**Meet the editor**

Sherif Amr is currently a professor of Orthopedics and Traumatology at the Faculty of Medicine, Cairo University. He is an orthopedic surgeon, a hand surgeon, a microsurgeon, a peripheral nerve surgeon, and a brachial plexus surgeon. He was born on March 31, 1961. He received his MBBCh degree from the Cairo University in 1985, MSc degree in 1989, and MD (PhD) degree in 1996.

He further graduated from the Faculty of Law, Cairo University, with a bachelor's degree in Law in 2000. He worked as an intern at the Faculty of Medicine, Cairo University, 1986; an orthopedic resident at the Department of Orthopedics, Cairo University, 1978–1990; an assistant lecturer at the Department of Orthopedics, Cairo University, 1990–1996; a lecturer at the same department, 1996–2001; and an assistant professor, 2001–2006, before being appointed as a full professor in 2006. Additionally, he worked as a visiting resident at the Department of Plastic Surgery Medical School Hannover (MHH), Germany, and a research worker at the Department of Engineering Biomechanics, Technical University Hamburg/Harburg, 1997. He was the director of the animal research facility at the Faculty of Medicine, Cairo University from 2007 to 2011. His main research interests are microsurgery, hand surgery, surgery of peripheral nerves, brachial plexus surgery, neuroscience, and experimental orthopedic biomechanics.

Contents

**Preface VII**

**Section 2 Perforator Flaps 35**

**Transplantation 3**

and Michael O. Glocker

Chapter 2 **Experimental Rat Flap Models 25**

Goktekin Tenekeci

Masaki Fujioka

**Fractures 77** Masaki Fujioka

**Section 3 Special Situations 101**

Merdan Serin and Mehmet Bayramicli

Chapter 3 **Perforator Flaps: Principles and Techniques 37**

**Requiring Vascularization 51**

Chapter 1 **Plasma Cytokine and Growth Factor Profiling during Free Flap**

Chapter 4 **Application of Free Flow‐Through Anterolateral Thigh Flap for the Reconstruction of an Extremity Soft Tissue Defect**

Chapter 5 **Emergent or Early Flap Resurfacing Is Required for Bone-Exposing Wounds of Gustilo-Anderson IIIB and IIIC**

Chapter 6 **Reconstruction for Mandibular Implant Failure 103**

Shih-Heng Chen, Hao-Chih Tai, Tai-Ju Cheng, Hung-Chi Chen, An-Ta

Ko, Tyng-Luan Roan, Yo-Shen Chen and Yueh-Bih Tang

Juliane C. Finke, Jingzhi Yang, Marius Bredell, Uwe von Fritschen

**Section 1 Basic Science 1**

## Contents

#### **Preface XI**

**Section 1 Basic Science 1**


#### Chapter 7 **Hand Coverage 121**

Francisco Martinez Martinez, M. Llanos Guerrero Navarro, Juan Garcia Navarro, Alberto Gimenez Ros and Alba Izquierdo Robledano

Preface

The development of flap surgery parallels the increasing complexity of soft-tissue defects needing reconstruction. Random and pedicled flaps as well as free muscle and fasciocutane‐ ous flaps have helped to reconstruct single soft-tissue defects. The multiplicity of defects needing reconstruction and donor-site morbidity in addition to tailored reconstruction have called for a revision of flap concepts in favor of perforator flaps. Unfortunately, we are faced with increasingly complex reconstructive issues. New reconstructive techniques, such as the Ilizarov method, have made orthopedic reconstruction after high energy and complex trauma possible. Revision surgeries after tumor resection and plastic surgery have brought about soft-tissue defects associated with extensive fibrosis and necrosis. As a result, previously non‐ salvageable limbs have been salvaged. The reconstructive surgeons are faced with the follow‐ ing situations: multiple soft-tissue defects, extensive fibrosis, possibility of major vessel loss, and possibility of damage of several perforators. In this book, we address some of these prob‐ lems. In the basic science section, Dr. Glocker Michael demonstrates how plasma cytokine and growth factor profiling during free flap transplantation may aid in minimizing ischemia re‐ perfusion injury during free flap planning. Dr. Serin Merdan provides many versatile experi‐ mental rat flap models. The principles and techniques of perforator flaps are revised by Dr. Tenekeci Goktekin. Dr. Fujioka Masaki contributes two important articles on the applications of perforator flaps: the application of free flow-through anterolateral thigh flap for reconstruc‐ tion of soft-tissue defects requiring vascularization and emergent or early flap resurfacing for bone-exposing wounds of Gustilo-Anderson IIIB and C fractures. Special situations need a special consideration. Prof. Tang Yueh-Bih illustrates his experience in reconstructing bone and soft-tissue defects for mandibular implant failure. Dr. Martinez Martinez Francisco pro‐ vides a valuable review on hand flaps. Dr. Khater Ashraf demonstrates his experience using omental flaps in breast reconstruction. Hypospadias surgery has always been a challenge be‐ cause of difficult flap planning and subsequent necrosis and fibrosis. Dr. Calonge Wenceslao

**Sherif Amr**

Cairo University, Egypt

contributes an article on overview of hypospadias surgery.

#### Chapter 8 **Omental Flap in Breast Reconstruction 147** Ashraf Khater, Adel Fathi and Hosam Ghazy

Chapter 9 **An Overview of Hypospadias Surgery 163** Wenceslao M. Calonge and Gianluca Sapino

## Preface

Chapter 7 **Hand Coverage 121**

**VI** Contents

Robledano

Chapter 8 **Omental Flap in Breast Reconstruction 147**

Chapter 9 **An Overview of Hypospadias Surgery 163**

Ashraf Khater, Adel Fathi and Hosam Ghazy

Wenceslao M. Calonge and Gianluca Sapino

Francisco Martinez Martinez, M. Llanos Guerrero Navarro, Juan Garcia Navarro, Alberto Gimenez Ros and Alba Izquierdo

> The development of flap surgery parallels the increasing complexity of soft-tissue defects needing reconstruction. Random and pedicled flaps as well as free muscle and fasciocutane‐ ous flaps have helped to reconstruct single soft-tissue defects. The multiplicity of defects needing reconstruction and donor-site morbidity in addition to tailored reconstruction have called for a revision of flap concepts in favor of perforator flaps. Unfortunately, we are faced with increasingly complex reconstructive issues. New reconstructive techniques, such as the Ilizarov method, have made orthopedic reconstruction after high energy and complex trauma possible. Revision surgeries after tumor resection and plastic surgery have brought about soft-tissue defects associated with extensive fibrosis and necrosis. As a result, previously non‐ salvageable limbs have been salvaged. The reconstructive surgeons are faced with the follow‐ ing situations: multiple soft-tissue defects, extensive fibrosis, possibility of major vessel loss, and possibility of damage of several perforators. In this book, we address some of these prob‐ lems. In the basic science section, Dr. Glocker Michael demonstrates how plasma cytokine and growth factor profiling during free flap transplantation may aid in minimizing ischemia re‐ perfusion injury during free flap planning. Dr. Serin Merdan provides many versatile experi‐ mental rat flap models. The principles and techniques of perforator flaps are revised by Dr. Tenekeci Goktekin. Dr. Fujioka Masaki contributes two important articles on the applications of perforator flaps: the application of free flow-through anterolateral thigh flap for reconstruc‐ tion of soft-tissue defects requiring vascularization and emergent or early flap resurfacing for bone-exposing wounds of Gustilo-Anderson IIIB and C fractures. Special situations need a special consideration. Prof. Tang Yueh-Bih illustrates his experience in reconstructing bone and soft-tissue defects for mandibular implant failure. Dr. Martinez Martinez Francisco pro‐ vides a valuable review on hand flaps. Dr. Khater Ashraf demonstrates his experience using omental flaps in breast reconstruction. Hypospadias surgery has always been a challenge be‐ cause of difficult flap planning and subsequent necrosis and fibrosis. Dr. Calonge Wenceslao contributes an article on overview of hypospadias surgery.

