Article Text

Original research
Metabolic features of cancer cells impact immunosurveillance
  1. Adrien Joseph1,2,3,
  2. Pan Juncheng1,2,3,
  3. Michele Mondini4,
  4. Nizar Labaied5,
  5. Mauro Loi6,
  6. Julien Adam7,8,
  7. Antoine Lafarge1,2,3,
  8. Valentina Astesana1,2,3,
  9. Florine Obrist1,2,3,
  10. Christophe Klein9,
  11. Norma Bloy1,2,3,
  12. Gautier Stoll1,2,
  13. Nicolas Signolle5,
  14. Catherine Genestie5,
  15. Diane Damotte10,
  16. Marco Alifano11,
  17. Alexandra Leary12,
  18. Patricia Pautier12,
  19. Philippe Morice13,
  20. Sebastien Gouy13,
  21. Eric Deutsch14,
  22. Cyrus Chargari14,
  23. Marie-Caroline Dieu-Nosjean15,
  24. Isabelle Cremer16,
  25. Judith Michels17,
  26. Guido Kroemer1,18,19,20 and
  27. Maria Castedo1,2
  1. 1Equipe 11 labellisée par la Ligue contre le Cancer, Université de Paris, Sorbonne Université, INSERM U1138, Centre de Recherche des Cordeliers, INSERM, Paris, France
  2. 2Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer Campus, Villejuif, France
  3. 3Faculté de médecine, Université de Paris Saclay, Kremlin Bicêtre, France
  4. 4INSERM U1030, Gustave Roussy, Université Paris-Saclay, Villejuif, France
  5. 5Pathology Department, Gustave Roussy Institute, Villejuif, Île-de-France, France
  6. 6INSERM U1030, Gustave Roussy, Université Paris-Saclay, INSERM, Villejuif, Val-de-Marne, France
  7. 7Pathology Department, Gustave Roussy Institute, Villejuif, Val-de-Marne, France
  8. 8Pathology Department, Gustave Roussy Cancer Campus, Villejuif, France
  9. 9Centre d'Histologie, Imagerie cellulaire et Cytométrie (CHIC), Centre de Recherche des Cordeliers, Paris, Île-de-France, France
  10. 10Departments of Pathology and Thoracic Surgery, Hospital Cochin Assistance Publique Hopitaux de Paris, APHP, Paris, Île-de-France, France
  11. 11Department of Thoracic Surgery, Hospital Cochin Assistance Publique Hopitaux de Paris, APHP, Paris, Île-de-France, France
  12. 12Department of Medical Oncology, Gustave Roussy Institute, Villejuif, Île-de-France, France
  13. 13Department of Gynecologic Surgery, Gustave Roussy Institute, Villejuif, Île-de-France, France
  14. 14Radiotherapy Department, Brachytherapy Unit, Gustave Roussy Institute, Villejuif, Val-de-Marne, France
  15. 15Sorbonne University, UMRS 1135, INSERM U1135, Centre d'Immunologie et des Maladies Infectieuses (Cimi-Paris), INSERM, Paris, Île-de-France, France
  16. 16INSERM U1138, Centre de Recherche des Cordeliers, Université de Paris, Sorbonne Université, 75006 Paris, France
  17. 17Department of Medical Oncology, Gustave Roussy Cancer Campus, Villejuif, France
  18. 18Suzhou Institute for Systems Medicine, Chinese Academy of Medical Sciences, Suzhou, China
  19. 19Karolinska Institute, Department of Women's and Children's Health, Karolinska University Hospital, Stockholm, Sweden
  20. 20Pôle de Biologie, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France
  1. Correspondence to Dr Maria Castedo, INSERM U1138 Equipe 11, Centre de Recherche des Cordeliers, 75006 Paris, Ile-de-France, France; maria.castedo-delrieu{at}sorbonne-universite.fr; Guido Kroemer; kroemer{at}orange.fr; Dr Judith Michels; michelsjudith{at}gmail.com

Abstract

Background Tumors rewire their metabolism to achieve robust anabolism and resistance against therapeutic interventions like cisplatin treatment. For example, a prolonged exposure to cisplatin causes downregulation of pyridoxal kinase (PDXK), the enzyme that generates the active vitamin B6, and upregulation of poly ADP-ribose (PAR) polymerase-1 (PARP1) activity that requires a supply of nicotinamide (vitamin B3) adenine dinucleotide. We investigated the impact of the levels of PDXK and PAR on the local immunosurveillance (ie, density of the antigen presenting cells and adaptive immune response by CD8 T lymphocytes) in two different tumor types.

