Key proteins as potential effective biomarkers under Intraoperative Radiotherapy (IORT) in tumor bed of Breast Cancer patients

Background Radiotherapy (RT) is recommended to all patients undergoing Breast Conserving Surgery (BCS). Two strategies can be applied to irradiation, External Beam RT (EBRT) in addition, Intraoperative Radiation Therapy (IORT). The aim of this study was to introduce a protein biomarker panel related to molecular function under IORT. Methods Six Breast Cancer (BC) patients as a pilot study were treated by 12 Gy (Boost dose) and 21 Gy (Radical dose). Samples tissue included Margin before IORT (MB), and Margin 24 hours After IORT (MA24 h). Isobaric Tag for Relative and Absolute Quantitation (iTRAQ) was performed to study proteomic of IORT-treated tumor bed. Results We classified 110 differentially expressed proteins (DEPs) as a protein biomarker panel by mapping the annotated coding region sequences to the reference canonical pathways in the KEGG database. Conclusion Our findings indicate that the DEPs may be key proteins in IORT-treated tumor bed and may serve as potential Effective biomarkers under IORT. indicate that the DEPs may be key proteins in IORT-treated tumor bed and may serve as potential Effective biomarkers under IORT.

The second strategy is IORT which delivers electron beams (IOERT) and low kv-x-ray (IOXRT) [8]. By applying IORT during BCS, a high single dose is delivered to the site at the highest risk to fight subclinical tumor cell contamination with high precision owing to direct visualization [9]. Tumor bed has been reported as the highest risk of breast tumor recurrence [10,11]. As a result, local recurrence can be significantly reduced by using an extra dose to the tumor bed [12]. EBRT can be replaced by accelerating partial breast irradiation, including an IORT session, due to approved several advantages including; lack of gap between surgery and RT, avoidance of long treatment duration, reduced radiation-induced toxicity, tumor bed delineation under direct palpation and visual assessments and sparing non-targeted tissues surrounding the tumor bed [12,13]. In addition to the delayed time of RT after tumor excision, EBRT has harmful effects, including cardiac attack, appearance of second tumors, or stimulation of tumor cell growth by neo angiogenesis and hypoxia condition [14]. Notably, IORT can also help to save money, time, and CO 2 emissions in some patients, inhibiting transportation [15]. Although researchers have shown great interest in a single high-dose clinical approaches for different cancers, limited research has examined the biological basis of IORT [16].
According to specific eligibility criteria, IORT may be delivered either as an anticipated Boost, followed by conventional external RT to guarantee optimal dose delivery, or as an exclusive single radiation dose of Radical, corresponding to the administration of the entire sequence of conventional adjuvant RT [17,18].
Proteomics analysis can provide a new insight of interactome profile of the efficacy of IORT. To the best of our knowledge, there have been only imperfect efforts to characterize genome or proteome underlying physiological and biological mechanisms of IOeRT-treated tumor beds.
The present study represents iTRAQ based on the samples collected from the tumor bed before and 24 after post irradiation. Our findings highlight the involvement of specific proteins and pathways signatures related to different doses. The analyses of protein functions and signaling pathways of these DEPs reveal a molecular response to IORT, which may shed light to design a model for the individual-centered radiotherapy introduced.

Identification of differentially expressed proteins classification
We performed iTRAQ quantification after labeling of samples in three replicates (for both doses, and tissue; MB and MA24 h). In total, 1045410 spectrums were generated; also, 31572 peptides and 5860 proteins were identified with 1% FDR. DEPs for each comparisons of group/treatments analyzed. We found that there were 110 DEPs (37 up regulated, 73 down regulated) as single high doseindependent, which were common in both Boost and Radical doses ( Table 2).  (Fig. 3).