> > **Sherif Amr** Cairo University, Egypt

**Section 1**

**Basic Science**

**Section 1**

## **Basic Science**

**Chapter 1**

**Provisional chapter**

**Plasma Cytokine and Growth Factor Profiling during**

Ischemia and reperfusion (I/R) is an unavoidable condition during free flap transplantation. Restoration of blood flow is usually associated with a profound inflammatory response. Cytokines and growth factors are the functional proteins which exert their specific influence on injury or repair during the healing period. Plasma concentrations of 18 cytokines and growth factor proteins (IL6, IL8, IP10, TNFα, MCP1, Fractalkine, GRO, bFGF, GMCSF, IFNg, MIP1a, VEGF, sCD40L, IL10, TGFα, IL1β, IL12P40, and TNFβ) have been analyzed with respect to I/R status during microsurgery tissue transplantation in both, artery and vein, from patients by multiplexed immunoassay. Both technical feasibility and biostatistics data analysis approaches were thoroughly assessed. It has been found that, from all investigated proteins, the venous plasma levels of IL6 significantly increased during the ischemia period and mostly sustained their high levels during reperfusion, while venous plasma levels of IL8 showed in general a significant increase in the ischemia period followed by a rapid decrease in the reperfusion period. In conclusion, these findings direct toward an active involvement of tissue-resting leukocytes which may become therapeutic targets for concomitant medication in flap surgery

**Plasma Cytokine and Growth Factor Profiling during** 

DOI: 10.5772/intechopen.70054

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

and reproduction in any medium, provided the original work is properly cited.

**Keywords:** IL6, IL8, multiplex analysis, microsurgery, free flap surgery, ischemia-reperfusion

Reconstructive microsurgery represents the most efficient approach to close large or complex tissue defects of the human body [1]. Microsurgical tissue transplantation, a standardized

**Free Flap Transplantation**

**Free Flap Transplantation**

http://dx.doi.org/10.5772/intechopen.70054

to improve wound healing.

**1. Introduction**

injury, reconstructive surgery, protein profiling

**Abstract**

Juliane C. Finke, Jingzhi Yang, Marius Bredell, Uwe von Fritschen and Michael O. Glocker

Juliane C. Finke, Jingzhi Yang, Marius Bredell, Uwe von Fritschen and Michael O. Glocker

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

**Provisional chapter**

## **Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation Free Flap Transplantation**

**Plasma Cytokine and Growth Factor Profiling during** 

DOI: 10.5772/intechopen.70054

Juliane C. Finke, Jingzhi Yang, Marius Bredell, Uwe von Fritschen and Michael O. Glocker Uwe von Fritschen and Michael O. Glocker Additional information is available at the end of the chapter

Juliane C. Finke, Jingzhi Yang, Marius Bredell,

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.70054

#### **Abstract**

Ischemia and reperfusion (I/R) is an unavoidable condition during free flap transplantation. Restoration of blood flow is usually associated with a profound inflammatory response. Cytokines and growth factors are the functional proteins which exert their specific influence on injury or repair during the healing period. Plasma concentrations of 18 cytokines and growth factor proteins (IL6, IL8, IP10, TNFα, MCP1, Fractalkine, GRO, bFGF, GMCSF, IFNg, MIP1a, VEGF, sCD40L, IL10, TGFα, IL1β, IL12P40, and TNFβ) have been analyzed with respect to I/R status during microsurgery tissue transplantation in both, artery and vein, from patients by multiplexed immunoassay. Both technical feasibility and biostatistics data analysis approaches were thoroughly assessed. It has been found that, from all investigated proteins, the venous plasma levels of IL6 significantly increased during the ischemia period and mostly sustained their high levels during reperfusion, while venous plasma levels of IL8 showed in general a significant increase in the ischemia period followed by a rapid decrease in the reperfusion period. In conclusion, these findings direct toward an active involvement of tissue-resting leukocytes which may become therapeutic targets for concomitant medication in flap surgery to improve wound healing.

**Keywords:** IL6, IL8, multiplex analysis, microsurgery, free flap surgery, ischemia-reperfusion injury, reconstructive surgery, protein profiling

#### **1. Introduction**

Reconstructive microsurgery represents the most efficient approach to close large or complex tissue defects of the human body [1]. Microsurgical tissue transplantation, a standardized

Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons

technique in plastic and reconstructive surgery, unavoidably involves a time of ischemia in which the transplanted tissue can be harmed [2]. Also inevitable is the ischemia-reperfusion injury (I/R injury) [3, 4], limiting tissue survival in any microsurgical tissue transplantation [5]. Minutes after the onset of ischemia, reversible changes appear in tissues [6]. Irreversible injury develops after 20–40 min of sustained ischemia in muscle cells [7]. Intracellular contents of necrotic cells initiate an inflammatory response and activate immune mechanisms. The main pathomechanisms of I/R injury involve the pathologic leukocyte-endothelium interaction [8, 9], production of reactive oxygen species [10, 11], and activation of the complement system [12] which can cause tissue damage [13] but also results in healing. The healing process starts immediately after injury and consists of three phases: inflammation, proliferation, and tissue remodeling [14]. Knowledge about pathophysiology of I/R injury is mostly based on animal models [5, 15]. There are just a few reports focusing on free human muscle tissue transfer [2, 16], and up to now data about molecular processes that occur during free flap tissue transfers of human skin or bone tissue are missing.

Since different tissues react in different ways to ischemia because of their specific metabolisms, I/R injury was studied in subgroups: the microvascular transfer of muscle flaps, fascio-cutaneous flaps, and osteo-cutaneous flaps. Assuming an involvement of tissue-resting leukocytes, intraoperative blood samples from 21 patients from artery and vein were collected at three different time points. To provide data on the protein concentration dynamics of cytokines and growth factors (CGFs), a multiplex bead array assay was applied because of the assay's high sensitivity, high throughput capability, and little sample consumption (only 25 μl plasma/serum) for analyzing numerous analytes in parallel [17, 18].

## **2. Results**

#### **2.1. Assay assessment, full analysis set, and per protocol set**

A study with 21 patients encompassed 10 female and 11 male adults with various flap transplants (**Table 1**). The osteo-cutaneous flaps (*n* = 9) were free fibula flaps for head and neck reconstructions in tumor diseases. Their ischemia times ranged from 90 to 220 min, in average 133 min. The muscle flaps (*n* = 6) were mostly latissimus dorsi muscle flaps (*n* = 4), one gracilis muscle flap, and one serratus anterior muscle flap. All muscle flaps were needed for lower limb reconstruction. Their ischemia times varied from 60 to 120 min, in average 78 min. All fasciocutaneous flaps (*n* = 6) were radialis flaps. They were used to cover defects in the head and neck areas in tumor diseases. Their ischemia times ranged from 60 to 150 min, in average 78 min.

Mean weights of the transplanted flaps for the osteo-cutaneous group, the muscle group, and the cutaneous group were 92.67 ± 25.63, 249.25 ± 38.26, and 36.25 ± 39.92 g, respectively.

and I/R injury and (ii) were matched with a commercially available bead-based immunoassay. From each of the patient samples, plasma concentrations of IL6, IL8, IP10, TNFα, MCP1, Fractalkine, GRO, bFGF, GMCSF, IFNg, MIP1a, VEGF, sCD40L, IL10, TGFα, IL1β, IL12P40, and TNFβ were simultaneously measured in duplicate. The raw data set of all 18 cytokines and growth factors of all samples encompassed 2088 data points which, after averaging and curation, were merged to the full analysis set (FAS) with 1044 protein concentration values

(data not shown).

n.d.: not determined.

