Tania L Maxwell

Laurent Augusto

Lucie Bon

Adèle Courbineau

Andreas Altinalmazis-Kondylis

Sylvie Milin

Mark R Bakker

Hervé Jactel

Nicolas Fanin
email: nicolas.fanin@inrae.fr

Effect of a tree mixture and water availability on soil nutrients and extracellular enzyme activities along the soil profile in an experimental forest

Keywords: biodiversity, drought, nutrients, precipitation, soil extracellular enzyme activity

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Forest biodiversity provides a multitude of ecosystem goods and services [START_REF] Gamfeldt | Higher levels of multiple ecosystem services are found in forests with more tree species[END_REF][START_REF] Jactel | Tree Diversity Drives Forest Stand Resistance to Natural Disturbances[END_REF][START_REF] Liang | Positive biodiversityproductivity relationship predominant[END_REF]. However, forests in many areas are threatened by more intense and frequent drought periods (IPCC, 2014;[START_REF] Schwalm | Reduction in carbon uptake during turn of the century drought in western North America[END_REF], with important negative consequences such as on nutrient cycling [START_REF] He | Drought effect on plant nitrogen and phosphorus: A meta-analysis[END_REF][START_REF] Schlesinger | Forest biogeochemistry in response to drought[END_REF] or even on tree survival [START_REF] Hartmann | Research frontiers for improving our understanding of drought-induced tree and forest mortality[END_REF]. A well-explored option to mitigate these negative effects is to increase tree stand diversity [START_REF] Lebourgeois | Mixed stands reduce Abies alba tree-ring sensitivity to summer drought in the Vosges mountains, western Europe[END_REF][START_REF] Pretzsch | Resistance of European tree species to drought stress in mixed versus pure forests : evidence of stress release by interspecific facilitation[END_REF]. Indeed, mixed-species forests generally have been found to be more productive than pure stands [START_REF] Baeten | Identifying the tree species compositions that maximize ecosystem functioning in European forests[END_REF][START_REF] Cardinale | Impacts of plant diversity on biomass production increase through time because of species complementarity[END_REF][START_REF] Liang | Positive biodiversityproductivity relationship predominant[END_REF][START_REF] Zhang | Forest productivity increases with evenness, species richness and trait variation: A global meta-analysis[END_REF] and are more stable to climatic fluctuations due to overyielding, species asynchrony and favorable species interactions (Jucker et al., 2014a;[START_REF] Kardol | Long-term effects of species loss on community properties across contrasting ecosystems[END_REF][START_REF] Morin | Temporal stability in forest productivity increases with tree diversity due to 36 asynchrony in species dynamics[END_REF]. However, recent studies have shown that the positive effect of tree diversity on forest productivity might be annihilated under drought conditions [START_REF] Jactel | Positive biodiversity-productivity relationships in forests: climate matters[END_REF]. In addition, not all tree species mixtures are more resistant to water stress [START_REF] Grossiord | Having the right neighbors: how tree species diversity modulates drought impacts on forests[END_REF]. Although many studies on biodiversity effects focused on aboveground plant productivity, only a few addressed belowground productivity and soil functioning [START_REF] Alberti | Tree functional diversity influences belowground ecosystem functioning[END_REF][START_REF] Brassard | Tree species diversity increases fine root productivity through increased soil volume filling[END_REF][START_REF] Ma | Effects of species diversity on fine root productivity in diverse ecosystems: a global meta-analysis[END_REF]. Furthermore, we know little about how limiting water conditions may affect biodiversity benefits and if their interactive effects may affect soil microbial activity and biogeochemical cycling in mixed forests.

An important step of carbon (C), nitrogen (N), and phosphorus (P) cycling is the decomposition of organic matter that derives from leaf and root litter [START_REF] Hättenschwiler | Biodiversity and Litter Decomposition in Terrestrial Ecosystems[END_REF][START_REF] Zechmeister-Boltenstern | The application of ecological stoichiometry to plant-microbial-soil organic matter transformations[END_REF]. Among the main mechanisms involved in decomposition, one process is based on extracellular enzymes [START_REF] Sinsabaugh | Allocation of extracellular enzymatic activity in relation to litter composition, N deposition, and mass loss[END_REF]. Soil microorganisms release extracellular enzymes to acquire energy and resources by degrading neighboring soil organic matter [START_REF] Burns | Enzyme activity in soil: Location and a possible role in microbial ecology[END_REF][START_REF] Burns | Soil enzymes in a changing environment: Current knowledge and future directions[END_REF]. Studying soil extracellular enzyme activities (EEAs) can thus give information on potential belowground microbial mineralization processes and how microbial communities drive C, N, and P cycling in soils [START_REF] Allison | Changes in enzyme activities and soil microbial community composition along carbon and nutrient gradients at the Franz Josef chronosequence, New Zealand[END_REF]Fanin et al., 2016a;[START_REF] Henry | Reprint of "Soil extracellular enzyme dynamics in a changing climate[END_REF]. Soil EEAs are measured to assess microbial responses to global changes, including precipitation changes in varying ecosystems [START_REF] Henry | Reprint of "Soil extracellular enzyme dynamics in a changing climate[END_REF]. EEAs have been found to be negatively affected by water stress [START_REF] Brockett | Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada[END_REF][START_REF] Schlesinger | Forest biogeochemistry in response to drought[END_REF], including in forests [START_REF] Sardans | Drought decreases soil enzyme activity in a Mediterranean Quercus ilex L. forest[END_REF]. A recent global meta-analysis concluded that drought led to a significant decrease in urease and phenol oxidase activity, while an increase in precipitation significantly increased N-related enzyme activities [START_REF] Xiao | A meta-analysis of soil extracellular enzyme activities in response to global change[END_REF].

However, these effects may vary with soil depth due to water runoff dynamics and infiltration from topsoil to deeper soils. Topsoil is thus expected to be more positively affected by an increase in precipitation due to its increase in soil moisture, a major factor determining EEAs in soils [START_REF] Brockett | Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada[END_REF], whereas deeper soils may be less affected by precipitation, have less varying moisture and thus less effect on EEAs [START_REF] Fanin | Relative Importance of Climate, Soil and Plant Functional Traits During the Early Decomposition Stage of Standardized Litter[END_REF].

Tree species may also have important effects on EEAs due to their varying litter qualities [START_REF] Weand | Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities[END_REF]. Recently, [START_REF] Alberti | Tree functional diversity influences belowground ecosystem functioning[END_REF] found a positive synergistic effect of tree diversity on EEAs, due to the influence of varying litter traits on soil C and N mineralization. These results suggest that an increase in tree species richness may influence biogeochemical cycling due to stimulation of microbial activity [START_REF] Hacker | Plant diversity shapes microberhizosphere effects on P mobilisation from organic matter in soil[END_REF][START_REF] Steinauer | Plant diversity effects on soil microbial functions and enzymes are stronger than warming in a grassland experiment[END_REF]. Because tree species diversity may positively influence microbial biomass and activity [START_REF] Chen | Meta-analysis shows positive effects of plant diversity on microbial biomass and respiration[END_REF][START_REF] Lucas-Borja | Soil microbial community structure and activity in monospecific and mixed forest stands, under Mediterranean humid conditions[END_REF][START_REF] Thakur | Plant diversity drives soil microbial biomass carbon in grasslands irrespective of global environmental change factors[END_REF][START_REF] West | Effects of plant species diversity, atmospheric [CO2], and N addition on gross rates of inorganic N release from soil organic matter[END_REF], and that both microbial biomass and substrate pools decrease with depth [START_REF] Agnelli | Distribution of microbial communities in a forest soil profile investigated by microbial biomass, soil respiration and DGGE of total and extracellular DNA[END_REF][START_REF] Fierer | Variations in microbial community composition through two soil depth profiles[END_REF], there is a need to study the effect of tree diversity on EEAs along the soil profile [START_REF] Herold | Vertical gradients of potential enzyme activities in soil profiles of European beech, Norway spruce and Scots pine dominated forest sites[END_REF][START_REF] Loeppmann | Enzyme properties down the soil profile -A matter of substrate quality in rhizosphere and detritusphere[END_REF][START_REF] Stone | Changes in extracellular enzyme activity and microbial community structure with soil depth at the Luquillo Critical Zone Observatory[END_REF]. The diversity effects may also directly depend on root biomass along the litter-soil continuum.

Mixing tree species with contrasting root systems may lead to niche partitioning along the soil profile [START_REF] Brassard | Tree species diversity increases fine root productivity through increased soil volume filling[END_REF], which can benefit exploration of the total soil volume [START_REF] Schmid | Root distribution of Norway spruce in monospecific and mixed stands on different soils[END_REF] and total nutrient uptake [START_REF] Richards | The influence of mixed tree plantations on the nutrition of individual species: A review[END_REF]. In addition, facilitation mechanisms between associated species, such as hydraulic lift [START_REF] Zapater | Evidence of hydraulic lift in a young beech and oak mixed forest using 18 O soil water labelling[END_REF], may be especially advantageous in mixed stands during drought events. Thus, investigating how tree diversity may offset the negative effects of drought along the soil profile would provide new insights into how biodiversity effects on nutrient cycling may change in a future climate.

In this study, our primary objective was to investigate the interactive effect between tree diversity and water availability on available nutrients and EEAs along the soil profile. In practice, we sampled soils at five depths in an experimental plantation where both tree diversity and water availability (through irrigation) were manipulated and tested three hypotheses. First, we tested the hypothesis (H1) that EEAs would be higher in a two-species mixture than in the corresponding pure plots since mixing different litter qualities may lead to more synergistic litter decomposition [START_REF] Chapman | Leaf Litter Mixtures Alter Microbial Community Development : Mechanisms for Non-Additive Effects in Litter Decomposition[END_REF][START_REF] Cornwell | Plant species traits are the predominant control on litter decomposition rates within biomes worldwide[END_REF]. Specifically, we hypothesized that the effect of mixing trees on EEAs should be higher in the topsoil layer, where the effect of tree species identity is highest [START_REF] Augusto | Impact of several common tree species of European temperate forests on soil fertility[END_REF] and where the organic matter quantity is highest and richest in nutrients [START_REF] Jobbágy | The distribution of soil nutrients with depth : Global patterns and the imprint of plants[END_REF][START_REF] Melillo | Carbon and nitrogen dynamics along the decay continuum: Plant litter to soil organic matter[END_REF]. Secondly, we hypothesized (H2) an increase in water supply would have a positive effect on EEAs by alleviating the water constraint [START_REF] Sardans | Drought decreases soil enzyme activity in a Mediterranean Quercus ilex L. forest[END_REF][START_REF] Xiao | A meta-analysis of soil extracellular enzyme activities in response to global change[END_REF]. We anticipate that the effect of increasing water availability should be highest in the topsoil, mainly because microbial communities at the soil surface are often more subjected to water stress than those living in deeper soil horizons [START_REF] Fanin | Relative Importance of Climate, Soil and Plant Functional Traits During the Early Decomposition Stage of Standardized Litter[END_REF]. Finally, we hypothesized (H3) that the positive effect of mixing two tree species on EEAs would be strongest in the plots experiencing the dry summers. This is because mixing tree species with contrasting root exploration strategies may favor drought resistance through facilitation mechanisms [START_REF] Bello | Complementary water uptake depth of Quercus petraea and Pinus sylvestris in mixed stands during an extreme drought[END_REF].

