Acute proteomic changes in lung after radiation: towards identifying initiating events of delayed effects of acute radiation exposure in non-human primate after partial body irradiation with minimal bone marrow sparing.

Abstract

Radiation-induced lung injury is a delayed effect of acute radiation exposure resulting in pulmonary pneumonitis and fibrosis. Molecular mechanisms that lead to radiation-induced lung injury remain incompletely understood. Using a nonhuman primate model of partial body irradiation with minimal bone marrow sparing, lung was analyzed from animals irradiated with 12 Gy at timepoints every 4 days up to 21 days after irradiation and compared to non-irradiated (sham) controls. Tryptic digests of lung tissues were analyzed by liquid chromatography-tandem mass spectrometry followed by pathway analysis. Out of the 3101 unique proteins that were identified, we found that 252 proteins showed significant and consistent responses across at least three time points post-irradiation, of which 215 proteins showed strong upregulation while 37 proteins showed downregulation. Canonical pathways affected by irradiation, changes in proteins that serve as upstream regulators, and proteins involved in key processes including inflammation, fibrosis and retinoic acid signaling were identified. The proteomic profiling of lung conducted here represents an untargeted systems biology approach to identify acute molecular events in the nonhuman primate lung that could potentially be initiating events for radiation-induced lung injury.

INTRODUCTION

Exposure to high-dose ionizing radiation results in organ-specific sequelae including acute radiation syndromes (ARS) and delayed effects of acute radiation exposure (DEARE). Radiation-induced lung injury (RILI) is a DEARE where RILI displays early phase radiation pneumonitis followed by late phase lung fibrosis (Mah and Van Dyk 1988; Mah et al. 1994). Initiation of cellular damage from radiation exposure results in chronic oxidative stress, tissue hypoxia, inflammation, and fibro-proliferation in lung leading to the development of fibrosis (Rodemann and Blaese 2007; Ding et al. 2013). Efforts to characterize the molecular mechanisms of RILI have included histological, cytokine, gene expression, and proteomic analyses however, the molecular mechanisms that lead to RILI remain incompletely understood (Finkelstein et al. 1994; Chen et al. 2001; Chen et al. 2002; Stone et al. 2003; Jackson et al. 2016; Jackson et al. 2017; Ghandhi et al. 2018; Huang et al. 2019a; Parker et al. 2019; MacVittie et al. 2020).

The partial body irradiation (PBI) with minimal, 2.5% or 5%, bone marrow (BM) sparing NHP model was developed to mimic intentional or accidental radiation exposures in humans. Such exposures are likely to include bone marrow sparing and to permit the concurrent analysis of coincident short- and long-term damage to organ systems in a time and dose dependent manner (MacVittie et al. 2012). RILI in the NHP PBI/BM model has been characterized for clinical, radiographic and histologic endpoints(MacVittie et al. 2019; Parker et al. 2019; Thrall et al. 2019). Additionally, a recent systematic review compared the PBI with minimal bone marrow sparing model to the whole lung thorax irradiation (WTLI) in Rhesus macaques(MacVittie et al. 2020). The dose response relationships of the PBI and WTLI models were equivalent relative to the primary endpoint all-cause mortality and that the latency, incidence, severity, and progression of the clinical, radiographic, and histological indices of lung injury were comparable (MacVittie et al. 2020).

Proteomic profiles and gene expression profiles have been acquired in mouse lung after WTLI (Jackson et al. 2016; Jackson et al. 2017; Huang et al. 2019a). Previous proteomic profiling in the mouse was acquired at radiation doses of 8, 10, 12, and 14 Gy WTLI at 1, 3, and 6 days post-exposure (Huang et al. 2019a). We selected early timepoints after radiation because studies in the murine WTLI model reported that ultrastructural damage and gene expression profiles suggest the response to radiation within the first 24 h post-exposure determines tissue fate (Jackson et al. 2017). Here, we interrogate the proteomic profile of NHP lung after 12 Gy PBI/BM2.5 at timepoints up to 21 days. The proteomic profiling conducted here represents an untargeted systems biology approach to identify acute molecular events that could potentially be initiating events for RILI.

MATERIALS AND METHODS

Radiation animal model.