Discussion
RT is recommended to all patients undergoing BCS and some of them after mastectomy [22]. Despite the technological advances made in recent decades, RT plans still advise the same total dose per organ tumor, without taking into account the biological differences attributable to the different tumor subtypes [23]. By applying IORT during BCS, a high single dose is delivered to the site at the highest risk to fight subclinical tumor cell contamination with high precision owing to direct visualization [9].
Tumor bed has been reported as the highest risk of breast tumor recurrence [10,11]. As a result, local recurrence can be significantly reduced by using an extra dose to the tumor bed [12].
Although researchers have shown great interest in a single high-dose clinical approaches for different cancers, limited research has examined the biological and molecular basis of single high-dose effects, especially after IORT [24]. Studies have described that Post-surgery wound fluids (WF) induces an increase in the cell proliferation, migration in addition invasion in BC cell line [25][26][27]. However, the proteomics analysis of IORT-treated WF has shown an inhibition of cell proliferation and invasion in the BC cell line [28,29]. In addition, Cell and molecular traits observed in MCF-7 cells showed a typical senescent phenotype associated with cell proliferation arrest after treatment with IORT [30]. A worthy study was reported that the IORT-induced gene expression profiles and pathways appear to be BC cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to hormone receptor status [31].
In the context of this radiation treatment modality, this study aimed to describe the molecular response, in terms of DEPs and pathways, according to the different doses of IORT. However, this type of investigation would need to be extended to numerous panels of samples; thus, the present work should be considered as a pilot study. Here, we report substantial alterations in proteins expression levels after RT in both dose (Boost and Radical). Our proteomics approach using ITRAQ is a necessary first step for a biological study to describe the common molecular features associated with types of IORT.
We have analyzed 110 DEPs as single high dose-independent. Cytoscape network analysis represented the most important proteins (Fig. 1). All DEPs were classified into 10 protein categories ( Fig. 2), in which the most proteins related to RT are PLG, VWF and A2M (Fig. 2). The protein panel obtained corresponds to genes involved in cancer processes whose significantly downregulated after IORT-treated tumor bed [32]. The Plasminogen system produced by PLG (plasminogen) plays a crucial role in physiological in addition, pathological events related to tissue regeneration, wound healing, immune response, angiogenesis, invasion and metastasis. The PLG is significantly downregulated after IORT-treated tumor bed and highly enriched in Complement and coagulation cascades. In addition, Von Willebrand Factor Protein (VWF) is a major platelet ligand that has been widely used, as a biomarker in cancer growth and metastasis and associated inflammation [32], is significantly downregulated at 24 h post irradiation also highly enriched in Complement and coagulation cascades.
As shown in figuere 4, reffre to complement and coagulation cascades kegg pathway data base, enrichment associated with changes in these related key pathway to RT have been illustrated which indicates that two doses of IORT (Fig. 3) is able to reduce cell growth and cell proliferation.
It has been reported in previous stydies that 21-gene recurrence score (RS) were evaluated for prognostic and predictive benefit in IORT patients [33]   The iTRAQ labeling reagents were recovered to ambient temperature, and then transferred into and combined with proper samples. Peptide labeling was performed by iTRAQ Reagent 8-plex Kit according to the manufacturer's protocol. The labeled peptides with different reagents were combined and desalted.

Peptide 1st Dimensional Fractionation
The peptides were reconstituted with buffer A (5% ACN, 95% H 2 O, adjusted pH to 9.8 with ammonia) and separated by a Shimadzu LC-20AB HPLC system coupled with a high pH RP column (5-µm particles, Phenomenex). The peptides were separated at a flow rate of 1 ml/min with a 60 min gradient: 5% buffer B (5% H 2 O, 95% ACN, adjusted pH to 9.8 with ammonia) for 10 min, 5-35% buffer B for 40 min, 35-95% buffer B for 1 min, and 95% buffer B for 3 min. The gradient was then decreased to 5% B within 1 min before re-equilibrating with 5% buffer B for 5 min. Elution was monitored by measuring absorbance at 214 nm and the eluted peptides were pooled as 20 fractions in a concatenation mode and vacuum dried.

Peptide 2nd Dimensional Fractionation
Each fraction was resuspended in buffer A (2% ACN and 0.1% FA in water) and loaded onto a C18 trap column using an LC-20AD nano-HPLC instrument (Shimadzu, Kyoto, Japan) by the Autosampler. Then, the peptides were eluted from the trap column and separated by an analytical C18 column (inner diameter 75 µm⋅20 cm, 3 µm) packed in-house. The IQuant software was used to quantitatively analyze the labeled peptides with isobaric tags [20]. It integrates Mascot Percolator, a well performing machine learning method for re-scoring database search results, to provide reliable significance measures. In order to assess the confidence of peptides, the PSMs were pre-filtered at a PSM-level FDR of 1%. Then, based on the "simple principle" (The parsimony principle), identified peptide sequences were assembled into a set of confident proteins. In order to control the rate of false-positive at the protein level, a protein FDR at 1%, which is based on Picked protein FDR strategy will also be estimated after protein inference (Protein-level FDR < = 0.01) [21]. The protein quantification process includes the following steps: Protein identification, Tag  The deregulated densest protein-protein network (blue nodes: proteins, red nodes: proteins involved in crucial pathways) in 110 DEPs Reffre to complement and coagulation cascades kegg pathway