Methods Tumors from patients with locally advanced cervical carcinoma (LACC) and non-small cell lung cancer (NSCLC) were stained for PAR, PDXK, dendritic cell lysosomal associated membrane glycoprotein (DC-LAMP) and CD8 T cell infiltration. Their correlations and prognostic impact were assessed. Cisplatin-resistant NSCLC cell clones isolated from Lewis-lung cancer (LLC) cells were evaluated for PAR levels by immunoblot. Parental (PARlow) and cisplatin-resistant (PARhigh) clones were subcutaneously injected into the flank of C57BL/6 mice. Tumors were harvested to evaluate their immune infiltration by flow cytometry.

Results The infiltration of tumors by CD8 T and DC-LAMP+ cells was associated with a favorable overall survival in patients with LACC (p=0.006 and p=0.008, respectively) and NSCLC (p<0.001 for both CD8 T and DC-LAMP cells). We observed a positive correlation between PDXK expression and the infiltration by DC-LAMP (R=0.44, p=0.02 in LACC, R=0.14, p=0.057 in NSCLC), and a negative correlation between PAR levels and CD8 T lymphocytes (R=−0.39, p=0.034 in LACC, R=−0.18, p=0.017 in NSCLC). PARP1 is constitutively hyperactivated in cisplatin-resistant LLC cells manifesting elevated intracellular levels of poly(ADP-ribosyl)ated proteins (PARhigh). Tumors formed by such cancer cells injected into immunocompetent mice were scarcely infiltrated by CD8 T (p=0.028) and antigen presenting cells (p=0.086).

Conclusions Oncometabolic features can impact local immunosurveillance, providing new functional links between cisplatin resistance and therapeutic failure.

  • immunotherapy
  • dendritic cells
  • tumor microenvironment
  • CD8-positive t-lymphocytes
  • lung neoplasms

Data availability statement

Data are available on reasonable request.

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Introduction

Cancer cell-intrinsic properties drive alterations in the microecosystem that is composed by malignant cells, stromal elements as well as tumor-infiltrating leukocytes. This latter point has been neglected for a long time, yet spurred ever expanding interest since the discoveries that (i) the presence of certain immune effectors, in particular CD8+ cytotoxic T lymphocytes (CTLs) and activated dendritic cells (DCs) have a major prognostic impact in most extracranial cancer types1 and (ii) immunotherapy with antibodies neutralizing the cytotoxic T-lymphocyte associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) has the potential to become a close-to-universal antineoplastic treatment.2 Today, it is common knowledge that tumors, to become truly life threatening, must fulfill a compendium of conditions including malignancy (ie, the unrestrained proliferation and dissemination of neoplastic cells) and escape from immunosurveillance (ie, camouflage of tumor cells to become invisible to the immune system and/or active immunosuppression).3

The metabolic features of tumors may also be interpreted in the sense of a constant dialog between malignant and immune cells. In essence, tumor cells must rewire their metabolisms to produce biomass, initially often in a hostile context with scarce supply of growth factors, glucose, amino acids and oxygen. Beyond these anabolic capacities and an increased capacity to ‘capture’ nutrients from the environment, oncometabolism also may subvert immunosurveillance (and hence interfere with immunometabolism). For example, lactate produced by malignant cells and low extracellular pH interfere with T cell functions.4 In addition, the expression levels of metabolic enzymes such as aldehyde dehydrogenase 7 family, member A1 (ALDH7A1) are associated with a paucity of immune effectors within the tumor bed, while that of lipase C, hepatic type (LIPC) positively correlates with abundant tumor infiltration by myeloid and lymphoid cells in several different human cancer types.5 As an extreme, some cancers have developed the capacity to engulf and cannibalize lymphocytes, thus converting their enemies into nutrients.6

Cancer cells can also rewire their metabolism in response to iatrogenic stresses. For example, cisplatin-based chemotherapy causes a selection/adaptation of malignant cells that often leads to the downregulation of the vitamin B6 activating enzyme pyridoxal kinase (PDXK)7 and the upregulation of the enzymatic activity of poly(ADP-ribose) (PAR) polymerase (PARP1) that requires a supply of nicotinamide adenine dinucleotide (NAD).8 Nicotinamide is also known as vitamin B3. These alterations are causatively involved in cisplatin resistance because re-expression of PDXK or depletion/inhibition of PARP1 restores cisplatin sensitivity of cancer cells.7 9 Moreover, low PDXK expression or high abundance of the PARP1 product PAR within malignant cells indicates poor prognosis in patients with non-small cell lung cancer (NSCLC).7 10

Here, we investigated the possibility that markers of the vitamin B metabolism, namely PDXK and PAR, would affect the density of the antigen presenting cells (ie, DCs measured by dendritic cell lysosomal associated membrane glycoprotein (DC-LAMP)) and the adaptive immune response as measured by the density of the CD8 T cells, in locally advanced cervical squamous cell carcinoma, which is known to be under CTL-mediated surveillance,11–13 and NSCLC, for both of which cisplatin still belongs to the standard of care.

