Moreira River

Ludovic Ferreira

Perret

Polynomial-Time Key-Recovery Attack on the NIST Specification of PROV

In this paper, we present an efficient attack against PROV, a recent variant of the popular Unbalanced Oil and Vinegar (UOV) multivariate signature scheme, that has been submitted to the ongoing NIST standardization process for additional post-quantum signature schemes. A notable feature of PROV is its proof of security, namely, existential unforgeability under a chosen-message attack (EUF-CMA), assuming the hardness of solving the system formed by the public-key non-linear equations. We present a polynomial-time key-recovery attack against the first specification of PROV (v1.0). To do so, we remark that a small fraction of the PROV secret-key is leaked during the signature process. Adapting and extending previous works on basic UOV, we show that the entire secret-key can be then recovered from such a small fraction in polynomial-time. This leads to an efficient attack against PROV that we validated in practice. For all the security parameters suggested in by the authors of PROV, our attack recovers the secret-key in at most 8 seconds. We conclude the paper by discussing the apparent mismatch between such a practical attack and the theoretical security claimed by PROV designers. Our attack is not structural but exploits that the current specification of PROV differs from the required security model. A simple countermeasure makes PROV immune against the attack presented here and led the designers to update the specification of PROV (v1.1).

Introduction

In 2022, the National Institute of Standards and Technology (NIST) selected the first post-quantum cryptographic standards after five years of competition. In particular, three digital signature schemes (DSS) relying either on structured lattices (Dilithium [START_REF] Schwabe | CRYSTALS-KYBER[END_REF] and Falcon [11]) or hash functions (SPHINCS+ [START_REF] Hülsing | SPHINCS +[END_REF]) have been selected for standardization. NIST also decided to start a new standardization process for additional post-quantum DSS to increase the diversity of hardness assumptions. From a practical point of view, the new call was especially targeting schemes with "short signature" and "fast verification" [START_REF]Call for Additional Digital Signature Schemes for the Post-Quantum Cryptography Standardization Process[END_REF].

Such practical features are typical of multivariate schemes. As such, UOV [START_REF] Kipnis | Unbalanced Oil and Vinegar signature schemes[END_REF] appears today as the most appealing candidate such that round-1 candidates of the new NIST standardization process [START_REF]Call for Additional Digital Signature Schemes for the Post-Quantum Cryptography Standardization Process[END_REF] includes about 8 UOV-based DSS 1 . A promising candidate among these UOV-variants is the PRovable Unbalanced Oil and Vinegar (PROV) that includes a strong security argument with an EUF-CMA security proof under the hardness assumption of solving PROV public-key multivariate equations. Until now, no security weakness has been reported against PROV.

Organization of the Paper and Main Results

We organize the paper as follows. In Section 2, we introduce the necessary notations, mathematical objects, and the security framework used in PROV. In Section 3, we recall the PROV signature scheme as defined in the NIST-specification v1.0 [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]. Section 4 describes our attack: Section 4.1 details a polynomial-time key-recovery attack against PROV specification v1.0 (Theorem 1). To do so, we exploit the fact that a small fraction of the secret-key is leaked during the signature generation. Then, we extend to the specific characteristics PROV a result from [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] on UOV demonstrating that the entire secret-key can be then recovered from this small leakage. The attack has a polynomialtime complexity and is also very efficient in practice. In Section 4.3, we present experimental results and show that the secret key can be recovered in a few seconds for all security levels (Table 2). Section 4.4 discusses a simple tweak allowing to avoid the attack and reestablish the validity of the security model used in [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]. We emphasize that the PROV designers has updated their specification (v1.1) with our countermeasure.

Acknowledgement

We thank Pierre Pébereau, who helped us with some technical details of his attack and implementation [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF]. Before publishing this work, we informed the authors of PROV that confirmed the flaw and released quickly a new specification (v.1.1). We would like to thank them for the constructive discussions. The second author would like to thank Google which partially supported this work thanks to a gift dedicated to post-quantum research. Finally, we acknowledge the financial support of the French Ministère des Armées -Agence de l'innovation de défense on this research.

Preliminaries

Notations

Let q be a prime or a prime power (for PROV, q = 2 8 ). We denote by bold lowercase (resp. capital) letter any column vector v ∈ F n q of size n in F q or respectively any matrix M ∈ F n×m q of size n × m in F q . In particular, let 0 n be the zero column vector of size n in F q , 0 n×m be the zero matrix of size n × m in F q and 1 n be the n-by-n identity matrix in F q . For a set of vector b = (b 1 , . . . , b m ) ∈ (F n q ) m , we denote by span(b) the linear span of b. Also, we express the kernel of a matrix M ∈ F n×m q or a linear map f respectively by Ker(M) and Ker(f ).

The function Upper takes as input a square matrix A = {a i,j } 1≤i,j≤n and outputs an upper triangular matrix Upper(A) = {b i,j } 1≤i,j≤n such that b i,j = a i,j + a j,i if i < j, b i,j = a i,j if i = j or b i,j = 0 otherwise. We refer by the symbol || either the concatenation of two bit-strings or the horizontal concatenation of two matrices (depending on the context). Let ∅ be the empty set, i.e. the set with no element. We denote by poly(n) a positive polynomial in the variable n (used to simplify complexity analysis).

Let F q [x 1 , . . . , x n ] be the ring of multivariate polynomials in n variables with coefficients over F q . In this work, every quadratic polynomial p ∈ F q [x 1 , . . . , x n ] will be homogeneous, i.e. p λ (x 1 , . . . , x n ) = λ 2 p(x 1 , . . . , x n ), for all λ ∈ F q . The polar form p * : F n q × F n q → F q of a homogeneous quadratic polynomial p ∈ F q [x 1 , . . . , x n ] is a bi-linear and symmetric function defined as p * (x, y) := p(x, y) -p(x) -p(y) for all x, y ∈ F n q . Any homogeneous quadratic polynomial p ∈ F q [x 1 , . . . , x n ] can be uniquely represented as p(x) = x ⊺ Qx, where Q ∈ F n×n q is an upper triangular matrix, and the corresponding polar form as p * (x, y) = x ⊺ (Q + Q ⊺ )y with x, y ∈ F n q . A multivariate quadratic map P : F n q → F m q is defined by a set of multivariate quadratic polynomials

P = (p 1 , . . . , p m ) ∈ F q [x 1 , . . . , x n ] m .

Security framework of PROV

Here, we recall the definition of a Weak Preimage-Sampleable Function (WPSF) used in the security analysis of PROV [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF].

Definition 1 (WPSF [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]). A WPSF T consists of four probabilistic polynomial-time algorithms:

• Gen: this algorithm takes as input a security parameter 1 λ and outputs a function F : X → Y with a trapdoor I; • F: this algorithm takes as input a value x ∈ X and deterministically outputs F(x); • I = (I 1 , I 2 ): the algorithm I 1 takes no input and outputs a value z ∈ Z; the algorithm I 2 takes as input z ∈ Z, y ∈ Y, and outputs x ∈ X such that F(x) = y, or outputs ⊥ if it failed;

• SampDom: this algorithm takes as input a function F : X → Y and outputs a value x ∈ X .

The Preimage Sampling (PS) security of a WPSF is defined as:

Definition 2 (PS security [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]). Let T be a WPSF. The advantage of an adversary A against the PS security of T is defined as:

Adv PS T (A) = Pr PS A 0 = 1 -Pr PS A 1 = 1
where PS 0 and PS 1 are the security games defined in Figure 1.

PS b (F, I) ← Gen(1 λ ) b * ← A Sample b (F) Return b * Sample0 zi ← I 1 () repeat yi $ ← Y xi ← I 2 (zi, yi) until xi ̸ = ⊥ Return xi Sample1 xi ← SampDom(F) Return xi
Fig. 1: PS security games.

Description of PROV

PRovable Unbalanced Oil and Vinegar (PROV) is a new signature scheme [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF] submitted to the recent NIST standardization process for additional post-quantum signature schemes [START_REF]Call for Additional Digital Signature Schemes for the Post-Quantum Cryptography Standardization Process[END_REF]. As several multivariate schemes submitted to this standardization process, PROV is a variant of the Unbalanced Oil and Vinegar (UOV) multivariate signature scheme [START_REF] Kipnis | Unbalanced oil and vinegar signature schemes[END_REF].

PROV uses the the recent definition of UOV introduced by W. Beullens in [START_REF] Beullens | Improved cryptanalysis of UOV and Rainbow[END_REF] in combination with an efficient variant of the so-called salt-UOV [START_REF] Sakumoto | On provable security of UOV and HFE signature schemes against chosen-message attack[END_REF], a provably secure variant of UOV.

In [START_REF] Beullens | Improved cryptanalysis of UOV and Rainbow[END_REF], the traditional UOV trapdoor [START_REF] Kipnis | Unbalanced oil and vinegar signature schemes[END_REF] is rephrased as the vanishing subspace of a multivariate quadratic map.

Definition 3. Let P : F n q → F m q be a multivariate quadratic map and O ⊂ F n q be a linear subspace. We shall say that O is a vanishing subspace of P if :

∀o ∈ O, P(o) = 0 m .
From a high-level point of view, the public-key in PROV is given by the multivariate quadratic map P : F n q → F m q and the corresponding secret-key is a vanishing subspace O ⊂ F n q of dimension m + δ with δ > 0. The main specificity of PROV is related to the parameter δ that allows a more efficient reduction than salt-UOV [START_REF] Sakumoto | On provable security of UOV and HFE signature schemes against chosen-message attack[END_REF]. From now on, we set v = n -m -δ.

