Aymeric Reshef

Cyril Riddell

Yves Trousset

Saïd Ladjal

Isabelle Bloch

Divergent-beam backprojection-filtration formula with applications to region-of-interest imaging

We propose a new backprojection-filtration (BPF) method for cone-beam computed tomography (CBCT) with flatpanel detectors over circular orbits. The method is exact in the fan-beam geometry and provides an approximate CBCT reconstruction that is different from the standard Feldkamp-Davis-Kress (FDK) method. More interestingly, it can be used for region-of-interest (ROI) reconstruction by complementing a truncated low-noise acquisition with dense angular sampling by additional non-truncated views that are either high-noise or angularly undersampled.

I. INTRODUCTION

Filtered backprojection (FBP) performs poorly when projections are truncated, unless data extrapolation is performed prior to filtering. Alternative direct reconstruction methods were derived to address the issue of ROI reconstruction [START_REF] Noo | A two-step Hilbert transform method for 2D image reconstruction[END_REF]. However, when not in parallel-beam geometry, they require a dense angular sampling of the projections.

In the case of interior tomography, it was shown that no unique solution could be obtained from the truncated projections only. However, a tiny additional information, such as a prior knowledge on the image itself [START_REF] Kudo | Tiny a priori knowledge solves the interior problem in computed tomography[END_REF] or a few additional untruncated measurements [START_REF] Reshef | Dualrotation C-arm cone-beam computed tomography to increase low-contrast detection[END_REF] is enough to stabilize the problem. Unfortunately, no closed-form analytical solution exists and iterative reconstruction has been used instead.

In this work, we propose a new backprojection-filtration (BPF) formula in cone-beam geometries with flat-panel detectors and circular orbits, which is used to design a direct reconstruction method for ROI imaging. The formula is derived in Section II. The application of the method to ROI imaging is described in Section III. Experiments are presented in Section IV and results are shown in Section V. projects onto the detector plane at coordinates (u θ (x), v θ (x)); without loss of generality, we write, for α ∈ Θ:

II. METHOD

A. Cone-beam geometry

x = x • α x α ⊥ , (1)
where x α ⊥ ∈ R 2 consists of the coordinates of x in the plane of equation x • α = 0. When looking only at points x belonging to a plane of equation: x • α = x α , where x α ∈ R, the relationship between (u θ (x), v θ (x)) and x is given by:

  s θ (x)u θ (x) s θ (x)v θ (x) s θ (x)   = H α θ (x α ) x α ⊥ 1 , (2)
where the matrix H α θ (x α ) ∈ R 3×3 is a homography matrix. The cone-beam projection of an image f at angle θ is denoted p θ . It is defined at each detector coordinate (u, v) as the integral of f along the line joining ξ θ to (u, v). The full-scan, cone-beam tomographic acquisition over a circular orbit is the collection p = {p θ | θ ∈ Θ}. We define the backprojection from angle θ of a single projection p θ as:

B θ [p θ ] = p θ (u θ , v θ ).

B. Feldkamp-Davis-Kress reconstruction

The Tuy conditions [START_REF] Tuy | An inversion formula for cone-beam reconstruction[END_REF] are not satisfied in the cone-beam geometry with a circular orbit. Hence, only approximate direct reconstruction methods exist, such as the Feldkamp-Davis-Kress method [START_REF] Feldkamp | Practical cone-beam algorithm[END_REF], which is a direct extension of the fanbeam FBP to cone-beam data. Given a full-scan tomographic acquisition p, FDK reconstructs an image f FDK as:

f FDK = 2π 0 D 2 s 2 θ B θ D [ p θ ]dθ, ( 3
)
where D is the ramp filter, and:

p θ (u, v) = 1 2 • d D • D √ D 2 + u 2 + v 2 • p θ (u, v). (4)
By design, FDK is equal to FBP when z = 0, yielding an exact reconstruction in the midplane. If the true image f is invariant along the z-axis, the reconstructed image f FDK is exact [START_REF] Feldkamp | Practical cone-beam algorithm[END_REF]; otherwise, it deviates from f as the cone angle increases, yielding cone-beam artifacts.

In the following, we define {Θ k } k=1•••K as a subdivision of Θ. Then by linearity of the integral:

f FDK = K k=1 g Θ k , where g Θ k = Θ k D 2 s 2 θ B θ D [ p θ ]dθ. (5) φ(t) H [φ] (t) H [ψ] (t) -ψ(t) tψ(t) tH [ψ] (t) -1 π +∞ -∞ ψ(t )dt δ(t) 1 πt 1 h 3 t+h 4 ψ h 1 t+h 2 h 3 t+h 4 , where h 1 h 4 -h 2 h 3 = ±1 sgn(h 1 h 4 -h 2 h 3 ) h 3 t+h 4 H [ψ] h 1 t+h 2 h 3 t+h 4
Table I: Useful Hilbert transforms to prove Eq. ( 7).

C. Proposed backprojection-filtration method

The proposed backprojection-filtration (BPF) formula is first derived in the fan-beam geometry. We rely on the decomposition of the ramp filter D into a spatial derivative operator and a Hilbert transform operator H:

D [p θ ] = 1 2π H ∂ pθ ∂u . (6)
When Θ k = {θ}, we write g θ = g {θ} . Let α ∈ Θ such that for any point x in the field of view, det (

H α θ (x • α)) = 0. We define σ α θ (x) = sgn (det (H α θ (x • α))).
The following holds:

g θ = σ α θ 2π H α [b θ ] , where b θ = D 2 s 2 θ B θ ∂ pθ ∂u , (7)
and H α applies the one-dimensional Hilbert transform to each line of the 2D plane that is colinear to α ⊥ . We sketch the proof of Eq. ( 7). The homography matrix

H α θ (x • α) is such that det (H α θ (x • α)) = 0, hence the determinant of the matrix |det H α θ (x • α)| -1/2 H α θ (x • α) is equal to σ α θ .
We use the last row of Table I to obtain the intermediate result:

s θ g θ = σ α θ 2π H α D 2 s θ B θ ∂ pθ ∂u
. We then apply again H α to each side of this equality and observe that s θ is an affine function of x. Using the other properties of the Hilbert transform recalled in Table I, we obtain Eq. [START_REF] Langet | Compressed-sensing-based content-driven hierarchical reconstruction: Theory and application to C-arm cone-beam tomography[END_REF].

If

Θ k = [θ k-1 , θ k ] and |θ k -θ k-1 | < π -γ,
where γ is the fan angle, we can find a common admissible α value, denoted α k , such that Eq. ( 7) holds for all θ ∈ Θ k ; hence:

g Θ k = 1 2π Θ k H α k [b θ ] dθ = 1 2π H α k [b Θ k ] , (8)
where b Θ k = Θ k b θ dθ.
We propose to reconstruct an image f BPF as:

f BPF = 1 2π K k=1 H α k [b Θ k ] . (9)
As in FDK, the reconstruction formula from Eq. ( 9) is always exact in the midplane; it is exact everywhere when the true image f is invariant along the z-axis [START_REF] Feldkamp | Practical cone-beam algorithm[END_REF].

D. Implementation

The support of the backprojection over each angular subset Θ k depends both on Θ k and on the value of α k . Provided that this support is large enough to compute all the backprojected lines colinear to α ⊥ k and intersecting the image field of view (Fig. 1), the Hilbert transform can be computed directly in the Fourier domain using zero-padding and periodicity. We divide Θ into frontal and lateral views. Frontal views correspond to

θ k α k α k ⊥ θ k -1 ξ θ k -1 ξ θ k
Θ FRT = π 4 , 3π 4 ∪ 5π 4 , 7π 4 . With α FRT = π 2 , image b ΘFRT is filtered horizontally. Lateral views correspond to Θ LAT = Θ\Θ FRT . With α LAT = 0, image b ΘLAT is filtered vertically. Thus: f BPF = 1 2π H π 2 [b ΘFRT ] + H 0 [b ΘLAT ] . (10)

III. APPLICATION TO REGION-OF-INTEREST IMAGING

Following [START_REF] Reshef | Dualrotation C-arm cone-beam computed tomography to increase low-contrast detection[END_REF], we define a dual-rotation acquisition as follows. Let p T be a set of truncated projections that finely sample the source-detector orbit. Projections p T are complemented by additional un-truncated projections p F . We do not intend to bring too much additional dose to the patient with the un-truncated projections, by either lowering the dose level per view or by reducing the number of views in p F .

Since local operations are applied to projections p T prior to backprojection, they correctly sample the unfiltered backprojected image b T within the ROI, denoted Ω . Outside the ROI, however, each backprojected point is observed over a limited angular range, which differs from one point to the other. We thus merge the ROI of b T with the unfiltered backprojected image b F obtained from p F , yielding image M(b F , b T ) such that:

M(b F , b T ) = η • b F + (1 -η) • b T inside Ω ; b F outside Ω . (11)
The function η : R 3 → [0, 1] is a continuous function that ensures a smooth transition from b T to b F at the boundaries of the ROI. The Fourier-based filtering step is then performed on the hybrid image M(b F , b T ). Using our BPF method, the merging step is performed separately for backprojections of the frontal views and of the lateral views.

IV. SIMULATIONS

All images were reconstructed on a 256 × 256 × 256 grid with isotropic voxels of size 1.17 mm 3 .

A. Full-volume reconstruction

A diagnostic CT scan of a head was forward-projected over an ideal circular orbit using D = d = 1180 mm. A total of 1440 projections sampling Θ was generated. The projections were reconstructed using FDK (yielding image f FDK ) and Eq. (10) (yielding image f BPF ). We computed the mean relative error (MRE) over a mask Ω 0 , denoted ∆ Ω0 (f BPF , f FDK ), using the formula:

∆ Ω (f, f * ) = 1 Card(Ω) x∈Ω |f (x) -f * (x)| |f * (x)| (12)
Mask Ω 0 was defined in order to keep only the voxels higher than -250 HU.

We repeated the experiment using modified projection data corresponding to 1.6 • 10 6 photons per ray emitted from the X-ray source, in order to check the stability of the method with respect to noise, yielding images f noisy FDK and f noisy BPF .

B. Region-of-interest reconstruction

The truncated projections p T were simulated by applying a digital transaxial truncation to the previous set of 1440 noisy projections, corresponding to a cylindrical, centered field of view Ω whose edges cross the head skull. It is thus expected that empirical projection extrapolation methods would not perform as well. Such a reconstruction was computed using [START_REF] Hsieh | Methods and apparatus for truncation compensation[END_REF], yielding image f ROI FDK . For the un-truncated projections p F , we simulated two configurations. In the first configuration, we simulated an acquisition of 1440 projections corresponding to 10 5 photons per ray emitted from the X-ray source, yielding image f ROI(1) BPF . In the second configuration, we simulated an acquisition of 90 projections corresponding to 1.6•10 6 photons per ray, yielding image f ROI(2) BPF . In both cases, the dose ratio between the un-truncated and the truncated acquisitions is fixed to 1/16. The merging step was performed using the following weighting function:

η(x) = 1 2 1 -cos π • |x| -r Ω ∆r , (13)
where r Ω denotes the radius of the cylindrical ROI Ω , and ∆r is the transition zone radial width. In the following, ∆r was arbitrarily set to 5 voxels. The MRE over the intersection set Ω = Ω ∩Ω 0 was computed with respect to the un-truncated FDK reconstruction f noisy FDK .