Materials and methods

Experimental site and sample collection

We conducted this study at the ORPHEE experiment in southwestern France, 40 km southwest of Bordeaux (44°44.35' N, 00°47.9' W, altitude of 60 m asl) [START_REF] Castagneyrol | Plant apparency, an overlooked driver of associational resistance to insect herbivory[END_REF]. It is part of the international Tree Diversity Network (TreeDivNet) and is located in the largest artificial forest in occidental Europe (Landes de Gascogne). The mean annual temperature is 12.5°C and the mean average precipitation is 870 mm , but most precipitation occurs from the fall to the spring, leading to very dry summers, which we consider representative of water stress. The former vegetation was a mature Pinus pinaster stand located on a flat area.

The tree plantation in ORPHEE occurred in 2008, after a clear-cut of the pine forest, with a single plough and fertilizer application of 60 kg of P2O5 and 60 kg of K2O per hectare prior to plantation. The predominant soil type is a podzol characterized by a coarse texture (95% sand) and low soil fertility [START_REF] Augusto | Is "grey literature" a reliable source of data to characterize soils at the scale of a region? A case study in a maritime pine forest in southwestern France[END_REF], particularly in phosphorus [START_REF] Trichet | Fifty years of fertilization experiments on Pinus pinaster in Southwest France: the importance of phosphorus as a fertilizer[END_REF]. The water table is relatively shallow in wintertime, generally ranging from 40 to 80 cm below the soil surface. A total of 256 plots were planted representing five species (Betula pendula Roth., Pinus pinaster Soland. in Aït., Quercus ilex L., Quercus pyrenaica Willd., Quercus robur L.) in all possible combinations from one (monocultures) to five species mixtures. Each plot has 100 trees within a 20 m by 20 m area. Trees are planted in a substitutive (same tree density irrespective of the composition) alternate (trees from one species have neighbors from all other associated species) pattern. The plots are separated by 3 m from one another, and randomly located within eight blocks: four control (dry) blocks and four irrigated blocks. The irrigation was started in 2015, and occurs seasonally from May to October to alleviate summer stress. The start and end dates of irrigation differ slightly between years depending on meteorological and technical constraints. The water is taken directly from the groundwater, which has low concentrations of nitrogen and phosphorus, but higher concentrations of other elements, such as calcium and magnesium [START_REF] Jolivet | Les sols du massif forestier des Landes de Gascogne: formation, historie, propriétés, et variabilité spatiale[END_REF]. A 2 m tall sprinkler installed in the center of each experimental plot sprays every day the equivalent of 3 mm of precipitation. On average for the three summers preceding our sampling, control blocks received 318 mm of water from early May to late September, while irrigated blocks received 777 mm of water during the same period. When using both temperature and precipitation (+ irrigation) to determine arid periods in an ombrothermic diagram [START_REF] Walter | Klimadiagramm-Weltatlas[END_REF], control blocks are subjected to more stress than irrigated blocks (Fig.

S1.).

Among all of the plots, we chose to work with three species composition treatments: pure silver birch (Betula pendula Roth.) plots, pure maritime pine (Pinus pinaster Soland. in Aït.) plots, and the mixed birch-pine plots, which we used as a proxy to study tree diversity effects. These two species were selected because, contrary to the three other tree species, they grew fast despite the poorness of the sandy soil, which enabled the building of fairly dense forest stands. In 2018, the average tree height was about 8 m for the two species. The understory was mostly composed of Bracken, Molinia, Gorse, and ericaceous shrubs, with a few minority species (Besom heath, Buckthorn, Bramble, Honeysuckle). As a whole, the understory layer represented less than 1 % of the total aboveground biomass and the diversity was similar across all treatments, with on average six to seven vascular species per plot.

We sampled plots in all eight blocks (4 irrigated, 4 dry) from March 19 th to 21 st 2018. In each plot, we collected samples at four different locations, each surrounded by four trees, i.e. four pines, four birches, or two pines and two birches.

The forest floor (layer of litter above the soil mineral layers) was collected using a quadrant (10 cm × 20 cm). Samples were dried at 40°C until weight stabilization and ground. At each sampling location, we also collected a soil core down to 0.9 m depth in two steps. The top 0-15 cm of soil was collected manually with a soil corer (8 cm width). The bottom 15-90 cm of soil was collected with a mechanical drill, attached onto an auger (4 cm width). Afterwards, the soil cores were divided into five layers: 0-5, 5-15, 15-30, 30-60, and 60-90 cm. Soil samples were immediately placed in coolers and transported to the nearby lab, where each sample was sieved to 2 mm and homogenized. The roots were cleaned and stored in 10% alcohol until further analyses. One soil subsample was kept at 4°C for immediate extraction of available nutrients, and a second subsample was stored at -20°C for enzyme assays. Soil moisture was assessed for each sample by comparing the fresh to the dry soil weights after at least 72 h at 50°C. There were thus a total of 480 samples collected for nutrients, enzymes, soil moisture and root analyses (3 species composition × 2 water levels × 4 blocks × 5 depths × 4 replicates, Fig. S2). Composites of the four cores were made for each soil layer per plot, and these samples were then air-dried for chemical analysis (3 species compositions × 2 water levels × 4 blocks × 5 depths = 120 samples).

In addition to the soil samples, we collected litterfall sampled from litter traps that were installed in all plots in three blocks per water treatment at the beginning of the 2017 fall season. Two circular traps were installed in each plot: the traps were plastic cylinders with a height of around 20 cm, a metal net on the inferior opening, and a surface area of 0.716 m 2 . We collected the litter in November 2017, made one composite per plot, dried the samples at 40°C until weight stabilization and then ground them up (3 species compositions × 2 water levels × 3 blocks = 18 samples).

The C:N ratios were determined after measuring total C and N by dry combustion (NF ISO 10694 and 13878).

Available nutrients

After sample collection, Available ammonium (NH4 + ), nitrate (NO3 -), and phosphate (PO4 -2 ) were measured in one aliquot of all the soil samples, corresponding to 480 analyses (Fig. S2). In brief, 15 mL of ultrapure water was added to a glass vial with a 3 g aliquot of the soil sample, which was then shaken for 16 h at 4°C. Water extraction was favored over KCl extraction due to potential interference of the extractant with available phosphate in sandy podzols [START_REF] Achat | Biodisponibilité du phosphore dans les sols landais pour les peuplements forestiers de pin maritime[END_REF], and because it has a similar extraction efficiency for mineral N as in saline solutions (Gallet-Budynek, personal communication). The solution was placed vertically at ambient temperature for an hour to enable sedimentation, after which the supernatant was transferred into a tube through a Whatman filter of 8µm mesh size. The solution was left at ambient temperature for 3 h, and then filtered a second time with a syringe equipped with a 5 µm mesh paper. The final solution extractant was poured into scintillation tubes to measure NO3 -, NH4 + and PO4 -by colorimetry (San++, Automated Wet Chemistry Analyzer, Breda, Netherlands). The total available mineral N was expressed as the sum of mineral N from NO3 -and NH4 + (µg N g -1 dry soil) and available mineral P as PO4 -2 (µg P g -1 dry soil).

Enzyme assays

In the same samples previously described for available nutrients, on the other aliquot stored frozen at -20°C, we measured the potential activity of seven hydrolytic soil enzymes. We measured enzymes that catalyze the degradation of organic carbon

(β-1,4-glucosidase [BGLU]), 1,4-β-D-cellobiohydrolase [CBH], α-1,4-glucosidase [AGLU], and β-xylosidase [XYL]), nitrogen (β-1,4-N-acetyl-glucosaminidase [NAG],
L-leucine aminopeptidase [LAP]), and phosphorus (acid phosphatase [AP]) [START_REF] Bell | High-throughput Fluorometric Measurement of Potential Soil Extracellular Enzyme Activities[END_REF][START_REF] Fanin | Consistent effects of biodiversity loss on multifunctionality across contrasting ecosystems[END_REF]. Briefly, 2.75 g of the thawed soil sample was homogenized in 91 ml of 50 mM sodium acetate buffer in a blender for 1 min. Soil slurries of two technical replicates were then added to a 96-deepwell (800 µl) microplate using an eight-channel electronic pipette (Eppendorf Xplorer Plus, Hamburg, Germany). Additional quench control replicates of the soil slurry, 4methylumbelliferone or 7-amino-4-methylcoumarin standard curves (200 µl of respectively 0-100 µM and 0-10 µM concentrations) and controls without substrate addition (soil + 200 µl water), were included with each sample. Soil slurries were incubated with fluorometric substrates for 3 h at 25 °C. After the incubation period, plates were centrifuged for 3 min at 3000 rpm, after which 250 µl of supernatant was transferred from each well into a black flat-bottomed 96-well plate. The fluorescence was measured by a microplate reader (Synergy H1 microplate reader, Biotek, Winooski, USA) using an excitation wavelength at 365 nm and emission wavelength at 450 nm. From the fluorescent values and standard calibration curves, each enzyme activity was calculated and converted to nmol g -1 dry soil h -1 , and then converted to mmol kg -1 to express the enzymes as quantities. We then summed the BGLU, CBH, AGLU, and XYL quantities for total C-related enzymes (hereafter referred to as Cenz), and the NAG and LAP quantities for the total N-related enzymes (in the following referred to as Nenz). We refer to the acid phosphatase (AP) quantity as Penz. The ratios of total enzymes were subsequently calculated, which we refer to as Cenz:Nenz , Cenz:Penz, and Nenz: Penz. This is a tool that has been frequently used to measure ecological stoichiometry and microbial limitations (Fanin et al., 2016a;[START_REF] Sinsabaugh | Stoichiometry of soil enzyme activity at global scale[END_REF][START_REF] Stone | Changes in extracellular enzyme activity and microbial community structure with soil depth at the Luquillo Critical Zone Observatory[END_REF]. However, differences between potential enzyme activities and enzyme responses to nutrient additions have recently been found to be ambiguous, so some care must be taken when interpreting enzyme ratios as growthlimiting factors [START_REF] Rosinger | Can enzymatic stoichiometry be used to determine growth-limiting nutrients for microorganisms ? -A critical assessment in two subtropical soils[END_REF].