Key-Generation in PROV

In order to generate a PROV key pair (Definition 3) (P, O) with P : F n q → F m q and a vanishing subspace O ⊂ F n q of dimension m + δ with δ > 0, they proceed as follows in [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]. They first generate a random basis of O in systematic form, i.e. namely a basis of the form :

(O ⊺ 1 m+δ ) ∈ F (m+δ)×n q , with O ∈ F v×(m+δ) q .
(1)

Then, the components p 1 , . . . , p m ∈ F q [x 1 , . . . , x n ] of P : F n q -→ F m q are constructed as follows :

p i (x) = x ⊺ P i x, P i = P (1) i P (2) i 0 (m+δ)×v P (3) i ∈ F n×n q , ∀i, 1 ≤ i ≤ m, (2)
with x = (x 1 , . . . , x n ) ∈ F n q , P (1) i
∈ F v×v q be an upper triangular matrix, P

∈ F v×(m+δ) q be a matrix and

P (3) i = Upper -O ⊺ P (1) i O -O ⊺ P (2) i ∈ F (m+δ)×(m+δ) q .
As proved in [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF], the linear subspace O generated as in ( 1) is a vanishing subspace of the map defined by the polynomials (2).

Signature Verification and Generation

The PROV signature for a message msg ∈ {0, 1} * is given by a vector s ∈ F n q and a fixed-length bit string salt ∈ {0, 1} len salt such that

P(s) = H(msg||salt),
where H : {0, 1} * → F m q is a hash function2 . The PROV trapdoor is based on the result below, demonstrating that the knowledge of the vanishing subspace allows one to compute a valid signature by solving a linear system.

Lemma 1. Let O ∈ F v×(m+δ) q
, P : F n q → F m q be represented with matrices (P 1 , . . . ,

P m ) ∈ (F n×n q ) m as defined in (2), v = v 0 m+δ , ō = O 1 m+δ o ∈ F n q , with v ∈ F v q and o ∈ F (m+δ) q
. For all h = (h 1 , . . . , h m ) ∈ F m q , it holds that :

P(v + ō) = h ⇐⇒ v ⊺ S i o = h i -v ⊺ P (1) i v, ∀ i, 1 ≤ i ≤ m, with S i = (P (1)
i + P

)O + P

.

In order to generate a signature of msg ∈ {0, 1} * , the signer generates a random pair (v, salt) ∈ F v q ×{0, 1} len salt and solves the corresponding linear system of Lemma 1 with h = H(msg||salt) ∈ F m q . If the linear system has no solution, then the signer samples a new salt ∈ {0, 1} len salt and solves the new system. The process is repeated until a solution exists. Finally, he recovers the signature s = v + ō. We detail the PROV signature generation in Algorithm 1.

Remark 1. Note that the vector ō belongs in the secret vanishing subspace O of the public key.

Given a matrix A ∈ F m×n q , and vector b ∈ F m q , the algorithm LinSolve outputs the set of all solutions x ∈ F n q of the linear system Ax = b.

Security of PROV

An appealing feature of PROV lies in its security proof where existential forgery under chosen message attacks (EUF-CMA) can be reduced to the problem of inverting the public-key polynomials defined as follows:

Definition 4 (UOV -problem). Let p = (p 1 , . . . , p m ) ∈ F q [x 1 , . . . , x n ] m be quadratic polynomials corresponding to a PROV public-key and d = (d 1 , . . . , d m ) ∈ F m q . The UOV -problem asks to find a solution to the non-linear system of equations :

p 1 -d 1 = 0, . . . , p m -d m = 0.
As discussed in [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF], the best approaches known for solving the UOV -problem are generic techniques for solving non-linear equations and then exponential in the classical and quantum settings [START_REF] Bettale | Hybrid approach for solving multivariate systems over finite fields[END_REF][START_REF] Bettale | Solving polynomial systems over finite fields: improved analysis of the hybrid approach[END_REF][START_REF] Faugère | Fast quantum algorithm for solving multivariate quadratic equations[END_REF][START_REF] Esser | ttcryptographicestimators: a software library for cryptographic hardness estimation[END_REF]. , the public key (P1, . . . , Pm) ∈ (F n×n q ) m and a message msg ∈ {0, 1} * . Result: The signature (s, salt) ∈ F n q × {0, 1} len salt of message msg.

1 v $ ← F v q 2 S ← ∅ 3 while S = ∅ do 4 salt $ ← {0, 1} len salt 5 (h1, . . . , hm) ← H(msg||salt) 6 for i from 1 to m do 7 ai ← v ⊺ ((P (1) i + P (1)⊺ i )O + P (2) i ) 8 bi = hi -v ⊺ P (1) i v 9 end 10 A := (a ⊺ 1 || . . . ||a ⊺ m ) ⊺ 11 b := (b1|| . . . ||bm) ⊺ 12 S ← LinSolve(A, b) 13 end 14 o $ ← S 15 s ← v 0 m+δ + O 1 m+δ o 16 Return (s, salt)
4 Polynomial-Time Attack against PROV Specification

Overview

Our attack relies on the fact that the (vinegar) vector v ∈ F v q is leaked and constant in the PROV specification v1.0 [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF]. More precisely, the designers described a probabilistic signature generation, similar to Algorithm 1, only for "ease of exposition". In practice, they deterministically generate v as H(3||msg) where H is the hash function SHAKE256. We emphasize that the reference implementation generates the vinegar vector v ∈ F v q similarly. The vinegar vector (and the corresponding signature) leaks information about the secret-key, precisely it reveals one vector in the secret linear subspace O ⊂ F n q . Recently, P. Pébereau [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] has introduced a polynomial-time key-recovery attack on UOV that uses only one vector in the secret linear subspace. In the next part, we adapt this key-recovery attack on PROV.

Description of the Attack

First, we explain why the PROV specification leaks one vector in the secret linear subspace. Let (v, s) ∈ F v q × F n q be a pair of a vinegar vector and a signature3 for the message msg ∈ {0, 1} * and the PROV key pair (P, O) with P : F n q → F m q and O ⊂ F n q . We recall than s = v + ō where v⊺ = (v ⊺ ||0 ⊺ m+δ ) ∈ F n q and ō ∈ F n q . As discussed above, the pair (v, s) is public. Therefore, any adversary can compute a vector in the secret linear subspace ō = sv ∈ O (see Remark 1).

In the following, we focus on the key-recovery attack assuming the knowledge of one non-zero vector in the linear subspace. Also, we assume that n ≤ 3m (this statement holds for concrete parameters proposed in the PROV submission, see Table 1) and that the rank of the matrices (P 1 + P ⊺ 1 , . . . , P m + P ⊺ m ) defined as in ( 2) is n. The attack from [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] uses a special property of the polar form of a PROV key pair.

Lemma 2 ([12]

). Let P : F n q → F m q be a multivariate quadratic map, O ⊂ F n q be a vanishing subspace of P and P * : F n q × F n q → F m q be the polar form of P. Then, for all (x, y) ∈ O 2 , we have P * (x, y) = P * (y, x) = 0 m . Now, we present an adaption of the attack from [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] to the PROV case (see Remark 2). Lemma 3. Let P : F n q → F m q be a PROV public-key, O ⊂ F n q be the vanishing subspace of P where P are represented with matrices (P 1 , . . . , P m ) ∈ (F n×n q ) m defined as in [START_REF] Bettale | Hybrid approach for solving multivariate systems over finite fields[END_REF]. Let o ∈ O \ {0} and J o (z) = (o ⊺ (P 1 + P ⊺ 1 )z, . . . , o ⊺ (P m + P ⊺ m )z) with z = (z 1 , . . . , z n ) a vector of variables. Then,

Ker(J o ) is an (n -m)-dimensional subspace such that O ⊂ Ker(J o ).
Proof. Let P * : F n q ×F n q → F m q be the polar form of P with components p * 1 , . . . , p * m where p * i (y, z) = y ⊺ (P i + P ⊺ i )z for all 1 ≤ i ≤ m. By Lemma 2, for all x ∈ O.

p * i (o, x) = 0, ∀1 ≤ i ≤ m.
This implies that the kernel of the linear application

p * i,o (z) = o ⊺ (P i + P ⊺ i )z contains O.
By hypothesis, all the matrices (P 1 + P ⊺ 1 , . . . , P m + P ⊺ m ) are of rank n and o ̸ = 0 n , therefore p * i,o (z) is non-zero. Since the linear map is non-zero, its kernel is a hyperplane. We have shown that O ⊂ Ker(p * i,o ), for all 1 ≤ i ≤ m. Therefore, we obtain :

O ⊂ 1≤i≤m Ker(p * i,o ) = Ker(J o )
Also, the hyperplanes are non-parallel, because we have O ⊂ Ker(p * i,o ) for all 1 ≤ i ≤ m. Therefore, the intersection of the m hyperplanes has dimension n -m. This concludes the proof.

Remark 2. In [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF], the authors consider finite fields of odd characteristics and exploit the bijective relation p = 2 -1 p * between any quadratic homogeneous polynomial p ∈ F q [x 1 , . . . , x n ] and its polar form p * : F n q × F n q → F q . Therefore, any homogeneous quadratic polynomial p ∈ F q [x 1 , . . . , x n ] can be represented with a symmetric matrix M ∈ F n×n q such that p(x) = x ⊺ Mx. However, a polynomial p(x) = x ⊺ Mx with a symmetric matrix M is either linear or zero in a finite field of characteristic two (as with PROV). In other words, the bijective relation does not hold for finite fields of characteristic two (as discussed in [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF][START_REF] Serre | A Course in Arithmetic[END_REF]). Therefore, we need to slightly adapt the approach from [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] by considering the polar form of the public-key and not by exploiting a symmetric representation of the public-key as in [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF]. The next step is then essentially similar to [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF]Theorem 7], namely we restrict the public-key polynomials on Ker(J o ) and obtain new polynomial with fewer variables and the same secret vanishing subspace O. The secret-key can be recovered in polynomial-time from these new polynomials.

Theorem 1. Let P : F n q → F m q be a PROV public-key, O ⊂ F n q be the vanishing subspace of P with dim(O) = m + δ where δ > 0 and P be represented by matrices (P 1 , . . . , P m ) ∈ (F n×n q ) m defined as in [START_REF] Bettale | Hybrid approach for solving multivariate systems over finite fields[END_REF]. Then, there exists an adversary A taking as input (P 1 , . . . , P m ), o ∈ (F n×n q ) m × O \ {0} that outputs a basis of O in polynomial-time.

The proof is similar to [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] but provided for the sake of correctness and completeness.