**Table 1.** Patient information and clinical parameters.

**Free flap type**

Osteocutaneous

Fasciocutaneous

a

**Patient ID Gender Age (y) Skin island** 

Muscle 201 Male 60 – – Latissimus

202 Female 66 – – Latissimus

203 Male 56 – – Latissimus

204 Male 40 – – Serratus

206 Female 49 – – Latissimus

205 Male 62 – – Gracilis n.d.a 70

301 Female 26 5 × 4 – Radialis 14 80

 Female 51 13 × 11 – Radialis 96 150 Female 64 6 × 5 – Radialis 20 80 Male 69 6 × 5 – Radialis 15 100 Female 79 9 × 5 – Radialis n.d.a 60 Female 37 14 × 12 – Radialis n.d.a 60

**(cm2 )**

101 Male 62 9 × 6 5.5 Fibula 80 90

 Male 54 10 × 5 21 Fibula n.d.a 120 Male 55 n.d.a 20 Fibula n.d.a 220 Female 66 6.5 × 5 10.5 Fibula 110 95 Male 43 5 × 3 12 Fibula 72 150 Male 58 7 × 4 15 Fibula n.d.a 120 Female 57 6.5 × 5 8 Fibula 98 120 Female 67 6 × 4 12 Fibula 132 100 Female 70 7 × 5 13 Fibula 64 180

**Bone (cm) Transplant tissue**

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

dorsi

dorsi

dorsi

anterior

dorsi

**Weight (g) Ischemia (min)**

5

http://dx.doi.org/10.5772/intechopen.70054

272 65

198 60

284 75

n.d.a 80

243 120

From each of the patients, three blood samples were taken during surgery. Artery (*n* = 21) represented the blood protein composition at a starting point, for comparison. At time point Vein 1, 18 samples, and at time point Vein 2, 19 samples were taken (see Appendix). Proteins whose concentrations were to be analyzed (i) were selected according to their main functions inflammation, angiogenesis, and apoptosis upon study of literature with respect to ischemia


a n.d.: not determined.

technique in plastic and reconstructive surgery, unavoidably involves a time of ischemia in which the transplanted tissue can be harmed [2]. Also inevitable is the ischemia-reperfusion injury (I/R injury) [3, 4], limiting tissue survival in any microsurgical tissue transplantation [5]. Minutes after the onset of ischemia, reversible changes appear in tissues [6]. Irreversible injury develops after 20–40 min of sustained ischemia in muscle cells [7]. Intracellular contents of necrotic cells initiate an inflammatory response and activate immune mechanisms. The main pathomechanisms of I/R injury involve the pathologic leukocyte-endothelium interaction [8, 9], production of reactive oxygen species [10, 11], and activation of the complement system [12] which can cause tissue damage [13] but also results in healing. The healing process starts immediately after injury and consists of three phases: inflammation, proliferation, and tissue remodeling [14]. Knowledge about pathophysiology of I/R injury is mostly based on animal models [5, 15]. There are just a few reports focusing on free human muscle tissue transfer [2, 16], and up to now data about molecular processes that occur during free flap tis-

Since different tissues react in different ways to ischemia because of their specific metabolisms, I/R injury was studied in subgroups: the microvascular transfer of muscle flaps, fascio-cutaneous flaps, and osteo-cutaneous flaps. Assuming an involvement of tissue-resting leukocytes, intraoperative blood samples from 21 patients from artery and vein were collected at three different time points. To provide data on the protein concentration dynamics of cytokines and growth factors (CGFs), a multiplex bead array assay was applied because of the assay's high sensitivity, high throughput capability, and little sample consumption (only 25 μl

A study with 21 patients encompassed 10 female and 11 male adults with various flap transplants (**Table 1**). The osteo-cutaneous flaps (*n* = 9) were free fibula flaps for head and neck reconstructions in tumor diseases. Their ischemia times ranged from 90 to 220 min, in average 133 min. The muscle flaps (*n* = 6) were mostly latissimus dorsi muscle flaps (*n* = 4), one gracilis muscle flap, and one serratus anterior muscle flap. All muscle flaps were needed for lower limb reconstruction. Their ischemia times varied from 60 to 120 min, in average 78 min. All fasciocutaneous flaps (*n* = 6) were radialis flaps. They were used to cover defects in the head and neck areas in tumor diseases. Their ischemia times ranged from 60 to 150 min, in average 78 min. Mean weights of the transplanted flaps for the osteo-cutaneous group, the muscle group, and the cutaneous group were 92.67 ± 25.63, 249.25 ± 38.26, and 36.25 ± 39.92 g, respectively.

From each of the patients, three blood samples were taken during surgery. Artery (*n* = 21) represented the blood protein composition at a starting point, for comparison. At time point Vein 1, 18 samples, and at time point Vein 2, 19 samples were taken (see Appendix). Proteins whose concentrations were to be analyzed (i) were selected according to their main functions inflammation, angiogenesis, and apoptosis upon study of literature with respect to ischemia

sue transfers of human skin or bone tissue are missing.

**2. Results**

4 Issues in Flap Surgery

plasma/serum) for analyzing numerous analytes in parallel [17, 18].

**2.1. Assay assessment, full analysis set, and per protocol set**

**Table 1.** Patient information and clinical parameters.

and I/R injury and (ii) were matched with a commercially available bead-based immunoassay. From each of the patient samples, plasma concentrations of IL6, IL8, IP10, TNFα, MCP1, Fractalkine, GRO, bFGF, GMCSF, IFNg, MIP1a, VEGF, sCD40L, IL10, TGFα, IL1β, IL12P40, and TNFβ were simultaneously measured in duplicate. The raw data set of all 18 cytokines and growth factors of all samples encompassed 2088 data points which, after averaging and curation, were merged to the full analysis set (FAS) with 1044 protein concentration values (data not shown).

Data from the FAS were inspected for completeness and categorized into three groups based on the detection rates. Group I contained those CGFs for which plasma protein concentrations could be determined in over 80% of all samples. Group II included those CGFs for which plasma protein concentrations could be determined in over 60% but less than 80% of all samples. Group III contained proteins whose concentrations were determined in less than 60% of all samples and sCD40L which did not pass the QC test. Group I proteins were IL8, IP10, MCP1, TNFα, GRO, IL6, Fractalkine, bFGF, and GMCSF. Group II contained four proteins: IFNg, MIP1α, VEGF, and IL10. Five proteins were placed in group III: TGFα, IL1β, IL12P40, TNFβ, and sCD40L (**Table 2**). Group III proteins were not subjected to further data analysis. Hence, the per protocol set (PPS) consisted of just group I and II proteins (13 proteins in total) and contained a total of 754 data points.

Some of the determined average plasma protein concentrations in the analyzed samples matched well with reported reference concentrations (e.g., TNFα and bFGF), whereas others did not. Differences between the "reference concentrations" and the concentrations determined in the here described study could be caused by (i) using different assays, (ii) different specimen (serum instead of plasma), (iii) different laboratory conditions, and (iv) different health conditions. Irrespective of such discrepancies, all the proteins of the PPS fell into the assay's detection range and fulfilled the quality requirements, enabling further data analysis.

The intra-assay precision (CV%) of the determined protein concentrations were calculated for two assay plates of all group I and group II proteins to determine technical reproducibility (**Table 2**). The lowest CV% value of 5.97 was obtained for IP10, and the highest (16.99) for GMCSF. These values were slightly higher than those stated by the assay provider, most likely due to the fact that in the investigated study protein concentration levels varied from sample to sample because of the biological heterogeneities of the donors. Nevertheless, the CV% values were below 20 for all of the 13 cytokines and growth factors of the PPS, which is considered satisfactory [25–27]. Inter-patient CV% values between the averaged samples ranged from 352.63 for IL6 (in artery) to 40.76 for GRO (in artery).

#### **2.2. Determination of data homogeneity**

For testing whether or not Vein 1 samples of patients followed a trend with respect to ischemia time, linear regression analyses were performed to correlate ischemia time with mean concentrations of the PPS, i.e., group I and group II proteins (**Figure 1**). Both coefficients of determination (*R*<sup>2</sup> values) and associated *p* values showed that there was no significant correlation between the two features for any of the tested proteins. This result indicated that sample values were rather randomly distributed with a fair homogenous distribution and only a few outliers.

In addition, hierarchical cluster analysis was conducted with group I proteins to characterize distribution of protein concentrations between patients. Plasma sampling time points (artery, Vein 1, and Vein 2) were analyzed independently from each other. The dendrograms and heat maps (**Figure 2**) revealed that in none of the sampling time points, the transplant types clustered together. Instead, within the blood sampling time points, all three transplant types seemed randomly distributed.

**PPS** Group I

IL6 IL8 IP10 MCP1 TNFα Fractalkine

GRO bFGF GMCSF

> Group II

IFNg MIP1a VEGF

IL10 aTotal number of samples:

bReference concentrations from healthy donors:

1Mean ± SE; multiplex bead assay: Yurkovetsky et al. [19].