Root biomass

Roots were extracted from the same soil samples in which available nutrients and enzymes were analyzed. Root extraction consisted of sieving the collected samples and then watering the remaining roots to clean them and remove the soil. The live roots were sorted and separated into the different species. A representative portion of each root sample was oven-dried for 4 days at 40°C and weighed. For each soil sample, the root biomass data of both the tree species (pine and birch) and the understory species were used in our statistical analyses to determine their effect on the potential enzyme activities in a redundancy analysis (see section 2.6).

Soil chemical analyses

The subsequent soil analyses were done at the plot level by making composites of the four soil cores at each of the five depths along the soil profile (3 species compositions × 2 water levels × 4 blocks × 5 depths = 120 samples). The soil pH was determined in a 1:10 soil:water suspension. The C:N ratios were determined after measuring total C and N by dry combustion (NF [i.e., French standard] ISO [i.e., international standard] 10694 and 13878; AFNOR, 1999). The particle size distribution was analyzed for each block (one composite sample per block and per soil layer), using the fractionation method without decarbonatation (for five fractions, i.e., clay, fine silt, coarse silt, fine sand, and coarse sand) according to French standards (norm NF X 31-107; AFNOR, 1999).

Statistical analyses

All of the statistical analyses were done using R software (version 3.5.1). First, extreme values were removed following the outlier labelling rule with a conservative tuning parameter of g = 2.2 [START_REF] Hoaglin | Fine-tuning some resistant rules for outlier labeling[END_REF]. On average, 1.25% of data were removed. Weighted means, using soil weight per layer, were used when presenting values per soil column.

Mixed models were used to assess the effect of the following fixed effect factors: tree species composition (pure birch, pure pine, mixed birch-pine), water availability (irrigation, control), soil depth (five depths as levelled factors) and their interaction, on the enzyme activities and available nutrients. Block was included as a random factor to account for the spatial structure of our experimental design. Plots were then nested within the block random factor to enable a comparison of treatments within each block separately. Finally, the sampling replicate number was nested within the plot to account for the non-independency of soil horizons within a soil core of a certain plot. Soil moisture was added as a co-variable in the mixed model. We then applied contrasts and performed post-hoc tests Tukey HSD post-hoc tests, with α = 0.05 used as the level to define significance.

We calculated non-additive effects of mixing birch and pine trees by comparing observed values in the mixed-species plots to expected values, calculated as the mean enzyme quantities of the component species in the monocultures [START_REF] Barantal | C , N and P fertilization in an Amazonian rainforest supports stoichiometric dissimilarity as a driver of litter diversity effects on decomposition[END_REF]. We used a Welch two sample t-test to test whether the observed enzyme quantities differed from the expected enzyme quantities for control and irrigated treatments. The percentage increase in enzyme quantities (the relative mixture effect) was calculated by ((observed -expected)/expected) * 100, according to [START_REF] Wardle | Biodiversity and plant litter: experimental evidence which does not support the view that enhanced species richness improves ecosystem function[END_REF]. Then, we used a redundancy analysis (RDA) to elucidate the relationships between individual enzymes and their respective biochemical variables (i.e. available nutrients, root biomass, and soil characteristics), included as the socalled environmental variables. We also included enzyme ratios as supplementary variables in the RDA. Finally, we used Mantel tests with Spearman's rank correlations (n = 999 permutations) to quantify the relationship between enzyme activities and environmental variables.

Results

Soil chemical properties

Soil texture did not vary between irrigated and control blocks with on average 95% sand, 2% silt, and 3% clay (Table S1). Soil pH increased down the soil profile in all plots (Table S2), and varied according the interaction between soil depth and plot species composition (p = 0.028). Additionally, soil moisture varied between depths in all plots (p < 0.001, Table S2), with a decreasing trend from the top to the bottom soil.

Averaged across all species treatments, soil moisture was significantly higher in the irrigated blocks than in the control blocks for the 0-5 cm (p < 0.05) and the 30-60 cm layers (p < 0.01) (Table S2), despite that the soil sampling was done in March, a period when the irrigation was switched off.

The forest floor C:N ratio was significantly higher in irrigated than in control blocks (p = 0.02, Table 1). The forest floor C:N in the pure birch was significantly lower than that in the mixed species plots (p = 0.002) and the pure pine plots (p < 0.001, Table 1). Irrigation increased the litterfall C:N ratio in the three different species compositions (Table 1).

Enzyme activities and available nutrients

There was a significant effect of the interaction between the plot species compositions and soil depth for the C-related EEAs (p < 0.0001), N-related EEAs (p = 0.01), and P-related EEA (p = 0.02) (Table 2). In both pure birch and pure pine plots, C-and N-related EEAs decreased steadily from the 0-5 cm to the 60-90 cm layer (Fig 1A). However, the pattern was different in mixed birch and pine plots: there was a sharp increase in EEAs from the 5-15 cm layer to the 15-30 cm layer. At this 15-30 cm mid soil layer, C-related EEAs were significantly higher than those in pure plots, with an increase on average of 77 % (Fig. 1A), and N-related EEAs were significantly higher (+ 49 %) than in pure pine plots (p = 0.037) (Fig. 1B). This resulted in synergistic, non-additive effects at this intermediate soil layer (Fig. 2): the effect of mixing birch and pine was however restricted to this soil depth, and was independent of irrigation with a similar increase in both control and irrigated blocks for C-and N-related EEAs. In contrast, the P-related enzyme activity decreased with depth similarly in all species compositions, but was 24 % lower in the mixed plot at the 30-60 cm layer compared with the monocultures (Fig. 1C). There were more C-and Nrelated EEAs in pure birch than pure pine plots at the 0-5 cm layer in control blocks, but no overall significant differences were observed along the soil profile between the monocultures for each of the C-, N-and P-related EEAs.

Our results also showed an overall positive effect of irrigation on N-related EEAs (Table 2): averaged among species treatments along the soil profile, irrigation increased N-related EEAs by 28 % compared with control blocks (Fig. 3A). From the 0-5 cm to the 5-15 cm soil layer, there was a sharp decrease of N-related EEAs in both control and irrigated blocks. These values remained steady down to the 15-30 cm layer, after which there was another steady decline down to the 60-90 cm layer.

For P-related EEAs, the overall enzyme pattern was similar to N-related EEAs, with a steady decline down to the 60-90 cm layer. However, the significant effect of irrigation on the P-related EEA depended on soil depth (Table 2): AP activity in irrigated blocks tended to be higher only in the first 30 cm, with an increase on average of 20 % compared with control blocks (Fig. 3B).

Although total N varied in the top 0-5 cm soil layer from an average of 1.06 mg N g -1 in control blocks to 1.26 mg N g -1 in irrigated blocks (data not shown), we found that available N was relatively low in both water treatments (Fig. 4). N availability was interactively affected by soil depth and irrigation (p < 0.0001): adding water decreased available N by 40 % in the first soil horizons layers (0-15 cm) while it increased available N by 55% in depth (30-90 cm) (Fig. 4A). Available P also differed along soil depth (Table 2). It increased from 0-5 to 5-15 cm in all plots and then steadily decreased until the 60-90 cm layer (Fig. 4B).

Environmental effects

Mantel tests showed that the seven individual hydrolytic enzymes were significantly correlated with the available nutrients and the belowground root traits (ρ = 0.569, p < 0.001). Biplots from the RDA distinguished the C-related EEAs (XYL, BGLU, AGL, CBH) from the N-related EEAs (NAG, LAP) and P-related EEA (AP) along the second axis, which weakly represented the variance of the system (Fig. 5).

Available N was negatively related to the N-related EEAs along the first axis. The total tree species' fine root biomass within a plot and soil moisture, were also negatively related to the available N. The C-related EEAs fitted closely with the available P, which was unrelated to the AP enzyme. Both the Cenz:Penz and Cenz:Nenz ratios (supplementary variables in green, Fig. 5) were closely related to the available P. The understory species fine root biomass within a plot species composition was generally unrelated to the individual enzyme activities.

As a whole, we found no correlation between the available N and the Cenz:Nenz ratio (adj. R 2 = 0.003, p = 0.12, Fig. 6A). However, we found a highly significant positive correlation between the available P and the Cenz:Penz enzyme ratios (adj. R 2 = 0.24, p < 0.0001, Fig. 6B). This relationship was consistent across the three species compositions and water availability treatments.

Discussion

By using a 10-year-old plantation which manipulates tree species composition and irrigation in southwestern France, we investigated the effect of mixing birch and pine, water availability, and their interaction on seven hydrolytic extracellular enzyme activities (EEAs) and available nutrients along the soil profile. Our results are partly in agreement with our two first hypotheses, thereby demonstrating that EEAs directly depend on tree species composition and water conditions. In contrast to our last hypothesis, we did not find any effect of the interaction between water availability and species mixing on EEAs, underlying that the negative effect of lower water availability cannot be offset by the positive effect of mixing tree species.