Proof. Let J o (z) = (o ⊺ (P 1 + P ⊺ 1 )z, . . . , o ⊺ (P m + P ⊺ m )z) with z = (z 1 , . . . , z n ) a vector of variables. By Lemma 3, O ⊂ Ker(J o ) for which a basis B ∈ F n×(n-m) q can be computed in O(n ω ), with 2 ≤ ω ≤ 3 the matrix multiplication exponent. Then, we restrict the public-key polynomials to Ker(J o ). This yields :

P i,Ker(Jo) = B ⊺ P i B, ∀ i, 1 ≤ i ≤ m.
The restricted public-key P Ker(Jo) : F

(n-m) q → F m q can be computed in polynomial-time O(mn ω ) and be represented with matrices P 1,Ker(Jo) , . . . , P m,Ker(Jo) ∈ F (n-m)×(n-m) q is a PROV public key with parameters (q, n -m, m, δ) because O ⊂ Ker(J o ). Let Ō ⊂ F n-m q be the vanishing subspace of P Ker(Jo) with dim( Ō) = m+δ. With our assumption n ≤ 3m, we obtain n-m-2m-2δ ≤ 0. As explained in the specification of PROV [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF], the so-called Kipnis-Shamir attack on PROV for parameters (q, n, m, δ) has complexity poly(n) q n-2m-2δ . This attack recovers a basis C ∈ F (n-m)×(m+δ) q of the secret subspace Ō in time poly(n). Then, for all i with 1 ≤ i ≤ m, we have

(BC) ⊺ P i BC = C ⊺ (B ⊺ P i B)C = C ⊺ P i,Ker(Jo) C = 0 (m+δ)×(m+δ) .
Namely, the matrix BC ∈ F n×(m+δ) q is a basis of O. Multiplying these matrices takes time O(n ω ) and concludes the proof that the secret-key can be recovered in O(m poly(n)).

Experimental results

In this part, we show that our attack is not only efficient from a theoretical point of view but also very practical. To do so, we implemented the attack (Theorem 1) in Sagemath4 ( [START_REF]SageMath, the Sage Mathematics Software System (Version 9[END_REF] taking as reference the code used in [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF]) with the parameters of PROV suggested in [START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF] (Table 1). The non-zero vector of the vanishing subspace of the public key is generated with an oracle since such vector is leaked in PROV specification (Sub-Section 4.2). As discussed in [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF], the Kipnis-Shamir attack is replaced by the "kernel approach" (see [START_REF] Pébereau | One vector to rule them all: Key recovery from one vector in uov schemes[END_REF] for details). We estimate the performance of the implementation on a single thread of a laptop with an Intel CPU i7-1365U at 5.2GHz and with 32GB of RAM. In Table 2, we report the experimental results obtained. To summarize, we recover the secret-key of PROV in a few seconds for every security level.

Countermeasure

Before presenting the countermeasure, we briefly recall the security model used PROV. One idea of the proof is to model the PROV signature scheme as a weak preimage-sampleable function (WPSF) (Definition 1), denoted T PROV , such as :

• The algorithm (pk, sk) ← Gen is the PROV key generation;

• The algorithm F evaluates the PROV public-key;

• The algorithm SampDom uniformly generates a value in F n q ; • The pair of algorithms I = (I 1 , I 2 ) are defined as follows:

• The algorithm I 1 outputs a uniformly distributed vector v ∈ F v q ; • The algorithm I 2 takes as input (pk, sk, v, y) with v ∈ F v q and y ∈ F m q , performs one iteration of the while loop in the signature generation (see Algorithm 1) for the given vector v and outputs a PROV signature s ∈ F n q for h = y or ⊥ if the iteration failed.

One can remark that the model assumes, in particular, that the vinegar vector should be uniform and kept secret to the adversary in PS security of T PROV (see Definition 2). Precisely, in the PS 0 game, the adversary has access to the oracle Sample 0 (both described in Figure 1). The oracle Sample 0 keeps secret the value z i ← I 1 used for I 2 from the adversary A. Also, the algorithm I 1 uniformly generates the vector z i ∈ F v q for T PROV . The specification of PROV v.1.0 differs from this model as the vinegar vector, which corresponds to a value z i ∈ F v q , is leaked during signature generation and constant. The countermeasure appears evident when knowing this flaw in the security model: the vinegar vector should be uniformly generated and kept secret. This tweak will prevent an adversary from recovering easily a vector in the secret linear subspace with the previous strategy and makes PROV immune against our polynomial-time key-recovery attack.

For example, we can suggest generating the vector v as H(3||s sk ||msg) where s sk is the secret seed uniformly generated during the key generation (this was the strategy followed by others UOV candidates to the ongoing NIST standardization process). We will obtain a deterministic signature generation, as desired in the PROV specification.

Finally, we have reported this vulnerability to the designer of PROV and they updated the specification (v1.1) with such countermeasure.

Algorithm 1 :

 1 PROV Signing Data: The secret key O ∈ F v×(m+δ) q

Table 1 :

 1 Parameter sets of the PROV signature scheme.

	Variant	λ q n m δ	v
	PROV-I 128 256 136 46 8 82
	PROV-III 192 256 200 70 8 122
	PROV-V 256 256 264 96 8 160

Table 2 :

 2 Key-recovery attack of PROV.

https://csrc.nist.gov/Projects/pqc-dig-sig/round-1-additional-signatures

Precisely, in[START_REF] Benoit Cogliati | PROV: Provable unbalanced Oil and Vinegar specification[END_REF], they generate h as H(4||hpk||msg||salt) where hpk is a hash of the public key and a secret seed. We omit this detail to simplify the presentation.

The salt is irrelevant for the attack, therefore we ignore it.

Our implementation is available at https://github.com/River-Moreira-Ferreira/prov-attack


Jebrane Bouaoud
email: jebrane.bouaoud@aphp.fr

Jean-Philippe Foy

Antonin Tortereau

Lucas Michon

Vincent Lavergne

Nicolas Gadot

Sandrine Boyault

Julie Valantin

Geneviève De Souza

Philippe Zrounba

Chloé Bertolus
email: chloe.bertolus@aphp.fr

Nathalie Bendriss- Vermare

Pierre Saintigny
email: pierre.saintigny@lyon.unicancer.fr

Frank Rojas Alvarez

Sylvie Lantuejoul

Auriole Tamegnon

Mei Jiang

Shanyu Zhang

Pandurengan Renganayaki

Karène Mahtouk

Edwin Roger Parra Cuentas

Paolo Bossi
email: paolo.bossi@unibs.it

Moshe Elkabets
email: moshee@bgu.ac.il

Sandra Schmitz
email: sandra.schmitz@uclouvain.be

Léon C Van Kempen
email: l.van.kempen@umcg.nl

Pierre Martinez
email: pierre.martinez@lyon.unicancer.fr

Sankar Jagadeeshan
email: jagadees@post.bgu.ac.il

Ingrid Breuskin
email: ingrid.breuskin@gustaveroussy.fr

Gerwin J Puppels
email: gpuppels@riverd.com

Caroline Hoffmann
email: caroline.hoffmann@curie.fr

Keith D Hunter
email: k.hunter@sheffield.ac.uk

Christian Simon
email: christian.simon@chuv.ch

Jean-Pascal Machiels
email: jean-pascal.machiels@saintluc.uclouvain.be

Vincent Grégoire
email: vincent.gregoire@lyon.unicancer.fr

Ruud H Brakenhoff
email: rh.brakenhoff@amsterdamumc.nl

Senada Koljenović
email: senada.koljenovic@uza.be

C Darido

Edgar K Selzer

Sandra Ortiz-Cuaran

Sandra Ortiz

Andy Karabajakian

Maxime Boussageon

Dorssafe Fekiri

Marie Robert

Kim-Arthur Baffert

Genevie ` Ve Herve

Pauline Quilhot

Vale ´ry Attignon

Ange ´lique Girod

Andre ´chaine

Mourad Benassarou

Christophe Caux

Carole Crozes

Isabelle Broche ´riou

Maurice Pe ´rol D

Je ´ro ˆme Fayette

Chloe ´bertolus

Early changes in the immune microenvironment of oral potentially malignant disorders reveal an unexpected association of M2 macrophages with oral cancer free survival

Keywords: Oral carcinogenesis, oral potentially malignant disorders, oral leukoplakia, immune microenvironment, M2 macrophages, stroma, 4-NQO model head and neck squamous-cell carcinoma, resistance, chemotherapy, cetuximab, immunotherapy, targeted therapy

Understanding the dynamics of the immune microenvironment is critical to the development of immunobased strategies for the prevention of oral potentially malignant disorders transformation to oral squamous cell carcinoma (OSCC). We used laser capture microdissection and RNA-sequencing to profile the expression of 13 matched pairs of epithelial versus stromal compartments from normal mucosa, hyperplasia, dysplasia, and invasive tumors in the 4-nitroquinolein (4-NQO) murine model of oral carcinogenesis. Genes differentially expressed at each step of transformation were defined. Immune cell deconvolution and enrichment scores of various biological processes including immune-related ones were computed. Immunohistochemistry was also performed to characterize the immune infiltrates by T-cells (T-cells CD3+, helper CD4+, cytotoxic CD8+, regulatory FoxP3+), B-cells (B220+), and macrophages (M1 iNOS+, M2 CD163+) at each histological step. Enrichment of three independent M2 macrophages signatures were computed in 86 oral leukoplakia with available clinical outcome. Most gene expression changes were observed in the stromal compartment and related to immune biological processes. Immune cell deconvolution identified infiltration by the macrophage population as the most important quantitatively especially at the stage of dysplasia. In 86 patients with oral leukoplakia, three M2 macrophages signatures were independently associated with improved oral cancer-free survival. This study provides a better understanding of the dynamics of the immune microenvironment during oral carcinogenesis and highlights an unexpected association of M2 macrophages gene expression signatures with oral cancer free survival in patients with oral leukoplakia.