V. RESULTS

A. Full-volume reconstruction

Noise-free reconstructed images are shown in Fig. 2. The images f FDK and f BPF are visually very similar. Both reconstructions are exact and identical in the fan-beam geometry of the midplane. However, f BPF is more sensitive to the conebeam incomplete sampling over a circular orbit (see the dark streaks near the temporal bones in the coronal and sagittal slices). Similar noise behavior occurs for both methods when reconstructing from noisy projections (images not shown). On average, the MRE inside Ω 0 is equal to 0.42% in the noisefree case and to 0.43% in the noisy case (Table II), the higher errors being located towards points with high cone angles. Full-volume ROI

Ω Ω 0 Ω ∩ Ω 0 f f * ∆ Ω (f, f * ) f BPF f noisy BPF f FDK f noisy FDK 0.42% 0.43% f ROI(1) BPF f ROI(2) BPF f noisy FDK f noisy FDK 0.44% 0.50%
Table II: Mean relative errors in region Ω.

B. Region-of-interest reconstruction

Results of ROI reconstruction are shown in Fig. 3. The first column shows the FDK reconstruction from the truncated projections only using empirical projection extrapolation. As expected, such extrapolation cannot perform well when highly contrasted structures such as bones lie at the edge of the field of view. The image f ROI FDK suffers from a shift in gray values and from low-frequency non-uniformities that prevent from using a narrow window display.

Results from our reconstruction method are shown in the second and third columns of Fig. 3. Both configurations yield images that are visually similar to the reference FDK reconstruction f noisy FDK (fourth column) inside the ROI Ω . Outside the ROI, image f

ROI(1) BPF

shows a very noisy reconstruction of the head, while image f

ROI(2) BPF

shows streaks characteristic of angular subsampling. However, neither the high noise contained in p F in the first configuration, nor the subsampling streaks of the second configuration propagate inside Ω . The values of the MRE inside region Ω = Ω ∩ Ω 0 with respect to f noisy FDK remain below 1%, at 0.44% for f ROI(1) BPF and 0.50% for f ROI(2) BPF (Table II).

VI. DISCUSSION

A new BPF formula was described for CBCT reconstruction with flat-panel detectors, that is exact in the fanbeam geometry and provides a different approximate reconstruction from FDK in the cone-beam geometry. It coincides with the parallel-beam Hilbert-transformed differentiated backprojection method (DBP-HT) [START_REF] Noo | A two-step Hilbert transform method for 2D image reconstruction[END_REF], when letting (d, D) → (+∞, +∞) and K = 1: in this case, image b Θ becomes the parallel-beam DBP image, and filtration needs to be performed using finite Hilbert transform inversion. However, our approach differs from the fan-beam DBP-HT formula of [START_REF] Noo | A two-step Hilbert transform method for 2D image reconstruction[END_REF]. In the fan-beam DBP-HT, the same DBP image is computed from fan-beam projections through a parallel-to-fan-beam change of variables, which requires a dense angular sampling. Instead, we propose to compute an alternative, intrinsically fan-beam DBP image, so that the whole backprojection step translates into a view-wise algorithm. Moreover, when K > 1, filtration is performed in the Fourier domain and does not require any finite Hilbert transform inversion. The method is thus expected to work as good as FDK with coarser angular sampling; it is also adapted to non-ideal circular geometries using calibrated projection matrices. As with FDK, the reconstructed images suffer from cone-beam artifacts, however, we anticipate faster iterative BPF reconstructions to reduce them [START_REF] Langet | Compressed-sensing-based content-driven hierarchical reconstruction: Theory and application to C-arm cone-beam tomography[END_REF]. Finally, excellent ROI reconstruction was obtained with only 6% of dose increase and flexible acquisition designs in terms of dose per view and angular sampling.

(axial) (c) f ROI(2) BPF (axial) (d) f noisy FDK (axial) (e) f ROI FDK (coronal) (f) f ROI(1) BPF (coronal) (g) f ROI(2) BPF (coronal) (h) f noisy FDK (coronal) (i) f ROI FDK (sagittal) (j) f ROI (

  Let Θ = [0, 2π]. For θ ∈ Θ, we write θ = (cos θ, sin θ, 0) T and θ ⊥ = (-sin θ, cos θ, 0) T . The X-ray source is located at point ξ θ = -dθ, where d is the source-to-rotation-axis distance. The detector is located at a distance D from the X-ray source. It is a plane orthogonal to the line passing through the center of rotation and the source point ξ θ . A 3D point x ∈ R 3 A. Reshef (corresponding author: aymeric.reshef@ge.com) is with GE Healthcare, Buc, France, and LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France. C. Riddell and Y. Trousset are with GE Healthcare, Buc, France. S. Ladjal and I. Bloch are with LTCI, Télécom ParisTech, Université Paris-Saclay, France. This work was supported by the CIFRE grant No. 873/2014 from the French Association Nationale de la Recherche et de la Technologie (ANRT).

Fig. 1 :

 1 Fig. 1: Extended support (dashed rectangle) for filtering b Θ k . Lines colinear to α ⊥ k (arrow) crossing the circular field of view (black circle) are all compactly supported (shaded area).

Fig. 2 :

 2 Fig. 2: Noise-free, full-volume reconstructions. Display window: [10 HU, 60 HU].

Fig. 3 :

 3 Fig. 3: ROI reconstruction. The ROI Ω is delineated in orange. Display windows: [-450 HU, -250 HU] (first column), [10 HU, 60 HU] (second to fourth columns).


Raimundo Gonçalves De Oliveira Júnior

Christiane Adrielly Alves Ferraz

Jackson Roberto Guedes Da Silva Almeida

Raphaël Grougnet

Valérie Thiéry

Laurent Picot
email: laurent.picot@univ-lr.fr

Sensitization of tumor cells to chemotherapy by natural products: a systematic review of preclinical data and molecular mechanisms

Keywords: cancer, chemotherapy, chemosensitization, drug resistance, natural products

Purpose: Tumor cells are spontaneously or adaptively resistant to chemotherapeutic drugs, eventually leading to the selection of multiresistant cells responsible for tumor growth and metastasis. Chemosensitization of tumor cells to conventional drugs using non-toxic natural products is a recent and innovative strategy aiming to increase the cytotoxic efficiency of anticancer drugs, limit their toxic side effects and delay the appearance of acquired chemoresistance. This systematic review summarizes data obtained from preclinical studies reporting the use of natural products to sensitize tumor cells to chemotherapeutic agents. It also details the cellular and molecular mechanisms involved in chemosensitization.

Design: Search terms were combined and used to retrieve English language reports in PubMed, Science Direct and Scopus databases, published until October 2017. All articles were carefully analyzed and data extraction was conducted through standardized forms. Methodological quality assessment of in vivo studies was also performed.

Results: From a total of 669 articles surveyed, 104 met the inclusion criteria established. The main studied compounds as chemosensitizers were phenolic derivatives (26.9%) and flavonoids (17.3%). Most reports were authored by researchers from China (33.7%) and USA (26.9%). A large number of articles were published from 2011 to 2015 (50.0%), suggesting that the use of natural products as chemosensitizers is a recent issue. In vivo studies were conducted mainly using xenograft models, which were considered of moderate methodological quality.

Conclusion:

Several natural products, belonging to diverse chemical families, are potent chemosentisizers in tumor cells enhancing the cytotoxicity of conventional drugs.

These molecules usually have a pleiotropic effect on different molecular targets, acting on several cellular and molecular processes with low selectivity. All studied molecules were obtained from terrestrial plants and major developments should arise from future studies, considering the chemodiversity of molecules purified from other terrestrial taxa and marine organisms.

Introduction

Cancer is one of the most impactful diseases of the 21 st century, affecting populations of diverse social, ethnic and economic characteristics. Although the genetic, epigenetic and pathophysiological mechanisms of cancer have been well described in recent years, cancer still represents the second cause of death in developed countries after heart disease [START_REF] You | Cancer Genetics and Epigenetics: Two Sides of the Same Coin?[END_REF][START_REF] Harris | The molecular pathology of cancer[END_REF].

To ensure their survival and proliferation, cancer cells acquire differentiated abilities compared to normal cells. In the development of malignant tumors, they may present constitutively active proto-oncogenes, which predisposes to carcinogenesis, maintaining proliferative signaling pathways active [START_REF] Hanahan | Hallmarks of cancer: the next generation[END_REF]. In addition, expression of tumor suppressor genes is usually decreased and the cell acquires sufficient autonomy to continue multiplying without the need for growth factors. Tumor cells also have replicative immortality mechanisms [START_REF] Shay | Role of telomeres and telomerase in cancer[END_REF] and greater resistance to cell death mediated by the regulation of anti and pro-apoptotic proteins [START_REF] Hassan | Apoptosis and Molecular Targeting Therapy in Cancer[END_REF]. For tumor maintenance and progression, they stimulate the production of angiogenic factors and modulate cellular metabolism in order to obtain more nutrients [START_REF] Hanahan | Hallmarks of cancer: the next generation[END_REF][START_REF] Fouad | Revisiting the hallmarks of cancer[END_REF].

In this sense, chemotherapy is one of the main alternatives for cancer treatment, using molecules capable of inhibiting proliferative signaling pathways, replicative immortality mechanisms and angiogenesis, besides inducing apoptosis of tumor cells [START_REF] Wong | Apoptosis in cancer: from pathogenesis to treatment[END_REF][START_REF] Zitvogel | Mechanism of action of conventional and targeted anticancer therapies: reinstating immunosurveillance[END_REF][START_REF] Otto | Cell cycle proteins as promising targets in cancer therapy[END_REF][START_REF] Galluzzi | Metabolic targets for cancer therapy[END_REF]. However, the efficacy of conventional chemotherapeutics has been limited by drug resistance mechanisms [START_REF] Housman | Drug resistance in cancer: an overview[END_REF]. Several studies have recognized that tumors exhibit a high degree of molecular and genetic heterogeneity, making them adapted to the usual cytotoxic agents. Unsuccessful treatments have been attributed to increased rates of drug efflux, alterations in drug metabolism (drug inhibition and degradation), cell death inhibition, epigenetic factor and mutations of drug targets (Figure 1). These mechanisms can act independently or in combination and through numerous signaling pathways [START_REF] Housman | Drug resistance in cancer: an overview[END_REF][START_REF] Cree | Molecular chess? Hallmarks of anti-cancer drug resistance[END_REF][START_REF] Holohan | Cancer drug resistance: an evolving paradigm[END_REF].