Effect of mixing tree species

In agreement with our first hypothesis, we found that mixing birch and pine had a positive effect on C-and N-related EEAs in interaction with soil depth (Table 2). However, contrary to our expectations that this effect should be more pronounced in the topsoil [START_REF] Alberti | Tree functional diversity influences belowground ecosystem functioning[END_REF], we observed a strong synergistic increase in Crelated and N-related EEAs in the 15-30 cm soil layer compared to both birch and pine monocultures (Fig. 1, Fig. 2). While the litter quality was significantly higher in birch than in pine plots (lower C:N ratio, Table 1), the EEAs in the pure birch plots were only slightly higher than those in the pure pine plots (Fig. 1). Although we expected an influence of tree species identity [START_REF] Purahong | Tree species, tree genotypes and tree genotypic diversity levels affect microbe-mediated soil ecosystem functions in a subtropical forest[END_REF] and litter quality on microbial decomposition and EEAs [START_REF] Sinsabaugh | Allocation of extracellular enzymatic activity in relation to litter composition, N deposition, and mass loss[END_REF], the little influence of the tree species on EEAs has been found in other studies. For instance, [START_REF] Herold | Vertical gradients of potential enzyme activities in soil profiles of European beech, Norway spruce and Scots pine dominated forest sites[END_REF] found no differences between coniferous and deciduous central European forests on six of our measured EEAs. Likewise, [START_REF] Weand | Effects of tree species and N additions on forest floor microbial communities and extracellular enzyme activities[END_REF] described no tree species effect on C-, N-and P-related enzymes in five single-species plots in an American Northeastern hardwood forest. This was also true for the N-and P-related EEAs studied in five tree species in a temperate secondary forest in Northeastern China [START_REF] Diao | Native broad-leaved tree species play key roles on maintaining soil chemical and microbial properties in a temperate secondary forest, Northeast China[END_REF]. Therefore, it is unlikely that the increase in EEAs at the mid-soil layer of the mixed birch-pine plot was related to the different and complementary foliar litter quality of the two species. Instead, we interpret our results as a consequence of the higher nutrient demand of mixed stands. Indeed, higher tree productivity in mixed stands may stimulate soil microbial biomass through an increase in root exudate quantity and diversity [START_REF] Steinauer | Root exudate cocktails: the link between plant diversity and soil microorganisms?[END_REF], or favor C allocation to ectomycorrhizal fungi to get N from organic molecules to sustain tree biomass production [START_REF] Fernandez | Revisiting the "Gadgil effect": do interguild fungal interactions control carbon cycling in forest soils?[END_REF][START_REF] Lindahl | Ectomycorrhizal fungi -potential organic matter decomposers, yet not saprotrophs[END_REF]. Alternatively, niche partitioning in root systems or increase in root biomass along the soil profile may have increased nutrient uptake [START_REF] Jose | Belowground ecological interactions in mixed-species forest plantations[END_REF], which may exacerbate, in turn, nutrient limitation of microorganism communities [START_REF] Kuzyakov | Competition between roots and microorganisms for nitrogen: mechanisms and ecological relevance[END_REF]. In both cases, this implies that there is likely a strong demand by microorganisms to degrade the soil organic matter [START_REF] Fatemi | Nitrogen and phosphorus regulation of soil enzyme activities in acid forest soils[END_REF] at this middle soil layer in mixed stands, and indicates that the potential effects of tree diversity on EEAs are not only limited to the superficial soil layers.

Contrary to C-and N-related EEAs, we found that there was a decrease in the P-related EEA in the 30-60 cm soil layer in the mixed-species plots compared to both birch and pine monocultures (Fig. 1C). This may be due to a shift in the nutrient needs of the microorganisms [START_REF] Mooshammer | Adjustment of microbial nitrogen use efficiency to carbon:nitrogen imbalances regulates soil nitrogen cycling[END_REF] or because the changes in tree species diversity may lead to a shift in the structure of microbial communities [START_REF] Liu | Effects of tree species and soil properties on the composition and diversity of the soil bacterial community following afforestation[END_REF][START_REF] Pei | Soil and tree species traits both shape soil microbial communities during early growth of Chinese subtropical forests[END_REF][START_REF] Schweitzer | Plant-soil-microorganism interactions: Heritable relationship between plant genotype and associated soil microorganisms[END_REF]. For instance, changes in fungi to bacteria ratios may alter the stoichiometric requirements at the community scale [START_REF] Fanin | An experimental test of 30 the hypothesis of non-homeostatic consumer stoichiometry in a plant littermicrobe system[END_REF], which could explain the reduced and different effect of tree diversity on N-and P-related EEAs. On the other hand, this may be caused by differential root uptake and competition for the available nutrients between microorganisms and both tree and understory roots [START_REF] Kuzyakov | Competition between roots and microorganisms for nitrogen: mechanisms and ecological relevance[END_REF][START_REF] Richardson | Soil microorganisms mediating phosphorus availability[END_REF]. This hypothesis is supported by the tendency of available N and P to decrease and increase respectively in mixed plots (Fig. S3), although the overall effect of tree species for the entire soil column was nonsignificant (Table 2). Taken together, these findings suggest that there is a shift in microbial C:N:P stoichiometry from monocultures to the two-species mixture along the soil profile.

Effect of water availability

In accordance with our second hypothesis, we found an increase in both Nand P-related EEAs with irrigation. Overall, EEAs were lower in the control blocks (Table S3), which were subject to the long dry summers of southwestern France (Fig. S1). Although we sampled in early spring, i.e. several months after the irrigation had been switched off, we still found differences in soil moisture between control and irrigated blocks (Table 1). The legacy of sub-optimal water conditions for the past eight years in the control blocks may have led to a decrease in both microbial biomass [START_REF] Brockett | Soil moisture is the major factor influencing microbial community structure and enzyme activities across seven biogeoclimatic zones in western Canada[END_REF] and tree and understory root biomass (Table S2; [START_REF] Brunner | How tree roots respond to drought[END_REF]. The lower EEAs in these dry control blocks could thus be due to fewer microorganisms and roots, leading to less root exudation and enzyme stimulation [START_REF] Zhang | Spatial pattern of enzyme activities depends on root exudate composition[END_REF]. This interpretation is supported by our RDA results, where tree fine root biomass points in the same direction as soil moisture (Fig. 5), demonstrating a positive covariation between these variables. The drought episodes experienced by control blocks and not by irrigated blocks, at various periods during the three summers (Fig. S1), may have caused a significant change in the composition of root exudates, both during these drought periods and after rewetting [START_REF] Gargallo-Garriga | Root exudate metabolomes change under drought and show limited capacity for recovery[END_REF]. Alternating periods of drying and rewetting, and changes in root exudation, can also have an influence on microbial hotspots and thus microbial abundance and activity [START_REF] Kuzyakov | Microbial hotspots and hot moments in soil: Concept & review[END_REF], which could help explain lower EEAs in control blocks.

In line with our expectations, the effect of irrigation was higher in the topsoil for the P-related EEA (Fig. 3). This is probably because microbial communities benefit more of increasing humidity in soil layers that are more subjected to drought and where the substrate is relatively nutrient rich [START_REF] Fanin | Relative Importance of Climate, Soil and Plant Functional Traits During the Early Decomposition Stage of Standardized Litter[END_REF]. However, this effect was relatively constant throughout the soil column for N-related EEAs. This result is in line with the idea that there is a shift in the requirements of microbial communities at the community scale along the soil profile [START_REF] Fanin | An experimental test of 30 the hypothesis of non-homeostatic consumer stoichiometry in a plant littermicrobe system[END_REF][START_REF] Mooshammer | Adjustment of microbial nitrogen use efficiency to carbon:nitrogen imbalances regulates soil nitrogen cycling[END_REF], and may explain the variability in nutrient availability from the top to the bottom soil layers (Fig. 4). Indeed, irrigation had a negative effect on available N in the topsoil. This is probably due to important N uptake by trees and the understory, coupled with a leaching of soluble mineral N-forms (NH4 + and NO3 -) into the deeper soil layers, where irrigation had a positive effect on available N (Table 2, Fig. 4A). In contrast, the available P was generally low and unaffected by the different factors (Table 2, Fig. 4B). The lack of significant increase in available P within the 0-30 cm soil layer may be due to a strong and rapid absorption by tree roots in the topmost layer. High understory root biomass in deeper soils (Table S2) and a general decrease in P desorption along the soil profile [START_REF] Achat | Contributions of microbial and physical-chemical processes to phosphorus availability in Podzols and Arenosols under a temperate forest[END_REF], may explain the decrease in available P along the soil profile. The differing effects of water availability on available nutrients point towards a strong influence of organic matter quality and associated microorganism communities to explain the EEAs' responses.

Furthermore, because C-related enzymes were not as affected as other EEAs by irrigation, the result reinforces the idea that changes in organic matter quality are also important drivers of EEAs under low water availability. The lower litterfall and forest floor C:N ratios in dry blocks compared to irrigated blocks support this hypothesis (Table 1). Indeed, higher tree growth rates when water conditions are favourable reduce available N input to soils, with further consequences on N limitations in our study system. Along the entire soil profile, we found less available N in the non-irrigated blocks (Table S3). Taken together, these results highlight that changes in precipitation regimes may have important consequences on EEAs through direct effects of water availability and indirect effects through tree growth on organic matter quality and nutrient availability.

Effect of the interaction between mixing tree species and water availability

Although we hypothesized that mixing birch and pine could mitigate the effects of lower water availability on nutrient availability and EEAs, we did not find such a compensatory effect (Table 2). Studies at larger scales have shown that biodiversity may become more beneficial as water limitations increase [START_REF] Lebourgeois | Mixed stands reduce Abies alba tree-ring sensitivity to summer drought in the Vosges mountains, western Europe[END_REF][START_REF] Pretzsch | Resistance of European tree species to drought stress in mixed versus pure forests : evidence of stress release by interspecific facilitation[END_REF][START_REF] Ratcliffe | Biodiversity and ecosystem functioning relations in European forests depend on environmental context[END_REF], but some other studies contradict this statement. For example, Jucker et al. (2014b) found that the magnitude of the biodiversity effect on aboveground biomass production decreases in strength during drought years, and [START_REF] Jactel | Positive biodiversity-productivity relationships in forests: climate matters[END_REF] found high overyielding due to mixing tree species at wet sites at the stand level. Additionally, we suggest that the lack of a significant interaction effect between mixing birch and pine trees and water availability might be due to the spatial segregation of the individual effects of these two factors. While mixing the two tree species tended to increase EEAs in the midsoil layer, irrigation tended to increase EEAs and decrease available N in the top soil.

Moreover, we collected our samples in March, when the control blocks were not under water stress and the irrigation treatment had not yet begun for the year (Table 1).