Introduction

Oral cavity is the most common site of Head and Neck Squamous Cell Carcinoma (HNSCC) which is ranked as the 8 th most common cancer worldwide. 1 Oral SCC (OSCC) is associated with significant morbidity and mortality. Because OSCC may develop from oral premalignant disorders (OPMD), prevention of OPMD malignant transformation may improve patients outcomes. 2 However, although several oncogenic-driven chemoprevention strategies have been proposed, no prevention strategy can be considered as a standard of care. 3 Identification of OPMD with a risk of malignant transformation is needed to develop relevant preventive strategies addressing the cancerization field. Besides clinical (inhomogeneity) and histological (severe dysplasia) OPMD characteristics, 4 several biomarkers 5,[START_REF] Saintigny | DeltaNp63 overexpression, alone and in combination with other biomarkers, predicts the development of oral cancer in patients with leukoplakia[END_REF] have been proposed to identify patients at high risk of OSCC development. Loss of heterozygosity (LOH) at specific chromosomal sites has been validated prospectively as the most robust biomarker of risk of oral cancer development in patients with OPMD. Using the 4-NQO murine model of oral carcinogenesis, [START_REF] Bouaoud | The 4-NQO mouse model: an update on a well-established in vivo model of oral carcinogenesis[END_REF] we have previously shown the role of early epithelial gene expression changes during OPMD malignant transformation. [START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] The role of the immune microenvironment (IME) during head and neck carcinogenesis has been recently emphasized. In particular, T-cells infiltrate has been associated with improved outcomes in patients with HNSCC, one of the most immuneinfiltrated cancer types. [START_REF] Mandal | The head and neck cancer immune landscape and its immunotherapeutic implications[END_REF] Recent clinical trials investigating immunotherapies represent an unprecedented advance in HNSCC. [START_REF] Ferris | Nivolumab for recurrent squamous-cell carcinoma of the head and neck[END_REF][START_REF] Burtness | Pembrolizumab alone or with chemotherapy versus cetuximab with chemotherapy for recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-048): a randomised, open-label, phase 3 study[END_REF] Within this context, the role of the IME during early steps of oral carcinogenesis has been reported, [START_REF] Ai | Microenvironmental regulation of the progression of oral potentially malignant disorders towards malignancy[END_REF] and immunoprevention strategies proposed. [START_REF] Gutkind | The next frontier: head and neck cancer immunoprevention[END_REF] We have previously identified two distinct gene expression based OPMD subtypes named immunological and classical respectively. [START_REF] Foy | Immunological and classical subtypes of oral premalignant lesions[END_REF] The immunological class was characterized by an activation of immune signaling pathways, an increased immune infiltrate and an overexpression of miR-142-5p, a microRNA involved in M1/M2 macrophage switch. Intriguingly, we found that a high miR-142-5p expression level was associated with improved oral cancer-free survival (OCFS), contrasting with the typical protumorigenic role of M2 macrophages in established tumors.

Herein, using the 4-NQO murine model of oral carcinogenesis, we show that early gene expression changes in the stroma underlying lesions, were mainly associated to immune biological processes, mainly involving the macrophage population. Moreover, using immunohistochemistry, significant changes in T-cells, B-cells, and macrophages stroma infiltration were observed at premalignant stages. In particular, M2 macrophages infiltrate changes were among the most important ones, especially at the stage of dysplasia. Surprisingly, three independently published M2 macrophages gene expression signatures were associated and highly predictive of improved OCFS in 86 OPMD. These results support the need to revisit the role of M2 macrophage during oral tumorigenesis.

Methods

Details are provided in Supplementary Methods for the 4-NQO model, laser microdissection, RNA extraction, sequencing, immunohistochemistry staining protocols, and bioinformatic analysis.

The 4-NQO mice model of oral carcinogenesis

As previously described, [START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] the experiments were performed in accordance with the animal care guidelines and were validated by the local Animal Ethic Evaluation Committee (CECCAPP_CLB_2016_014). Briefly, six-week-old mice were exposed to the chemical carcinogen 4-NQO. The 4-NQO treatment is given ad libidum at a dose of 100 μg/mL for 8 weeks. The 4-NQO was then replaced by normal drinking water. Few weeks after the cessation of the 4-NQO, mice developed progressively premalignant lesions (hyperplasia and dysplasia) and later tumors. Mice were sacrificed every 4 weeks after the cessation of the 4-NQO. In all the manuscript, the specified times (in weeks) refer to the time of the experiment.

Based on the histological mapping of a veterinary pathologist (A.T.) examining the paraffin-embedded (FFPE) tongues of CBA mice from this model, we selected several biological replicates of each histological stage: 3 normal samples from control mice (at week 16, 20, and 24), 3 hyperplastic lesions (at week 20, 24, and 32), 4 dysplastic lesions (at week 16, 24, 28 and 32), and 3 tumor samples (at week 28 and 2 at week 32) from the 4-NQO treated mice (Supplementary Figure S1 andS2). Only typical pathological diagnoses were selected from mice that were sacrificed at different time points to avoid a potential bias due to the biological effect of age.

Laser Capture microdissection (LCM)

Using three FFPE sections of each histological stage, we performed LCM (PALM MicroBeam IV Zeiss®) of epithelial cells (E-samples) as well as underlying stroma (S-samples) to generate gene expression profiles (Supplementary Figure S3-S5; Supplementary Video).

Total RNA extraction and RNA-sequencing

After total RNA extraction (QIAGEN RNeasy® FFPE-kit), samples (n = 13 epithelial and n = 13 stromal, subsequently referred as E-samples and S-samples, respectively) were sequenced (NextSeq 550 Illumina®) (quality controls in Supplementary Table 1). Raw data were deposited at Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/ geo/) (GSE164619).

Immunohistochemistry (IHC)

The HALO™ software system (Indica Labs, v.2.0.1145. 19) was used to quantify immune infiltrates for T-cells (CD3, CD4, CD8, FoxP3), B-cells (CD45R0/B220), and macrophages (M1 iNOS1 and M2 CD163) in the epithelium, the underlying stroma and muscle, of both normal (N) mucosa, hyperplasia (H), dysplasia (D) and tumor (T) samples (6 replicates for each condition totalizing 24 samples for each antibody). Data were normalized by the surface analyzed (n cells/mm 2 ). In addition, to control for a potential inflammatory effect of 4-NQO, normal areas at distance of hyperplasia, dysplasia, and tumor lesions were analyzed (Supplementary Figures S6-S11).

Bioinformatics analysis

We defined sets of genes differentially expressed between tumor and normal mucosa called the "tumor gene set" (TGS), for both E-and S-samples i.e., TGSE and TGSS respectively (Supplementary Table 2 and Supplementary Figure S12). TGSE and TGSS were divided into four non-overlapping gene subsets to study the dynamics of gene expression changes during oral tumorigenesis, as previously described: [START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] the "early" (EGS), the "intermediate" (IGS) and the "late" (LGS) gene subsets, representing changes observed at each step (i.e. H vs. N, D vs. H and T vs. D, respectively). The fourth gene subset, named "progressive" gene set (PGS), included genes changing progressively overtime but not included in other subsets (Supplementary Table 3-5 and Supplementary Figure S12 andS13).

The single-sample Gene Set Enrichment Analysis (ssGSEA) projection tool from GenePattern (ssGSEA v8) was used to compute separate enrichment scores (ES) for each sample using different gene sets (TGS, EGS, IGS, LGS, and PGS) in various datasets downloaded from GEO (GSE75421; GSE9844; and GSE30784). Standard GSEA analysis (GSEA v6.3) was performed to compute the ES of 4 762 curated gene sets (C2 gene set, MSigDB database v6.1, default parameters) using the log 2 fold-change in tumor versus normal mucosa as the input.

Seq-ImmuCC (http://218.4.234.74:3200/immune/) was used for immune cell populations deconvolution and infer the relative proportions of ten major immune cells (B-cells, CD4 and CD8 T-cells, Dendritic cells, Eosinophils, Macrophages, Mast cells, Monocytes, Neutrophils, and NK cells).

M2 macrophages signatures and oral cancer risk

We have evaluated the association of some M2 macrophages gene expression signatures with Oral Cancer Free Survival (OCFS) using data previously published from 86 patients with OPMD, in particular, oral leukoplakia [START_REF] Saintigny | Gene expression profiling predicts the development of oral cancer[END_REF] (GSE26549) (Supplementary Table 6). Briefly, gene expression profile was measured in 86 Oral leukoplakia patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. [START_REF] Papadimitrakopoulou | Randomized Trial of 13-cis Retinoic Acid Compared With Retinyl Palmitate With or Without Beta-Carotene in Oral e1944554-10 J. BOUAOUD ET AL. Premalignancy[END_REF] After inclusion, the patients were randomly assigned to intervention (13cis-retinoic acid versus retinyl palmitate with or without betacarotene). OCFS was defined as the time from random assignment until diagnosis of any OSCC. Analysis of OCFS was performed in the entire intent-to-treat population and was analyzed by the Kaplan-Meier method. The median follow-up time was 7.11 years and 35 of the 86 patients developed oral cancer over the course. The average time between the OL and OSCC diagnosis is 3.11 years (0.18-14.33).

Immunological and classical subtypes of OPMD

We have recently identified two distinct gene expression based OPMD subtypes named immunological and classical respectively. [START_REF] Foy | Immunological and classical subtypes of oral premalignant lesions[END_REF] Briefly, based on genome-wide expression profiles of 86 oral leucoplakias (GSE26549) [START_REF] Saintigny | Gene expression profiling predicts the development of oral cancer[END_REF] and using the 2,500 most variable genes, we performed an unsupervised and unbiased clustering of these samples (discovery dataset). Two main clusters, including 42 (cluster 1) and 44 (cluster 2) OPMD, respectively, were identified. Cluster 1, showing a strong and significant enrichment of immune pathways was named 'immunological' while cluster 2, characterized by a moderate enrichment of pathways involved in xenobiotic metabolism as well as EGFR signaling, was named 'classical'. By comparing genome-wide expression profiles of immunological as well as classical OPMD, we have identified the 200 most overexpressed genes and the 200 most under-expressed genes. These genes were used to build an "Enrichment Score-based classifier" allowing the classification of OPMD as being immunological or classical if the score was >0 or <0, respectively (ssGSEA). This classifier was then validated using OPMD samples from three independent datasets, including 17 (GSE30784),13 (GSE10174), and 15 (GSE85195) OPMD.