Materials and methods

Patients and survival data

The cohort of patients with cervical cancer (n=66) included paraffin-embedded baseline tumor biopsies from patients with locally advanced cervical cancer (LACC) undergoing curative-intent concurrent chemoradiation followed by uterovaginal brachytherapy boost. They were treated in our institution between March 2004 and August 2011.14 Only squamous cell carcinomas, which is the most frequent histology, were included in the analysis. A second cohort of paraffin-embedded baseline NSCLC surgical samples was evaluated from patients (stage I to III-IV according to 7th edition TNM classification) undergoing primary surgery at Hôtel-Dieu Hospital (Paris, France) between 2001 and 2005.15 All tumor specimens were collected before chemotherapy. The patients’ main clinical and pathological features are described in online supplemental tables S1 and S2. A written informed consent was obtained from all patients, in application with the article L.1121–1 of French law and the two studies were approved by the local ethics committee (CPP 2012–0612).

Supplemental material

Pearson’s correlation coefficients with their significance value were calculated and depicted in scatter plots. Kaplan-Meier curves were stratified using the median value of the cohort for PAR and PDXK expression and DC-LAMP and CD8 infiltration and the log-rank test was used to compare overall and relapse-free survival of patients between groups. The start of follow-up was the date of biopsy for patients with LACC and NSCLC. Statistical testing was done at the two-tailed α level of 0.05. Statistics were managed using R software V.3.4.2 (R Foundation for Statistical Computing, Vienna, Austria; https://www.R-project.org/, packages survival, survminer, Hmisc and corrplot).

Immunohistochemistry

In the lung cancer cohort, tumor samples were fixed in neutral buffered 10% formalin solution and paraffin embedded. Tumors were freshly cut for immunohistochemical analysis, paraffin section was dewaxed, followed by antigen retrieval with Target Retrieval Solution (Dako) in a preheated water bath (98°C, 30 min). Sections were cooled at room temperature for 30 min and endogenous peroxidase was blocked with 3% hydrogen peroxide. Thereafter, sections were incubated with diluted 5% human serum for 30 min and incubated with PAR (AM80, Calbiochem), PDXK (AP7167a, Abgent), DC-LAMP (DDX0191, clone 1010E1.01) and CD8 (clone SP16, Spring Bioscience) antibodies. We chose to evaluate PAR activity and not protein expression because, as previously shown, low PARP1 protein levels do not preclude a high activity of this enzyme10 and PARP1 expression do not correlate with survival.16 PAR and PDXK were manually evaluated by trained observers. In the NSCLC cohort, 186 samples were available for PAR/PDXK staining. The correlations were calculated according to the median (ie, markerhigh equivalent or superior to the median, markerlow is less than the median). DC-LAMP+ cells were counted manually by two trained observers on five selected regions of interest and expressed as an absolute number of positive cells/mm2 (density) of tumor. CD8 positive cells were counted using Visiopharm image analysis software on the same five manually selected regions of interest and expressed as an absolute number (density) of positive cells/mm2 of tumor.

Scoring of expression levels

Staining percentage of reactive tumor cells was scored on a 0%–100% scale for PDXK and PAR. The correlations and survival were calculated according to the median (ie, markerhigh equivalent or superior to the median, markerlow is less than the median). The median value for the five regions of the density for DC-LAMP+ and CD8 was taken into account for the survival and correlation analyses.

Cell lines, culture conditions and chemicals

Culture media and cell culture supplements were purchased from Life Technologies (Carlsbad, California, USA). Cells were routinely maintained at 37°C under 5% CO2, in the following culture medium: Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 100 units/mL penicillin G sodium and 100 mg/mL streptomycin sulfate. Mouse Lewis lung carcinoma (LLC) cell line was purchased from American Type Culture Collection. Cisplatin-resistant clones were obtained in vitro by prolonged culture of parental (also known as wild type (WT)) cells with sublethal concentrations of cisplatin (Sigma-Aldrich). In parallel, control clones were obtained from the untreated WT cells. Both parental and cisplatin-resistant cells were never passaged more than 1 month before use in experimental determinations.

Quantification of apoptotic features

Adherent and non-adherent cells were collected and costained for 30 min at 37°C in 300 µL of culture medium containing 40 nM 3,3’ dihexiloxalocarbocyanine iodide (DiOC6(3)), Molecular Probes-Invitrogen), a mitochondrial transmembrane potential-sensitive dye, and 1 µg/mL propidium iodide, which only accumulates in cells exhibiting plasma membrane permeabilization. Cytofluorometric acquisitions were carried out on a Milteny cytofluorometer (MACSQuant Analyzer 10), and statistical analyses were performed by using the FlowJo software (LLC, Oregon, USA) on gating on events exhibiting normal forward scatter and side scatter parameters.