Finally, the lack of effect due to the species mixing may be simply the consequence of the lack of differences between the tree species themselves. Indeed, we did not see different patterns of the effect of water availability on EEAs between the two monocultures. This might be surprising given that Pinus pinaster is a fairly more drought tolerant species compared to Betula pendula [START_REF] Choat | Global convergence in the vulnerability of forests to drought[END_REF].

However, the tolerance difference is quantitatively modest (sapwood hydraulic vulnerability P50: Pinus pinaster = -2.8 to -3.7 Mpa, Betula pendula = -2.2 to -2.4

Mpa [START_REF] Choat | Global convergence in the vulnerability of forests to drought[END_REF]Delzon, unpublished data)), and both species' roots similarly explored the entire soil profile in the dry control and irrigation treatments (Table S2), which could explain the small effects of species identity and, in turn, of mixing species. Additional analyses including more tree species and more sampling dates are needed to further evaluate the relationship between EEAs and tree diversity, as well as intra annual temporal variation of EEAs and biodiversity effects [START_REF] Cardinale | Biodiversity loss and its impact on humanity[END_REF].

Environmental effects and larger implications for nutrient cycling

The RDA gives us new insight into how environmental variables may have an effect on different enzyme activities (Fig. 5). Available N was negatively correlated with the tree species' fine root biomass along the first axis, likely due to rapid nutrient absorption by roots, which led to N-depletion in the topsoil where roots thrive [START_REF] Giehl | Root Nutrient Foraging[END_REF]. N-related EEAs may have been stimulated by this low N availability in order to maintain high growth rates [START_REF] Kaye | Competition for nitrogen between plants and soil microorganisms[END_REF], or by tree root exudation [START_REF] Renella | Microbial activity and hydrolase activities during decomposition of root exudates released by an artificial root surface in Cd-contaminated soils[END_REF][START_REF] Zhang | Spatial pattern of enzyme activities depends on root exudate composition[END_REF]. Indeed, N-related EEAs were also positively correlated to tree species' fine root biomass (Fig. 5). To a lesser extent, the P-related enzyme was negatively correlated to available P, likely due to similar feedback mechanisms.

Interestingly, we also found that C-related EEAs were strongly related to available P. This implies that when P availability is high, microorganisms are strongly limited by C, inciting them to produce more C-related enzymes to get access to the energy produced by decomposing organic matter [START_REF] Fanin | Stoichiometric plasticity of microbial communities is similar between litter and soil in a tropical rainforest[END_REF](Fanin et al., , 2016b)). This hypothesis was supported by the significant positive correlation between available P and the Cenz:Penz ratio across all species and water availability treatments (Fig. 6B), which we did not find between the available N and the Cenz:Nenz ratio (Fig. 6A). This is likely because alleviating P limitation generates a new constraint for microorganisms and thus the necessity to acquire C from organic molecules in these P-poor podzol soils [START_REF] Achat | Evaluation of the phosphorus status of P-deficient podzols in temperate pine stands: Combining isotopic dilution and extraction methods[END_REF][START_REF] Augusto | Soil parent material -A major driver of plant nutrient limitations in terrestrial ecosystems[END_REF]. This relationship was true regardless of species composition, water availability, or soil depth, suggesting that P limitation plays a more important role in controlling C-related enzymes. Thus, potential C sequestration is likely to be limited by P availability in these nutrient-poor forests.

Conclusions

This study revealed that water supply and mixing pine and birch trees could have important long-term effects on soil extracellular enzyme activities (EEAs). First, from a management perspective, our results suggest that overall C sequestration in our system is likely to be constrained by P availability, regardless of water availability.

Second, we found C-N-P decoupling effects as a result of tree species mixing or improved water availability, which may alter microorganism stoichiometry and belowground C, N, P fluxes. Finally, the lack of interactive effects between mixing birch and pine, and water supply, suggests that the negative effect of lower water availability on microbial activity cannot be offset by the positive effect of mixing these two species. The next step will be to sample at different seasons to investigate the possible temporal variations of EEAs and to measure other belowground processes such as protein depolymerisation and mineralization, in order to assess the dynamics of interactive effects between water availability and tree diversity over seasons and disentangle underlying mechanisms. A) Non-correlation between available nitrogen and the ratio between the C-related enzymes the and the N-related enzymes (Cenz:Nenz); B) Positive correlation between the available phosphorus and the ratio between the C-related enzymes and the P-related enzyme (Cenz:Penz). The water availability treatments were pooled for each species composition treatment. Table 1 2 Selected properties of the study site in the three different tree species compositions, each in 3 both dry control and irrigated blocks. Data are mean ± standard error of the mean (n = the total 4 number of samples per treatment).

5 Note: Litterfall was collected in the fall, while forest floor, soil moisture and soil pH were collected in 6 early spring. Three blocks of each water availability treatment were sampled for litterfall while four 7 blocks were sampled for the other variables. We analyzed one composite sample per plot for litterfall, 8 forest floor and pH or four replicates per plot for soil moisture. Weighted means were calculated for 9 soil pH and soil moisture along the soil profile and detailed data per soil depth layer can be found in 10 Results of the linear mixed effects models to test for the effects of tree species composition (pure birch, pure pine, mixed birch +pine), water availability (irrigation, dry control), soil depth and their interactions on C-related EEAs (sum of XYL, AGLU, BGLU, and CBH), Nrelated EEAs (sum of NAG and LAP), P-related EEA (AP), available N and available P. Soil moisture was used as a covariable in the model and not shown here. Significant results are in bold font.

FiguresFigure Captions Fig. 1 .

 Captions1 Figures

Fig. 2 .

 2 Fig. 2. Synergistic non-additive effect of mixing birch and pine in the 15-30 cm soil layer on

Fig. 3 .

 3 Fig. 3. Distribution of the extracellular enzyme activities (EEAs) along the soil profile in dry

Fig. 4 .

 4 Fig. 4. Distribution of the available nutrients along the soil profile in dry control blocks(circles, red) and irrigated blocks (squares, blue); A) available N (µg N g -1 ); and B) available P (µg P g -1 ). The tree species composition treatments were pooled for each water availability

Fig. 5 .

 5 Fig. 5. Redundancy analysis (RDA) ordination biplot of the seven hydrolytic extracellular

Fig. 6 .

 6 Fig.6. Relationship between available nutrients and enzyme ratios in the pure birch (circles,

  Figure 1

Figure 6 1

 61 Figure 6

Table S2 .

 S2 11

			Birch	Birch + Pine	Pine
		n	Control	Irrigation	Control	Irrigation	Control	Irrigation
	Litterfall C:N	3 39.88 ± 3.69 50.96 ± 3.47	99.50 ± 21.78	110.19 ± 27.54	149.39 ± 9.22	160.43 ± 4.22
	Forest floor C:N	4 35.85 ± 0.88 37.42 ± 2.78	42.15 ± 4.61	61.00 ± 4.79	51.58 ± 2.95	69.61 ± 8.05
	Soil moisture (%) 16 13.21 ± 0.45 12.79 ± 0.45	12.46 ± 0.61	12.86 ± 0.76	12.54 ± 0.81	13.91 ± 0.63
	Soil pH [H2O]	4	4.50 ± 0.04	4.62 ± 0.06	4.45 ± 0.05	4.46 ± 0.04	4.49 ± 0.05	4.67 ± 0.17

Acknowledgements

We thank Coralie Chesseron, Nathalie Gallegos, Cathy Lambrot, and Kathina Müssig for their help in the field and the laboratory, Bastien Castagneyrol for his guidance and help, Els Dhiedt for the tree graphics, and Lukas Weilguny for help with supplementary figure design. We thank the Forest experimental Facility and especially Bernard Issenhuth for maintenance of the ORPHEE experiment. This work was supported by the ANR project DiPTiCC (16-CE32-0003), the BEnEFIC project to NF supported by the EFPA department at INRAE, and the "Thèses en partenariat international" project of the Excellence Initiative of the University of Bordeaux to TLM.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Souad Assaad

Virginie Avrillon

Marie-Line Fournier

Benedicte Mastroianni

Bruno Russias

Aurélie Swalduz

Philippe Cassier

Lauriane Eberst

Marie-Pierre Steineur

Marianne Kazes

Maurice Perol

Anne-Sophie Michallet

Philippe Rey

Anne-Sophie Erena-Penet

Astrid Morel

Mehdi Brahmi

Armelle Dufresne

Olivier Tredan

Gisèle Chvetzoff

Jérome Fayette

Christelle De La Fouchardiere

Isabelle Ray-Coquard

Thomas Bachelot

Pierre Saintigny

Mayeul Tabutin

Aurélien Dupré

Emmanuelle Nicolas-Virelizier

Amine Belhabri

Pierre-Eric Roux

Christine Fuhrmann

Franck Pilleul

Alexandre Basle

Amine Bouhamama

Christelle Galvez

Andrée-Laure Herr

Julien Gautier

Sylvie Chabaud

Philippe Zrounba

David Perol

Prof J.-Y Y Blay

High mortality rate in cancer patients with symptoms of COVID-19 with or without detectable SARS-COV-2 on RT-PCR

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The death rate of COVID-19 patients is reported to be close to 2% [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention[END_REF]. Cancer patients are a group at higher risk of serious and lethal complications of COVID-19 [START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF]. The 30-days survival of patients with cancer presenting with documented COVID-19 has been reported to be 60% to 70% in recent series [START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF]. These results were reported in particular from large oncology hospital in China, and were compared with patients with COVID-19 without cancer. Variability in death rates has been reported across countries and within countries possibly related to differences in screening strategies but also different population susceptibility [START_REF] Richardson | Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area[END_REF][START_REF] Rodriguez-Morales | Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis[END_REF][START_REF] Goyal | Clinical Characteristics of Covid-19 in New York City[END_REF][START_REF] Borges Do Nascimento | Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis[END_REF][START_REF]Geographic Differences in COVID-19 Cases, Deaths, and Incidence -United States[END_REF].

The mechanisms by which the associated condition of cancer influences the risk of death to COVID-19 remains unclear. Whether this is related to the age group of cancer patients, coexisting causes (tobacco, comorbidities …), to cancer staging, or to cancer treatment recently applied is not clear. Identifying the characteristics of cancer patients with COVID-19 at risk of a severe complication, or death would be useful to propose specific preventive measures and to adapt clinical trials.