Statistical analysis

Statistical analyses and plots were performed using R 4.0.0 and the GSVA_1.36.2, the survival_3.1-12, survminer_0.4.7, PMCMRplus_1.5.0, pROC_1.16.2, and ggplot2 packages. Non-parametric Kruskal-Wallis test was used to compare to compare GSEA ES as well as immune cell counts between more than two groups and Mann Whitney for two groups' comparisons. Post hoc Steel-Dwass-Flinger test was used for comparisons with false discovery rate adjusted P-value <.05. Survival distributions were estimated using the Kaplan-Meier method and compared with the log-rank test between two groups (clustered by a Gaussian mixture model). Correlations between the ES of two signatures were computed using the Spearman test. Prediction of oral cancer risk was computed using the multivariate Cox model including ES normalized by inter-quartile range. Three-folds cross validated AUC was performed, and 95% confidence intervals were computed by bootstrap (DeLong method). For Cox models, proportional hazards assumption was tested. P-values ≤0.05 were considered to be statistically significant.

Results

Gene expression changes in stroma discriminate OSCC from normal mucosa

A total of three control mice and nine mice treated by 4-NQO and sacrificed at different ages were included (Supplementary Figure S1 andS2). The histological mapping of 270 FFPE-tongues H&E sections from the nine 4-NQO treated mice showed an increasing incidence of histological lesions (i.e., Hyperplasia (H), Dysplasia (D), and Tumor (T)) over time (Figure 1). Preneoplastic lesions (H and D) were more common during the first 24 weeks. At week 28, histological lesions were observed in 97% of the sections analyzed. At week 32, T were observed in 72% of the sections analyzed.

Gene expression profiles were generated in 12 selected mice from microdissected epithelium (E-samples) and underlying stroma (S-samples), including 3 N, 3 H, 4 D, and 3 T. Using whole genome expression profiles, E-samples and S-samples were divided into two distinct clusters (Figure 2a).

We identified two sets of genes differentially expressed between T and N in E-samples and S-samples, respectively called TGSE and TGSS that included 837 and 1,519 genes respectively (Supplementary Table 4). Both gene sets were divided in a UP and DOWN subsets including genes which were coordinately up-or down-regulated within a sample. The overlap between TGSE and TGSS was 373 (16%). TGSE and TGSS were able to discriminate cancer from normal samples in three independents murine (GSE75421) and human (GSE9844 and GSE30784) datasets (Figure 2b).

In summary, gene expression changes were more abundant in the stroma and different from those occurring in the epithelial compartment and the 4-NQO model is relevant to understand the dynamic changes observed during oral carcinogenesis.

Gene expression changes in the stroma and mainly related to immune biological processes

To study the dynamics of gene expression changes during oral carcinogenesis, we divided the TGSS as well as the TGSE into four non-overlapping gene subsets associated with histological changes i.e., "early" (EGS), "intermediate" (IGS), "late" (LGS) and "progressive" (PGS) gene subsets either in the epithelial or the stroma compartment (Supplementary Tables 2345, Supplementary Figures S12 andS13). In the epithelium, the number of genes specifically and differentially expressed was higher between normal mucosa to hyperplasia while it was more evenly distributed during tumorigenesis in the stromal compartment In order to get some insight into the biological significance of gene expression changes during oral carcinogenesis, we first used GSEA. In the stroma, among the 34 gene sets significantly enriched between tumor vs normal mucosa (FDR q-value <1e-5; Supplementary Table 7), more than half were involved in immune and inflammation regulation processes, including a signature up-regulated in macrophages (Figure 3a). In the epithelium, most of the 122 significantly enriched pathways were related to carcinogenesis and invasiveness processes (Supplementary Table 7, Figure 3b). Interestingly, in the epithelium, Interferon related pathways, especially Interferon-gamma, were highly enriched in the early stage of oral carcinogenesis (Hyperplasia vs. Normal) while head and neck carcinogenesis pathways were enriched during malignant transformation of Dysplasia into Tumor in both the Epithelium and underlying Stroma.

We then used the five gene sets previously proposed to determine the cancer immune subtypes [START_REF] Thorsson | The immune landscape of cancer[END_REF] and computed an ES using ssGSEA in our samples. Among them, in both the epithelium and the stroma compartments, the "wound healing" and "TGF-beta" gene sets were the most positively enriched, while the "leukocyte infiltration" gene set was the most negatively enriched, but the three of them had limited variation during tumorigenesis. The "Interferon gamma" gene set ES increased overtime in both compartments but remained negative. Interestingly, the "CSF1 response" gene set ES, an M2 macrophage related signature, was increasing overtime in both compartments, but became positively enriched in the stroma only (Supplementary Table 8, Supplementary Figure S14).

The dynamics of immune cell populations during oral carcinogenesis

Using gene expression profiles generated in the stroma, we performed immune cell populations deconvolution (http:// wap-lab.org:3200/immune/) to infer the relative proportions of ten major immune cells (Figure 4). While macrophages represent less than 20% of immune infiltrating cells in normal/hyperplastic tissues, immune infiltrates in dysplasia and tumor tissues are dominated by macrophages (almost 35% and >50% of immune infiltrate respectively). In order to get a direct insight into the dynamics of immune cell populations during oral carcinogenesis, we performed immunostaining for T-and B-cells, and macrophages populations. Results were analyzed by combining the epithelium and stroma compartments or by considering them separately.

When combining the epithelium and stroma compartments, immune cells infiltrates were increasing overtime for T-cells (T-cells CD3+, helper CD4+, cytotoxic CD8+, regulatory FoxP3+), B-cells (B220+), and macrophages (M1 iNOS+, M2 CD163+) (Figure 5). For almost all immune cell populations, the infiltrate was the highest in dysplasia. Of note, these changes were related to histological changes and not to a potential inflammatory effect of 4-NQO (Supplementary Figure S11). Except for CD3 + T-cells, the increase in CD163+ M2 infiltrate was the most important one quantitatively. When analyzing the epithelial and stroma compartments separately, the increase of the immune cells infiltrate, including the CD163+ M2 population, was mainly seen in the stroma compartment (Figure 6).

M2 macrophages signatures and oral cancer risk

To investigate the precise role of M2 macrophages during oral carcinogenesis, we identified 13 murine and human gene expression signatures previously reported in the literature 18- 28 (Supplementary Figure S15a). Surprisingly, virtually no overlap was observed between genes included in these signatures (Supplementary Figure S15b).

We then evaluated the association of each M2 signature with OCFS using data from 86 patients with OPMD (oral leukoplakia, GSE26549, Supplementary Table 6). [START_REF] Saintigny | Gene expression profiling predicts the development of oral cancer[END_REF] ssGSEA was used to compute an ES of each individual sample. Analysis was first done in the overall population in which none of the M2 macrophages signatures was associated with oral cancer-free survival (Supplementary Figure 16).

We then explored the signatures in the immunological (n = 42) versus classical (n = 44) subtypes of OPMD. As expected, the ES of 11/13 signatures was significantly higher in OPMD of the immunological subtype than in OPMD of the classical subtype (Supplementary Figure S17). A similar trend for improved OCFS in immunological OPMD with high ES was observed for a majority of M2 signatures (Supplementary Figure S18) and with a P-value <0.01 for 3 signatures (Figure 7). No such association was observed when considering classical OPMD (data not shown) or when considering the 4-NQO gene sets as tested signatures (Supplementary Figures S19 andS20).

We next tested the ability of these signatures to predict OSCC development in immunological OPMD and if combining them do improve this prediction (Cox model, 3-folds cross validated AUC) (Figure 8). We found AUCs significantly higher to 0.5, supporting the excellent prediction ability of these signatures. Given that there were no statistical differences between AUCs of different models as well as the associated Hazard ratios, we found that all signatures were predictive of better OCFS in immunological OPMD, in particular the "Martinez2013_M2". Overall, these results showed an unexpected association between M2 macrophages infiltrates and OCFS in the immunological subtype of OPMD.

Discussion

In this work, by carefully analyzing, in the 4-NQO model, of the epithelial and the underlying stromal compartments, using gene expression profiles as well as immunostaining and semiquantitative assessment of different immune cell populations, we report that immunological changes are observed in early stages of oral tumorigenesis. Using different data mining approaches, we identify changes associated with M2 macrophages as being the most prominent quantitatively. Intriguingly, M2 macrophages gene expression signatures were consistently associated with a decreased oral cancer-risk in patients with an immunological OPMD subtype that we have previously reported. [START_REF] Foy | Immunological and classical subtypes of oral premalignant lesions[END_REF] Our study shows that all immune cell populations (T-and B cells, macrophages) are increasing early during mucosal transformation. It is striking that most of the changes seen in terms of the immune cell infiltration were observed at the stage of hyperplasia and did not dramatically change afterward. This is contrasting with stromal gene expression changes that were distributed across the different stages of tumorigenesis. This difference may be explained by immune cells functional changes rather than changes in the immune cell subtypes.

As expected, the dynamic changes observed were mostly seen in the stromal compartments. However, it is interesting to note that some significant changes were also observed in the epithelial compartment, especially for T-cells. Their impacts need to be better understood. Several authors have recently reported that a decrease in CD3+, CD4+, (helper) and CD8+ (cytotoxic) T-cells infiltrates was associated with malignant transformation of patients with OPMD. [START_REF] Chaves | Reduced CD8+ T cells infiltration can be associated to a malignant transformation in potentially malignant oral epithelial lesions[END_REF][START_REF] Kouketsu | Regulatory T cells and M2-polarized tumour-associated macrophages are associated with the oncogenesis and progression of oral squamous cell carcinoma[END_REF][START_REF] Öhman | Presence of CD3-positive T-cells in oral premalignant leukoplakia indicates prevention of cancer transformation[END_REF] In our model, CD4 + T-cells were significantly increased in hyperplasia vs. normal mucosa, while CD8 + T-cells were significantly increased at the stage of dysplasia vs. normal mucosa, but none of them were decreasing significantly in established tumors. This might be related to the small number of lesions analyzed.