A wide variety of natural compounds has been reported for cancer therapy [START_REF] Shukla | Anticancer potential of medicinal plants and their phytochemicals: a review[END_REF][START_REF] Ruiz-Torres | An Updated Review on Marine Anticancer Compounds: The Use of Virtual Screening for the Discovery of Small-Molecule Cancer Drugs[END_REF]. Natural products are an inexhaustible source of molecules with unique structural models and innovative mechanisms of action. In fact, natural compounds can be used in a versatile manner, especially in cancer management: a) as chemotherapeutic agents [START_REF] Sukhdev | Lead Phytochemicals for Anticancer Drug Development[END_REF][START_REF] Calcabrini | Marine Sponge Natural Products with Anticancer Potential: An Updated Review[END_REF]; b) in cancer prevention (chemopreventive agents) [START_REF] Kotecha | Dietary phytochemicals and cancer chemoprevention: a review of the clinical evidence[END_REF][START_REF] Wang | Plants Against Cancer: A Review on Natural Phytochemicals in Preventing and Treating Cancers and Their Druggability[END_REF]; c) or improving the effectiveness of conventional chemotherapy (chemosensitizer agents) [START_REF] Vinod | Phytochemicals as chemosensitizers: from molecular mechanism to clinical significance[END_REF].

Most of the identified chemosensitizer natural compounds are phytochemicals, which are classified as phenolic derivatives, flavonoids, alkaloids, carotenoids, terpenoids, quinones, saponins and steroids depending on their molecular structure [START_REF] Vinod | Phytochemicals as chemosensitizers: from molecular mechanism to clinical significance[END_REF][START_REF] Dandawate | Novel strategies targeting cancer stem cells through phytochemicals and their analogs[END_REF]. In general, these molecules act by increasing the residence time of chemotherapeutics in tumor cells, inducing cell death by up-regulation of pro-apoptotic targets, promoting DNA damage or regulating the expression of altered and unaltered drug targets (Figure 1). When associated, these mechanisms enhance the cytotoxic effect of anticancer drugs, promoting a synergistic effect even in cells with acquired resistance [START_REF] Hussain | Natural Polyphenols in Cancer Chemoresistance[END_REF][START_REF] Jacquemin | Combining naturally occurring polyphenols with TNF-related apoptosis-inducing ligand: a promising approach to kill resistant cancer cells?[END_REF][START_REF] Gupta | Chemosensitization of tumors by resveratrol[END_REF].

The present systematic review was designed to summarize and analyze reports involving the use of natural products as chemosensitizers. Our focus was on preclinical studies (in vitro and in vivo approaches) in order to demonstrate to readers how these experimental models can contribute to the achievement of alternative strategies for cancer therapy.

Materials and methods

Search strategy

A systematic review was conducted through a literature search performed in October 2017 and included all reports published to date. This literature search was performed on specialized databases (PubMed, Science Direct and Scopus) using different combinations of the following keywords: chemosensitization, cancer, tumor, natural products, phytotherapy, medicinal plants, marine products and marine drugs. We did not contact investigators and we did not attempt to identify unpublished data. This systematic review was performed in accordance with the criteria described on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [START_REF] Moher | Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement[END_REF].

Study selection

Manuscript selection was based on the inclusion criteria: pre-clinical (in vitro and in vivo) studies involving the use of natural compounds/secondary metabolites as chemosensitizer agents of tumor cells to chemotherapeutic drugs, as well as pre-clinical (in vitro and in vivo) studies involving associations/combinatorial treatment between natural compounds/secondary metabolites and conventional chemotherapeutic drugs for antitumor therapy; only articles published in English and containing keywords in the title or abstract were selected. Other review articles, meta-analysis, abstracts, conferences, editorials/letters, case reports, conference proceedings, manuscripts without full text available or articles that did not meet the inclusion criteria were excluded from this systematic review. Studies involving extracts, fractions, synthetic or semisynthetic derivatives were also excluded.

For the selection of the manuscripts, two independent investigators (RGOJ and CAAF) first selected the articles according to the title, then to the abstract and finally through an analysis of the full-text publication. In cases of non-consensus, a third independent review was consulted (JRGSA). The selected articles were carefully reviewed with the purpose of identifying and excluding the reports that did not fit the criteria described above. Additional papers were included in this review after the analysis of all references from the selected articles.

Data were collected and examined by the authors using standardized forms. The information from the selected manuscripts on studied natural compounds, experimental models, associated chemotherapeutic agent, doses or concentrations, route of administration, cell lines, biochemical assays, histological assessments and molecular mechanisms studied were extracted and assessed.

Methodological quality assessment

The risk of bias and quality of the in vivo preclinical investigations were assessed using a checklist adapted from Hooijmans et al. [START_REF] Hooijmans | SYRCLE's risk of bias tool for animal studies[END_REF] and Siqueira-Lima et al. [START_REF] Siqueira-Lima | Natural products assessed in animal models for orofacial paina systematic review[END_REF]. This analysis allowed evaluating the methodological quality of the selected studies regarding the randomization of the treatment allocation, blinded drug administration, blinded outcome assessment and outcome measurements. Studies that reported randomization of animals, blinding and outcome measurements were considered of higher methodological quality.

Results

The primary search identified 669 reports (08 from PubMed, 562 from Science Direct and 99 from Scopus). However, 147 manuscripts were indexed in two or more databases and were considered only once, resulting in 552 original articles. After an initial screening of titles and abstract, 436 articles were excluded since they did not meet the inclusion criteria or presented extremely different themes from the proposal of this systematic review. Finally, 86 articles were fully analyzed and among these 39 were excluded. A detailed analysis of the list of references from all selected articles was performed, leading to the addition of 57 papers pertinent to this review and that met all inclusion criteria established after title, abstract and full text analysis. In total, 104 articles were included for data extraction. A flowchart illustrating the progressive study selection and numbers at each stage is shown in Figure 2. The articles selected for this review were categorically analyzed in relation to the country where the study was conducted, year of publication, natural compounds evaluated as chemosensitizers, cell lines and corresponding cancers. Table 1 summarizes the main informations contained in the selected in vitro and in vivo reports.

In general, the studies were conducted by research groups located in about 20 different countries. However, most of the investigations were authored by researchers from China (35 reports, 33.7%) and USA (28 reports, 26.9%). Regarding the annual evolution of the publications, a large number of articles were published from 2011 to 2015 (52 reports, 50.0%). Only in the last two years, 18 articles (17.3%) have been published, suggesting that the use of natural products as chemosensitizers is a recent issue that has attracted researchers' attention. 1.

Similarly, a wide variety of natural compounds have been reported as chemosensitizer agents. Most of the molecules studied belong to the class of phenolic derivatives (28 reports, 26.9%) and flavonoids (18 reports, 17.3%). Besides these, terpenoids, alkaloids, saponins, quinones and steroids were also considerably cited. These and other important outcomes are graphically presented in figure 3. Concerning to methodological quality, all in vivo studies were carefully analyzed through a standard checklist adapted for preclinical trials. As shown in Figure 5, all studies described the objectives, outcomes to be measured and main findings obtained.

In general, combinatorial treatments (chemosensitizer and conventional chemotherapeutic, doses, routes of administration and frequency of treatment) were properly reported. Most of the studies (31 reports, 83.8%) have also reported randomization of animal allocation. On the other hand, none of the included articles reported sample size calculations. In addition, no information on blinding strategy was provided.

Discussion

Cancer therapy is based on the use of one or more treatment strategies, including surgical removal of the tumor, radiotherapy, immunotherapy, phototherapy and chemotherapy. Although chemotherapy is recognized as one of the most effective strategies in the treatment of various types of cancer, the phenomenon of chemoresistance has become increasingly frequent, representing an obstacle to the use of anticancer drugs [START_REF] Baguley | Multiple drug resistance mechanisms in cancer[END_REF]. Tumor cells may develop a multidrug-resistant phenotype depending on the carcinogenic process per se, or even due to exposure to conventional chemotherapeutics [START_REF] Wu | Multi-drug resistance in cancer chemotherapeutics: mechanisms and lab approaches[END_REF]. In this sense, chemosensitization represents an alternative for overcoming chemoresistance. It consists in the use of molecules capable of improving the activity of another through the modulation of one or more mechanisms of resistance (Figure 1).

Historically, natural products have been shown to be more effective than conventional anticancer drugs because of their multi-target potential and low toxicity.

Such compounds are already widely known as promising anti-tumor and chemopreventive agents. Fortunately, several research groups have also investigated the role of natural products in sensitizing tumor cells. In this systematic review, most of the included studies were published after 2011 (Figure 3), indicating that the use of natural compounds as chemosensitizer agents is still recent.

Interestingly, China has been the country that most explores the use of natural products as chemosensitizers (Figure 3). In fact, Traditional Chinese Medicine (TCM) has contributed to the development of new pharmaceutical products based on plant extracts or even molecules with unique chemical structures and innovative mechanisms of action [START_REF] Wu | TCM-based new drug discovery and development in China[END_REF]. In cancer therapy, TCM has provided molecules with antitumor and chemopreventive properties [START_REF] Liu | Traditional Chinese medicine and cancer: History, present situation, and development[END_REF] and, more recently, chemosensitizing potential.

Shikonin, a natural naphthoquinone derived from the Chinese medicinal herb Lithospermum erythrorhizon, showed synergistic effect with gemcitabine, cisplatin and arsenic trioxide against pancreatic [START_REF] Wang | Shikonin suppresses tumor growth and synergizes with gemcitabine in a pancreatic cancer xenograft model: Involvement of NF-κB signaling pathway[END_REF], colon [START_REF] He | Enhancement of cisplatin-induced colon cancer cells apoptosis by shikonin, a natural inducer of ROS in vitro and in vivo[END_REF] and hepatocellular [START_REF] Song | Shikonin potentiates the effect of arsenic trioxide against human hepatocellular carcinoma in vitro and in vivo[END_REF] cancer, respectively. Song et al. [START_REF] Song | Synergistic effect of oxymatrine and angiogenesis inhibitor NM-3 on modulating apoptosis in human gastric cancer cells[END_REF] and Liu et al. [START_REF] Liu | Oxymatrine synergistically enhances the inhibitory effect of 5-fluorouracil on hepatocellular carcinoma in vitro and in vivo[END_REF] have also demonstrated the chemosensitizing effect of oxymatrine, one of the major components extracted from Sophora flavescens, widely used in TCM. In addition, several phenolic derivatives and flavonoids commonly found in Chinese medicinal plants were investigated as chemosensitizers, including resveratrol [START_REF] Fulda | Sensitization for anticancer drug-induced apoptosis by the chemopreventive agent resveratrol[END_REF], curcumin [START_REF] Hour | Curcumin enhances cytotoxicity of chemotherapeutic agents in prostate cancer cells by inducing p21(WAF1/CIP1) and C/EBPbeta expressions and suppressing NF-kappaB activation[END_REF], naringenin [START_REF] Zhang | Naringenin enhances the anti-tumor effect of doxorubicin through selectively inhibiting the activity of multidrug resistanceassociated proteins but not P-glycoprotein[END_REF] and myricetin [START_REF] Wang | Myricetin enhance chemosensitivity of 5fluorouracil on esophageal carcinoma in vitro and in vivo[END_REF].