Immunoblotting

Cells were trypsinized, collected, washed twice with phosphate-buffered saline (PBS) and lysed in a buffer containing 50 mM Tris HCl pH 6.8, glycerol 10%, 2% Sodium dodecyl sulfate (SDS), 10 mM ithiothréitol (DTT) and 0.005% bromophenol blue. Subsequently, 30 µg of proteins were separated on 4%–12% sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) gels (Invitrogen) and electrotransferred to nitrocellulose membranes (Biorad) followed by immunoblotting with a primary antibody specific for PAR (Clone 10H, mAb to poly ADP-ribose, Abcam, 1:1000). An antiactin antibody (mAb to beta actin, ab 49900, Abcam, 1:5000) was used to control equal lane loading. Thereafter, membranes were incubated with appropriate horseradish peroxides-conjugated secondary antibodies (Southern Biotech), followed by chemiluminescence detection with the ECLTM Prime Western Blotting Detection Reagent (GE Healthcare), before being revealed by the ImageQuantTM LAS 4000 Biomolecular Imager (GE Healthcare Life Sciences). Finally, protein expression was quantified by ImageJ software (NIH, USA).

Mouse housing and murine cancer model

Eight-week-old female C57Bl/6 mice were purchased from Envigo France. Animals were maintained in specific pathogen-free conditions, at 25°C with 12 hours light/12 hours dark cycles. All animals were used under an approved protocol by the local Ethics Committee (C2EA 05 n° B-75-06-12, protocol 7810–20 l6112810578922v2) under conditions in accordance with the EU Directive 63/2010. Sample sizes were calculated to detect a statistically significant effect. For tumor induction, 1.2–1.7×106 WT and cisplatin-resistant (R) LLC cells were resuspended in 100 µL of PBS and subcutaneously injected in the flank of mice under anesthesia (2.5% isoflurane). The estimation of the tumor area (longest dimension × perpendicular dimension) was measured using a common caliper. Tumor ulceration, weight loss superior to 20% as compared with the beginning of the treatment and poor body condition were considered as endpoints.

Ex vivo analysis of mouse tumor immune infiltrate

When the surface of the tumors derived from WT and cisplatin-resistant LLC cells reached 1 cm2, corresponding to approximately 30 days after tumor cells injection, tumors were harvested, weighed and transferred on ice in gentleMACS C tubes (Miltenyi Biotec, USA) containing 1 mL Dulbecco's modified eagle medium (DMEM) medium. Tumors were dissociated mechanically with scissors, then enzymatically using the Miltenyi Biotec mouse tumor dissociation kit and a gentleMACS Octo Dissociator following the manufacturer’s instructions. Then, the homogenates were filtered through 70 µm MACS SmartStrainers (Miltenyi Biotec) and washed twice with PBS. Thereafter, tumor cells were resuspended in PBS and 50 mg of the initial tumor sample were stained with LIVE/DEAD Fixable Yellow dye (Thermo Fisher Scientific). Fc receptors were blocked with anti-mouse CD16/CD32 (clone 2.4G2, Mouse BD Fc Block, BD Pharmingen). Surface staining of murine T-cell population infiltrating the tumor was performed with the following fluorochrome-conjugated antibodies: anti-CD3 APC V450 (clone 17A2, Thermo Fisher Scientific), anti-CD8 PE (clone 53–6.7, BD Pharmingen). Myeloid populations were stained with the following antibodies: anti-CD45 APC-Fire750 (clone 30F-11, BioLegend), anti-Ly-6G PE (clone 1A8, BD Pharmingen), anti-Ly-6C FITC (clone AL-21, BD Pharmingen), anti-CD11b V450 (clone M1/70, BD Pharmingen), anti-CD11c PE-Vio770 (REA754, Miltenyi Biotec) and anti-I-A/E (MHC-II) APC (clone M5/114.15.2, BioLegend). Finally, stained samples were run through a BD LSR II flow cytometer. Data were acquired using BD FACSDiva software (BD biosciences) and analyzed using FlowJo software (TreeStar).