The precise role of M2 macrophages during oral carcinogenesis is unclear. [START_REF] Qualls | Chapter ten -tumor macrophages: protective and pathogenic roles in cancer development[END_REF] While they have been largely reported to be associated with worse prognosis in patients with established tumors [START_REF] Mandal | The head and neck cancer immune landscape and its immunotherapeutic implications[END_REF] and besides the paucity of reports studying M2 macrophages in OPMD patients, conflicting results have been published. Some authors reported an increased M2 infiltrate in OPMD that subsequently transformed into OSCC compared to those that did not transform. [START_REF] Kouketsu | Regulatory T cells and M2-polarized tumour-associated macrophages are associated with the oncogenesis and progression of oral squamous cell carcinoma[END_REF][START_REF] Weber | Malignant transformation of oral leukoplakia is associated with macrophage polarization[END_REF][START_REF] Yagyuu | Programmed death ligand 1 (PD-L1) expression and tumor microenvironment: implications for patients with oral precancerous lesions[END_REF] Among them, Yagyuu et al. found that subepithelial CD163-positive cell count was significantly associated with malignant-free survival; of note, only 8/120 (7%) of the patients developed OSCC in their cohort. [START_REF] Yagyuu | Programmed death ligand 1 (PD-L1) expression and tumor microenvironment: implications for patients with oral precancerous lesions[END_REF] Weber et al. recently published the same conclusions in a large cohort of 103 OPMD with long term follow-up (60 months), including 50 patients that developed OSCC. Interestingly, the M2 infiltrate found in the epithelium was prognostic, while the one in the subepithelial compartment was not found to be associated with prognosis. [START_REF] Weber | Malignant transformation of oral leukoplakia is associated with macrophage polarization[END_REF] In our study of the 4-NQO model as well as in another report, [START_REF] Stasikowska-Kanicka | T cells are involved in the induction of macrophage phenotypes in oral leukoplakia and squamous cell carcinoma-a preliminary report[END_REF] M2 macrophages infiltrate within the epithelial cells compartment was very limited. More recently, Yagyuu et al. reported a series including n = 200 OPMD in which the subepithelial CD163 + cell count was not associated with malignant transformation of OPMD. [START_REF] Yagyuu | Effect of smoking status and programmed death-ligand 1 expression on the microenvironment and malignant transformation of oral leukoplakia: a retrospective cohort study[END_REF] On the other hand, the CD163/CD68 expression ratio in the stroma, which can be considered as a good indicator of M2 macrophages polarization, was significantly associated with non-transformed OPMD in the Weber et al. as well as the Stasikowska-Kanicka et al. studies. [START_REF] Weber | Malignant transformation of oral leukoplakia is associated with macrophage polarization[END_REF][START_REF] Stasikowska-Kanicka | T cells are involved in the induction of macrophage phenotypes in oral leukoplakia and squamous cell carcinoma-a preliminary report[END_REF] These results are consistent with our recent observation that miRNA 142-5p, that promotes M1 to M2 switch, [START_REF] Su | miR-142-5p and miR-130a-3p are regulated by IL-4 and IL-13 and control profibrogenic macrophage program[END_REF] is associated with improved OCFS in immunological OPMD. [START_REF] Foy | Immunological and classical subtypes of oral premalignant lesions[END_REF] Overall, the precise role of M2 macrophages during oral carcinogenesis is not yet established. [START_REF] Grigolato | Leukoplakia and immunology: new chemoprevention landscapes?[END_REF] Some discrepancies may be related to the tissue compartment that is being analyzed (epithelial versus underlying stroma). As stated by Shigeoka et al., in their recent systematic review "the biological features of macrophages in oral carcinogenesis differ drastically depending on the anatomical compartment that they infiltrate". [START_REF] Shigeoka | Alteration of macrophage infiltrating compartment: a novel view on oral carcinogenesis[END_REF] Also, as recently reported at the transcriptional level, macrophages are recognized as being extremely plastic during macrophage polarization, [START_REF] Liu | Trajectory analysis quantifies transcriptional plasticity during macrophage polarization[END_REF] and intermediate stages may not be properly recapitulated by the "classical" M1 or M2 subtypes and impact differently oral tumorigenesis.

Herein, we report three independent M2 macrophages gene expression signatures [START_REF] Martinez | Genetic programs expressed in resting and IL-4 alternatively activated mouse and human macrophages: similarities and differences[END_REF][START_REF] Jablonski | Novel markers to delineate murine M1 and M2 macrophages[END_REF][START_REF] Tuit | Transcriptional signature derived from murine tumor-associated macrophages correlates with poor outcome in breast cancer patients[END_REF] that are associated with better OCFS in the subgroup of patients harboring an OPMD of the immunological subtype. While our results are not fitting conventional role of M2 macrophages and remain to be validated by further biological investigations, they underline that the "classic" association between M2 macrophages infiltrate and worse prognosis in established tumors may not translate in early stages of tumorigenesis. [START_REF] Mandal | The head and neck cancer immune landscape and its immunotherapeutic implications[END_REF][START_REF] Balermpas | Head and neck cancer relapse after chemoradiotherapy correlates with CD163+ macrophages in primary tumour and CD11b+ myeloid cells in recurrences[END_REF] It is interesting to note that the impact of M2 macrophages signature was not observed in patients with the classical subtype that is characterized by a "cold" OPMD. We believe this is an important observation in the context of the ongoing effort of the scientific community to develop immunoprevention strategies and argues in favor of proper patient stratification as those strategies are being or will be evaluated in clinical trials.

In summary, our study improves our understanding of early changes in the immune microenvironment during oral tumorigenesis and reveals an unexpected association of M2 macrophages with OCFS in immunologically active OPMD. It provides a detailed description of dynamic changes in the 4-NQO murine model that will be important to consider when evaluating new immune-prevention strategies in this model. [START_REF] Palladini | Cancer immunoprevention: from mice to early clinical trials[END_REF]

Highlights

Oral carcinogenesis is characterized by early immune-related gene expression and immune infiltrate changes. In oral leukoplakia, enrichment in M2 macrophage signatures is associated with improved oral cancer-free survival.

Background Oral squamous cell carcinomas (OSCC) prognosis remains poor. While AJCC TNM 8th edition has slightly improved patients' stratification with regard to prognostic, innovative approaches to are still needed. As in other tumor types, tumor immune microenvironment (TiME) might represent an opportunity to improve prognostic assessment. Methods TiME landscape of 47 HPV-negative OSCC was analyzed using multiplex immunofluorescence (mIF). Markers for tumor cells (PanCK), tumor infiltrating lymphocytes (CD3, CD8), macrophages (CD68), inhibitory (PD-1, PD-L1, TIM3, LAG3, VISTA) or stimulatory (OX40, ICOS) immune checkpoints (ICP) were studied. Regions of interest (ROI), 5 in the tumor core and 5 at the invasion front, were subjected to cell markers identification and quantification (scoring) as well as tissue compartmentalization to divide them in tumor-epithelial and tumor-stroma compartments, respectively. A total of 20 cell phenotypes were defined based on previous work (CK+, CK+PD-L1+, CD3+, CD3+CD8+, CD3+PD-1+, CD3 +CD8+PD-1+, CD3+PD-L1+, CD3+CD8+PD-L1+, CD3 +PD-L1+PD-1+, CD3+CD8+PD-L1+PD-1+, CD68+, CD68+PD-L1+, CK+OX40+, CD3+VISTA+, CD3+ICOS+, CD3+LAG3+, CD3+OX-40+, CD3+TIM3+). Results were correlated with clinical features including disease-specific survival (DSS) using the Kaplan-Meier method and a multivariate Cox model. A multivariate general linear model (GLM) was built to test the specific association of each variable with a given cell density by correcting the possible confusion due to other variables. Results Immune cells densities were significantly higher overall in the stroma. The intra-tumor stroma showed a significant enrichment of in CD3+PD-1+ T cells compared to peri-tumor stroma. None of the clinical or pathological (resection margin, tumor stage, lymph node invasion, perineural invasion) was significantly associated with DSS. In contrast, the following cell phenotypes in the tumor invasion front were strongly associated with a poor DSS, including CD3+PD-L1+ (P-value= 0.004), CD3+PD1+PD-L1+ (P-value= 0.02) and CD3+OX40+ (P-value= 0.02) T cells as well as CD3+CD8 +PD-1+ (P-value= 0.048), CD3+CD8+PD-L1+ (P-value= 0.008) and CD3+CD8+PD1+PD-L1+ (P-value= 0.01) cytotoxic T cells. In the tumor core, CD68+PD-L1-macrophages (P-value= 0.06) were marginally associated with better DSS. Using a GLM, we found that tumor from smoker-drinker patients and/or with pN+, were significantly more infiltrated by PD-1-and/or PD-L1-positive immune cells. On the other hand, floor of mouth and gingiva-mandibular OSCC were significantly less infiltrated than others.

Conclusions

The prognostic value of PD-1+ and/or PD-L1+ cells in the invasion front of resected OSCC was remarkable, underlying the importance of this area when studying the TiME. Incorporating TiME analysis in the invasion front may improve prognostic evaluation of patients treated for OSCC, especially in the context of immunotherapy. Background Head and Neck Squamous Cell Carcinoma is the 8th leading cancer worldwide and it is associated with significant morbidity and mortality. 1 2 Tumor microenvironment (TME) is dynamic and it plays an important role in head and neck carcinogenesis. 3 4 Cytotoxic T-cells, immune checkpoint molecules such as programmed cell death 1 (PD-1), its ligand (PD-L1), and other checkpoints molecules have been described in these tumors. 1 3 This study aimed to characterize the TME of oral squamous cell carcinoma (OSCC) and compare with their pathology features.

INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is the sixth most incident cancer worldwide, responsible for more than 700,000 cases worldwide per year and around 350,000 deaths, making it a particularly fatal disease (1).

Squamous cell cancers of the oral cavity, the pharynx, and the larynx (the most frequent) are linked to smoking and alcohol consumption, and squamous cell carcinomas of the oropharynx are most

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INTRODUCTION

Genomic alterations in genes of the mitogenactivated protein kinase (MAPK) pathway, or activation of receptor tyrosine kinases (RTK), induce constant activation of MEK-ERK signaling, which regulates cell proliferation, survival, migration, and transformation. 1 2 Since hyperactivation of the MAPK pathway is involved in the pathogenesis of head and neck cancer (HNC) 3 4 5 , blockade of the MAPK pathway has been studied as a therapeutic approach for counteracting HNC progression. For example, cetuximab, an antiepidermal growth factor receptor (EGFR) antibody that blocks the MAPK pathway, showed a significant but transient antitumor effect in HNC patients. [START_REF] Saintigny | DeltaNp63 overexpression, alone and in combination with other biomarkers, predicts the development of oral cancer in patients with leukoplakia[END_REF]

Figure 1 .