The number of cancer patients affected with COVID is possibly underestimated. The sensivity of RT-PCR diagnostic tests for COVID -19 ranges from 37% to 55% according to published evidence for patients with typical clinical presentation of COVID-19 [START_REF] Patel | Report from the American Society for Microbiology COVID-19 International Summit[END_REF][START_REF] Vashist | In Vitro Diagnostic Assays for COVID-19: Recent Advances and Emerging Trends[END_REF][START_REF] Li | Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19[END_REF]. Repeated testing may increase improve detecttion rate in patients with initial negative SARS-COV-2 RT-PCR [START_REF] Vashist | In Vitro Diagnostic Assays for COVID-19: Recent Advances and Emerging Trends[END_REF].

It is therefore important to further analyze the clinical presentation and outcome of cancer patients presenting with suspicion of COVID-19 to identify predictive factors for unfavorable outcome.

In this study (named PRE-ONCOVID-19) was investigated the survival of the exhaustive cohort of 302 patients presenting with clinical suspicion of COVID-19 consulting in a comprehensive cancer center and tested for the presence of the virus using a RT-PCR diagnostic test. The RT-PCR positive and negative subgroups were compared. Cancer patients with documented COVID-19 were found at high risk of death after diagnosis, but cancer patients without documented SARS-COV-2 infection presenting with similar symptoms were also at high risk of death. The latter subgroup represented the majority of patients succumbing during this period suggesting an important underdiagnosis of the SARS-COV-2 infection in cancer patients.

Patients material and methods

Objectives

The objective of the PRE-ONCOVID-19 study was to describe the clinical characteristics and survival of cancer patients presenting with COVID-19 symptoms, comparing 1) patients with documented SARS-COV-2 by RT-PCR, 2) patients with negative SARS-COV-2 RT-PCR test.

Study design

PRE-ONCOVID-19 is a retrospective study of cancer patients presenting to the Comprehensive Cancer Center of Lyon (Centre Leon Berard, CLB), with a suspicion of COVID-19 from March 1st to April 15th 2020. Patient cases were collected using a web based tool enabling the collection of clinical information integrated to the electronic patient record, after Institutional Review Board approval. Patients not agreeing for the use of their clinical data for an academic study, were excluded, according to the national and European laws. The study was approved by the Institutional review board of the Centre Leon Berard on 12 March of 2020.

Patients

The inclusion criteria were : an histological diagnostic of cancer, and the prescription of a diagnostic test of SARS-COV-2 with RT-PCR on a nasopharyngeal sample from March 1st 2020 to April 15th. For SARS-COV-2 RT-PCR, the cobas® SARS-CoV-2 Test (Roche , Neuilly, France) was used, exploring ORF1/a, & the Pan SARS gene E. Cancer patients presenting with clinical symptoms of COVID-19, fever and/or dry cough and/or dyspnea and/or dysgueusia anosmia and/or diarrhea, and/or suspect images on CT scan with or without a contact with a COVID-19-suspected or demonstrated contact person were included in this study. The median follow-up of the present series is 25 days.

Clinical definition of a group of patients with respiratory symptoms

We identified a group of patients with respiratory symptoms suspect of COVID-19 which was defined as patients presenting with at least 2 of the 3 following symptoms : fever, dry cough, dyspnea. The observation period was from March 1st to April 25th. SARS-COV-2 RT-PCR positive and negative patients were compared, for demographics, cancer presentation, cancer characteristics, cancer treatment, clinical, radiological or biological symptoms of COVID-19 and survival.

Data collected in this study

The following data were collected retrospectively : demographic characteristics (age, weight, body mass index, gender,…), cancer characteristics (histotypes, stage, relapse), the clinical presentation at the time of COVID-19 suspicion (Karnofski performance status [KPS], fever, dyspnea, cough, diarrhea, O2 requirement, CNS symptoms, vascular symptoms), presence of characteristic COVID-19 images on CT scan when performed, a selected set of biological analysis at the time of the infectious event (CRP, lymphocyte counts,..), previous cancer treatments in the last month, patient outcome (survival), comorbidities (COPD, hypertension, diabetes) in the electronic patient records. As benchmark, the comorbidities reported in the population of 43171 cancer patients in the CLB since 01/01/2015 are: COPD : 2541 (5.8%), hypertension : N=11204 (25.9%), diabetes : N=8514 (19.7%). Several additional biological factors not suystematically collected were available in less than 15% of the patients ((D-Dimers, troponine, CPK) and for LDH in 35% of the patients and therefore not analyzed in this series.

Because neutrophil counts are strongly influenced by recent (<1 month) cytotoxic treatements (administered in N=137, 45% of the patients in this series), we used absolute lymphocyte counts and not neutrophil/lymphocyte ratio in this work.

Statistical analysis

The distribution of risk factors or clinical characteristics were analyzed using the Chi square test, Fisher exact test, Mann-Withney U test. The Bonferroni correction was used for multiple Chi quare testing. Survival were plotted from the date of first symptoms to the date of death or to the date of last news if alive at the time of the analysis (April 25 th , 2020). Survival was plotted according to the inverse Kaplan-Meier method, and groups were compared using the logrank test. Risk of death was evaluated using Cox proportional hazard model in univariate and then multivariate analysis. Backward selection procedure was used to determine the final model by removing non-significant variables (p>0.10) one at a time. All statistical analyses will be performed using SPSS 23.0 software SPSS (IBM, Paris, France).

Results

Clinical characteristics of 302 cancer patients consulting for a suspicion of COVID-19 (Table 1)

As shown on Table 1, only 55 of 302 (18.2%) patients consulting for suspicion of COVID-19 had detectable SARS-COV-2 with RT-PCR on nasopharyngeal samples. SARS-COV-2 RT-PCR+ patients were older, had more frequently haematological malignancies, respiratory symptoms, diarrhea, and anosmia/agueusia, as well as suspected COVID-19 pneumonia of CT scan (Table 1). No single solid tumor subtypes were over-represented in the SARS-COV-2 RT-PCR+ subgroup (Table 1, legend). Present tobacco use (N=35, 11.6%), former tobacco use (N=61, 20.2%), report of COPD (N=26, 8.6%), diabetes (N=55, 18.2%), hypertension (N=79, 26.2%) in the electronic patient records were not significantly different between the SARS-COV-2 RT-PCR positive and negative subgroups. Recent cancer treatments (any, cytotoxics, PD1 Ab, anti-CD20, mTOR inhibitors, antiangiogenic tyrosine kinase inhibitors) were not different between the 2 groups (Table 2). However, 94 of 247 (38%) RT-PCR negative patients at the date of symptoms also had COVID-19 respiratory symptoms (defined as at least 2 of the following : fever, dry cough, dyspnea), and 32 of the 247 (20%) had characteristic CT scan images of COVID-19 pneumonia. The majority of patients in both subgroups were lymphopenic : 91 (33.5%) had deep lymphopenia<700/µL at the time of the infection. Similarly, both subgroups of patients had major inflammatory syndrom with a median CRP level of 96 mg/L at the date of RT-PCR, and over 16% of patients with CRP levels above 200mg/L.

Survival of RT-PCR positive and negative cancer patients

Figure 1 shows the survival of SARS-COV-2 RT-PCR+ and RT-PCR-patients in the observation period between march 1st and April 25th. Eight of the 55 RT-PCR+ patients and 22 of the 147 RT-PCR-patients had died at the time of the analysis. With a median follow-up of 25 days, the death rates of RT-PCR positive and negative patients 25 days after the first symptoms were respectively 21% and 10%, and were not significantly different. Both the RT-PCR negative and positive groups had therefore a high death rate. None of the 302 patients of this series have received azithromycine, chloroquine, lopinavir/ritonavir, or remdesivir. One patient each received GNS561 (a chloroquin analog) and tocilizumab as part of an ongoing randomized clinical trial s standard treatment (Immunoncovid-20, NCT04333914).

The majority (24/30,80%) of cancer patients who died in this observation period had metastatic disease, both in the RT-PCR+ and RT-PCR-patients. Five patients had febrile neutropenia and none died (not shown). Present or past tobacco use, body mass index, histological subtype of the solid tumor, haematological malignancies, smoking history, comorbidities as described above were not correlated to the risk of death in these series (not shown). The administration of any cancer treatment in the month prior to the date of the first symptoms was not associated to an increased risk of death. Treatment with cytotoxics, anti CD20, anti-PD1/PDL1, mTOR inhibitors, or antiangiogenic tyrosine kinase inhibitors were not associated with an increased risk of death, neither in the SARS-COV-2 RT-PCR+ nor in the RT-PCR-subgroups (Table 2).

Table 3 shows parameters associated with an increased risk of death in the whole series and in the two SARS-COV-2 RT-PCR+ and RT-PCR-subgroups. Both in the RT-PCR positive and negative groups (Table 3), significant risk factors for death in univariate and multivariate analysis. were male gender, KPS<60, treatment at relapse relapse, and respiratory symptoms (defined as at least 2 of the 3 : fever, dry cough, dyspnea, see patients and methods).

The multivariate analysis of risk factors for death identified these clinical parameters as well as lymphopenia <700/µL as independent risk factors for death, both in the overall population and in the SARS-COV-2 RT-PCR negative population (Table 3). A multivariate analysis was not performed in the SARS-COV-2 RT-PCR positive population given the limited sample.

Importanly, the presence of a SARS-COV-2 RT-PCR positive test was not significantly correlated to the risk of death in the overall population in univariate or multivariate analysis.

In view of these observations, we compared the survival of patients with positive and negative SARS-COV-2 RT-PCR presenting with respiratory symptoms (defined above in patients in methods, i.e. at least 2 of the following symptoms fever, dry cough, dyspnea) and/or CT scan images of COVID-19 pneumonia to that of the remaining patients. As shown of figure 2, the survival of RT-PCR positive and negative patients with respiratory symptoms and/or COVID-19 pneumonia at entry was worse than than of other patients. They were also similar in the SARS-COV-2 RT-PCR negative and positive subbroups with 18.4% and 19.7% death rate at day-25 after the initial symptoms (Figure 2). Most of the patients who succumbed during the observation period (22/30, 73%) were negative for SARS-COV-2 on RT-PCR.