2Median ± quartile difference; multiplex bead assay: Geyer et al. [20].

3Mean ± SE; EIA: Damas et al. [21].

4Mean ± SD; multiplex bead assay: Hang et al. [22].

5Mean ± SE; ELISA: Lee et al. [23].

6Mean ± SD; ELISA: Larsson et al. [24].

cArtery blood was collected before anastomosis (

dVein 1 blood was collected directly after anastomosis (

eVein 2 blood was collected 2 min after Vein 1 blood (

**Table 2.**

*N* = 21).

*N* = 18).

*N* = 19).

Averaged plasma concentrations of the per protocol set cytokines/growth factors in artery and vein samplesa

.

7

P22301

7.63 ± 5.952 *N* = 58 from 21 transplantation patients.

66.79 ± 129.79

194.31

63.28 ± 162.14

256.23

79.89 ± 170.61

213.54

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

http://dx.doi.org/10.5772/intechopen.70054

P15692

32.20 ± 21.806

283.19 ± 356.83

126.00

310.49 ± 385.78

124.25

305.3 ± 349.13

114.36

P10147

88.10 ± 14.311

22.14 ± 33.49

151.27

14.62 ± 16.86

115.34

14.22 ± 16.51

116.13

P01579

18.30 ± 9.152

42.18 ± 92.71

219.80

28.70 ± 39.87

138.89

51.41 ± 100.51

195.51

P04141

2.43 ± 0.085

8.59 ± 6.33

73.70

10.80 ± 10.81

100.11

8.47 ± 6.50

76.73

P09038

76.60 ± 17.532

90.76 ± 82.81

91.25

117.07 ± 73.80

63.04

87.27 ± 56.81

65.10

P09341

212.20 ± 21.804

1780.41 ± 725.66

40.76

2301.17 ± 1287.76

55.96

2423.88 ± 1253.26

51.70

P78423

423.00 ± 25.003

137.17 ± 110.49

80.55

126.62 ± 119.15

94.10

151.21 ± 124.79

82.53

P01375

34.22 ± 11.461

18.78 ± 10.70

56.98

20.50 ± 10.83

52.82

18.67 ± 9.49

50.83

P13500

173.20 ± 15.401

2160.00 ± 2626.43

121.59

2654.86 ± 2462.78

92.76

2520.15 ± 2208

87.61

P02778

248.00 ± 96.502

759.29 ± 485.42

63.93

860.02 ± 645.74

75.08

815.83 ± 581.65

71.30

P10145

9.56 ± 0.401

123.55 ± 161.52

130.73

138.29 ± 117.54

85.00

119.45 ± 105.28

88.13

P05231

22.80 ± 7.001

433.37 ± 1528.12

352.62

749.14 ± 916.28

122.31

692.80 ± 905.71

130.73

**Protein name**

**Uniprot acc.** 

**Ref. value** 

**Arteryc** **Mean ± SD** 

**CV%**

**Mean ± SD** 

**CV%**

**Mean ± SD** 

**CV%**

**(pg/mL)**

**(pg/mL)**

**(pg/mL)**

**Vein 1d**

**Vein 2e**

**(pg/mL)3**

**no.**


Data from the FAS were inspected for completeness and categorized into three groups based on the detection rates. Group I contained those CGFs for which plasma protein concentrations could be determined in over 80% of all samples. Group II included those CGFs for which plasma protein concentrations could be determined in over 60% but less than 80% of all samples. Group III contained proteins whose concentrations were determined in less than 60% of all samples and sCD40L which did not pass the QC test. Group I proteins were IL8, IP10, MCP1, TNFα, GRO, IL6, Fractalkine, bFGF, and GMCSF. Group II contained four proteins: IFNg, MIP1α, VEGF, and IL10. Five proteins were placed in group III: TGFα, IL1β, IL12P40, TNFβ, and sCD40L (**Table 2**). Group III proteins were not subjected to further data analysis. Hence, the per protocol set (PPS) consisted of just group I and II proteins (13 proteins in total)

Some of the determined average plasma protein concentrations in the analyzed samples matched well with reported reference concentrations (e.g., TNFα and bFGF), whereas others did not. Differences between the "reference concentrations" and the concentrations determined in the here described study could be caused by (i) using different assays, (ii) different specimen (serum instead of plasma), (iii) different laboratory conditions, and (iv) different health conditions. Irrespective of such discrepancies, all the proteins of the PPS fell into the assay's detection range and fulfilled the quality requirements, enabling further data analysis.

The intra-assay precision (CV%) of the determined protein concentrations were calculated for two assay plates of all group I and group II proteins to determine technical reproducibility (**Table 2**). The lowest CV% value of 5.97 was obtained for IP10, and the highest (16.99) for GMCSF. These values were slightly higher than those stated by the assay provider, most likely due to the fact that in the investigated study protein concentration levels varied from sample to sample because of the biological heterogeneities of the donors. Nevertheless, the CV% values were below 20 for all of the 13 cytokines and growth factors of the PPS, which is considered satisfactory [25–27]. Inter-patient CV% values between the averaged samples

For testing whether or not Vein 1 samples of patients followed a trend with respect to ischemia time, linear regression analyses were performed to correlate ischemia time with mean concentrations of the PPS, i.e., group I and group II proteins (**Figure 1**). Both coefficients of deter-

between the two features for any of the tested proteins. This result indicated that sample values were rather randomly distributed with a fair homogenous distribution and only a few outliers.

In addition, hierarchical cluster analysis was conducted with group I proteins to characterize distribution of protein concentrations between patients. Plasma sampling time points (artery, Vein 1, and Vein 2) were analyzed independently from each other. The dendrograms and heat maps (**Figure 2**) revealed that in none of the sampling time points, the transplant types clustered together. Instead, within the blood sampling time points, all three transplant types

values) and associated *p* values showed that there was no significant correlation

ranged from 352.63 for IL6 (in artery) to 40.76 for GRO (in artery).

and contained a total of 754 data points.

6 Issues in Flap Surgery

**2.2. Determination of data homogeneity**

seemed randomly distributed.

mination (*R*<sup>2</sup>

**Table 2.** Averaged plasma concentrations of the per protocol set cytokines/growth factors in artery and vein samplesa .

eVein 2 blood was collected 2 min after Vein 1 blood (

*N* = 19).

**Figure 1.** Linear regression plots for group I proteins between ischemia time and protein concentrations of all patients' Vein 1 samples. Trend lines are shown. *R*<sup>2</sup> values are given.

GMCSF, TNFα, Fractalkine, bFGF, and IL8 were found in low concentrations (below 500 pg/ mL; colored black in **Figure 3**), whereas IP10 was found with intermediate concentration (500 pg/mL < protein concentration < 1000 pg/mL; colored dark grey) in all three sampling time points (artery, Vein 1, and Vein 2). MCP1 and GRO were present in highest concentrations (above 1000 pg/mL; colored bright grey) in most samples of all three sampling time points. Interestingly, IL6 was found to change in concentration from low in artery to intermediate in both, Vein 1 and Vein 2 samples, and prompted to analyze protein concentration differences between sampling time points.

#### **2.3. Analysis of individual protein concentration dynamics**

To investigate expression differences between the sampling time points for each patient, ratios between the respective protein concentrations were calculated. Quotient I (artery/ artery), quotient II (Vein 1/artery), and quotient III (Vein 2/artery) showed individual values for all three time points in a normalized fashion. Combining these quotients, values with straight lines visualized "up" and "down" and/or "no" changes, respectively. From all investigated protein concentrations, a "dynamic" expression was observed for IL6 and IL8 in individual patients.

**Figure 2.** Hierarchical clustering analysis of protein concentrations from artery (A), Vein 1 (B), and Vein 2 (C) plasma samples of flap transplant patients. Proteins are indicated on the left. Patient IDs (**Table 1**) are given between the dendrogram and the heat map illustration. Grey scales indicate protein concentration: black—low, dark grey—medium,

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9

bright grey—high.