Concerning to in vivo studies included, natural products were investigated using xenograft model. In this model, human tumor cells are transplanted via subcutaneous inoculation or into the organ type in which the tumor originated, into immunocompromised animals that do not reject human cells [START_REF] Richmond | Mouse xenograft models vs GEM models for human cancer therapeutics[END_REF]. Xenograft models have been used not only to determine the in vivo activity of new anticancer drugs, but also to determine drug dose, treatment schedules and routes of administration [START_REF] Jung | Human Tumor Xenograft Models for Preclinical Assessment of Anticancer Drug Development[END_REF]. In this context, in vivo reports included in this review were appropriately described. In addition to in vitro protocols, these models offer a wealth of information on the mechanisms of action involved in the chemosensitizing effect of natural products.

However, animal experiments should be well designed, efficiently executed and data must to be correctly analyzed and interpreted [START_REF] Festing | Guidelines for the design and statistical analysis of experiments using laboratory animals[END_REF]. Regarding the methodological quality assessment, we found that most of studies were conducted randomly, but no information on blinding was provided (Figure 5). In addition, no study reported sample size calculations. Although these parameters are often required in clinical trials, the need of randomization and blinding have been strongly recommended for preclinical protocols in order to minimize the risk of bias and avoid unexpected outcomes in clinical trials [START_REF] Hirst | The need for randomization in animal trials: an overview of systematic reviews[END_REF][START_REF] Karanicolas | Blinding: Who, what, when, why, how? Can[END_REF][START_REF] Aguilar-Nascimento | Fundamental steps in experimental design for animal studies[END_REF]. For this reason, we consider that the in vivo studies included in this review presented moderate methodological quality.

In general, phenolic derivatives and flavonoids were the most cited compounds (Figure 3). Curcumin, resveratrol and epigallocatechin-3-gallate have been extensively evaluated in combinatorial treatment with clinically used chemotherapeutics. These compounds are widely found in various medicinal plants and foods, such as red wine, fruits, vegetables and spices. The use of these molecules has been increasingly encouraged in cancer treatment mainly because of their low toxicity and immediate availability. Besides, phenolic compounds possess a strong antitumor activity by modulating different pathways involved in cell proliferation, invasion, metastasis and angiogenesis [START_REF] Wang | Plants Against Cancer: A Review on Natural Phytochemicals in Preventing and Treating Cancers and Their Druggability[END_REF][START_REF] Vinod | Phytochemicals as chemosensitizers: from molecular mechanism to clinical significance[END_REF][START_REF] Dandawate | Novel strategies targeting cancer stem cells through phytochemicals and their analogs[END_REF][START_REF] Hussain | Natural Polyphenols in Cancer Chemoresistance[END_REF]. Usually, when cancer cells were treated by natural products in combination with chemotherapeutic drugs, there was an additive cytotoxic effect caused by the activation of alternative signaling pathways that induce cell death, or even by increasing the residence time of the anticancer drug in the cell, improving its performance.

Next, we selected the natural compounds most cited in this review in order to better understand the different mechanisms of action involved in the sensitization of tumor cells. All findings described below were extracted from in vitro and in vivo included studies.

Curcumin

Curcumin (diferuloyl methane) is a naturally occurring phenolic pigment found in rhizomes of Curcuma longa Linn., commonly known as turmeric. Usually, curcumin content in turmeric varies from 1 to 5% and it is widely used in foods, as a cosmetic ingredient, and in some medicinal preparations [START_REF] Govindarajan | Turmeric: chemistry, technology, and quality[END_REF]. It has potent anti-inflammatory, anticancer and chemopreventive properties, but without exhibiting toxic effects in animal models even at high doses [START_REF] Chainani-Wu | Safety and anti-inflammatory activity of curcumin: a component of tumeric (Curcuma longa)[END_REF][START_REF] Chandran | A randomized, pilot study to assess the efficacy and safety of curcumin in patients with active rheumatoid arthritis[END_REF][START_REF] Gupta | Therapeutic Roles of Curcumin: Lessons Learned from Clinical Trials[END_REF]. Curcumin has demonstrated multiple anticancer effects, including inhibition of cell proliferation, induction of apoptosis, inhibition of angiogenesis and metastasis. Several mechanisms have been implicated in these effects, such as activation of pro-apoptotic proteins and inhibition of nuclear factor κB (NF-κB) and phosphatidylinositol (PI)3-kinase/Akt (PI3K/Akt) pathways, commonly activated in multiresistant tumor cells [START_REF] Vinod | Phytochemicals as chemosensitizers: from molecular mechanism to clinical significance[END_REF]. In figure 6, we show the main mechanisms involved in the chemosensitizing effect of curcumin.

In contrast to healthy cells, NF-κB pathway is constitutively active in the majority of solid and hematopoietic tumor cell lines. Additionally, chemotherapeutic agents and pro-inflammatory cytokines also activate NF-κB over time, contributing to chemoresistance of tumor cells. NF-κB is a tumorigenic transcription factor associated with evasion of apoptosis, sustained cell proliferation, invasion, metastasis and angiogenesis. It is a complex protein composed of different subunits (p50, p52, p65, RelB and c-Rel), mainly p50/p65. Under normal conditions, NF-κB is retained in the cytoplasm by its interaction with inhibitors of κB (IκBα, IκBβ or IκBε). However, IκB kinases (IKKs) are able to phosphorylate IκB portion, resulting in its subsequent ubiquitination and proteasome-mediated degradation, and consequently in the release of NF-κB, which then translocates to the nucleus [START_REF] Hartojo | Curcumin promotes apoptosis, increases chemosensitivity, and inhibits nuclear factor kappaB in esophageal adenocarcinoma[END_REF][START_REF] Karin | Nuclear factor-κB in cancer development and progression[END_REF]. In this review, we have identified that curcumin down-regulates NF-κB activation induced by chemotherapeutic agents, such as paclitaxel [START_REF] Aggarwal | Curcumin suppresses the paclitaxel-induced nuclear factor-kappaB pathway in breast cancer cells and inhibits lung metastasis of human breast cancer in nude mice[END_REF][START_REF] Bava | Sensitization of taxol-induced apoptosis by curcumin involves down-regulation of nuclear factor-??B and the serine/threonine kinase Akt and is independent of tubulin polymerization[END_REF][START_REF] Bava | Akt is upstream and MAPKs are downstream of NF-??B in paclitaxel-induced survival signaling events, which are down-regulated by curcumin contributing to their synergism[END_REF], 5-fluorouracil [START_REF] Shakibaei | Curcumin Enhances the Effect of Chemotherapy against Colorectal Cancer Cells by Inhibition of NF-κB and Src Protein Kinase Signaling Pathways[END_REF] and capecitabine [START_REF] Kunnumakkara | Curcumin sensitizes human colorectal cancer to capecitabine by modulation of cyclin D1, COX-2, MMP-9, VEGF and CXCR4 expression in an orthotopic mouse model[END_REF] in cervical, breast and colon cancer. Western blot and immunohistochemical analysis showed that curcumin inhibits NF-κB (p65 subunit), IκBα/β phosphorylation and IKK activation, resulting in synergistic antitumor effect when combined with conventional chemotherapeutic agents [START_REF] Hour | Curcumin enhances cytotoxicity of chemotherapeutic agents in prostate cancer cells by inducing p21(WAF1/CIP1) and C/EBPbeta expressions and suppressing NF-kappaB activation[END_REF][START_REF] Shakibaei | Curcumin potentiates antitumor activity of 5-fluorouracil in a 3D alginate tumor microenvironment of colorectal cancer[END_REF].

NF-κB can also be stimulated via the PI3K/Akt signaling pathway. Initially, exposure to cellular survival factors (growth factors, cytokines, etc.) hyperactivates PI3K, leading to high Akt activation, conferring cell survival and resistance to chemotherapy-induced apoptosis. In fact, Akt protects apoptosis by stimulating antiapoptotic proteins (e.g. survinin) and inhibiting pro-apoptotic signals (e.g. BAD).

Furthermore, Akt induces the release of NF-κB through activation of IKK [START_REF] Wang | Curcumin potentiates antitumor activity of L-asparaginase via inhibition of the AKT signaling pathway in acute lymphoblastic leukemia[END_REF][START_REF] Vivanco | The phosphatidylinositol 3-Kinase AKT pathway in human cancer[END_REF].

Once available, NF-κB upregulates the expression of multiple MDR genes in tumor cells that play a role in apoptosis, cell proliferation, invasion, metastasis and angiogenesis [START_REF] Kunnumakkara | Curcumin sensitizes human colorectal cancer to capecitabine by modulation of cyclin D1, COX-2, MMP-9, VEGF and CXCR4 expression in an orthotopic mouse model[END_REF]. In this sense, pharmacological investigations have demonstrated that curcumin potentiates anticancer effects of chemotherapeutics not only by inhibiting PI3K, Akt and NF-κB factors [START_REF] Bava | Sensitization of taxol-induced apoptosis by curcumin involves down-regulation of nuclear factor-??B and the serine/threonine kinase Akt and is independent of tubulin polymerization[END_REF][START_REF] Bava | Akt is upstream and MAPKs are downstream of NF-??B in paclitaxel-induced survival signaling events, which are down-regulated by curcumin contributing to their synergism[END_REF][START_REF] Wang | Curcumin potentiates antitumor activity of L-asparaginase via inhibition of the AKT signaling pathway in acute lymphoblastic leukemia[END_REF][START_REF] Shakibaei | Curcumin Enhances the Effect of Chemotherapy against Colorectal Cancer Cells by Inhibition of NF-κB and Src Protein Kinase Signaling Pathways[END_REF], but also the proteins expressed by the activation of these signaling pathways, including those involved in cell proliferation (e.g. Cyclin D1, COX-2, c-Myc), invasion (e.g. MMP-9), metastasis (e.g. CXCR4 and ICAM-1) and angiogenesis (e.g. VEGF) [START_REF] Kunnumakkara | Curcumin sensitizes human colorectal cancer to capecitabine by modulation of cyclin D1, COX-2, MMP-9, VEGF and CXCR4 expression in an orthotopic mouse model[END_REF][START_REF] Wang | Curcumin potentiates antitumor activity of L-asparaginase via inhibition of the AKT signaling pathway in acute lymphoblastic leukemia[END_REF][START_REF] Shakibaei | Curcumin potentiates antitumor activity of 5-fluorouracil in a 3D alginate tumor microenvironment of colorectal cancer[END_REF]. Finally, curcumin also acts synergistically with chemotherapeutics in the induction of apoptosis through stimulation of pro-apoptotic (e.g. BAD, BID, BIM, BAX, caspases 3, 8 and 9) proteins and inhibition of anti-apoptotic proteins (e.g. Bcl-2, Bcl-xL and survinin) [START_REF] Kunnumakkara | Curcumin sensitizes human colorectal cancer to capecitabine by modulation of cyclin D1, COX-2, MMP-9, VEGF and CXCR4 expression in an orthotopic mouse model[END_REF][START_REF] Bava | Akt is upstream and MAPKs are downstream of NF-??B in paclitaxel-induced survival signaling events, which are down-regulated by curcumin contributing to their synergism[END_REF][START_REF] Qian | Curcumin enhanced adriamycin-induced human liver-derived Hepatoma G2 cell death through activation of mitochondriamediated apoptosis and autophagy[END_REF].