Discussion

Since January 2020, COVID-19 epidemic has resulted in a very large number of deaths worldwide, in particular in frail patient populations [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention[END_REF][START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF][START_REF] Richardson | Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area[END_REF][START_REF] Rodriguez-Morales | Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis[END_REF][START_REF] Goyal | Clinical Characteristics of Covid-19 in New York City[END_REF][START_REF] Borges Do Nascimento | Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis[END_REF][START_REF]Geographic Differences in COVID-19 Cases, Deaths, and Incidence -United States[END_REF]. The population of cancer patients has been reported to be particularly at risk of early death during COVID-19, with 30-days death-rates up to 39% in the initial report, vs 2.3% in the general population [START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF]. Since then, additional series confirmed a high risk of death in cancer patients, which represents one of the highest risk population along with elderly patients, patients with overweight, diabetes, hypertensive disease and other associated conditions [START_REF] Wu | Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention[END_REF][START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF][START_REF] Richardson | Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area[END_REF][START_REF] Rodriguez-Morales | Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis[END_REF][START_REF] Goyal | Clinical Characteristics of Covid-19 in New York City[END_REF][START_REF] Borges Do Nascimento | Novel Coronavirus Infection (COVID-19) in Humans: A Scoping Review and Meta-Analysis[END_REF][START_REF]Geographic Differences in COVID-19 Cases, Deaths, and Incidence -United States[END_REF]. This death rate of cancer patients is higher to that observed in large series of cancer patient consulting in emergency reported from this and other institutions, most often <5% [START_REF] Glare | Diagnostic accuracy of the palliative prognostic score in hospitalized patients with advanced cancer[END_REF][START_REF] Bourgeois | Clinical validation of a prognostic tool in a population of outpatients treated for incurable cancer undergoing anticancer therapy: PRONOPALL study[END_REF][START_REF] Lalami | Impact of chemotherapy-induced neutropenia (CIN) and febrile neutropenia (FN) on cancer treatment outcomes: An overview about well-established and recently emerging clinical data[END_REF][START_REF] Ray-Coquard | Identification of patients at risk for early death after conventional chemotherapy in solid tumours and lymphomas[END_REF][START_REF] Ray-Coquard | Baseline and early lymphopenia predict for the risk of febrile neutropenia after chemotherapy[END_REF][START_REF] Péron | CD4 lymphopenia to identify end-of-life metastatic cancer patients[END_REF]. This death rate is also higher than that reported for seasonal influenza in large historical series (9%) and close to that reported with H1N1 (16%) [START_REF] Cooksley | Epidemiology and outcomes of serious influenza-related infections in the cancer population[END_REF][START_REF] Ángeles-Sistac | Influenza in patients with cancer after 2009 pandemic AH1N1: An 8-year follow-up study in Mexico[END_REF].

The description of COVID-19 mortality is further complexified by the limited sensivity of the diagnostic tests [START_REF] Patel | Report from the American Society for Microbiology COVID-19 International Summit[END_REF][START_REF] Vashist | In Vitro Diagnostic Assays for COVID-19: Recent Advances and Emerging Trends[END_REF][START_REF] Li | Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19[END_REF][START_REF] Solodky | Lower detection rates of SARS-COV2 antibodies in cancer patients vs healthcare workers after symptomatic COVID-19[END_REF]. Biological diagnostic tests of COVID-19 are based on the detection of the virus using RT-PCR from biological (nasopharyngeal samples) or on the detection of specific antibodies [START_REF] Patel | Report from the American Society for Microbiology COVID-19 International Summit[END_REF][START_REF] Vashist | In Vitro Diagnostic Assays for COVID-19: Recent Advances and Emerging Trends[END_REF][START_REF] Li | Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19[END_REF][START_REF] Solodky | Lower detection rates of SARS-COV2 antibodies in cancer patients vs healthcare workers after symptomatic COVID-19[END_REF]. Both types of tests have limits in sensitivity, leading to false negative testing in a a significant proportion of patients, even in the acute phase of the disease. For RT-PCR, the sensitivity has been reported to be inferior to 40% for the first testing, increasing up to 50% on repeated testing [START_REF] Vashist | In Vitro Diagnostic Assays for COVID-19: Recent Advances and Emerging Trends[END_REF]. A large proportion of patients with COVID-19 are therefore not detected by this test and clinical as well as CT scans symptoms are important to identify COVID-19 patients. Serological test also lack senstitivity , in particular in cancer patients [START_REF] Solodky | Lower detection rates of SARS-COV2 antibodies in cancer patients vs healthcare workers after symptomatic COVID-19[END_REF]. The results obtained in the PRE-ONCOVID-19 study show that only a minority, 18.2% (55/302) cancer patients presenting with clinical symptoms of COVID-19 had demonstrated SARS-COV-2 with RT-PCR performed on nasopharyngeal samples. RT-PCR+ patients were slightly older, more frequently affected with haematological malignancies, and frequently presenting with clinical respiratory symptoms, anosmia/agueusia, diarrhea and COVID-19 suspect images on CTscan, but these symptoms were also observed in a large proportion of RT-PCR-patients : close to 40% of patients presented with respiratory symptoms and/or CT scan images of COVID-19. Comorbidities (smoking history, obesity, COPD, diabetes, hypertension) were similar in RT-PCR+ and negative patients in the present series.

The biological characteristics of the RT-PCR+ and RT-PCR-patients were also similar : both populations presented similar major lymphopenia and a major inflammatory syndrome with increased CRP levels, an accurate surrogate of circulating IL-6 levels [START_REF] Solodky | Lower detection rates of SARS-COV2 antibodies in cancer patients vs healthcare workers after symptomatic COVID-19[END_REF][START_REF] Kang | Historical overview of the interleukin-6 family cytokine[END_REF][START_REF] Blay | Serum level of interleukin 6 as a prognosis factor in metastatic renal cell carcinoma[END_REF] reported to be increased in severe COVID-19 [START_REF] Blay | Role of interleukin-6 in the paraneoplastic inflammatory syndrome associated with renal-cell carcinoma[END_REF][START_REF] Negrier | Groupe Francais d'Immunotherapie.Interleukin-6, interleukin-10, and vascular endothelial growth factor in metastatic renal cell carcinoma: prognostic value of interleukin-6--from the Groupe Francais d'Immunotherapie[END_REF].

The majority (24/30) of cancer patients who died, in both groups, had a cancer in relapse. This parameter was retained in the multivariate analysis as a risk factor for death with a high hazard ratio in the whole series and in the 2 subgroups, while comorbidities, of SARS-COV-2 detection on RT-PCR were not. Indeed, the risk of death of SARS-COV-2 RT-PCR positive and negative patients was not found significanly different in this series in univariate or in mutivariate analysis. It was high in both subgroups, close to that reported in previous studies for the SARS-COV-2 RT-PCR+ subgroup [START_REF] Liang | Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China[END_REF][START_REF] Zhang | Clinical characteristics of COVID-19-infected cancer patients: A retrospective case study in three hospitals within Wuhan, China[END_REF][START_REF] Yu | SARS-CoV-2 Transmission in Patients With Cancer at a Tertiary Care Hospital in Wuhan, China[END_REF][START_REF] Xia | Risk of COVID-19 for patients with cancer[END_REF]. It was also found to be high (10% at 30 days) for SARS-COV-2 RT-PCR negative patients, higher than that of COVID-19 patients in general (1), and also higher than expected from large series of patients with cancer emergencies from the same and other institutions [START_REF] Glare | Diagnostic accuracy of the palliative prognostic score in hospitalized patients with advanced cancer[END_REF][START_REF] Bourgeois | Clinical validation of a prognostic tool in a population of outpatients treated for incurable cancer undergoing anticancer therapy: PRONOPALL study[END_REF][START_REF] Lalami | Impact of chemotherapy-induced neutropenia (CIN) and febrile neutropenia (FN) on cancer treatment outcomes: An overview about well-established and recently emerging clinical data[END_REF][START_REF] Ray-Coquard | Identification of patients at risk for early death after conventional chemotherapy in solid tumours and lymphomas[END_REF][START_REF] Ray-Coquard | Baseline and early lymphopenia predict for the risk of febrile neutropenia after chemotherapy[END_REF][START_REF] Péron | CD4 lymphopenia to identify end-of-life metastatic cancer patients[END_REF]. It was conversely close to the mortality reported in cancer patients with seasonal influenza, and H1N1 [START_REF] Cooksley | Epidemiology and outcomes of serious influenza-related infections in the cancer population[END_REF][START_REF] Ángeles-Sistac | Influenza in patients with cancer after 2009 pandemic AH1N1: An 8-year follow-up study in Mexico[END_REF].

Extreme lymphopenia and increased inflammatory syndrome, as evidenced by high CRP levels, are well known risk factors for early death in cancer [START_REF] Kang | Historical overview of the interleukin-6 family cytokine[END_REF][START_REF] Blay | Serum level of interleukin 6 as a prognosis factor in metastatic renal cell carcinoma[END_REF][START_REF] Blay | Role of interleukin-6 in the paraneoplastic inflammatory syndrome associated with renal-cell carcinoma[END_REF]. Still, the death rate of SARS-COV-2 RT-PCR negative cancer patients iss unusually high in this series. Actually, 22 (73%) of the 30 deaths observed occured in cancer patients with respiratory symptoms without detected SARS-COV-2 on RT-PCR. These observations strongly suggest an underdiagnosis of COVID-19 in this population of cancer patients and an major underestimation of SARS-COV-2 contribution as a cause of death in cancer patients. The management of cancer patients with febrile respiratory symptoms in this period of epidemic should therefore be particularly careful even in the absence of SARS-COV-2 detection. Dedicated clinical trials for this patient population are ongoing , testing immunotherapies, chloroquine analogs , or anti-IL-6 (Immunoncovid-20, NCT04333914).