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation http://dx.doi.org/10.5772/intechopen.70054 9

GMCSF, TNFα, Fractalkine, bFGF, and IL8 were found in low concentrations (below 500 pg/ mL; colored black in **Figure 3**), whereas IP10 was found with intermediate concentration (500 pg/mL < protein concentration < 1000 pg/mL; colored dark grey) in all three sampling time points (artery, Vein 1, and Vein 2). MCP1 and GRO were present in highest concentrations (above 1000 pg/mL; colored bright grey) in most samples of all three sampling time points. Interestingly, IL6 was found to change in concentration from low in artery to intermediate in both, Vein 1 and Vein 2 samples, and prompted to analyze protein concentration differences

**Figure 1.** Linear regression plots for group I proteins between ischemia time and protein concentrations of all patients'

values are given.

To investigate expression differences between the sampling time points for each patient, ratios between the respective protein concentrations were calculated. Quotient I (artery/ artery), quotient II (Vein 1/artery), and quotient III (Vein 2/artery) showed individual values for all three time points in a normalized fashion. Combining these quotients, values with straight lines visualized "up" and "down" and/or "no" changes, respectively. From all investigated protein concentrations, a "dynamic" expression was observed for IL6 and IL8

between sampling time points.

Vein 1 samples. Trend lines are shown. *R*<sup>2</sup>

8 Issues in Flap Surgery

in individual patients.

**2.3. Analysis of individual protein concentration dynamics**

**Figure 2.** Hierarchical clustering analysis of protein concentrations from artery (A), Vein 1 (B), and Vein 2 (C) plasma samples of flap transplant patients. Proteins are indicated on the left. Patient IDs (**Table 1**) are given between the dendrogram and the heat map illustration. Grey scales indicate protein concentration: black—low, dark grey—medium, bright grey—high.

patients followed a related progression (**Figure 3B**) as well. The dominant protein profile for IL6 followed an "up-no" trend. Noteworthy, with a few patients (104, 106, 108, 206, and 304) from the IL6 group, a "fast dynamics" of protein concentration changes ("up-down" trend)

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Subgroup analysis of protein profiles with respect to different transplant types was performed to check whether the trend of the general protein concentration profiles of either IL6 or IL8 was found consistently in the clinical subgroups. In each of the three transplant groups (**Figure 4**), the "up-no" trend of IL6 was dominant (10 cases), followed by the "up-down"

Notably, the PPS data in the osteo-cutaneous group showed very large differences of IL6 concentrations between the pre-ischemia time point (artery) and the second post-ischemia time point (Vein 2) in patients 103, 105, and 109 ("up-no" trend). In patient 103, the difference was 2398.4 pg/mL; in patient 105, it was 3320.68 pg/mL; and in patient 109, 1549.19 pg/mL. These three patients experienced the longest ischemia times during operation (**Table 1**). Patient 109 developed a venous thrombosis after venous anastomosis, so a revision of the anastomosis

Of note, in the skin flap group, the pre-ischemia value (artery) of IL6 was higher in patients with clinical conspicuities compared to the other patients. In patient 305, the pre-ischemia IL6 concentration was 144.98 pg/mL, and in patient 302, it was 147.34 pg/mL. In the other patients of this group, the pre-ischemia IL6 concentrations were much lower and the mean was 52.15 pg/mL. Patient 305 developed an intraoperative thrombosis of the artery after venous anastomosis. In patient 302, ischemia time was the longest in the whole group with

In case of IL8, the "up-down" trend was dominant (five cases) in both, the osteo-cutaneous group (**Figure 5A**) and the cutaneous group (**Figure 5C**), followed by the "up-no" trend (four cases). Only the muscle group seemed to behave different (**Figure 5B**). Here, no dominant

Again, when looking at the PPS data also in the muscle group, the two patients (patients 202 and 203) with clinical conspicuities were standing out by looking at the concentrations of IL6 and additionally of IL8. In these patients, the pre-ischemia values (artery) of both, IL6 and IL8, were significantly higher than those of the other patients. The IL6 concentration of patient 202 was 30.47 pg/mL and that of patient 203 was 7064.18 pg/mL. Although both values were very different, they were much higher than the mean concentration of the other patients which was 12.81 pg/mL. Similarly, the IL8 concentration of patient 202 was 530.33 pg/mL and that of patient 203 was 477.09 pg/mL. These concentrations were again much higher than the mean (202.16 pg/mL) of all other patients in this group. Patient 202 suffered from partial flap necrosis, whereas patient 203 developed an intraoperative venous thrombosis after venous anastomosis, so a revision of the anastomosis with thrombectomy

with thrombectomy and an interposition of a vein graft became necessary.

trend could be defined, but "up-down" cases were present.

**2.4. Subgroup analysis of different free flap tissue groups**

was observed.

trend (5 cases).

150 min.

was necessary.

**Figure 3.** Line graphs of concentration ratios from 21 patients (58 plasma samples) for IL8 (A) and IL6 (B). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery. Patient IDs (**Table 1**) and respective symbols are shown at the right.

Nearly all line graphs for IL8 in all patients showed progression lines that were quite similar to each other (**Figure 3A**). The dominant protein concentration change profile of IL8 followed a rapid "up-down" trend. A few patients in the IL8 group (104, 107, 201, 302, and 305) represented a "slow dynamic," i.e., an "up-no" trend. Interestingly, line graphs for IL6 of most patients followed a related progression (**Figure 3B**) as well. The dominant protein profile for IL6 followed an "up-no" trend. Noteworthy, with a few patients (104, 106, 108, 206, and 304) from the IL6 group, a "fast dynamics" of protein concentration changes ("up-down" trend) was observed.

#### **2.4. Subgroup analysis of different free flap tissue groups**

Subgroup analysis of protein profiles with respect to different transplant types was performed to check whether the trend of the general protein concentration profiles of either IL6 or IL8 was found consistently in the clinical subgroups. In each of the three transplant groups (**Figure 4**), the "up-no" trend of IL6 was dominant (10 cases), followed by the "up-down" trend (5 cases).

Notably, the PPS data in the osteo-cutaneous group showed very large differences of IL6 concentrations between the pre-ischemia time point (artery) and the second post-ischemia time point (Vein 2) in patients 103, 105, and 109 ("up-no" trend). In patient 103, the difference was 2398.4 pg/mL; in patient 105, it was 3320.68 pg/mL; and in patient 109, 1549.19 pg/mL. These three patients experienced the longest ischemia times during operation (**Table 1**). Patient 109 developed a venous thrombosis after venous anastomosis, so a revision of the anastomosis with thrombectomy and an interposition of a vein graft became necessary.

Of note, in the skin flap group, the pre-ischemia value (artery) of IL6 was higher in patients with clinical conspicuities compared to the other patients. In patient 305, the pre-ischemia IL6 concentration was 144.98 pg/mL, and in patient 302, it was 147.34 pg/mL. In the other patients of this group, the pre-ischemia IL6 concentrations were much lower and the mean was 52.15 pg/mL. Patient 305 developed an intraoperative thrombosis of the artery after venous anastomosis. In patient 302, ischemia time was the longest in the whole group with 150 min.

In case of IL8, the "up-down" trend was dominant (five cases) in both, the osteo-cutaneous group (**Figure 5A**) and the cutaneous group (**Figure 5C**), followed by the "up-no" trend (four cases). Only the muscle group seemed to behave different (**Figure 5B**). Here, no dominant trend could be defined, but "up-down" cases were present.

Again, when looking at the PPS data also in the muscle group, the two patients (patients 202 and 203) with clinical conspicuities were standing out by looking at the concentrations of IL6 and additionally of IL8. In these patients, the pre-ischemia values (artery) of both, IL6 and IL8, were significantly higher than those of the other patients. The IL6 concentration of patient 202 was 30.47 pg/mL and that of patient 203 was 7064.18 pg/mL. Although both values were very different, they were much higher than the mean concentration of the other patients which was 12.81 pg/mL. Similarly, the IL8 concentration of patient 202 was 530.33 pg/mL and that of patient 203 was 477.09 pg/mL. These concentrations were again much higher than the mean (202.16 pg/mL) of all other patients in this group. Patient 202 suffered from partial flap necrosis, whereas patient 203 developed an intraoperative venous thrombosis after venous anastomosis, so a revision of the anastomosis with thrombectomy was necessary.

