| Literature DB >> 35057068 |
Douglas Steinhauff1,2, Mark Martin Jensen3, Ethan Griswold1,2, Jolanta Jedrzkiewicz4, Joseph Cappello5, Siam Oottamasathien3,6, Hamidreza Ghandehari1,2,5.
Abstract
Semisynthetic glycosaminoglycan ethers (SAGEs) are short, sulfated hyaluronans which combine the natural properties of hyaluronan with chemical sulfation. In a murine model, SAGEs provide protection against radiation induced proctitis (RIP), a side effect of lower abdominal radiotherapy for cancer. The anti-inflammatory effects of SAGE have been studied in inflammatory diseases at mucosal barrier sites; however, few mechanisms have been uncovered necessitating high throughput methods. SAGEs were combined with silk-elastinlike polymers (SELPs) to enhance rectal accumulation in mice. After high radiation exposure to the lower abdominal area, mice were followed for 3 days or until they met humane endpoints, before evaluation of behavioral pain responses and histological assessment of rectal inflammation. RNA sequencing was conducted on tissues from the 3-day cohort to determine molecular mechanisms of SAGE-SELP. After 3 days, mice receiving the SAGE-SELP combination yielded significantly lowered pain responses and amelioration of radiation-induced rectal inflammation. Mice receiving the drug-polymer combination survived 60% longer than other irradiated mice, with a fraction exhibiting long term survival. Sequencing reveals varied regulation of toll like receptors, antioxidant activities, T-cell signaling, and pathways associated with pain. This investigation elucidates several molecular mechanisms of SAGEs and exhibits promising measures for prevention of RIP.Entities:
Keywords: radiation induced proctitis; semi-synthetic glycosaminoglycan ethers; silk-elastinlike polymers
Year: 2022 PMID: 35057068 PMCID: PMC8777937 DOI: 10.3390/pharmaceutics14010175
Source DB: PubMed Journal: Pharmaceutics ISSN: 1999-4923 Impact factor: 6.321
Figure 1Behavioral pain responses 3-day post irradiation. (A) Response rates of irradiated animals receiving selected treatments and healthy controls. (B) Response rates with the 0.4-g filament. (C) Change in response rates from baseline measurements with the 0.16-g filament. (D) Threshold required to elicit an allodynic response as measured by an increase in 30% from the baseline. Red box indicates animals with no allodynic response (na) (** p < 0.01, * p < 0.05).
Figure 2Histological analysis of tissues 3 days following irradiation. (A) Histological sections of healthy and irradiated animals receiving selected treatments. Black arrows indicate apoptosis, arrowheads indicate epithelial cell pleomorphism, and red arrows indicate mitoses. (B) Blinded scoring of histological sections to determine injury score.
Figure 3Animal body weights and survival. (A) Change in mice body weight as a percentage of baseline weights. Each line represents the body weight of a single animal. (B) Mean percentage of body weight loss per day. (C) Survival curves of irradiated animals receiving prophylactic treatments. (** p < 0.01, * p < 0.05).
Figure 4Behavioral pain responses at the time of sacrifice. (A) Response rates of irradiated animals receiving selected treatments and healthy controls. (B) Response rates with the 0.16-g filament. (C) Threshold required to elicit an allodynic response as measured by an increase in 30% from the baseline. Red box indicates animals with no allodynic response (na). (** p < 0.01, * p < 0.05).
Figure 5Time of sacrifice histological evaluation of rectal tissues. (A) Histological sections of healthy and irradiated animals receiving selected treatments. Arrows indicate epithelial erosion and arrowheads indicate crypt dropout. (B) Blinded scoring of histological sections to determine injury scores.
Canonical pathways identified from protection of GM–SELP in a RIP model.