MDRs may also involve efflux pumps that reduce the residence time of chemotherapeutic drugs in cancer cells. Anuchapreeda et al. [START_REF] Anuchapreeda | Modulation of Pglycoprotein expression and function by curcumin in multidrug-resistant human KB cells[END_REF] have investigated the role of curcumin in P-glycoprotein (Pgp) expression. Pgp, also known as multidrug resistance protein, is an important transmembrane protein that pumps many foreign drugs out of cells. Many synthetic Pgp modulators successfully reverse the MDR phenotype in vitro. On the other hand, the use of these compounds has been discouraged due to their toxicity profile observed in animal models and clinical trials. In this review, Pgp expression was found to be decreased by 11, 31, 60 and 64% in response to 1, 2, 3 and 4 days of treatment with 25 µM curcumin, respectively, enhancing sensitivity of KB-V1 cells (cervical cancer) to vinblastine [START_REF] Anuchapreeda | Modulation of Pglycoprotein expression and function by curcumin in multidrug-resistant human KB cells[END_REF]. Since curcumin is considered a safe natural product, it has served as a prototype for obtaining new Pgp-modulating drugs [START_REF] Ooko | Modulation of P-glycoprotein activity by novel synthetic curcumin derivatives in sensitive and multidrug-resistant T-cell acute lymphoblastic leukemia cell lines[END_REF]. properties. Resveratrol has presented an ability to target multiple signaling pathways implicated in tumor cell survival, inflammation, invasion, metastasis and angiogenesis [START_REF] Varoni | Anticancer Molecular Mechanisms of Resveratrol[END_REF][START_REF] Whitlock | The anticancer effects of resveratrol -Modulation of transcription factors[END_REF]. Several studies showed its antitumor activity in human cancer from different origin, including skin, breast, prostate, liver, pancreas, colon, lung and stomach [START_REF] Amiri | Synergistic anti-proliferative effect of resveratrol and etoposide on human hepatocellular and colon cancer cell lines[END_REF][START_REF] Aluyen | Resveratrol: potential as anticancer agent[END_REF]. In recent years, resveratrol has been evaluated not only as a chemopreventive or chemotherapeutic agent, but also as a chemosensitizer. In our review, in vitro and in vivo evidences demonstrated that resveratrol potentiates the antitumor effect of several chemotherapeutics, mainly doxorubicin [START_REF] Fulda | Sensitization for anticancer drug-induced apoptosis by the chemopreventive agent resveratrol[END_REF][START_REF] Osman | Modulation of doxorubicin cytotoxicity by resveratrol in a human breast cancer cell line[END_REF][START_REF] Díaz-Chávez | Proteomic Profiling Reveals That Resveratrol Inhibits HSP27 Expression and Sensitizes Breast Cancer Cells to Doxorubicin Therapy[END_REF], 5-Fluorouracil [START_REF] Fulda | Sensitization for anticancer drug-induced apoptosis by the chemopreventive agent resveratrol[END_REF][START_REF] Wu | Effect of resveratrol and in combination with 5-FU on murine liver cancer[END_REF][START_REF] Buhrmann | Resveratrol induces chemosensitization to 5-fluorouracil through up-regulation of intercellular junctions, Epithelial-to-mesenchymal transition and apoptosis in colorectal cancer[END_REF], etoposide [START_REF] Amiri | Synergistic anti-proliferative effect of resveratrol and etoposide on human hepatocellular and colon cancer cell lines[END_REF] and gemcitabine [START_REF] Harikumar | Resveratrol, a multitargeted agent, can enhance antitumor activity of gemcitabine in vitro and in orthotopic mouse model of human pancreatic cancer[END_REF].

Similar to curcumin, resveratrol sensitizes tumor cells by inhibiting the NF-κB signaling pathway [START_REF] Buhrmann | Resveratrol induces chemosensitization to 5-fluorouracil through up-regulation of intercellular junctions, Epithelial-to-mesenchymal transition and apoptosis in colorectal cancer[END_REF], as shown in figure 7. In addition, this phenolic derivative modulates the expression of MDR genes by down-regulating targets related to cell proliferation (e.g. cyclin D1, COX-2 and c-Myc), invasion (e.g. MMP-9), metastasis (e.g. CXCR4 and ICAM-1) and angiogenesis (e.g. VEGF) [START_REF] Harikumar | Resveratrol, a multitargeted agent, can enhance antitumor activity of gemcitabine in vitro and in orthotopic mouse model of human pancreatic cancer[END_REF][START_REF] Buhrmann | Resveratrol induces chemosensitization to 5-fluorouracil through up-regulation of intercellular junctions, Epithelial-to-mesenchymal transition and apoptosis in colorectal cancer[END_REF]. Resveratrol also enhances the cytotoxicity of chemotherapeutics through the induction of apoptosis by regulating the expression of pro (e.g. p53, caspases 3 and 8) and anti-apoptotic (e.g.

Bcl-2, Bcl-xL, XIAP and survinin) mediators in tumor cells [START_REF] Fulda | Sensitization for anticancer drug-induced apoptosis by the chemopreventive agent resveratrol[END_REF][START_REF] Harikumar | Resveratrol, a multitargeted agent, can enhance antitumor activity of gemcitabine in vitro and in orthotopic mouse model of human pancreatic cancer[END_REF][START_REF] Amiri | Synergistic anti-proliferative effect of resveratrol and etoposide on human hepatocellular and colon cancer cell lines[END_REF][START_REF] Buhrmann | Resveratrol induces chemosensitization to 5-fluorouracil through up-regulation of intercellular junctions, Epithelial-to-mesenchymal transition and apoptosis in colorectal cancer[END_REF].

Díaz-Chávez et al. [START_REF] Díaz-Chávez | Proteomic Profiling Reveals That Resveratrol Inhibits HSP27 Expression and Sensitizes Breast Cancer Cells to Doxorubicin Therapy[END_REF] showed that resveratrol sensitizes breast cancer cells to doxorubicin therapy by inhibiting HSP27 expression. HSP27 is present in several cell types, located mainly in the cytosol, but also in the perinuclear region, endoplasmic reticulum and nucleus. It is usually overexpressed during different stages of cell development and differentiation. High HSP27 expression has been observed in several types of cancer, suggesting that it plays an important role in cell proliferation, metastasis and chemoresistance. HSP27 acts as an independent ATP chaperone by inhibiting protein aggregation and stabilizing partially denatured proteins. In apoptosis, it interacts with mitochondrial membranes, interfering with the activation of the cytochrome-c/Apaf-1 complex and consequently preventing the activation of procaspase 9 [START_REF] Acunzo | Hsp27 as a therapeutic target in cancers[END_REF].

Interestingly, resveratrol also enhances the efficacy of chemotherapeutics not only by interfering with intracellular signaling pathways, but also by modulating the expression of transmembrane proteins involved in cell proliferation and cytoskeleton stabilization. Buhrmann et al. [START_REF] Buhrmann | Resveratrol induces chemosensitization to 5-fluorouracil through up-regulation of intercellular junctions, Epithelial-to-mesenchymal transition and apoptosis in colorectal cancer[END_REF] showed that resveratrol induces chemosensitization of colon cancer cells to 5-fluorouracil through up-regulation of intercellular junctions, epithelial-to-mesenchymal transition and apoptosis. In this investigation, resveratrol increased the expression of adhesion molecules, such as E-cadherin and claudin-2 (also involved in tight junctions), ensuring greater cell adhesion and consequently preventing mechanisms of cell proliferation. Furthermore, resveratrol significantly attenuated drug resistance by inhibiting epithelial-mesenchymal transition factors, such as vimentin.

This protein is attached to the nucleus, endoplasmic reticulum and mitochondria, laterally or terminally. The vimentin filaments are associated with the nuclear and plasma membranes, maintaining the position of the nucleus and the mitotic spindle and guaranteeing flexibility to the cell. It is a component of the cytoskeleton that interacts closely with microtubules, ensuring their stabilization [START_REF] Satelli | Vimentin in cancer and its potential as a molecular target for cancer therapy[END_REF]. Once inhibited by resveratrol, vimentin disperses in aggregates, causing loss of cytoplasmic integrity and changes in cellular morphology (Figure 7). Epigallocatechin-3-gallate (EGCG) is a major flavonoid found in green tea (Camelia sinensis) that possesses a broad spectrum of pharmacological activities, including antiangiogenic [START_REF] Sakamoto | Effects of epigallocatechin-3gallate (EGCG) on A549 lung cancer tumor growth and angiogenesis[END_REF], anticarcinogenic [START_REF] Fujiki | Anticarcinogenic effects of (-)epigallocatechin gallate[END_REF], antimetastatic [START_REF] Braicu | Epigallocatechin-3-Gallate (EGCG) inhibits cell proliferation and migratory behaviour of triple negative breast cancer cells[END_REF][START_REF] Shankar | EGCG inhibits growth, invasion, angiogenesis and metastasis of pancreatic cancer[END_REF] and chemopreventive effects [START_REF] Lambert | Mechanisms of cancer prevention by tea constituents[END_REF]. These properties are attributed to its antioxidant potential, cell signaling modulation, apoptosis induction, cell cycle arrest and inhibition of different MMPs (matrix metalloproteinases). In recent years, ECGC has been shown to be effective in sensitizing tumor cells to conventional chemotherapy. In fact, EGCG potentiates the antitumor effect of TRAIL (TNFα-related apoptosis-inducing ligand)