Nearly all line graphs for IL8 in all patients showed progression lines that were quite similar to each other (**Figure 3A**). The dominant protein concentration change profile of IL8 followed a rapid "up-down" trend. A few patients in the IL8 group (104, 107, 201, 302, and 305) represented a "slow dynamic," i.e., an "up-no" trend. Interestingly, line graphs for IL6 of most

**Figure 3.** Line graphs of concentration ratios from 21 patients (58 plasma samples) for IL8 (A) and IL6 (B). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery. Patient IDs

(**Table 1**) and respective symbols are shown at the right.

10 Issues in Flap Surgery

**Figure 4.** Line graphs of concentration ratios for IL6 from osteo-cutaneous flaps (A), muscle flaps (B), and skin flaps (C). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery. Patient IDs (**Table 1**) and respective symbols are shown at the right.

In sum, subgroup analysis confirmed that the dynamics of protein concentration differences of IL6 and IL8 correlated with I/R and seemed capable to characterize I/R-related processes on a molecular level for both the patients that showed clinical conspicuities or complications and those that did not. These concentration differences point toward a (transient) activation of leukocytes.

**2.5. Conclusion**

Patient IDs (**Table 1**) and respective symbols are shown at the right.

The dynamic nature of the circulating blood system and its constituents reflects diverse physiological or pathological states and, together with the ease with which blood can be sampled,

**Figure 5.** Line graphs of concentration ratios for IL8 from osteo-cutaneous flaps (A), muscle flaps (B), and skin flaps (C). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery.

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Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation http://dx.doi.org/10.5772/intechopen.70054 13

**Figure 5.** Line graphs of concentration ratios for IL8 from osteo-cutaneous flaps (A), muscle flaps (B), and skin flaps (C). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery. Patient IDs (**Table 1**) and respective symbols are shown at the right.

#### **2.5. Conclusion**

In sum, subgroup analysis confirmed that the dynamics of protein concentration differences of IL6 and IL8 correlated with I/R and seemed capable to characterize I/R-related processes on a molecular level for both the patients that showed clinical conspicuities or complications and those that did not. These concentration differences point toward a (transient) activation of leukocytes.

**Figure 4.** Line graphs of concentration ratios for IL6 from osteo-cutaneous flaps (A), muscle flaps (B), and skin flaps (C). Individual ratios were calculated from protein concentrations: I: artery/artery, II: Vein 1/artery, and III: Vein 2/artery.

Patient IDs (**Table 1**) and respective symbols are shown at the right.

12 Issues in Flap Surgery

The dynamic nature of the circulating blood system and its constituents reflects diverse physiological or pathological states and, together with the ease with which blood can be sampled, makes it a logical choice for biomarker investigations [28]. Based on the inspection of the individual protein profiles of 18 cytokines and growth factors in the investigated study cohort (**Table 3**), IL8 and IL6 showed dynamic changes within the measured time frame.

IL6 together with TNFα and IL1β belongs to the so-called pro-inflammatory cytokines. IL6 is supposed to activate the coagulation system in experimental models, due to cross-links


between inflammation and coagulation [32, 33]. Activated coagulation can result in microvascular thrombosis that possibly increases I/R injury [34]. Myocardial ischemia studies assume that changes in coagulation affect the resolution of ischemia during reperfusion due to changes in no-flow regions [35, 36]. In mice, IL6 deficiency reduced myocardial infarct size at 3 h reperfusion from which it was concluded that IL6 contributed to the development of infarct size in the early phase of reperfusion [37]. These results correspond to significantly elevated concentrations of IL6 in the venous blood samples of patients that experienced long

Undetermined sCD40L Cytokine (TNF) CD40 Dendritic cells, B

IL1β Cytokine/interleukin CD121a, CD121b T cells,

TNFβ Cytokine (TNF) CD120a, CD120b T cells,

IL12P40 Cytokine/interleukin IL-12β1c + IL-12β2 NK cells, T cells

TGF α Growth factor (EGF-like domain)

Comparisons of means of protein concentrations between sampling time points artery, Vein 1, and Vein 2.

Means are different between sampling time points artery, Vein 1, and Vein 2.

**Table 3.** Classification of proteins according to their averaged plasma concentrations.

Means are similar between sampling time points artery, Vein 1, and Vein 2.

**Protein family Receptorb,c Cytokine/growth** 

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

**factor target cell typesc,d**

15

cells, macrophages

macrophages

macrophages

EGFR Epithelial cells

http://dx.doi.org/10.5772/intechopen.70054

IL8 is a prototypical member of the CXC chemokine family. Chemokines control innate immune cell trafficking between the bone marrow, blood, and peripheral tissues during inflammation. IL8 is a potent chemoattractant for neutrophils in vitro [38]. It has been reported to be a chemoattractant for a subset of T-lymphocytes [39]. IL8 is also called neutrophil-activating protein 1 (NAP-1) because it stimulates release of neutrophil granules. Like many other chemoattractants, IL8 induces re-arrangement of the cytoskeleton, changes in intracellular Ca2+ levels, activation of integrins, exocytosis of granule proteins, and respiratory burst [40]. IL8 concentration dynamics results in the here described study are consistent with published data, demonstrating the potential of IL8 as a marker protein of I/R injury in transplantation surgery. Interestingly, in cases of clinical conspicuities or complications, IL6

The activated forms of both macrophages and keratinocytes can release a number of inflammatory and cytotoxic active molecules that play essential roles in wound repair and/or tissue damage [41–43]. Macrophages, by secreting IL6, were suggested to interact with keratinocytes

and IL8 react differently as compared to inconspicuous cases.

ischemia periods.

a

b

c

e

f

Baggiolini et al. [29].

Janeway et al. [30]. <sup>d</sup>Huret et al. [31].

**Classification<sup>a</sup> Cytokine/growth** 

**factor**


a Comparisons of means of protein concentrations between sampling time points artery, Vein 1, and Vein 2.

b Baggiolini et al. [29].

c Janeway et al. [30]. <sup>d</sup>Huret et al. [31].

makes it a logical choice for biomarker investigations [28]. Based on the inspection of the individual protein profiles of 18 cytokines and growth factors in the investigated study cohort

IL6 together with TNFα and IL1β belongs to the so-called pro-inflammatory cytokines. IL6 is supposed to activate the coagulation system in experimental models, due to cross-links

Dynamic change<sup>e</sup> IL8 Cytokine/chemokine CXCR1, E482 Neutrophils,

No dynamic change<sup>f</sup> MCP1 Cytokine/chemokine CCR2 T cell monocytes,

IL6 Cytokine/interleukin CD126, CD130 T cells, B cells

bFGF Growth factor (fibroblast) FGFR Epithelial cells GRO Cytokine/chemokine CXCR2 Neutrophils,

Fractalkine Cytokine/chemokine CX3CR1 Activated T cells,

GMCSF Cytokine/interleukin CD116, βc Bone marrow

IP 10 Cytokine/chemokine CXCR3A, CXCR3B Activated T cells,

TNF α Cytokine (TNF) CD120a, CD120b T cells, B cells,

MIP 1α Cytokine/chemokine CCR1, CCR5 Immune cells,

IL10 Cytokine/interleukin IL-10Rα, IL-10Rβc Macrophages, T

IFNγ Cytokine/interleukin CD119, IFNGR2 Monocytes,

VEGF Growth factor (vascular endothelial)

**Protein family Receptorb,c Cytokine/growth** 

**factor target cell typesc,d**

basophils, CD8 T cells, epithelial and endothelial

NK cells, B cells, endothelial cells

fibroblasts, melanoma cells

progenitors

cells

neutrophils, NK

NK cells, B cells, endothelial cells

endothelial cells

smooth muscle cells, endothelial

endothelial cells, hematopoietic stem cells, megakaryocytes

endothelial cells, macrophages

cells

cells

VEGFR Vascular

cells

(**Table 3**), IL8 and IL6 showed dynamic changes within the measured time frame.

**Classification<sup>a</sup> Cytokine/growth** 

14 Issues in Flap Surgery

**factor**

e Means are different between sampling time points artery, Vein 1, and Vein 2.

f Means are similar between sampling time points artery, Vein 1, and Vein 2.

