermore, transcripts associated with immune effector function such as NKG2D, CD45, CD3, CD4, CD8, MHC-II, β2M, perforin, granzyme B, the CT-antigen CT7 and macrophages (CD68, CD163) seem to be upregulated in a coordinated fashion following radiotherapy (Fig. 3A). To determine the significance of correlation between 2 target genes, the ΔΔCt values of each of the target genes were computed against the other using a two-tailed bivariate analysis and the Spearman's ρ correlation coefficient. For mathematical reasons, we excluded patients with de novo expression or loss of expression following radiotherapy from the analysis. We found a positive correlation between several immune effectors and an inverse correlation between the transcripts of several immune effectors and immune suppressors. The scattered dot plots for the significant correlations are represented in Supplementary Fig. S6. The Spearman's ρ correlation coefficient for all the correlations is listed in the Supplementary Table S7.

To correlate the gene expression profile in sarcoma patients following radiotherapy in relation to their survival status, we plotted the change in expression (ΔΔCt) levels of the target genes following radiotherapy in a heatmap. We excluded the CT-antigen SSX-2 from this analysis, because it was expressed in only 2 tumor samples. All patients who survived for 3 or more years after radiotherapy, irrespective of the clinical outcome at the end of the follow up, formed one group. Those who survived for less than 3 years after radiotherapy and were dead at the end of the follow up formed the other group. The heatmap reveals a clear downregulation of genes associated with immune suppression such as arginase-1, BTLA, CTLA-4, IDO, iNOS, PD-1, PD-L1, IL-10, TGF-β, TNF-α, FoxP3, macrophages (CD68, CD163), and CT10 in samples of patients who survived for a period of 3 years or more after radiotherapy, but not in those who died. The immune effector genes followed a more homogenous pattern of expression independent of the survival status following radiotherapy (Fig. 4).

Radiotherapy is an integrated treatment option for sarcoma patients. For considerable time it was thought that radiotherapy may have immunosuppressive effects (20), however evidence from recent animal studies suggests that radiotherapy supports local antitumor immunity (18, 21, 22). This study shows in human sarcoma patients that radiotherapy indeed changes the local tumor microenvironment from immunosuppressive into one that is reminiscent of protective immunity. We compared the immune infiltrate in paired biopsies from 38 human sarcoma patients collected before and after radiotherapy and found that radiotherapy induced remarkable changes, all of which suggest a skewing toward protective effector immunity. The activation of CD8⁺ T and CD4⁺ T cells contributes to antitumor immunity (23, 24) and is also known to facilitate the efficacy of radiotherapy (25, 26); this is clearly supported by a higher tumor incidence in immunosuppressed patients (27). We observed a higher infiltration of both CD4⁺ and CD8⁺ T cells in most of the sarcoma patients after radiotherapy. In addition, we observed that radiotherapy resulted in an upregulated expression of MHC-I and of different CT-antigens in most sarcoma patients, which makes tumors more visible to CD8⁺ T cells. These data are in accordance with published data showing that nonlethal doses of radiation induce a dose-dependent increase of MHC-I (28) and CT-antigens resulting in better recognition by specific CD8⁺ T cells in vitro (17). Importantly, radiotherapy sometimes changed the heterogeneous expression of MHC-I and/or CT-antigens, which is thought to result from immune escape (3, 29), to a homogeneous expression, thus enabling a more complete surveillance of the tumor. In addition to changes that improve immunological visibility of tumor cells, we also detected de novo expression of the highly immunogenic CT-antigens in some patients as a result of radiotherapy; this is well in line with our previous data (17). The observed changes are relevant as the loss of MHC-I expression in the equilibrium phase is thought to contribute to escape from immune control leading to tumor progression (30).

The tumor microenvironment is often immunosuppressive, thereby failing to activate local immune responses (31). Several studies have described the roles of immunosuppressive cytokines such as TGF-β and IL-10 in aiding tumor progression and that of stimulatory cytokines such as TNF-α, IL-12, and IFN-γ in supporting antitumor effects (32–36). We observed a higher expression of immune effector molecules, including perforin, granzyme B, NKG2D, IFN-γ, TNF-α, and IL-12, some of which were only expressed after radiotherapy in particular patients. At the same time many molecules and cell types associated with immunosuppression, including arginase-1, BTLA, CTLA-4, PD-1, PD-L1, IDO, FoxP3, macrophages, TGF-β, and IL-10 were expressed at lower level or even disappeared completely after radiotherapy. In search for immune parameters that predict the response to radiotherapy, we found that radiotherapy-induced downregulation of several immune suppressors correlated with survival status. In addition, the correlation analysis revealed that the transcripts associated with immune suppression (IDO, BTLA, FoxP3, PD-L1, IL-10, TGF-β, and macrophages) have a similar pattern of expression. Also immune effectors such as NKG2D, CD45, CD3, CD4, CD8, MHC-II, β2M, perforin, and granzyme B respond in a similar and presumably coordinated fashion upon radiotherapy. Despite the clinical heterogeneity in the cohort of sarcoma patients in our study, the response to radiotherapy was similar as were the changes in the immune infiltrate.