| Ingenuity Canonical Pathways | −log ( | Ratio | Z | Molecules |
|---|---|---|---|---|
| PKCθ Signaling in T Lymphocytes | 1.65 | 0.0179 | −2.646 | CACNA1I, CACNG1, CARD11, CD4, HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, NFKBIA, Trbc1 |
| Crosstalk between Dendritic Cells and Natural Killer Cells | 5.94 | 0.0879 | −2.449 | CCR7, CD83, CSF2RB, HLA-A, HLA-DRA, HLA-DRB5, IL2RG, ITGAL |
| Th1 Pathway | 3.19 | 0.0492 | −2.449 | CD4, HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, IL27RA |
| PD-1, PD-L1 cancer immunotherapy pathway | 2.66 | 0.0472 | 2.236 | HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, IL2RG |
| Senescence Pathway | 1.37 | 0.0202 | 2.236 | CACNG1, CAPN9, HBP1, PDHA1, PDHB, PPP2R5A |
| Corticotropin Releasing Hormone Signaling | 2.03 | 0.0336 | 2 | ADCY9, CACNA1I, CACNG1, SLC39A7, SMO |
| Antioxidant Action of Vitamin C | 1.82 | 0.036 | 2 | CSF2RB, NFKBIA, PLA2G2D, PLCB2 |
| Insulin Receptor Signaling | 1.49 | 0.0286 | 2 | GAB1, PPP1CB, RHOQ, SHC1 |
| T Cell Receptor Signaling | 2.6 | 0.0212 | −1.941 | CARD11, CD4, CD8B, HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, ITGAL, NFKBIA, PTPN6, PTPN7, SKAP1, Trbc1 |
| ICOS-ICOSL Signaling in T Helper Cells | 1.51 | 0.0178 | −1.89 | CD4, HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, IL2RG, NFKBIA, SHC1, Trbc1 |
Upstream regulators identified from protection with GM–SELP in RIP model.
| Upstream | Activation Z-Score | Molecules | |
|---|---|---|---|
| TNF | −3.784 | 0.00334 | ACADM, BCL2A1, BTBD3, CAMP, CCL5, CCR7, CD4, CD83, CDK5R1, CSF1R, CSF2RB, CX3CR1, CXCL13, CXCL2, GAB1, Glycam1, HLA-A, HLA-DRA, IL16, IL27RA, ITGAL, KCNJ2, LAMP3, MUC2, NFKBIA, PLK3, SMO, VCL, ZNF750 |
| IFNG | −3.694 | 0.000314 | ABCB1, BCL2A1, C1QB, CCL5, CCR7, CD4, CD83, CDK5R1, CSF1R, CSF2RB, CX3CR1, CXCL2, HCK, HLA-A, HLA-DMB, HLA-DRA, HLA-DRB5, Ighg3, ITGAL, Klrk1, LAMP3, LAT2, MUC2, NFKBIA, PDHA1, PTPN6, RAB27A |
| AHR | −3.268 | 0.000668 | C1QB, CARD11, CCL5, CCR7, CD4, CD8B, CSF2RB, CX3CR1, CXCL13, CXCL2, IL9R, VCL |
| Lipopolysaccharide | −3.193 | 0.000000174 | ABCB1, ACADM, BCL2A1, CAMP, CCL5, CCR7, CD4, Cd52, CD83, CDK5R1, CNNM2, CNST, CSF1R, CSF2RB, CX3CR1, CXCL13, CXCL2, FBN1, GAB1, GIMAP7, HACD2, HCK, HLA-A, HLA-DMB, HLA-DRB5, IER5, Ighg3, IKZF1, IL16, IL2RG, ITGAL, ITPKC, LAMP3, LYZ, MUC2, NFKBIA, PLA2G2D, PLK3, PPP1CB, PTPN7, TFDP2, TNFRSF13B, VCL |
| IL6 | −3.064 | 0.000261 | BTC, CCL5, CCR7, CD83, CSF1R, CSF2RB, CX3CR1, CXCL13, CXCL2, HLA-A, HLA-DRB5, IL2RG, LYZ, NFKBIA, PLA2G2D, RAB27A, RNASE6, SMO |
| −2.918 | 0.00022 | C1QB, CCL5, CCR7, Cd52, CD83, CXCL2, HLA-A, LCP1, NFKBIA, PTPN6 | |
| CSF2 | −2.905 | 0.00291 | BCL2A1, CARD11, CCR7, CD83, CSF1R, CSF2RB, CX3CR1, CXCL2, IL16, LAMP3, LCP1, NFKBIA |
| IL10RA | 2.813 | 0.00667 | ABCB1, CCL5, CCR7, FBN1, HLA-A, IL2RG, Klrk1, Treml4 |
| TLR7 | −2.764 | 0.00014 | ACAP1, BCL2A1, CCL5, CCR7, CD83, CXCL13, CXCL2, NFKBIA, PTPN6 |
| CD28 | −2.621 | 0.0385 | BCL2A1, CXCL13, CXCL2, IL27RA, ITGAL, LCP1, NFKBIA |
Figure 6EnrichR analysis of differentially expressed genes (p adjusted < 0.05) with an absolute log2 fold change greater than 1. Gene ontology as determined via “GO Biological Process 2021”. p-values are listed on figure. *: adjusted p < 0.05.