**Table 3.** Classification of proteins according to their averaged plasma concentrations.

between inflammation and coagulation [32, 33]. Activated coagulation can result in microvascular thrombosis that possibly increases I/R injury [34]. Myocardial ischemia studies assume that changes in coagulation affect the resolution of ischemia during reperfusion due to changes in no-flow regions [35, 36]. In mice, IL6 deficiency reduced myocardial infarct size at 3 h reperfusion from which it was concluded that IL6 contributed to the development of infarct size in the early phase of reperfusion [37]. These results correspond to significantly elevated concentrations of IL6 in the venous blood samples of patients that experienced long ischemia periods.

IL8 is a prototypical member of the CXC chemokine family. Chemokines control innate immune cell trafficking between the bone marrow, blood, and peripheral tissues during inflammation. IL8 is a potent chemoattractant for neutrophils in vitro [38]. It has been reported to be a chemoattractant for a subset of T-lymphocytes [39]. IL8 is also called neutrophil-activating protein 1 (NAP-1) because it stimulates release of neutrophil granules. Like many other chemoattractants, IL8 induces re-arrangement of the cytoskeleton, changes in intracellular Ca2+ levels, activation of integrins, exocytosis of granule proteins, and respiratory burst [40]. IL8 concentration dynamics results in the here described study are consistent with published data, demonstrating the potential of IL8 as a marker protein of I/R injury in transplantation surgery. Interestingly, in cases of clinical conspicuities or complications, IL6 and IL8 react differently as compared to inconspicuous cases.

The activated forms of both macrophages and keratinocytes can release a number of inflammatory and cytotoxic active molecules that play essential roles in wound repair and/or tissue damage [41–43]. Macrophages, by secreting IL6, were suggested to interact with keratinocytes which are associated with epithelialization [44]. IL8 has a profound effect on the migration of keratinocytes which is again critical to wound epithelialization [45]. In vitro experiments on the effect of recombinant human IL8 on keratinocyte proliferation revealed a rise in cell numbers, whereas in vivo topically applied IL8 on human skin grafts in a chimeric mouse model enhanced re-epithelialization due to elevated numbers of mitotic keratinocytes [46]. The dynamic occurrence of chemokines IL8, GROα, MCP-1, IP-10, and Mig in the different phases of wound healing was described in a skin repair model in adult humans [47].

binds a discontinuous epitope on IL8 overlapping the receptor binding site, and it is capable to interrupt IL8 activity in vivo [50]. Both therapeutic antibodies would neutralize increased levels of interleukins and directly interfere in leukocyte signaling with potentially positive

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

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17

These results indicate the sequential function of endogenous MCSF [51], IL8, and IL6 in wound healing which in case of overexpression may be clinically managed by administering appropriate medication, i.e., management of an individuals' systemic inflammatory status to reduce or even prevent conspicuities and complications during perioperative and postoperative periods. Concomitant medication may become an important if not indispensable part of

Presented and discussed data are from a study that was approved by the Institutional Review Board of the University Hospital Zurich, Switzerland (StV 8-2009). Written informed consent was obtained from all participating patients. Three groups of free flap transfers were defined: (i) muscle flaps, e.g., gracilis flap, latissimus dorsi flap, serratus anterior flap, (ii) fascio-cutaneous flaps, e.g., radialis flap, anterolateral thigh flap, and (iii) osteo-cutaneous flaps, i.e., fibula flaps. Clinical measurements include the ischemia time, flap weight, length of bone (in fibula flaps), and the dimension of the skin island. Patients qualified for the study had to be with normal weight (BMI 20–25), non-diabetics, in no manifest infection situation, and of good health with no essential diseases besides the main diagnosis (**Table 1**). Blood samples were taken intraoperatively prior to arterial anastomosis from the arterial inflow and after arterial anastomosis from the venous flap outflow. Vein 1 samples were taken directly after anastomosis and Vein 2 samples 2 min after collecting Vein 1 samples in 1.5 mL portions using S-Monovette® Lithium Heparin syringes (Monovette®, Sarstedt, Germany). Blood samples were immediately subjected to sedimentation of blood cells by centrifugation at 2000 g at room temperature for 15 min. Plasma was aspirated and sterile-filtered (0.2 μm pore size) [52]. Five samples had to be excluded from the study because of too less material after centrifugation and sterile filtration: patient 109 (Vein 1), patient 203 (Vein 2), patient 204 (Vein 1), and patient 306 (Vein 1 and Vein 2). In total, 58 plasma samples had been collected.

Aliquots of 100 μL per portion were stored at –80°C prior to further analysis.

The Human Cytokine/Chemokine Magnetic Bead Panel from Milliplex® (Map kit HCYTOMAG-60K, Billerica, MA, USA) contained antibodies against 18 proteins that were delivered immobilized onto color-coded beads. All kit reagents were brought to 25°C. Then, the two quality control samples were reconstituted with 250 μL deionized water, each. Serum matrix was reconstituted with 1.0 mL deionized water. The human cytokine standard mixture was reconstituted with 250 μL deionized water to give a 10,000 pg/mL concentration for each of the standards. This

**4.2. Multiplexed bead-based immunoassay**

effects on tissue and wound healing processes.

state-of-the-art flap surgery in the future.

**4.1. Clinical specimen collection**

**4. Appendix**

#### **3. Outlook**

The concept of targeting receptor cells that bind to IL6 or IL8 might become of importance for clinical interventions with the aim to accelerate wound healing as well as to attenuate fibrosis in response to individually determined cytokine/growth factor concentrations (**Figure 6**). Sequential function of endogenous IL8 and IL6 in all phases of human wound healing suggests to administering appropriate medication [48] in case of overexpression.

For instance, the anti-interleukin-6 receptor monoclonal antibody, tocilizumab, which was approved for the treatment of inflammatory diseases [49], might be tested in an off-label clinical study for its effect in modulating immune responses during free flap healing. A similar therapeutic concept may make use of HuMab 10FB, a fully human mAb against IL8, which

**Figure 6.** Implications of leucocytes (macrophages) in wound healing processes and clinical management without (left) and with (right) neutralizing antibody-based medication. Overproduced cytotoxic mediators or their receptors may be targeted. Pro-inflammatory mediators and enzymes may be clinically managed, whereas anti-inflammatory mediators would not be affected.

binds a discontinuous epitope on IL8 overlapping the receptor binding site, and it is capable to interrupt IL8 activity in vivo [50]. Both therapeutic antibodies would neutralize increased levels of interleukins and directly interfere in leukocyte signaling with potentially positive effects on tissue and wound healing processes.

These results indicate the sequential function of endogenous MCSF [51], IL8, and IL6 in wound healing which in case of overexpression may be clinically managed by administering appropriate medication, i.e., management of an individuals' systemic inflammatory status to reduce or even prevent conspicuities and complications during perioperative and postoperative periods. Concomitant medication may become an important if not indispensable part of state-of-the-art flap surgery in the future.

## **4. Appendix**

which are associated with epithelialization [44]. IL8 has a profound effect on the migration of keratinocytes which is again critical to wound epithelialization [45]. In vitro experiments on the effect of recombinant human IL8 on keratinocyte proliferation revealed a rise in cell numbers, whereas in vivo topically applied IL8 on human skin grafts in a chimeric mouse model enhanced re-epithelialization due to elevated numbers of mitotic keratinocytes [46]. The dynamic occurrence of chemokines IL8, GROα, MCP-1, IP-10, and Mig in the different

The concept of targeting receptor cells that bind to IL6 or IL8 might become of importance for clinical interventions with the aim to accelerate wound healing as well as to attenuate fibrosis in response to individually determined cytokine/growth factor concentrations (**Figure 6**). Sequential function of endogenous IL8 and IL6 in all phases of human wound healing suggests

For instance, the anti-interleukin-6 receptor monoclonal antibody, tocilizumab, which was approved for the treatment of inflammatory diseases [49], might be tested in an off-label clinical study for its effect in modulating immune responses during free flap healing. A similar therapeutic concept may make use of HuMab 10FB, a fully human mAb against IL8, which

**Figure 6.** Implications of leucocytes (macrophages) in wound healing processes and clinical management without (left) and with (right) neutralizing antibody-based medication. Overproduced cytotoxic mediators or their receptors may be targeted. Pro-inflammatory mediators and enzymes may be clinically managed, whereas anti-inflammatory mediators

phases of wound healing was described in a skin repair model in adult humans [47].

to administering appropriate medication [48] in case of overexpression.

