Local and Systemic Cytokine Profiling for Pancreatic Ductal Adenocarcinoma to Study Cancer Cachexia in an Era of Precision Medicine
Abstract
:1. Introduction
2. Results
2.1. Xenograft Selection
2.2. PDX Model Preserves Cancer-Associated Cachexia
2.3. Atrophy Related Genes Are Expressed in PDX Models
2.4. PDX Model Confers Unique Splenic Soluble Protein Profiles
2.5. PDX Model Confers Unique Tumor Microenvironment Soluble Protein Profiles
2.6. Splenic and Tumor Soluble Protein Associations
3. Discussion
4. Materials and Methods
4.1. Patient Derived Xenograft Model
4.2. Mouse Tissue Harvest and Processing
4.3. Genetic Expression Profiling
4.4. Soluble Protein Analysis
4.5. Statistical Analysis
Author Contributions
Funding
Conflicts of Interest
Abbreviations
PDX | Patient Derived Xenograft |
PDAC | Pancreatic Ductal Adenocarcinoma |
NSG | NOD.Cg-Prkdcscid IL2rgtm1Wjl/SzJ |
IACUC | Institutional Animal Care and Use Committee |
TA | Tibialis Anterior |
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Patient Demographics | G59 | G68 |
---|---|---|
Age | 73 | 64 |
Charlson comorbidity index | 5 | 4 |
Race | White | White |
Sex | Female | Female |
BMI | 27.3 | 29.2 |
Weight at time of surgery (pounds) | 149 | 170 |
Weight loss prior to surgery (pounds) | 10 (6.3%) | 25 (12.8%) |
Psoas Index at time of surgery | 0.639 | 0.526 |
Neoadjuvant therapy | No | No |
Operative & Oncologic Factors | ||
Pathologic diagnosis | Adenocarcinoma | Adenocarcinoma |
EBL | 600 | 200 |
Transfusion, intra-op | No | No |
Transfusion, post-op | No | Yes |
Portal vein resection | No | No |
Total lymph nodes | 15 | 18 |
Positive lymph nodes | 4 | 2 |
Tumor size (cm) | Indeterminate | 3.8 |
Margins | Uninvolved | Uninvolved |
Differentiation | Moderate | Moderate |
Stage | T3N1 | T3N1 |
Postoperative Complications | ||
Length of stay (days) | 7 | 74 |
Pancreatic leak | No | Yes |
Post pancreatectomy hemorrhage | No | Yes |
Major morbidity (clavien III/IV) | No | Yes |
Death (Postoperative day) | 711 | 169 |
Splenic Lysate Proteins | Control (n = 9) | G59 (n = 5) | G68 (n = 5) | Control vs. G59 | Control vs. G68 | G59 vs. G68 |
---|---|---|---|---|---|---|
Mean (SD) | Mean (SD) | Mean (SD) | P-Value | P-Value | P-Value | |
FGF-2 | 2587.5 (557.5) | 1491.0 (398.6) | 1690.2 (552.9) | 0.002 | 0.013 | 0.532 |
VEGF | 75.1 (12.0) | 9.7 (7.7) | 8.9 (3.8) | <0.001 | <0.001 | 0.846 |
Fractalkine | 56.6 (28.8) | 67.8 (24.3) | 19.8 (13.7) | 0.478 | 0.021 | 0.005 |
IL-8 | 1.5 (1.1) | 17.4 (15.2) | 155.5 (113.9) | 0.007 | 0.001 | 0.028 |
GRO | 1.4 (1.2) | 108.2 (51.0) | 158.6 (66.1) | <0.001 | <0.001 | 0.214 |
MDC | 21.7 (14.9) | 25.7 (7.9) | 3.0 (1.4) | 0.590 | 0.017 | <0.001 |
IFNα2 | 15.3 (3.7) | 11.8 (2.5) | 10.7 (2.6) | 0.080 | 0.028 | 0.511 |
IL-7 | 9.8 (1.9) | 8.4 (1.8) | 5.7 (1.6) | 0.229 | 0.002 | 0.031 |