 1 Figure 1. Histological changes in the 4-nitroquinoleine-1-oxyde (4-NQO) treated mice. A total of 270 formalin-fixed paraffin-embedded tongues slides from the nine mice were treated with 4-NQO.

Figure 2 .

 2 Figure 2. Global gene expression changes in the epithelial and stromal compartments. (a) Principal Component Analyses using the 1% genes with the highest mediation absolute deviation. Two distinct patterns of distribution were observed. (b) TGSE and TGSS enrichment scores computed using ssGSEA in murine (GSE75421) and human (GSE9844, GSE30784) independent datasets. Significant changes related to histological stages are observed. (TGSE: tumor gene set Epithelium; TGSS: tumor gene set Stroma; UP: version for genes upregulated; DN: version for genes downregulated; UP+DN: combined version; ssGSEA: single sample gene set enrichment analysis).

Figure 3 .

 3 Figure 3. Graphical representation of some Enrichment Scores of genes specifically and differentially expressed between tumor and normal mucosa in the Stroma (a) and the Epithelium (b) for the 4,762 of the C2 "curated gene sets". High enriched scores (peak of the plot) for signatures related to immune regulation and cancer invasiveness were observed (https://software.broadinstitute.org/gsea/doc/GSEAUserGuideFrame.html).

Figure 4 .

 4 Figure 4. Deconvolution of immune cell populations in stroma samples. Each immune cell type is given as a percentage (T-cells: T lymphocytes; B-cells: B lymphocytes; NK: Natural Killer).

Figure 5 .

 5 Figure 5. Quantification of immune cells infiltrate at each stage of oral tumorigenesis in the 4-nitroquinoleine-1-oxyde model. T-cells (total CD3+, helper CD4 +, cytotoxic CD8+, regulatory FoxP3+), B-cells (B220+) and macrophages (M1 iNOS+, M2 CD163+) were immunostained and quantified in normal mucosa (n), hyperplasia (h), dysplasia (d) and established tumor (t).

Figure 6 .

 6 Figure 6. Quantification of immune cells infiltrate in the epithelial and underlying stroma compartment (a) and changes in the CD163+ M2 macrophages infiltrate in the stromal compartment in the in the 4-nitroquinoleine-1-oxyde model during oral tumorigenesis (b). T-cells (total CD3, regulatory FoxP3+) and macrophages (M1 iNOS+, M2 CD163+) were immunostained and quantified in normal mucosa (n), hyperplasia (h), dysplasia (d) and established tumor (t).

Figure 7 .

 7 Figure 7. Association of three independent M2 macrophages gene expression signature with oral cancer-free survival of patients with oral potentially malignant disorders of the immunological subtype.

Figure 8 .

 8 Figure 8. Three independent M2 macrophages gene expression signatures are predictive of oral cancer-free survival. Each signature (Martinez2013, Jablonski2015, Tuit2019) demonstrates an excellent prediction (AUC 0.5, Hazard Ratio [0.3-0.8]) of improved oral cancer-free survival in patients with oral potentially malignant disorders of the immunological subtype (Cox model, 3-folds cross validated AUC).

  Ethics ApprovalThe study was conducted in accordance with all applicable laws, rules, and requests of French and European government authorities. Written informed consent was obtained from all patients and the study was approved by the Centre Leon Bérard institutional review board (Lyon, France). Samples were obtained from the CRB Centre Léon Bérard (n°BB-0033-00050) which is quality certified according NFS96-900 French standard and ISO 9001 for clinical trials. Consent Written informed consent was obtained from all patients and the study was approved by the Centre Leon Bérard institutional review board (Lyon, France) http://dx.doi.org/10.1136/jitc-2021-SITC2021.917

	Abstracts STUDY OF THE TUMOR MICROENVIRONMENT OF ORAL SQUAMOUS CELL CARCINOMA USING MULTIPLEX IMMUNOFLUORESCENCE AND IMAGE ANALYSIS APPROACHES Frank Rojas*, 2 Jebrane Bouaoud, 1 Edwin Parra, 2 Pierre Saintigny, 1 Auriole Tamegnon, 1 1 Mei Jiang, 3 Shanyu Zhang, 1 Pandurengan Renganayaki, 4 Lucas Michon, 2 Nicolas Gadot, 2 Sylvie Lantuejoul, 4 Philippe Zrounba, 2 Jean-Philippe Foy, 2 Karene Mahtouk, 2 Chloe Bertolus. 1 MD Anderson Cancer Center, Houston, TX, USA; 2 University Claude Bernard Lyon, Lyon, France; 3 MD Anderson Cancer Canter, Houston, TX, USA; 4 Centre Leon Berard, Lyon, France	Acknowledgements This study was supported by a strategic alliance between the Translational Molecular Pathology-Immu-noprofiling las (TMP-IL) at the Department Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center and the Université Claude Bernard Lyon, Centre de Recherche en Cancérologie de Lyon and the Department of Translational Medicine, Centre Léon Bérard, Lyon, France. The authors would acknowledge ITMO Cancer 2020, "Formation à la Recherche Fondamentale et Translation-nelle en Cancérologie" (JB); CLARA 2020 "Soutien à la mobi-lité des jeunes chercheurs en oncologie, N°C VPPRCAN000198" (JB); Fondation de France 2020 "Aide à la mobilité international de médecins et pharmaciens, N°0 0112162" (JB); Ligue contre le cancer 2021, comité de Saône-et-Loire (PS); 2017-INCa-DGOS-Inserm_12563: INCa SIRIC-LYriCAN INCa-DGOS-Inserm_12563 (PS) copyright. J Immunother Cancer: first published as 10.1136/jitc-2021-SITC2021.917 on 10 November 2021. Downloaded from
		http://jitc.bmj.com/
		on December 18, 2021 by guest. Protected by
	A962	J Immunother Cancer 2021;9(Suppl 2):A1-A1054

  Conclusions Our findings of a diminished immune response in larger tumors might be correlated to their potential role in tumor aggressiveness and progression. Furthermore, high cell density of macrophages on tumor bone invasion may suggest an immune suppressive M2 response supported by the presence of PDL1+ expression. All these results can be the first approach for the development of a treatment based of immune interception. Acknowledgements This study was supported by a strategic alliance between the Translational Molecular Pathology-Immunoprofiling las (TMP-IL) at the Department Translational Molecular Pathology, the University of Texas MD Anderson Cancer Center and the Université Claude Bernard Lyon, Centre de Recherche en Cancérologie de Lyon and the Department of Translational Medicine, Centre Léon Bérard, Lyon, France. The authors would acknowledge ITMO Cancer 2020, "Formation à la Recherche Fondamentale et Translationnelle en Cancérologie" (JB); CLARA 2020 "Soutien à la mobi-Fondation de France 2020 "Aide à la mobilité international de médecins et pharmaciens, N°0 0112162" (JB); Ligue contre le cancer 2021, comité de Saône-et-Loire (PS); 2017-INCa-DGOS-Inserm_12563: INCa SIRIC-LYriCAN INCa-DGOS-Inserm_12563 (PS)

	lité	des	jeunes	chercheurs	en	oncologie,	N°C
	VPPRCAN000198" (JB);
	Methods Four microns thickness consecutives slides from rep-
	resentative OSCC (N=46) cases were stained and analyzed
	using 11 biomarkers (CK, CD3, CD8, CD68, PD1, PDL1,
	LAG3, TIM3, ICOS, VISTA, OX40) placed in two multiplex
	immunofluorescence panels to characterize the TME. For
	image analysis, the samples were divided in tumor, stroma and
	peritumoral compartment. Co-expression of markers (cell phe-
	notypes) where analyzed as densities by mm2 in each com-
	partment. For PD-L1 expression by malignant cells (CK+PD-
	L1+) we set up a cutoff of positive case as than 1%. Cell
	phenotypes were correlated with anatomopathological informa-
	tion retrieved from records such as tumor size, margin status,
	stage and perineural, lymphovascular, and bone invasion
	among others. Statistical analyses and plots were performed
	using SPSS and Graphpad prism8 software packages.
	Results We found significant higher cell density for CK+PDL1
	+ (P= 0.038), CD3+PDL1+ (P= 0.027), CD3+CD8+PDL1
	+ (P=0.040) in female patients compared with the male pop-
	ulation. Interestingly, smaller tumor size (£ median, 25mm)
	showed higher densities of CD3+ (P= 0.006), CD3+CD8+
	(P= 0.007), CD3+PDL1+ (P= 0.037), CD3+CD8+PDL1+
	(P= 0.016), CD3+ICOS+ (P= 0.036), CD3+VISTA+ (P=
	0.001), CD68+ (P= 0.001) and CD68+PD-L1+ (P= 0.008)
	than large tumors. Additionally, high cell density CD3+OX40
	+ (P= 0.011) was observed in tumors without margin inva-
	sion and high cell density for macrophages CD68+ (p=
	0.005) in tumors without bone invasion. In ulcerative and
	infiltrative tumor pattern we observed higher cell density of
	CD3+PDL1+ (P= 0.020), CD3+CD8+PDL1+ (P=0.006)
	and CD3+OX40+ (P= 0.022) than non-ulcerate and no infil-
	trative pattern. Lastly, 58.7% of cases were PDL1+.