**3. Outlook**

16 Issues in Flap Surgery

would not be affected.

#### **4.1. Clinical specimen collection**

Presented and discussed data are from a study that was approved by the Institutional Review Board of the University Hospital Zurich, Switzerland (StV 8-2009). Written informed consent was obtained from all participating patients. Three groups of free flap transfers were defined: (i) muscle flaps, e.g., gracilis flap, latissimus dorsi flap, serratus anterior flap, (ii) fascio-cutaneous flaps, e.g., radialis flap, anterolateral thigh flap, and (iii) osteo-cutaneous flaps, i.e., fibula flaps. Clinical measurements include the ischemia time, flap weight, length of bone (in fibula flaps), and the dimension of the skin island. Patients qualified for the study had to be with normal weight (BMI 20–25), non-diabetics, in no manifest infection situation, and of good health with no essential diseases besides the main diagnosis (**Table 1**). Blood samples were taken intraoperatively prior to arterial anastomosis from the arterial inflow and after arterial anastomosis from the venous flap outflow. Vein 1 samples were taken directly after anastomosis and Vein 2 samples 2 min after collecting Vein 1 samples in 1.5 mL portions using S-Monovette® Lithium Heparin syringes (Monovette®, Sarstedt, Germany). Blood samples were immediately subjected to sedimentation of blood cells by centrifugation at 2000 g at room temperature for 15 min. Plasma was aspirated and sterile-filtered (0.2 μm pore size) [52]. Five samples had to be excluded from the study because of too less material after centrifugation and sterile filtration: patient 109 (Vein 1), patient 203 (Vein 2), patient 204 (Vein 1), and patient 306 (Vein 1 and Vein 2). In total, 58 plasma samples had been collected. Aliquots of 100 μL per portion were stored at –80°C prior to further analysis.

#### **4.2. Multiplexed bead-based immunoassay**

The Human Cytokine/Chemokine Magnetic Bead Panel from Milliplex® (Map kit HCYTOMAG-60K, Billerica, MA, USA) contained antibodies against 18 proteins that were delivered immobilized onto color-coded beads. All kit reagents were brought to 25°C. Then, the two quality control samples were reconstituted with 250 μL deionized water, each. Serum matrix was reconstituted with 1.0 mL deionized water. The human cytokine standard mixture was reconstituted with 250 μL deionized water to give a 10,000 pg/mL concentration for each of the standards. This solution was serially diluted by a factor of 5 and yielded in diluted human cytokine standards with the following concentrations: 10,000, 2000, 400, 80, 16, and 3.2 pg/mL. Next, each antibody-bead containing vial was sonicated for 30 s and then vortexed for 1 min. Sixty microliters of antibody-bead slurry from each of the 18 vials was added to the mixing bottle, and 1.92 mL "bead diluent" was added to achieve a final volume of 3.0 mL. Two 96-well plates were pre-wetted with 200 μL wash buffer, each. After sealing, the plates were fixed on the shaker (Heidolph® Promax 2020, Schwabach, Germany) and gently agitated for 10 min at room temperature. The wash buffer was decanted, and the residual amount was removed by inverting the plates and gently tapping onto absorbent towels for several times. Twenty-five microliters, each, of all six diluted human cytokine standards and the two quality control samples were added into their dedicated wells. Twenty-five microliters, each, of assay buffer were added to two "background" wells and to the wells that were dedicated to patient samples. Second, 25 μL of serum matrix was added into each of the diluted human cytokine standard wells, the background wells, and the quality control sample wells. Twenty-five microliters of each patient plasma was added into one of the patient sample wells. Twenty-five microliters, each, of antibody-bead slurry from the mixing bottle was added to all the wells. Afterwards, plates were sealed and incubated in the dark for 18 h at 4°C on the plate shaker. Solvents from each well were removed, avoiding loss of beads, and beads were washed twice with wash buffer (200 μL, for each well, 1 min incubation). After removal of wash buffer, 25 μL, each, of detection antibody solution was added to all wells. After 1 h incubation at 25°C, 25 μL of phycoerythrin-loaded streptavidin containing solution was added to all wells. The plates were sealed again, covered with aluminum foil, and then fixed on the plate shaker for 30 min at 25°C. Subsequently, beads were washed twice with wash buffer (200 μL, for each well, 1 min incubation). After removal of wash buffer, 150 μL of sheath fluid (Bio-Rad Laboratories, Hercules, CA, USA) was added to all wells and beads were resuspended on the plate shaker for 5 min. Plates were placed into the Bio-Plex suspension array 200 System (Bio-Rad Laboratories, Hercules, CA, USA), which had been calibrated with Bio-Plex® 200 calibration kit and validated with Bio-Plex® validation kit 4.0 (Bio-Rad Laboratories, Hercules, CA, USA). Measurement settings were as follows: data acquisition, 50 beads per region; sample size, 100 μL; and doublet discriminator gate, 5000–25,000 (low photomultiplier tube). The Bio-Plex suspension array 200 reader system contains a red laser for identification of the bead which is analyzed and a green laser for quantification of fluorescence intensity of phycoerythrinloaded streptavidin. All standards, controls, background, and plasma samples were prepared in duplicate and measured once. From the 2088 independent measurements, the Bio-Plex® manager 6.1 software (Bio-Rad Laboratories, Hercules, CA, USA) calculated median fluorescence intensity (MFI) and standard deviations of each duplicate recording. Fluorescence values of human cytokine standards were plotted as standard curves which were used for determining plasma concentrations (pg/mL) based on their fluorescence intensities of all proteins and all time points. In total, 1044 data points (raw data set) were stored as Excel files.

II included those CGFs for which plasma protein concentrations could be determined in over 60% but less than 80% of all samples. Group III contained proteins whose concentrations were determined in less than 60% of all samples and sCD40L which did not pass the QC test. In both, group I and group II proteins, the missing values were imputed using the lower limit of quantitation (LLOQ) except for MCP1 for which upper limit of quantitation (ULOQ) was imputed. After imputing, the "full analysis set (FAS)" contained a total of 1044 curated data points (data not shown). The "per protocol set (PPS)" was generated out of the "full analysis

Plasma Cytokine and Growth Factor Profiling during Free Flap Transplantation

http://dx.doi.org/10.5772/intechopen.70054

19

set (FAS)" by including only group I and group II CGFs, resulting in 754 data points.

, Marius Bredell<sup>3</sup>

1 Proteome Center Rostock, University Medicine and Natural Science Faculty,

2 Division of Plastic Surgery and Hand Surgery, HELIOS Clinic Emil von Behring,

3 Department of Cranio-Maxillofacial and Oral Surgery, University Hospital of Zürich,

[1] Bui DT, Cordeiro PG, Hu QY, Disa JJ, Pusic A, Mehrara BJ. Free flap reexploration: Indications, treatment, and outcomes in 1193 free flaps. Plastic and Reconstructive

Surgery. 2007;**119**(7):2092-2100. DOI: 10.1097/01.prs.0000260598.24376.e1

, Uwe von Fritschen2

and

Statistical analyses were performed using the PPS with the IBM statistics software SPSS (version 20.0, SPSS Inc., Chicago, USA). Linear fit analysis between ischemia time and protein concentration was performed using the Origin statistics software (version. 8.1 G; OriginLab Corporation, Northampton, MA, USA). Linear regression was performed to calculate *R*<sup>2</sup> values, and ANOVA tests were performed to calculate *p* values to estimate whether protein concentration was related to the ischemia time [53]. Hierarchical cluster analysis and dendrogram presentation were performed on the Knowledge Discovery Environment (KDE) platform (InforSense Ltd., London, UK). Parameter settings were single linkage and Euclidean distance. CV% for each analyte was calculated as the ratio of the standard deviation to the

**4.4. Biostatistical analysis**

plasma mean concentration [25, 26].

, Jingzhi Yang1#

\*Address all correspondence to: michael.glocker@uni-rostock.de

\*

University of Rostock, Rostock, Germany