Results

Relationship between the immune infiltrate and metabolic parameters in patients with LACC

We found a positive effect of tumor infiltration by CD8+ T lymphocytes (determined by immunohistochemistry, figure 1A) to be associated with improved overall survival (figure 1C) and a trend for improved relapse-free survival (figure 1D) in patients with LACC stratified by tumor stage. We also determined the density of the tumor infiltrating DC-LAMP+ cells (which are activated DCs) by immunohistochemistry (figure 1B). None of the women with a DC-LAMPhigh tumor died, meaning that high DC-LAMP+ density was significantly (p=0.0081, log-rank test) associated with overall survival (figure 1E) as well as a tendency for improved relapse-free survival (figure 1F) (online supplemental table S3). DC-LAMPhigh tumors were densely infiltrated by CD8+ T cells (p=0.03 by χ2 test, p=0.08 when computed as continuous values) (figure 2A,B). The combination of a low infiltration by both CD8 and DCs carried a significantly worse prognosis compared with tumors highly infiltrated (p=0.003, log-rank test) (figure 2C,D). We also determined the expression level of PDXK (figure 3A,B) and PAR (figure 3C,D) by cancer cells. Of note, we observed a positive correlation (Pearson test, p=0.002) between DC-LAMP density and PDXK expression, as well as a significant (p=0.0034) negative correlation between CD8 density and PAR expression (figure 3E,F). PARhigh/PDXKlow tumors showed a tendency for worse overall (figure 4A) and relapse-free (figure 4B) survival. These results suggest that tumor cell-intrinsic metabolic characteristics may affect local immunosurveillance.

Figure 1

Prognostic value of CD8 and DC-LAMP stratification in patients with locally advanced squamous cell cervical cancer. (A–B) Immunohistochemical detection of CD8 (A) and DC-LAMP+ (B) cells with high density in resected cervical cancer tumors. CD8 or DC-LAMP+ positive cells are shown in brown. Representative images are reported (scale bare=30 µm). (C–D, E–F) Kaplan-Meier curves of overall survival and relapse-free survival on stratification of patients according to FIGO stage and CD8 (C,D) or FIGO stage and DC-LAMP (E,F) median expression, respectively. P values were determined by means of the log-rank test. Tables summarize the number of patients at risk in each group at baseline and at several time points. Two-by-two comparisons only show a significant survival and relapse-free survival advantage for DC-LAMP infiltration in FIGO IIb tumors (p=0.006). DC-LAMP, dendritic cell lysosomal associated membrane glycoprotein; FIGO, International Federation of Gynecology and Obstetrics.

Figure 2

Correlation between CD8 and DC-LAMP in patients with locally advanced squamous cell cervical cancer. (A) Number of patients in each group at baseline as determined by immunohistochemistry. Distribution in CD8 and DC-LAMP groups were compared by means of the χ² test. (B) Correlation between CD8 and DC-LAMP densities. A total of 30 patients’ samples were evaluable. Each point represents one patient, with rug added on X and Y axis. The regression line from a linear regression model between CD8 and DC-LAMP densities is depicted in blue with its 95% CI in gray. P values were based on Pearson’s product moment correlation coefficient. (C,D) Kaplan-Meier curves of overall survival (C) and relapse-free survival (D) on stratification of patients according to FIGO stage and CD8low/DC-LAMPlow status. Tables summarize the number of patients at risk in each group at baseline and at several time points. DC-LAMP, dendritic cell lysosomal associated membrane glycoprotein; FIGO, International Federation of Gynecology and Obstetrics.

Figure 3

Immunohistochemical detection of PDXK (A,B) and PAR (C,D) cells in locally advanced squamous cell carcinoma samples. Note in (C) the presence of lymphocytes (left side) that were used as an internal positive control. Representative images are reported (scale bare=50 µm). (E,F) Correlations between PDXK and DC-LAMP density (F) or PAR and CD8 density (F), as determined by immunohistochemistry with specific antibodies on biopsies from patients with cervical cancer, followed by calculation of Pearson’s correlation coefficient. Each point represents one patient, with rug added on X and Y axes. The regression line from a linear regression model between CD8 and DC-LAMP densities is depicted in blue with its 95% CI in gray. P values were based on Pearson’s product moment correlation coefficient. DC-LAMP, dendritic cell lysosomal associated membrane glycoprotein; PAR, poly adenosine ribose; PDXK, pyridoxal kinase.

Figure 4

Kaplan-Meier curves of overall survival (A) and relapse-free survival (B) on stratification of patients with advanced squamous cell cervical cancer according to FIGO stage and PARhigh/PDXKlow status. P values were determined by means of the log-rank test. Tables summarize the number of patients at risk in each group at several time points. Two-by-two comparisons show non-significant poorer overall survivals in PARhigh/PDXKlow tumors compared with others in both FIGO stage IIb (p=0.5) and stage IIIa-IVb (p=0.7) and relapse-free survivals in PARhigh/PDXKlow tumors FIGO stage IIb (p=0.3) and stage IIIa-IVb (p=0.3). FIGO, International Federation of Gynecology and Obstetrics; PAR, poly adenosine ribose; PDXK, pyridoxal kinase.