  Currently, multiple clinical trials are testing MAPK/RTK inhibitors in combination with different modalities in patients with HNC. Trametinib, a MEK1/2 kinase inhibitor approved for treatment of MAPK-driven melanoma and non-small cell lung cancer, exhibited a favorable but transient antitumor effect in HNC patients with on March 19, 2022 at INSERM Consortia. Protected by copyright. http://jitc.bmj.com/ J Immunother Cancer: first published as 10.1136/jitc-2021-003917 on 15 March 2022. Downloaded from

J. BOUAOUD ET AL.

ONCOIMMUNOLOGYe1944554-11

J Immunother Cancer: first published as 10.1136/jitc-2021-SITC2021.938 on 10 November 2021. Downloaded from

Acknowledgments

To the French association "les Chirurgiens Maxillo-Faciaux" and the Equipex ANR-11-EQPX-0035 PHENOCAN. 1 Prasad M, et al. J Immunother Cancer 2022;10:e003917. doi:10.1136/jitc-2021-003917

Funding

Fondation Nuovo Soldati 2019 (JB); ITMO Cancer 2020, "Formation à la Recherche Fondamentale et Translationnelle en Cancérologie" (JB); Ligue contre le cancer 2017, comité du Rhône (PS); 2017-2020: INCa PLBIO17-171 (PS); 2017-INCa-DGOS-Inserm_12563: INCa SIRIC-LYriCAN INCa-DGOS-Inserm_12563 (PS).

ORCID

Jebrane Bouaoud http://orcid.org/0000-0003-2964-2579

Disclosure of potential conflicts of interest

PS is a member of HTG Diagnostics Scientific Advisory Board and receives research grants from HTG Diagnostics, Inivata, ArcherDx, Bristol-Myers Squibb, Roche Molecular Diagnostics, Roche, AstraZeneca, Novartis, Bristol-Myers Squibb Foundation, and Illumina.

Author contributions statement

All authors have participated to the conception and design, acquisition, analysis, interpretation of data and to the drafting the article or revising it critically for important intellectual content; All authors have approved the final version to be published.

Ethics Approval

The study was conducted in accordance with all applicable laws, rules, and requests of French and European government authorities. Written informed consent was obtained from all patients and the study was approved by the Centre Leon Bérard institutional review board (Lyon, France). Samples were obtained from the CRB Centre Léon Bérard (n°BB-0033-00050) which is quality certified according NFS96-900 French standard and ISO 9001 for clinical trials.

Abstract

The early detection and management of oral premalignant lesions (OPMDs) improve their outcomes. Animal models that mimic histological and biological processes of human oral carcinogenesis may help to improve the identification of OPMD at-risk of progression into oral squamous cell carcinoma and to develop preventive strategies for the entire field of cancerization. No animal model is perfectly applicable for investigating human oral carcinogenesis. However, the 4-nitroquinoline 1-oxide (4-NQO) mouse model is well established and mimics several morphological, histological, genomic and molecular features of human oral carcinogenesis. Some of the reasons for the success of this model include its reproducible experimental conditions with limited variation, the possibility of realizing longitudinal studies with invasive intervention or gene manipulation, and sample availability for all stages of oral carcinogenesis, especially premalignant lesions. Moreover, the role of histological and molecular alterations in the field of cancerization (i.e., macroscopically healthy mucosa exposed to a carcinogen) during oral carcinogenesis can be easily explored using this model. In this review, we discuss the advantages and drawbacks of this model for studying human oral carcinogenesis. In summary, the 4-NQO-induced murine oral cancer model is relevant for investigating human oral carcinogenesis, including the immune microenvironment, and for evaluating therapeutic and chemoprevention agents.

Introduction

Among head and neck squamous cell carcinoma (HNSCC), the oral cavity is the most common site ( Head and neck squamous cell carcinoma (HNSCC) is the sixth most incident cancer worldwide. More than half of HNSCC patients experience locoregional or distant relapse to treatment despite aggressive multimodal therapeutic approaches that include surgical resection, radiation therapy, and adjuvant chemotherapy. Before the arrival of immunotherapy, systemic chemotherapy was previously employed as the standard first-line protocol with an association of cisplatin or carboplatin plus 5-fluorouracil plus cetuximab (anti-EFGR antibody). Unfortunately, acquisition of therapy resistance is common in patients with HNSCC and often results in local and distant failure. Despite our better understanding of HNSCC biology, no other molecular-targeted agent has been approved for HNSCC. In this review, we outline the mechanisms of resistance to the therapeutic strategies currently used in HNSCC, discuss combination treatment strategies to overcome them, and summarize the therapeutic regimens that are presently being evaluated in early-and late-phase clinical trials.

Open access

Manu Prasad, 1,2 Jonathan Zorea, 1,2 Sankar Jagadeeshan, 1,2 Avital B Shnerb, 1,2 Sooraj Mathukkada, 1,2 Jebrane Bouaoud, 3,4 Lucas Michon, 4 Ofra Novoplansky, 1,2 Mai Badarni, 1,2 Limor Cohen, 1,2 Ksenia M Yegodayev, 1,2 Sapir Tzadok, 1,2 Barak Rotblat, 5 Libor Brezina, 1,2 Andreas Mock, [START_REF] Saintigny | DeltaNp63 overexpression, alone and in combination with other biomarkers, predicts the development of oral cancer in patients with leukoplakia[END_REF][START_REF] Bouaoud | The 4-NQO mouse model: an update on a well-established in vivo model of oral carcinogenesis[END_REF] Andy Karabajakian, 3,4,[START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] Jérôme Fayette, 3,4,[START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] Idan Cohen, 1,2 Tomer Cooks, 1,2 Irit Allon, 2,[START_REF] Mandal | The head and neck cancer immune landscape and its immunotherapeutic implications[END_REF] Orr Dimitstein, 2,[START_REF] Ferris | Nivolumab for recurrent squamous-cell carcinoma of the head and neck[END_REF] Benzion Joshua, 2,[START_REF] Burtness | Pembrolizumab alone or with chemotherapy versus cetuximab with chemotherapy for recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-048): a randomised, open-label, phase 3 study[END_REF] Dexin Kong, [START_REF] Ai | Microenvironmental regulation of the progression of oral potentially malignant disorders towards malignancy[END_REF] Elena Voronov, 1,2 Maurizio Scaltriti, [START_REF] Gutkind | The next frontier: head and neck cancer immunoprevention[END_REF] Yaron Carmi, [START_REF] Foy | Immunological and classical subtypes of oral premalignant lesions[END_REF] Cristina Conde-Lopez, [START_REF] Saintigny | Gene expression profiling predicts the development of oral cancer[END_REF] Jochen Hess, [START_REF] Papadimitrakopoulou | Randomized Trial of 13-cis Retinoic Acid Compared With Retinyl Palmitate With or Without Beta-Carotene in Oral e1944554-10 J. BOUAOUD ET AL. Premalignancy[END_REF][START_REF] Thorsson | The immune landscape of cancer[END_REF] Ina Kurth, [START_REF] Saintigny | Gene expression profiling predicts the development of oral cancer[END_REF] Luc G T Morris, [START_REF] Martinez | Genetic programs expressed in resting and IL-4 alternatively activated mouse and human macrophages: similarities and differences[END_REF] Pierre Saintigny , 3,4,[START_REF] Foy | The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer[END_REF] Moshe Elkabets

ABSTRACT

Background Although the mitogen-activated protein kinases (MAPK) pathway is hyperactive in head and neck cancer (HNC), inhibition of MEK1/2 in HNC patients has not shown clinically meaningful activity. Therefore, we aimed to characterize the effect of MEK1/2 inhibition on the tumor microenvironment (TME) of MAPK-driven HNC, elucidate tumor-host interaction mechanisms facilitating immune escape on treatment, and apply rationale-based therapy combination immunotherapy and MEK1/2 inhibitor to induce tumor clearance. Methods Mouse syngeneic tumors and xenografts experiments were used to analyze tumor growth in vivo. Single-cell cytometry by time of flight, flow cytometry, and tissue stainings were used to profile the TME in response to trametinib (MEK1/2 inhibitor). Co-culture of myeloidderived suppressor cells (MDSC) with CD8 + T cells was used to measure immune suppression. Overexpression of colony-stimulating factor-1 (CSF-1) in tumor cells was used to show the effect of tumor-derived CSF-1 on sensitivity to trametinib and anti-programmed death-1 (αPD-1) in mice. In HNC patients, the ratio between CSF-1 and CD8A was measured to test the association with clinical benefit to αPD-1 and αPD-L1 treatment. Results Using preclinical HNC models, we demonstrated that treatment with trametinib delays HNC initiation and progression by reducing tumor cell proliferation and enhancing the antitumor immunity of CD8 + T cells. Activation of CD8 + T cells by supplementation with αPD-1 antibody eliminated tumors and induced an immune memory in the cured mice. Mechanistically, an early response to trametinib treatment sensitized tumors to αPD-1-supplementation by attenuating the expression of tumor-derived CSF-1, which reduced the abundance of two CSF-1R + CD11c + MDSC populations in the TME. In contrast, prolonged treatment with trametinib abolished the antitumor activity of αPD-1, because tumor cells undergoing the epithelial to mesenchymal transition in response to trametinib restored CSF-1 expression and recreated an immune-suppressive TME. Conclusion Our findings provide the rationale for testing the trametinib/αPD-1 combination in HNC and highlight the importance of sensitizing tumors to αPD-1 by using MEK1/2 to interfere with the tumor-host interaction. Moreover, we describe the concept that treatment of cancer with a targeted therapy transiently induces an immune-active microenvironment, and supplementation of immunotherapy during this time further activates the antitumor machinery to cause tumor elimination.


to implementing user-oriented evaluation criteria § Relevance • Making progresses in Mapping soil functions and soil quality (Challenge 7) • Extend DSM applications to new properties required by users (deep soil layers, biological properties etc …) § Integrity • Improve the mapping of uncertainties on soil property and soil function mapping § Intelligibility • Searching more intuitive visualizations to communicate uncertainty ( next communication) • Increase the traceability of the mapping approaches Ø Develop tools for understanding machine learning predictions (challenge 3) Ø Develop dynamic users interfaces to communicate complex mapping contents • Involve users in the mapping process through participative approaches Ø Soil data collection Ø Soil function assessements Conclusions § Evaluating DSM products is fine. Evaluating them from an user's point of view is even finer § Relevance, integrity and intelligibility can be the three pillars of an user-oriented evaluation of DSM products § Pedometricians have a lot to bring for increasing the user-perceived quality of DSM products § Close collaboration with future users is mandatory (co-construction)