[47], 4-MU (4-methylumbelliferone) [START_REF] García-Vilas | Screening of synergistic interactions of epigallocatechin-3-gallate with antiangiogenic and antitumor compounds[END_REF], taxane [START_REF] Stearns | Synergistic Effects of the Green Tea Extract Epigallocatechin-3-gallate and Taxane in Eradication of Malignant Human Prostate Tumors[END_REF], IL-1Ra (IL-1 receptor antagonist) [START_REF] Hönicke | Combined administration of EGCG and IL-1 receptor antagonist efficiently downregulates IL-1-induced tumorigenic factors in U-2 OS human osteosarcoma cells[END_REF], capecitabine [START_REF] Wu | Capecitabine combined with (-)-epigallocatechin-3gallate inhibits angiogenesis and tumor growth in nude mice with gastric cancer xenografts[END_REF], vorinostat [START_REF] Kwak | Synergistic Anticancer Effects of Vorinostat and Epigallocatechin-3-Gallate against HuCC-T1 Human Cholangiocarcinoma Cells[END_REF], cisplatin [START_REF] Shervington | The sensitization of glioma cells to cisplatin and tamoxifen by the use of catechin[END_REF], tamoxifen [START_REF] Chisholm | Tamoxifen and epigallocatechin gallate are synergistically cytotoxic to MDA-MB-231 human breast cancer cells[END_REF][START_REF] Shervington | The sensitization of glioma cells to cisplatin and tamoxifen by the use of catechin[END_REF],

docetaxel [START_REF] Wang | Sensitization to docetaxel in prostate cancer cells by green tea and quercetin[END_REF] and doxorubicin [START_REF] Stammler | Green tea catechins (EGCG and EGC) have modulating effects on the activity of doxorubicin in drug-resistant cell lines[END_REF] in various types of cancer, mainly breast [START_REF] Chisholm | Tamoxifen and epigallocatechin gallate are synergistically cytotoxic to MDA-MB-231 human breast cancer cells[END_REF][START_REF] García-Vilas | Screening of synergistic interactions of epigallocatechin-3-gallate with antiangiogenic and antitumor compounds[END_REF] and prostate cancer [START_REF] Siddiqui | Green tea polyphenol EGCG sensitizes human prostate carcinoma LNCaP cells to TRAIL-mediated apoptosis and synergistically inhibits biomarkers associated with angiogenesis and metastasis[END_REF][START_REF] Stearns | Synergistic Effects of the Green Tea Extract Epigallocatechin-3-gallate and Taxane in Eradication of Malignant Human Prostate Tumors[END_REF][START_REF] Wang | Sensitization to docetaxel in prostate cancer cells by green tea and quercetin[END_REF].

In vitro and in vivo assays have demonstrated that EGCG enhances the antitumor effect of other drugs by inducing apoptosis. In general, EGCG up-regulates apoptotic proteins (e.g. BAD, BAK, BAX, caspases 3, 6, 7, 8 and 9) and down-regulates antiapoptotic factors (e.g. Bcl-2, Bcl-xL, XIAP, CIAP-1, survinin and Smac/Diablo) [START_REF] Siddiqui | Green tea polyphenol EGCG sensitizes human prostate carcinoma LNCaP cells to TRAIL-mediated apoptosis and synergistically inhibits biomarkers associated with angiogenesis and metastasis[END_REF][START_REF] Kwak | Synergistic Anticancer Effects of Vorinostat and Epigallocatechin-3-Gallate against HuCC-T1 Human Cholangiocarcinoma Cells[END_REF][START_REF] Wang | Sensitization to docetaxel in prostate cancer cells by green tea and quercetin[END_REF]. EGCG also induces the expression of genes that are directly associated with cell cycle arrest and apoptosis, such as p53, p73 and p21 [START_REF] Stearns | Synergistic Effects of the Green Tea Extract Epigallocatechin-3-gallate and Taxane in Eradication of Malignant Human Prostate Tumors[END_REF].

Several studies have demonstrated that EGCG synergistically inhibits biomarkers associated with angiogenesis (e.g. VEGF, angiopoietin 1 and 2), invasion and metastasis (MMP-2, 3, and 9) [START_REF] Siddiqui | Green tea polyphenol EGCG sensitizes human prostate carcinoma LNCaP cells to TRAIL-mediated apoptosis and synergistically inhibits biomarkers associated with angiogenesis and metastasis[END_REF][START_REF] Hönicke | Combined administration of EGCG and IL-1 receptor antagonist efficiently downregulates IL-1-induced tumorigenic factors in U-2 OS human osteosarcoma cells[END_REF][START_REF] Wu | Capecitabine combined with (-)-epigallocatechin-3gallate inhibits angiogenesis and tumor growth in nude mice with gastric cancer xenografts[END_REF][START_REF] Kwak | Synergistic Anticancer Effects of Vorinostat and Epigallocatechin-3-Gallate against HuCC-T1 Human Cholangiocarcinoma Cells[END_REF], improving the performance of chemotherapy in reducing tumor weight and/or volume in xenograft models [START_REF] Wu | Capecitabine combined with (-)-epigallocatechin-3gallate inhibits angiogenesis and tumor growth in nude mice with gastric cancer xenografts[END_REF].

Although inhibition of the NF-κB pathway does not appear to be directly involved in the mechanism of EGCG-induced tumor cell sensitization, this flavonoid inhibits the Akt pathway, indirectly resulting in lower expression of factors associated with cell proliferation, invasion, metastasis, angiogenesis, and apoptosis. In addition, Wang et al. [START_REF] Wang | Sensitization to docetaxel in prostate cancer cells by green tea and quercetin[END_REF] showed that EGCG combined with quercetin inhibits STAT3 (signal transducer and activator of transcription Considering that chemosensitization of cancer cells by natural products is a recent strategy and that only few resources have been explored at the moment, this research field should be expanding rapidly in the coming years and provide efficient alternatives to manage tumor chemoresistance.

Figure 1 .

 1 Figure 1. General drug resistance mechanisms implicated in cancer therapy and possibilities of intervention of natural products (NP) as chemosensitizer agents.

Figure 2 .

 2 Figure 2. Flowchart detailing literature search according to PRISMA statement [25].

Figure 3 .

 3 Figure 3. Distribution of the selected studies by country (A), year of publication (B), type of cancer studied (C) and chemical class of natural product evaluated as chemosensitizer (D).

Figure 4 .

 4 Figure 4.

Figure 4 .Figure 5 .

 45 Figure 4. Chemical structure of the major natural compounds evaluated as chemosensitizer agents (in vitro and in vivo evidences).

Figure 6 .

 6 Figure 6. Molecular mechanisms of curcumin-mediated chemosensitization. Curcumin modulates signaling pathways involved in apoptosis, cell proliferation, invasion, metastasis and angiogenesis

Figure 7 .

 7 Figure 7. Molecular mechanisms of resveratrol-mediated chemosensitization. Resveratrol interferes in the expression of adhesion molecules and in the stability of the cell cycle (A), and modulates signaling pathways involved in apoptosis, cell proliferation, invasion, metastasis and angiogenesis (B).

  3) expression, contributing to sensitization of prostate cancer cells to docetaxel. In the same study, the authors also demonstrated the potential of these flavonoids to block MRP1 (multidrug resistance-associated protein 1), increasing the residence time of docetaxel in tumor cells. All mechanisms involved in the sensitization of tumor cells by EGCG are summarized in figure 8.

Figure 8 .

 8 Figure 8. Molecular mechanisms of epigallocatechin-3-gallate (EGCG)-mediated chemosensitization. EGCG modulates signaling pathways involved in apoptosis, cell proliferation, invasion, metastasis and angiogenesis

Table 1 .

 1 General characteristics of included studies (in vitro and in vivo reports).

Authors, year, country Model Chemosensitizer Combined conventional drug Tumor cell line Cancer

  Combinatorial therapy (natural compounds and conventional chemotherapeutic) were used in various types of cancer. Breast and colon cancer were the most cited (16 reports each), followed by leukemia and associate cancers, lung, pancreatic, prostate and cervical cancer. Concerning the conventional anticancer drugs mentioned, about 40 different chemotherapeutic agents have been reported in combination with one or more natural molecules, varying according to the type of cancer studied, as shown in Table