Immunological and metabolic characteristics of non-small cell lung cancer

Intrigued by the aforementioned results, we decided to evaluate our observations in a different neoplastic disease, NSCLC, for which it was known that low expression of PDXK and high abundance of PAR are negative prognostic markers.7 10 Pearson analyses revealed a negative correlation (p=0.017) between PAR levels and CD8+ T lymphocytes (figure 5A) and a positive trend (p=0.057) between PDXK expression and infiltration by DC-LAMP+ cells (figure 5B). As expected,17 18 the detection of high levels of CD8+ or DC-LAMP+ cells in tumors was associated with improved overall survival (figure 5C,D) (online supplemental table S4), and this effect was independent from age, gender, histology, smoking status and tumor stage in a multivariate Cox model (p=0.001 and <0.001 for CD8 and DC-LAMP). The combined low infiltration by CD8 and DCs have a significantly worse prognosis compared with tumors highly infiltrated (p=0.0001, log-rank test) (figure 5E,F). Patients with PARhigh/PDXKlow cancers had a reduced overall survival, particularly in stage I-II tumors (figure 6), and this effect was independent from age, gender, histology, smoking status and tumor stage (p=0.02). Altogether, these results confirm the conjecture that tumor cell-intrinsic metabolic alterations may impact the composition of the local immune infiltrate.

Figure 5

Prognostic value of CD8 and DC-LAMP stratification in patients with non-small-cell lung cancer. (A,B) Correlations between PAR/CD8 (A) (n=184) and DC-LAMP/PDXK (B) (n=186), respectively. The expression of PAR and PDXK by malignant cells was plotted against the density of CD8 and DC-LAMP, respectively, followed by calculation of Pearson’s correlation coefficients. Each point represents one patient, with rug added on X and Y axes. (C,D) Kaplan-Meier curves of overall survival on stratification of patients according to CD8 and tumor stage (I−II vs III−IV) (C) or DC-LAMP and tumor stage (D) expression, respectively. (E,F) Kaplan-Meier curves of overall survival on stratification of patients according to combined CD8 and DC-LAMP (E) or CD8low/DC-LAMPlow status and tumor stage (I−II vs III−IV) (F) expression, respectively. P values were determined by means of the log-rank test. Tables summarize the number of patients at risk in each group at baseline and at several time points. Two-by-two comparisons show a significant survival advantage of CD8 infiltration in stage I−II (p=0.002, OR=0.64 (0.48 to 0.86)) but not in stage III−IV (p=0.3, OR=0.82 (0.57 to 1.18)) tumors, and DC-LAMP infiltration in both stage I−II (p<0.001, OR=0.58 (0.44 to 0.77)) and stage III−IV (p=0.02, OR=0.65 (0.45 to 0.94)) tumors. CD8low/DC-LAMPlow tumors have a significantly poorer survival compared with other immune phenotypes in stage I−II (p<0.001, OR=1.24 (0.85 to 1.81)) but not in stage III−IV (p=0.1, OR=1.32 (0.91 to 1.92)) tumors. DC-LAMP, dendritic cell lysosomal associated membrane glycoprotein; PAR, poly adenosine ribose; PDXK, pyridoxal kinase.

Figure 6

Kaplan-Meier curve of overall survival on stratification of patients with lung cancer according to tumor stage and PARhigh/PDXKlow status. P values were determined by means of the log-rank test. Tables summarize the number of patients at risk in each group at several time points. Two-by-two comparisons show a trend towards poorer overall survival in PARhigh/PDXKlow tumors in stage I−II (p=0.1) and not in stage III−IV (p=0.6). PAR, poly adenosine ribose; PDXK, pyridoxal kinase.

Cause-effect relationship between PARP1 activation and immunosuppression

In human cervical and lung cancers, high abundance of PAR correlated with a reduced density of CD8+ T lymphocytes in the tumors. To establish a causal relationship between high PAR levels and reduced tumor immunosurveillance, we took advantage of Lewis lung cancer (LLC) cells (a mouse NSCLC cell line) that had been selected in vitro for cisplatin resistance, hence enhancing their capacity to maintain mitochondrial function and viability in vitro (figure 7A,B). Such cells manifested upregulation of PAR, as detectable by immunoblot analyses (figure 7C). Parental WT (online supplemental figure S1A,B) and cisplatin resistant (R) clones were injected subcutaneously into mice and their immune infiltrate was characterized by immunofluorescence and flow cytometry (online supplemental figures S1C and S2) when the tumors had reached a surface of 1 cm2. Importantly, the density of CD8+ T cells was reduced for resistant (PARhigh) tumors (p=0.028). Moreover, the LLC PARhigh tumors were less infiltrated in antigen presenting cells, (i) activated DCs (CD45+CD11c+MHCII+) (p=0.0859) and (ii) myeloid cells (CD45+CD11b+Ly6G Ly6Clow/intermediate) (p=0.0012) as compared with their PARlow counterparts (figure 7D–F). These results indicate that the metabolic phenotype of tumor cells may indeed shape the tumor microenvironment at the immunological level.