The apparent immunostimulation of radiotherapy per se argues for combining this therapy with treatments that interfere with immunoregulation and/or enhance immune stimulation. There is evidence in humans and mice that local radiotherapy under CTLA-4 blockade results in tumor regression of nonirradiated tumors as well (abscopal effect; refs. 37, 38). Similar results may be obtained when radiotherapy is combined with blockade of other coinhibitory molecules, such as Tim-3, PD-1, or BTLA (39–41). A recent study has shown that anti-PD-1 antibody produced objective responses, 1 in 4 to 1 in 5 patients with advanced non-small cell lung cancer, melanoma, or renal-cell cancer (42). This obviously is a promising combination especially in the case of micro-metastases. Another option may be combination radiotherapy with the targeted delivery of immunostimulatory cytokines, which has been shown to synergize with chemotherapy in human and murine cancers (43, 44). A previous study reported that a combination of radiotherapy with IL-12 improves both local and distant tumor control compared to either therapy alone (45). In addition, radiotherapy may create a favorable environment for adoptively transferred tumor-specific T cells (18, 46), which argues for combining adoptive T-cell therapy and radiotherapy. Preclinical studies in carcinoembryonic antigen (CEA) transgenic mice and a murine carcinoma cell line transfected with CEA, on combined treatment with low-dose radiation and vaccine expressing CEA and costimulatory molecules, could show a 50% reduction in tumor growth and a massive trafficking of T cells, when compared to either treatment alone (47). A clinical trial in cancer patients, vaccinated with NY-ESO-1 DNA vaccine showed induction of antigen-specific T-cell responses in 93% of vaccinated patients, however this did not lead to a clinical benefit (48). A recent study also showed that NY-ESO-1 OLP vaccine could rapidly induce integrated immune responses (antibody, CD8⁺, and CD4⁺) in nearly all vaccinated patients with advanced ovarian cancer, when administered with appropriate adjuvants (49). A phase I clinical trial in HLA-A2+ melanoma patients using immunization with autologous PBMCs pulsed with a MAGE-3 or a Melan-A peptide, increased specific CD8⁺ T-cell responses, and 6 of 8 patients had evidence of clinical activity (50). These studies show that on vaccination with a relevant CT-antigen the peripheral responses could be boosted in cancer patients, however they clearly do not show the desired antitumor efficacy. Therefore, combining radiotherapy with immune stimulation may support the immune modulating potential of radiotherapy by interfering with the local immunosuppressive milieu. Future trials with a large cohort of patients are required to evaluate the question of clinical outcome and the safety of this combination. This may lead to new concepts in the clinical management of cancer.

M. Okoniewski is employed (other than primary affiliation; e.g., consulting) as a Data integration specialist, bioinformatician in University Hospital Zurich, Department of Neuroimmunology and MS Research. No potential conflicts of interest were disclosed by the other authors.

Conception and design: A. Sharma, A. Knuth, L. von Boehmer, M. van den Broek

Development of methodology: A. Sharma, B. Bode, H. Moch, M. van den Broek

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A. Sharma, B. Bode, A. Knuth, L. von Boehmer

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): A. Sharma, B. Bode, M. Okoniewski, A. Knuth, L. von Boehmer, M. van den Broek

Writing, review, and/or revision of the manuscript: A. Sharma, H. Moch, A. Knuth, L. von Boehmer, M. van den Broek

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A. Sharma, B. Bode, H. Moch, A. Knuth, L. von Boehmer

Study supervision: H. Moch, A. Knuth, M. van den Broek

Other: Radiation treatment planning/realization/surveillance and provision of all related RT data of the patients: G. Studer

The authors thank M. Storz, M. Bieri (Department of Pathology, University Hospital Zurich, Switzerland) and S. Behnke (Sophistolab, Eglisau, Switzerland) for expert immunohistochemistry.

This work was supported by the Cancer Research Institute (Cancer Vaccine Collaborative), the Arigon Generalunternehmung AG, Zurich and medalumni Zurich, the Hartmann Müller Foundation, and the Dr. Leopold and Carmen Ellinger Foundation.

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