	(2009) [72], USA (2013) [82], [126], China	in vivo			SW620 HCT116+ch3 AsPC-1
	Liu et al. (2015a) Dhanalakshmi et al. Kwak et al. (2013) Anuchapreeda et al. Germany Quinones Saponins Yuan et al. (2017) Ben-Eltriki et al.	In vitro and In vitro In vitro In vitro In vitro and In vitro	Oxymatrine Silibinin Epigallocatechin-3-Curcumin Ginsenoside Rg3 20(S)-protopanaxadiol	5FU CIP and CAP VOR VBL PTX CAL	Hep-G2 and SMMC-DU145 HuCC-T1 KB-V1 MDA-MB-231, LNCaP and C4-2	Hepatocellular carcinoma Prostate cancer Cholangiocarcinoma Cervical cancer Breast cancer Prostate cancer
	[36], China (2003) [44], USA [54], South Korea (2002) [63], Yu et al. (2009) [73], [109], China (2016) [118], Butturini et al.	in vivo In vitro in vivo In vitro	gallate Curcumin Cynaropicrin	FOLFOX CIP and DTX	7721 HCT116 and HT29 THP-1	Colon cancer Monocytic leukemia
	Thailand USA Carlson et al. (2014) Jafri et al. (2010) Choi et al. (2003) Canada (2013) [127], Italy	In vitro In vitro and In vitro	Curcumin + resveratrol DOX Thymoquinone CIP Protopanaxatriol DOX	SKOV-3 NCI-H460 and NCI-AML-2/D100 and AML-MDA-MB-453 and BT-	Ovarian cancer Lung cancer Acute myeloid leukemia
	Doddapaneni et al. Chisholm et al. Suzuki et al. (2014) [83], USA [91], USA [100], South Korea Alkaloids (2016) [37], USA (2004) [45], New [55], USA Hour et al. (2002) Hartojo et al. (2010) Terpenoids Liu et al. (2013)	In vitro In vitro In vitro and in vivo in vivo In vitro In vitro In vitro and	Noscapine Epigallocatechin-3-Genistein gallate Curcumin Curcumin Lupeol	DTX TOF 5FU DOX, 5FU and 5FU and CIP S14161	MDA-MB231 MDA-MB-231 MIA PaCa-2 H146 2/DX100 549 PC-3 and DU145 Flo-1 and OE33 HepG2 and SMMC7721 Hepatocellular carcinoma Breast cancer Breast cancer Pancreatic cancer Prostate cancer Esophageal adenocarcinoma
	Song et al. (2007) [28], China Zhao et al. (2016) [38], China Zealand Peng et al. (2007) Wang et al. (2014a) [56], China [64], China Fulda and Debatin [74], USA Bava et al. (2011) Qian et al. (2014) Li et al. (2010) [92], Singapore Kim et al. (2010) [101], South Korea Steroids Holland et al. (2006) [128], China [84], China Lee et al. (2009) [119], Australia Bamodu et al. (2015)	In vitro and in vivo In vitro In vitro In vitro and in vivo In vitro In vitro In vitro In vitro In vitro In vitro in vivo In vitro In vitro	Oxymatrine Berberine Deguelin Myricetin Resveratrol Curcumin Curcumin Thymoquinone Ginsenoside Rg3 Cannabidiol, Δ 9 -Withaferin A tetrahydrocannabinol Ovatodiolide	NM-3 CIP DOX and DTX 5FU PTX DOX, VP16, ACD, PTX ADM BTZ and TLD DTX VBL TRAIL DOX	SGC-7901, MKN-45 and MKN-74 MCF-7 SKBR-3, MCF-7 and EC9706 SHEP; U373MG; HeLa HepG2 U266 and RPMI 8226 LNCaP, PC-3 and DU145 CCRF-CEM and Caki, Huh7, SK-Hep1 CEM/VLB 100 MDA-MB-231, HS578T	Gastric cancer Breast cancer Breast cancer Esophageal carcinoma Neuroblastoma; malignant Cervical cancer Hepatocellular carcinoma Multiple myeloma Prostate cancer Acute T-lymphoblastoid Renal cancer leukemia Breast cancer
	Banerjee et al. (2009) [29], USA [46], USA (2004) [65], [75], India Buhrmann et al. Sandur et al. (2010) Ming et al. (2010) [110], South Korea [129], Taiwan Sung et al. (2010) [30], USA Carotenoids Rajendran et al. Siddiqui et al. (2008) [47], USA Abaza et al. (2015) [57], Kuwait Germany Sreekanth et al. (2011) [76], India (2015) [85], [93], USA [102], China Sieber et al. (2009) Chen et al. (2010) [120], Germany Liu et al. (2016) Germany Effenberger-Wang et al. (2012b) [111], South Africa [130], China Chougule et al. (2011) [31], USA Tong et al. (2012a) [32], China Qi et al. (2013) [33], USA Wang et al. (2013a) [34], China Guo et al. (2014) [35], China (2010) [39], Singapore Liu et al. (2015b) [40], China Zhang et al. (2016) [41], China Coumarins Kim et al. (2014) [42], South Korea Flavonoids Stammler and Volm (1997) [43], Germany Shervington et al. (2009) [48], UK Zhang et al. (2009) [49], China Jin et al. (2011) [50], South Korea Stearns and Wang (2011) [51], USA Hönicke et al. (2012) [52], Germany Wu et al. (2012) [53], China Wang et al. (2015) [58], USA García-Vilas et al. (2016) [59], Spain Krajnovic et al. (2016) [60], Serbia Naphthodianthrones Lin et al. (2016) [61], China Lin et al. (2017) [62], China Phenolic derivatives Wu et al. (2004) [66], China Aggarwal et al. (2005) [67], USA Bava et al. (2005) [68], India Li et al. (2007) [69], USA Chen et al. (2009) [70], Taiwan Harikumar et al. (2009) [71], USA Kunnumakkara et al. In vitro and Curcumin In vitro and in vivo 3,3-diindolylmethane In vitro Resveratrol In vitro Plumbagin In vitro β-aescin In vitro Noscapine In vitro γ-Tocotrienol In vitro Epigallocatechin-3-gallate In vitro Naringenin In vitro and in vivo Curcumin In vitro Artesunate In vitro Cucurbitacin B In vitro and Lupeol In vitro Thymoquinone In vitro and Escin in vivo In vitro and in vivo Noscapine In vitro Berberine In vitro and in vivo Noscapine In vitro and in vivo Sinomenine In vitro Berberine In vitro and in vivo α-carotene In vitro and in vivo β-carotene In vitro Bergamottin In vitro Epigallocatechin-3-gallate In vitro Epigallocatechin-3-gallate In vitro and in vivo Naringenin In vitro Naringenin In vitro and in vivo Epigallocatechin-3-gallate In vitro Epigallocatechin-3-gallate In vivo Epigallocatechin-3-gallate In vitro Epigallocatechin-3-gallate + quercetin In vitro Epigallocatechin-3-gallate In vitro and in vivo Isoxanthohumol In vitro Hypericin In vitro Hypericin In vivo Resveratrol In vitro and in vivo Curcumin In vitro Curcumin In vitro and in vivo Curcumin In vitro Tannic acid In vitro and in vivo Resveratrol Osman et al. (2012) [77], Saudi Arabia In vitro Resveratrol Saleh et al. (2012) [78], Egypt In vitro Curcumin Wang et al. (2012a) [79], China In vitro Curcumin Amiri et al. (2013) [80], Iran In vitro Resveratrol Díaz-Chávez et al. (2013) [81], Mexico In vitro Resveratrol Shakibaei et al. In vitro Curcumin Abaza et al. (2016) [88], Kuwait In vitro Methylferulate Ooko et al. (2016) [89], Germany In vitro Curcumin Tyagi et al. (2017) [117], China in vivo Wang et al. (2012c) In vitro Pristimerin [90], USA In vitro Calebin A [96], China He et al. (2016) [97], China In vitro and in vivo Shikonin Song et al. (2016) [98], China In vitro and Wang et al. (2017) [99], China In vitro Cryptotanshinone Liu et al. (2017) [108], China In vitro Paris saponin I Li et al. (2015) In vitro and Withaferin A [125], China (2015) [116], USA Tong et al. (2012b) In vitro Pseudolaric acid B in vivo Shikonin Lee et al. (2014) [107], South Korea In vitro Ginsenoside Rg3 El-Senduny et al. In vitro Cucurbitacin B [124], USA [115], USA in vivo Prasad et al. (2012) In vivo Ursolic acid Chang et al. (2014) Fong et al. (2012) In vitro and Withaferin A [106], China In vivo Ginsenoside Rg3 [114], USA Cohen et al. (2012) In vitro Withaferin A [123], Spain in vivo tetrahydrocannabinol Daqian et al. (2015) In vitro Chimaphilin [105], China in vivo Torres et al. (2011) In vitro and Cannabidiol and Δ 9 -Cote et al. (2015) Shakibaei et al. (2015) [87], Germany In vitro Curcumin [94], Germany Wang et al. (2014b) [95], China In vitro and in vivo Shikonin Yang et al. (2012) [104], China In vivo Ginsenoside Rg3 Wang et al. (2013b) In vitro and Steroidal saponin Lee et al. (2011) [113], USA In vitro and in vivo Cucurbitacin B Singapore (2011) [122], esulatin M Kannaiyan et al. In vitro Celastrol epoxywelwitschene and [131], Portugal and B, welwitschene, [112], USA [86], USA In vitro Resveratrol + quercetin DOX CIP, OXP and GCT PTX, MET, CYT, 5FU BTZ and TLD 5FU TNF, TLD, PTX and BTZ DOX and PTX TRAIL CPT, 5FU, DOX, CIP, ELP, ETP, CAP and CPA 5FU, CHM, MMS, TMD and NCD PTX RUX CIP 5FU DOX GCT GCT DOX TMZ, BCE and CIP 5FU RPM PTX 5FU BTZ and TLD DOX CIP and TOF DOX TRAIL TXN IL-1Ra CCT DTX 4MU PTX OXA OXP 5FU PTX PTX OXA ATO GCT CCT DOX ETP LAP ETP DOX 5FU CPT, 5FU, DOX, OXP, PTX, VBL, VCR, ETP, ELP, AMS, HHG and APD DOX GCT 5FU and TLD CIP PTX CPT OXP ABT-737*** ATO CIP CIP CCT DOX PTX + CIP SOF DOX and CIP TMZ 5FU GCT PTX DOX, 5FU, PTX MET TLD and BTZ Neidnicht and [103], China in vivo He et al. (2011) In vitro Lupeol TRAIL Schobert (2011) Iwanski et al. (2010) In vivo Cucurbitacin B GCT [121], China Reis et al. (2016) In vitro Euphowelwitschines A DOX	PANC-1, Colo-357 and PANC-28 MCF 10A PANC1; MCF7; LNCaP; HCT116, HCT116R, U266 and MM.1S SMMC-7721 and Hep3B and MCF-7 KBM-5 and U266 HepG2, C3A, SNU-387, LNCaP SW1116 and SW837; HTB26 and HTB132 Jurkat T-cell and Reh B-cell 3-MC* Ramos SW480 and SW480R SRB1, SRB12, SCC13 SGC7901 and BGC823 HL-60; 518A2; HT-29; L6, BxPC-3, PANC-1, and COLO160 A549 and H460 A549; HeLa; HepG2 U87MG Eca-109 SMMC7721 and HepG2 Hepatocellular carcinoma glioma; pancreatic cancer; Colon cancer Multiple myeloma Hepatocellular carcinoma Pancreatic cancer Hepatocellular carcinoma Prostate cancer Colon cancer; breast cancer breast cancer; prostate cancer; leukemia Cervical cancer B-lymphoma Cutaneous squamous Gastric carcinoma Leukemia; melanoma; colon Pancreatic cancer carcinoma Leukemia Lung cancer Lung cancer; cervical cancer; hepatocellular carcinoma Glioblastoma Esophageal carcinoma and PLC/PRF5 LLC** Lung cancer EC1 and Eca109 Esophageal carcinoma U266 Multiple myeloma SSW620-dox Colon cancer 1321N1; U87-MG Astrocytoma; glioblastoma A549; HepG2; MCF-7 and MCF-7/DOX Lung cancer; hepatocellular carcinoma; breast cancer A549 Lung cancer PC-3ML Prostate cancer U-2 OS Osteosarcoma BGC-823 Gastric cancer LAPC-4-AI and PC-3 Prostate cancer MDA-MB231 Breast cancer B16, A375 and B16F10 Melanoma HCT8 and HCT116 Colon cancer HCT116 and HCT8 Colon cancer H 22 Hepatocellular carcinoma MDA-MB-435 Breast cancer HeLa, SiHa, CaSki, and ME-180 Cervical cancer LoVo and Colo205 Colon cancer HL-60 Leukemia AsPC-1, MIA PaCa-2 and PANC1 Pancreatic cancer HCT116, HT29 and Colon cancer MCF-7 Breast cancer MCF-7; HeLa; HCT116; HepG2; U251 Breast cancer; cervical cancer; colon cancer; glioblastoma RS4;11, Reh and Jurkat Acute lymphoblastic leukemia HepG2; HCT116 Hepatocellular carcinoma; colon cancer MCF-7 Breast cancer HCT116 and Colon cancer SW1116 and SW837 CCRF-CEM and CEM/ADR5000 Acute lymphoblastic leukemia and SW1990 BxPC-3, PANC-1 and Pancreatic cancer KBM-5 Chronic myeloid leukemia HCT116, HT29 and CAL 27 and SCC 9 Tongue squamous cell carcinoma H1299; H520; H460; H446 lung large cell carcinoma PANC-1, MIAPaCa-2 Pancreatic cancer DU145 squamous cell carcinoma; LNCaP, PC-3 and Prostate cancer Lung adenocarcinoma; lung HepG2, Hep3B, Huh7 Hepatocellular carcinoma HTB5, J82, JON, A2780 and A2780CP Ovarian cancer Caco2 UMUC14 and T24 CaOV3 HCT116, HT29, and Colon cancer Bladder cancer SW620 Colon cancer A2780, A2780/CP70 and Ovarian cancer SW1088, and LN405 Eca-109 (U373), T98G (T98), Esophageal carcinoma BCPAP and SW1736 SW1783, U373MG Thyroid cancer Colon cancer U-2OS and U-2OSMR Osteosarcoma U87MG (U87), A172, Glioma hepatocellular carcinoma; HCT116 and HCT116R Colon cancer PANC-1, BxPC-3 and AsPC-1 Pancreatic cancer MCF-7 HepG2 and R-HepG2 and SJSA Hepatocellular carcinoma U2OS, G292, MG-63, 8226-LR-5 HT-161, HOS, SAOS-2, RPMI-8226 and RPMI-Osteosarcoma U266, RPMI 8226, Multiple myeloma Breast cancer SKOV-3 KB-V1; MCF-7 cancer; cervical cancer; SMMC7721 and HepG2 Hepatocellular carcinoma Ovarian cancer breast cancer CFPAC-1 and SW-1990 PANC-1 Pancreatic cancer L5178Y T-lymphoma