Supplemental material

Supplemental material

Figure 7

Immune infiltrate and PARP activity in a mouse lung cancer model. (A) Illustration of the strategy to obtain cisplatin-resistant LLC cells, test cisplatin sensitivity and PARylation level, inject selected clones subcutaneously in C57BL/6 mice and analyze peritumoral immune infiltrate by flow cytometry. (B) Parental WT mouse LLC lung cancer cells and cisplatin-resistant derivatives (R) were maintained in control conditions or treated with increasing concentrations of cisplatin (5, 10, 20, 30 and 50 µmol/L) for 48 hours. Thereafter, cells were subjected to the cytofluorometric assessment of apoptosis-related parameters on costaining with the vital dye PI and the mitochondrial membrane potential-sensing dye DiOC6(3). White and black columns illustrate the percentage of dying [DiOC6(3)lowPI-] and dead (PI+) cells, respectively (means±SEM, n=3). *P<0.05; **p<0.01 (Student t-test), compared with equally treated WT cells. (C) WT LLC cell line and R derivatives were cultured in normal growth medium and processed for the immunoblotting-based assessment of PAR-containing proteins. Actin levels were monitored to ensure equal loading of lanes. (D–F) Characterization of the T cell infiltrate in mouse lung cancers derived from PARhigh and parental PARlow cells. C57BL/6 mice were injected subcutaneously with PARlow and PARhigh clones (55 and 53 mice, respectively; three independent experiments). Boxplots illustrate the proportion of CD8+ (among CD3+ cells), CD11c+MHCII+ (among CD11c+ cells) and Ly6G-CD11b+Ly6Clow/intermediate (among CD45+ cells), respectively, in PARhigh and PARlow tumors. P values were calculated by Student’s t test. *P<0.05, NS, non-significant, as compared with T cell infiltrate in WT tumors. CD, cluster of differentiation; LLC, Lewis-lung cancer; PAR, poly adenosine ribose; PI, propidium iodide; WT, wild type.

Discussion

In an attempt to extend the general rule that oncometabolism may affect immunosurveillance, we have investigated the expression/activity of two enzymes, PDXK and PARP1, both implicated in the vitamin B metabolism, in the context of two distinct malignant diseases, cervical cancer and NSCLC. We observed that PDXK expression by malignant cells correlated with tumor infiltration by DCs, while PAR (which reflects PARP1 activity) anticorrelated with the local presence of CTLs. This is supported by transcriptional data for the positive correlation between myeloid DCs and PDXK and the negative correlation of T cells and PARP in patients with NSCLC.5 In mice, tumors formed by cisplatin-resistant PARhigh cells were scarcely infiltrated by CD8+ T lymphocytes, hinting to a potential link between the tumor-intrinsic changes in metabolism and the local immune tonus (rather than the selection of PARlow cells by immunosurveillance). Hence, PARP1 and PDXK activity within tumor cells may influence the composition of the immune infiltrate.

Chemotherapies are rarely given with a curative intent in metastatic solid tumors. Cisplatin is a poor stimulator of anticancer immune responses when compared with other common chemotherapeutics including anthracyclines, cyclophosphamide, oxaliplatin and taxanes.19 Moreover, the scenario emerges that metabolic adaptations of cancer cells that render them cisplatin-resistant are actually contributing to immunosubversion. Thus, the downregulation of PDXK expression and activity may selectively diminish the recruitment of DCs (or their precursors) into the tumor bed. Moreover, high PARP1 activity may impede the infiltration of tumors by CD8+ T cells. Thus, cisplatin would cause cancer cell resistance to its cell-autonomous tumoricidal effects and alter the phenotype of cancer cells in a way that they escape from immunosurveillance. Of note, we have previously reported a synergy of cisplatin and the vitamin B6 precursor pyridoxine with LLC tumors that was only observed if the immune system was intact.20 Thus, metabolic manipulations of the tumors might impact their immune infiltration.