In conclusion, this retrospective series of cancer patients presenting with suspicion of COVID-19 indicates that the death rate at 30 days after diagnosis is high both in patients with and without documented SARS-COV-2 on RTPCR, the later group representing 80% of patients. This subgroup of cancer patients presenting with COVID-19 symptoms without documented SARS-COV-2 gathers also 73%, of the observed deaths at 30 days. Specific therapeutic procedures suggested to improve COVID-19 patient survival, eg anti-IL-6 Ab [START_REF] Kang | Historical overview of the interleukin-6 family cytokine[END_REF][START_REF] Blay | Role of interleukin-6 in the paraneoplastic inflammatory syndrome associated with renal-cell carcinoma[END_REF][START_REF] Lagunas-Rangel | High IL-6/IFN-γ ratio could be associated with severe disease in COVID-19 patients[END_REF][START_REF] Chen | Detectable serum SARS-CoV-2 viral load (RNAaemia) is closely correlated with drastically elevated interleukin 6 (IL-6) level in critically ill COVID-19 patients[END_REF], chloroquine analogs [START_REF] Borba | Effect of High vs Low Doses of Chloroquine Diphosphate as Adjunctive Therapy for Patients Hospitalized With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Randomized Clinical Trial[END_REF], remdesivir [START_REF] Grein | Compassionate Use of Remdesivir for Patients with Severe Covid-19[END_REF], should be investigated also in this SARS-COV-2 negative cancer patient population presenting with severe symptoms suggestive of COVID-19.

Legends of the tables and figures : Table 1 : Characteristics of the patients

Solid tumors : breast adenocarcinoma (N=42, 13.9%), colorectal adenocarcinoma ( N=18, 5.9%) ; soft tissue sarcomas (N=15, 5.0%) ; Renal cell carcinoma (N=12, 4.0%) ; Pancreas (N=10, 3.3%) ; uterine (N=9, 3.0%) ; Bone ( N=7, 2.3%) ; Peritoneal, oesophagus, adrenal (each N=4, 1.3%) ; Anal carcinoma, ovarian adeno carcinoma, prostate adenocarcinoma, testis adenocarcinoma, Glioma (each N=3, 1.0%) ; Duodenum , parotid, mxillary sinus, supraglottis, thymoma, bladder carcinoma , CUP (each, N=2, 0.7%). All other cancer types were N=1 (0.3%).

  The objective of the present PRE-ONCOVID-19 study was to analyze the characteristics, symptoms and outcome of the exhaustive population of cancer patients presenting with clinical or radiological symptoms of COVID-19 in this comprehensive cancer center, from March 1st to April 25th. This study served as the first step to build the prospective multicenter national prospective study open since April 2020 (ONCOVID-19, NCT04363632) investigating in a multicentric setting and in more details the presentation and outcome of cancer patient with documented or suspected COVID -19.

Figure 1 :

 1 Figure 1 : Survival of SARS-COV-2 RT-PCR positive and negative cancer patients with a suspected COVID-19.

Figure 2 :

 2 Figure 2: Survival of cancer patients consulting for suspected COVID-19 with or without respiratory symptoms.Patients with respiratory symptoms were defined as patients with at least 2 of the 3 following clinical symptoms (fever, dyspnea, dry cough) and/or typical images of COVID-19 pneumonia on CT-scan. A : all patients, B : RT-CPR+ patients, C : RT-PCR negative patients.

Figure 1 :Figure 2 :

 12 Figure 1 : Survival of SARs-COV2 RT-PCR positive and negative cancer patients with a suspected COVID-19 infection

Table 1 : Characteristics of the patients

 1

			SARS-COV2 RT-PCR	p
			________________________
		All (N,%)	Negative (n, %) Positive (n, %)
	Characteristics
	ALL	302 (100%)	247 (81.8%)	55 (18.2%)
	Female	158 (52.3%)	129 (52.2%)	29(52.7%)
	Male	144 (47.7%)	118 (47.8%)	(47.3%)	0.93
	Age (mean, SE)	58.2 (1.1)	56.9 (1.2)	63.8 (2.2)	0.006
	>60	179 (59.3%)	139 (56.3%)	40 (72.7%)	0.02
	Cancer type
	Solid tumors*	234 (77.5%)	199 (80.6%)	35 (63.6%)
	Haematological	68 (22.5%)	48 (19.4%)	20(36.4%)	0.007
	Lung	42 (13.9%)	35 (14.2%	7 (12.7%)	0.78
	KPS (mean, SE)	69.8 (1.1)	69.1 (1.2)	72.9 (2.8)	0.15
	KPS<60	114 (37.7%)	97 (39.3%)	17 (30.9%)	0.25
	BMI (mean, SE)	24.3 (0.3)	24.2 (0.34)	24.7 (0.58)	0.43
	BMI>30	120 (39.7%)	100 (40.5%)	20 (36.4%)	0.57
	Metastatic disease	161 (53.3%)	132 (53.4%)	29 (52.7%)	0.92
	Relapsed disease	177 (58.8%)	146 (59.1%)	31 (56.4%)	0.71
	Cancer treatment<1 month	194 (64.2%)	165(66.8%)	29(52.7%)	0.049
	Symptoms at entry
	Fever	191 (63.7%)	150 (61.2%)	41 (74.5%)	0.06
	Cough	135 (45%)	96 (39.2%)	39 (70.9%)	0.000
	Dyspnea	94 (31.4%)	75 (30.6%)	19 (35.2%)	0.51
	2

or more of the above 130 (43.5%) 94 (38.4%) 36 (66.7%) 0.000 Diarrhea 42 (14.1%) 30 (12.3%) 12 (22.6%

				)	0.05
	Anosmia/agueusia	21 (7%)	4 (1.6%)	17 (30.6%)	0.000
	Neurological	7 (2.3%)	3 (1.2%)	4 (7.3%)
	COVID-19 suspect on CT scan 59 (29.5%)	32 (20.0%)	27 (67.5%)	0.000
	CRP (mean, SE)	96.2 (6.4)	97.9 (6.9)	86.2 (17.3)	0.55
	CRP>50	133 (54.1%)	115 (55.3%)	18 (47.4%)	0.36
	CRP>200	40 (16.3%)	35 (16.8%)	5 (13.2%)	0.57
	Lymphocyte
	counts (mean, SE)	1136 (45.4)	1142 (49.8)	1106 (112.1)	0,78
	<700/µL	91 (33.5%)	78 (34.1%)	13 (30.2%)	0.57
	<400/µL	33 (12.1%)	28 (12.2%)	5 (11.6%)	0.62

* :See legend for the different subtypes

Table 3 : Prognostic factors for survival

 3

	_______________________________________________________________________________________________________________________________________________________________________
			Deaths	Univariate analysis		Multivariate analysis
				____________________________	___________________________
		N	N (%)	HR (95%CI)	p	HR (95%CI)	p
	All patients	302 (100%) 30 (10%)
	Age>60	179	22 (12,2%)	2,01 (1,21-2,81)	0,083
	Male gender	144	21 (14,5%)	2,66 (1,90-3,42)	0,01	2,75 (1,91-3,59)	0,019
	KPS<60	114	20 (17,5%)	9,01 (8,07-9,95)	<0,001	4,87 (3,87-5,87)	0,002
	Relapsing cancer	177	27 (15,2%)	6,81 (5,63-7,99)	<0,001	3,05 (1,83-4,27)	0,073
	Fever & respiratory symptoms	130	25 (19,2%)	6,90 (5,94-7,86)	<0,001	5,09 (4,11-6,07)	0,001
	Lung cancer	42	8 (19,0%)	2,38 (1,58-3,18)	0,03
	Covid-19 suspect CT Scan	59	9 (15,2%)	2,55 (1,63-3,47)	0,051
	SARS-COV2 RT-PCR+	55	8 (14,5%)	1,92 (1,12-2,72)	0,1
	CRP>50	133	22 (16,5%)	3,13 (2,23-4,03)	0,009
	Ly<700/µL	91	18 (19,7%)	4,84 (4,02-5,66)	<0,001	3,05 (2,19-3,91)	0,05
	SARS-COV2 RT-PCR + pts	55 (100%)	8 (14%)
	Age>60	40	8 (20%)	33,9(27,4-40,5)	0,026
	Male gender	26	7 (26,9%)	8,19 (6,09-10,3)	0,014
	KPS<60	17	6 (35,2%)	7,7 (6,09-9,31)	0,005
	Fever & respiratory symptoms 36	8 (22,2%)	36,9(30,5-43,3)	0,017
	Lung cancer	7	3 (42,9%)	4,69 (3,24-6,14)	0,16	ND
	Covid-19 suspect CT Scan	27	7 (25,9%)	0,89 (-0,64-2,42)	0,072
	Relapsing cancer	31	7 (22,5%)	5,29 (3,19-7,39)	0,061
	CRP>50	18	6 (

66,6%) 6,87 (4,75-8,99) 0,039 Ly<700/µL 13 3 (23,1%) 8,98 (6,71-11,3) 0,037 SARS-COV2 RT-PCR neg. pts 247 22 (8%)

	Age>60	139	14 (10.1%)	1,4 (0,54-2,26)	0,43
	Male gender	118	14 (11.9%)	1,97 (1,11-2,83)	0,11
	KPS<60	97	19 (19.6%)	10,6 (9,38-11,82)	<0,001	6,64 (5,41-7,87)	0,003
	Relapsing cancer	146	20 (13.7%)	7,5 (6,05-8,95)	<0,001	4,26 (2,79-5,73)	0,053
	Fever & respiratory symptoms	94	17 (18.1%)	5,78 (4,78-6,78)	<0,001	4,9 (3,90-5,90)	0,002
	Covid-19 suspect CT Scan	32	2 (6.2%)	0,89 (-0,64-2,42)	0,87
	CRP>50	115	16 (13.9%)	2,67 (1,67-3,67)	0,05
	Ly<700/µL	78	15 (19.2%)	4,39 (3,49-5,29)	0,001	2,16 (1,24-3,08)	0,09
	_____________________________________________________________________________________________________________________________________________________

GIST, Eurosarc (FP7-278742), la Fondation ARC, Infosarcome, InterSARC (INCA), LabEx DEvweCAN (ANR-10-LABX-0061), Ligue de L'Ain contre le Cancer, La Ligue contre le Cancer, EURACAN (EC 739521) funded this study.

* : Rates of SARS-COV-2 RT-PCR positivity were not significantly different for any of the treatment categories after correction for the number of tests performed (n=8, significant p value of p>0.00625) : all p values were above 0.04 using the Chi2 test.). † : Death rates were not significantly different for any of the subgroups of treatments after correction for the number of tests performed (n=8, significant p value of p>0.00625) : all p values were above 0.15 using the Chi2 test.