4-methylumbelliferone (4MU); 5-fluorouracil (5FU); adriamycin (ADM); amsacrine (AMS); actinomycin D (ACD); aphidicolin (APD); arsenic trioxide (ATO); bis-chloroethylnitrosourea (BCE); bortezomib (BTZ); calcitrol (CAL); camptothecin (CPT); capecitabine (CCT); carboplatin (CAP); cisplatin (CIP); cyclophosphamide (CPA); cycloheximide (CHM); cytarabine (CYT); docetaxel (DTX); doxorubicin (DOX); ellipticine (ELP); etopside (ETP); 5FU + oxilaplatin (FOLFOX); gemcitabine (GCT); homoharrigtonine (HHG); ifosfamide (IFO); IL-1 receptor antagonist (IL-Ra); L-asparaginase (LAP); methotrexate (MET); mimosine (MMS); nocodazole (NCD); oxaliplatin (OXP); paclitaxel (PTX); rapamycin (RPM); rituximab (RUX); sorafenib (SOF); tamoxifen (TOF); taxane (TXN): DTX + PTX; temozolamide (TMZ); thalidomide (TLD); thymidine (TMD); TNF-Related Apoptosis Inducing Ligand (TRAIL); vinblastine (VBL); vincristine (VCR); vorinostat (VOR). *3-Methylcholanthrene (3-MC)-induced tumorigenesis in Swiss albino mice. **LLC: mouse Lewis lung cancer cell line. ***ABT-737: Bcl-2 inhibitor.

Table 2 .

 2 In vivo studies involving natural compounds as chemosensitizer agents.

	Chemosensitizer	Dose (route) Combined	Dose (route) Model	Main outcomes (Cancer)	R B Reference
			drug		(animal/sex)
	3,3'-	5 mg/day	OXP	15 mg/kg	Xenograft	Synergistic decrease in	Y N Banerjee et al.
	diindolylmethane	(p.o.)		(i.v.)	(Mi/F)	tumor weight and	(2009) [29]
						appearance of nodal
						metastasis (pancreatic
						cancer)
	Cucurbitacin B	0.5 or 1	GCT	25 mg/kg/day	Xenograft	Synergistic decrease in	Y N Iwanski et al.
		mg/kg/day		(i.p.)	(Mi/F)	tumor volume and weight,	(2010) [112]
		(i.p.)				synergistic inhibition of
						metastasis (pancreatic
						cancer)
		0.5 or 1	MET	50 or 150	Xenograft	Synergistic decrease in	Y N Lee et al.
		mg/kg (i.p.)		mg/kg (i.p.)	(Mi/F)	tumor volume and weight	(2011) [113]
						(osteosarcoma)
	Curcumin	2% w/w/day	PTX	10	Xenograft	Synergistic inhibition of	Y N Aggarwal et al.
		(p.o.)		mg/kg/week	(Mi/F)	breast cancer metastasis to	(2005) [67]
				(i.p.)		the lung (breast cancer)
		1 g/kg/day	CCT	60	Xenograft	Synergistic decrease in	Y N Kunnumakkara
		(p.o.)		mg/kg/twice	(Mi/M)	tumor volume, synergistic	et al. (2009)
				weekly (p.o.)		inhibition of metastasis	[72]
						(colon cancer)
	Curcumin (liposomal	40	OXP	5	Xenograft	Synergistic decrease in	Y N Li et al. (2007)
	formulation)	mg/kg/thrice		mg/kg/thrice	(Mi/F)	tumor volume, synergistic	[69]

Combined drugs: 5-fluorouracil (5FU); arsenic trioxide (ATO); capecitabine (CCT); cisplatin (CIP); docetaxel (DTX); doxorubicin (DOX); gemcitabine (GCT); methotrexate (MET); oxaliplatin (OXP); paclitaxel (PTX); temozolamide (TMZ). Routes: i.g. (intragastric), i.t. (intratumoral), i.p. (intraperitoneal), i.v. (intravenous), p.o. (per oral), s.c. (subcutaneous). F: female. M: male. NR: not reported. Mi: mice. R: reporting of randomization. B: reporting of blinding.

ACKNOWLEDGEMENTS

We are grateful to the French Ministry of Research and Higher Education for funding RGOJ's PhD grant. We thank the French cancer league (Comité 17 de la Ligue Nationale contre le Cancer) for financial support and the "Cancéropôle Grand Ouest, axe Valorisation des produits de la mer en cancérologie" and Brazilian Society of Pharmacognosy for scientific support.

CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.


Damien M De Vienne
email: damien.de-vienne@univ-lyon1.fr

Tanglegrams are misleading for visual evaluation of tree congruence

Evolutionary Biologists are often faced with the need to compare phylogenetic trees. One popular method consists in visualizing the trees face to face with links connecting matching taxa. These tanglegrams are optimized beforehand so that the number of lines crossing (the entanglement) is minimal. This representation is implicitly justified by the expectation that the level of entanglement is correlated with the level of similarity (or congruence) between the trees compared. Using simulations, we show that this correlation is actually very weak, which should preclude the use of such technique for getting insight into the level of congruence between trees.

Tanglegram is a classical way of graphically representing correspondence between two labeled phylogenies, two hierarchical clusters, or any pair of tree-like structures. It is widely used in the host-parasite literature where host and parasite trees are represented face to face and links between leaves depict their interactions. The idea behind this visualization is straightforward: after having found the graphical layout that produces the minimum crossings of the lines linking both trees, the obtained tanglegram is expected to help in more clearly visualizing co-evolutionary relationships between species [START_REF] Matsen | Tanglegrams: A Reduction Tool for Mathematical Phylogenetics[END_REF]. Numerous studies focused on finding the best algorithm for reordering the leaves in order to produce the less entangled representation [START_REF] Bansal | Generalized Binary Tanglegrams: Algorithms and Applications[END_REF][START_REF] Böcker | A faster fixed-parameter approach to drawing binary tanglegrams[END_REF][START_REF] Fernau | Comparing trees via crossing minimization[END_REF]Venkatachalam et al. 2010 and references therein;[START_REF] Scornavacca | Tanglegrams for rooted phylogenetic trees and networks[END_REF]. But none ever questioned the real utility of such representation for getting insight into the level of topological similarity (or congruence) between the compared trees. There seems to be a common belief that the level of entanglement between two trees (the number of lines crossing) gives an approximation of their level of congruence, justifying the use of tanglegrams as a visual tool for "comparing" trees. However, this has never been explored. [START_REF] Planet | Tree disagreement: Measuring and testing incongruence in phylogenies[END_REF] clearly formulated this question: "It is not clear if more tangle actually translates to more incongruence." Here we address this question on simulated data and evaluate the validity of tanglegrams for getting insight into the level of (dis)similarity between trees. Pairs of random tree topologies with 20 leaves were generated in R using the rtree function of the ape package [START_REF] Paradis | APE: Analyses of Phylogenetics and Evolution in R language[END_REF], and sorted according to their topological distance (using the commonly used RF distance, [START_REF] Robinson | Comparison of Phylogenetic Trees[END_REF]. 1000 pairs of trees were kept for each possible value of RF and an optimized tanglegram (minimizing the number of lines crossing) was computed for each pair with the R package dendextend [START_REF] Galili | dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering[END_REF]. The optimization used, described in [START_REF] Dwyer | Optimal leaf ordering for two and a half dimensional phylogenetic tree visualisation[END_REF], consisted in solving repeatedly the One Tree Crossing Minimization problem (see [START_REF] Fernau | Comparing trees via crossing minimization[END_REF], each time switching the roles of the two trees. Figure 1A represents the observed level of entanglement between the trees (measured by the number of lines crossing in the tanglegram) as a function of their topological distance. While there is a tendency for increased entanglement at large topological distances, there is also a very strong overlap between the distributions of entanglement at different topological distances (Figure 1B). The same observations were made when using a different measure of congruence between the trees (the Icong index, de Vienne, Giraud, Martin 2007; data not shown). This shows that the level of entanglement is a poor estimate of the level of congruence between the trees compared. As an illustration, using the number of lines crossing in the tanglegram as a surrogate for testing if a pair of trees is more congruent than another one would give the wrong answer in almost one out of four cases (22.6%) when sampling from the population of tree pairs displayed in Figure 1.

Figure 1. A. Relationship between the topological distance (RF) between trees (x-axis) and the level of entanglement obtained after optimization (y-axis). Each dot represents one pair of trees, and dots are grouped and colored by their RF distance. 1000 pairs were generated for each possible RF distance. B. Distributions of RF distances for increasing entanglement (from 0 -no tangle -to 62). This is however not surprising a posteriori: two trees can have very different topologies but show no tangle at all in the tanglegram. In fact, the number of such cases for a tree with N+1 leaves is the number of unlabeled rooted binary trees with N internal nodes (which is the Catalan number C N , minus 1 to remove self comparison). So for a 20-leaf tree, there are 1,767,263,189 topologically distinct trees for which the tanglegram would show no crossing! As far as we know, this is the first analysis that explores the link between the level of entanglement in a tanglegram and the level of congruence between trees. Given the very weak predictive power of the former on the latter, we advocate that no conclusion should be drawn from the visual inspection of tanglegrams on the overall similarity between the trees analyzed. This could question the very use of tanglegrams, notably in the host-parasite literature.