Admittedly, the mechanistic links between PDXK downregulation or PARP1 activation and local immunosubversion are elusive. However, from the pharmacological point of view, both alterations appear druggable. Thus, high-dose supplementation with pyridoxine (vitamin B6) does improve the tumor growth-reducing activity of cisplatin20 and actually stimulates immunosurveillance, as we have recently shown for hormone-induced breast cancer.21 Moreover, it appears that PARP1 inhibition does cell-autonomously enhance DNA damage in cancer cells22 and increases the infiltration of tumors by T cells23–28 and sensitizes tumors to immune checkpoint blockade, as shown in mouse models27 and in human tumors.28 Obviously, the possibility to combine PARP inhibitors with immune checkpoint inhibitors is under active clinical investigation (NCT02571725 and NCT03598270). Mechanistically, DNA fragments generated in the context of inefficient DNA repair can activate the cGAS/STING pathway and elicit a Type-1 interferon response that has been well documented to enhance the production of T cell-recruiting chemokines.27 Extracellular PAR has been shown to activate Toll-like receptors 2 and 4, suggesting yet another possible link between oncometabolism and innate immune effectors.29 Perhaps more importantly, PARP1 activation may be expected to locally deplete NAD, which is consumed by PARP1, and supplementation with nicotinamide (which replenishes NAD) can stimulate anticancer immunosurveillance.21 In preclinical experiments, nicotinamide can be advantageously combined with PD-1 blocking antibodies to achieve tumor control.21 In essence, oncometabolic aberrations may yield novel actionable targets for improving cancer immunosurveillance.

The most important limitation of this study is the relatively low number of samples subjected to complete (clinical+metabolic+immunological) characterization, a weakness that is partially compensated for the fact that similar overall trends were found for two distinct cancer types, LACC and NSCLC. One limitation of this study is that the correlations between metabolic features (PDXK protein expression and PARP activity resulting into PAR accumulation) and features of immunosurveillance (presence of CD8+ T cells and DCs in the tumor) are relatively weak, perhaps reflecting the heterogeneity among the tumor types investigated in this paper. There are precedents for other metabolic properties of cancer (like the mRNA expression levels of aldehyde dehydrogenase 7 family member A1, ALDH7A1 and LIPC) correlates with the abundance of immune effectors in the tumor bed,5 suggesting that a whole series of metabolism-related characteristics may affect (or be affected by) the local immune system. Future studies should validate the findings obtained in this work in prospective studies, in the context of state-of-the-art immunotherapies. If the conjecture that low PDXK and high PARP1 activities subvert anticancer immunosurveillance in patients can be confirmed, future combination trials that combine metabolism-targeting agents with immune checkpoint blockers might profit from a patient stratification that includes PDXK and PAR expression levels.

Data availability statement

Data are available on reasonable request.

Ethics statements

Acknowledgments

We thank Kariman Chaba for histopathological analyses.

References

Supplementary materials

Related Data

Footnotes

  • Twitter @AdrienJoseph9, @CremerIsabelle

  • Contributors MC, JM and GK designed the study, interpreted the results and wrote the manuscript. AJ, VA, JP, FO and AL performed the animal ad in vitro experiments. MM, NL, ML, JA, MCDN, IC, NB and AJ performed immunohistological analyses. AJ performed the statistical analysis. AL, PP, PM, SG, ED and CG enrolled patients and collected clinical and laboratory information. All of the authors critically reviewed and substantially improved the manuscript.

  • Funding GK is supported by the Ligue contre le Cancer (équipe labellisée); Agence National de la Recherche (ANR)—Projets blancs; ANR under the frame of E-Rare-2, the ERA-Net for Research on Rare Diseases; AMMICa US23/CNRS UMS3655; Association pour la recherche sur le cancer (ARC); Association “Ruban Rose”; Cancéropôle Ile-de-France; Chancelerie des universités de Paris (Legs Poix), Fondation pour la Recherche Médicale (FRM); a donation by Elior; European Research Area Network on Cardiovascular Diseases (ERA-CVD, MINOTAUR); Gustave Roussy Odyssea, the European Union Horizon 2020 Project Oncobiome; Fondation Carrefour; High-end Foreign Expert Program in China (GDW20171100085), Institut National du Cancer (INCa); Inserm (HTE); Institut Universitaire de France; LeDucq Foundation; the LabEx Immuno-Oncology (ANR-18-IDEX-0001); the RHU Torino Lumière; the Seerave Foundation; the SIRIC Stratified Oncology Cell DNA Repair and Tumor Immune Elimination (SOCRATE); and the SIRIC Cancer Research and Personalized Medicine (CARPEM). AJ is supported by a grant from Fondation ARC pour la Recherche sur le Cancer. This study contributes to the IdEx Université de Paris ANR-18-IDEX-0001. ED, MM and ML are supported by INCa-DGOS TRANSLA 11-077. AnL is supported by a grant of ITMO Cancer (Plan Cancer 2014-2019).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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