Flt-3L | 6.4 (3.5) | 3.5 (1.1) | 2.0 (0.7) | 0.107 | 0.019 | 0.034 |
EGF | 4.6 (1.5) | 2.8 (1.3) | 2.5 (0.9) | 0.040 | 0.013 | 0.667 |
IFNγ | 4.3 (2.2) | 4.8 (1.6) | 0.8 (0.3) | 0.663 | 0.004 | 0.001 |
IP-10 | 2.7 (1.7) | 1.2 (0.9) | 4.4 (3.0) | 0.090 | 0.183 | 0.049 |
IL-17A | 2.4 (0.8) | 2.0 (0.6) | 0.2 (0.3) | 0.308 | <0.001 | <0.001 |
IL-4 | 1.1 (1.1) | 2.7 (1.1) | 2.3 (0.7) | 0.024 | 0.053 | 0.498 |
IL-1RA | 0.1 (0.3) | 20.4 (26.3) | 1.4 (0.6) | 0.033 | <0.001 | 0.144 |
G59 (n = 5) | G68 (n = 5) | ||
---|---|---|---|
Mean (SD) | Mean (SD) | P-value | |
IL-1RA | 1056.9 (198.8) | 248.9 (126.9) | <0.001 |
GRO | 689.7 (215.8) | 293.5 (185.9) | 0.014 |
FGF-2 | 635.8 (359.7) | 236.2 (135.2) | 0.049 |
IL-8 | 194.3 (122.0) | 267.8 (153.8) | 0.426 |
Fractalkine | 121.8 (60.7) | 62.9 (12.7) | 0.066 |
RANTES | 88.6 (46.4) | 82.7 (75.6) | 0.885 |
IP-10 | 13.1 (6.1) | 65.0 (53.0) | 0.061 |
GM-CSF | 3.6 (1.5) | 16.3 (7.5) | 0.006 |
TGFα | 15.2 (5.2) | 3.6 (2.1) | 0.002 |
IL-1α | 4.1 (2.9) | 11.6 (8.1) | 0.085 |
MDC | 7.0 (2.8) | 2.4 (1.0) | 0.009 |
TNFα | 2.9 (1.3) | 6.0 (7.2) | 0.364 |
IFNα2 | 6.6 (1.3) | 2.2 (1.4) | 0.001 |
IL-15 | 4.9 (0.6) | 3.8 (0.5) | 0.008 |
MCP-1 | 3.4 (3.9) | 4.8 (6.5) | 0.679 |
IL-7 | 3.5 (1.5) | 1.5 (0.6) | 0.026 |
IL-6 | 2.9 (2.2) | 1.3 (1.0) | 0.167 |
G-CSF | 2.8 (0.6) | 0.8 (0.4) | <0.001 |
Flt-3L | 2.4 (0.5) | 0.9 (0.3) | <0.001 |
IFNγ | 2.0 (1.0) | 0.7 (0.4) | 0.022 |
IL-4 | 1.9 (1.1) | 0.5 (0.1) | 0.020 |
EGF | 1.6 (1.0) | 0.5 (0.2) | 0.033 |
MCP-3 | 1.3 (0.9) | 0.5 (0.2) | 0.083 |
IL-12p40 | 1.2 (0.4) | 0.6 (0.4) | 0.049 |
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Gerber, M.H.; Underwood, P.W.; Judge, S.M.; Delitto, D.; Delitto, A.E.; Nosacka, R.L.; DiVita, B.B.; Thomas, R.M.; Permuth, J.B.; Hughes, S.J.; et al. Local and Systemic Cytokine Profiling for Pancreatic Ductal Adenocarcinoma to Study Cancer Cachexia in an Era of Precision Medicine. Int. J. Mol. Sci. 2018, 19, 3836. https://doi.org/10.3390/ijms19123836
Gerber MH, Underwood PW, Judge SM, Delitto D, Delitto AE, Nosacka RL, DiVita BB, Thomas RM, Permuth JB, Hughes SJ, et al. Local and Systemic Cytokine Profiling for Pancreatic Ductal Adenocarcinoma to Study Cancer Cachexia in an Era of Precision Medicine. International Journal of Molecular Sciences. 2018; 19(12):3836. https://doi.org/10.3390/ijms19123836
Chicago/Turabian StyleGerber, Michael H., Patrick W. Underwood, Sarah M. Judge, Daniel Delitto, Andrea E. Delitto, Rachel L. Nosacka, Bayli B. DiVita, Ryan M. Thomas, Jennifer B. Permuth, Steven J. Hughes, and et al. 2018. "Local and Systemic Cytokine Profiling for Pancreatic Ductal Adenocarcinoma to Study Cancer Cachexia in an Era of Precision Medicine" International Journal of Molecular Sciences 19, no. 12: 3836. https://doi.org/10.3390/ijms19123836