All animal procedures were conducted in accordance with the NIH guidelines for the care and use of laboratory animals and experiments were performed with prior approval from the University of Maryland Institutional Animal Care and Use Committee (IACUC). Tissue was collected from a similar region of the lung of male rhesus macaques (Macaca mulatta); tissues were snap frozen in liquid nitrogen and stored at −80 ºC until assay. Samples were provided by the laboratory of Thomas J. MacVittie, University of Maryland School of Medicine, Department of Radiation Oncology (Baltimore, MD). Description of the animal models, including radiation exposure and dosimetry, medical management (supportive care and health monitoring), as well as collection of tissue have been previously described (MacVittie et al. 2012). NHP were exposed to 12 Gy partial body irradiation with 2.5% bone marrow sparing (PBI/BM2.5) with 6 MV linear accelerator (LINAC)-derived photons with an average energy of 2 MV at 0.80 Gy min⁻¹. Bone marrow sparing was accomplished with tibiae outside the beam field. Lung was obtained from a natural history study where timed euthanasia was planned at day 4, 8, 15, and 21 after radiation. Additional lung samples were obtained from animals that were euthanized according to criteria specified in the IACUC protocol. We grouped animals from both planned and for-cause euthanasia at day 4, day 8 and 9, day 11 and 12, day 15, and day 21 and 22 to increase the numbers of n at the timepoints across our study. Two non-irradiated animals were used as baseline controls. Thirty-two lung samples were analyzed in total with the numbers of NHP at each time point (n) as follows: day 0 (baseline), n=2; day 4, n=4; day 8-day9, n=11; day 11-day 12, n=7; day 15, n=5; day 21–22, n=3.

Proteomic sample preparation.

Lung tissues were homogenized in 50 mM ammonium bicarbonate buffer (pH 7.8) by bead beating using Precellys CK14 lysing kit (Bertin Corp., Rockville, MD) as described previously(Huang 2019). The lysates were further washed, reduced, alkylated and trypsinolyzed in filter as described previously (Huang et al. 2020b).

Liquid chromatography-tandem mass spectrometry data acquisition.

Tryptic peptides were separated on a nanoACQUITY UPLC analytical column (BEH130 C18, 1.7 μm, 75 μm x 200 mm, Waters) over a 165-minute linear acetonitrile gradient (3 – 40%) with 0.1 % formic acid on a Waters nano-ACQUITY UPLC system and analyzed on a coupled Thermo Scientific Orbitrap Fusion Lumos Tribrid mass spectrometer as previously described (Huang et al. 2019a). Full scans were acquired at a resolution of 240,000, and precursors were selected for fragmentation by collision induced dissociation (normalized collision energy at 35 %) for a maximum 3-second cycle.

Liquid chromatography-tandem mass spectrometry data analysis.

Tandem mass spectra were searched against a UniProt Macaca mulatta reference proteome using Sequest HT algorithm described previously (Eng et al. 2008) and MS Amanda algorithm developed by Dorfer et al. (Dorfer et al. 2014) with a maximum precursor mass error tolerance of 10 ppm. Carbamidomethylation of cysteine and deamidation of asparagine and glutamine were treated as static and dynamic modifications, respectively. Resulting hits were validated at a maximum false discovery rate of 0.01 using a semi-supervised machine learning algorithm Percolator developed by Käll et al. (Kall et al. 2007). Label-free quantifications were performed using Minora, an aligned AMRT (Accurate Mass and Retention Time) cluster quantification algorithm (Thermo Scientific, 2017). Protein abundance ratios between groups were measured by comparing the MS1 peak volumes of peptide ions, whose identities were confirmed by MS2 sequencing as described above.

Bioinformatic and statistical analysis.

Pathway, upstream regulator, and statistical analysis were performed as described previously (Huang et al. 2019b). Proteins showing at least a 2-fold change (FC) with a false discovery rate (FDR) adjusted ANOVA p-value < 0.05 were considered significantly changed and used for further analysis. Ingenuity Pathway Analysis (IPA) analysis was used to predict canonical pathways and upstream regulators according to the proteins that were significantly different using a Benjamini-Hochberg corrected Fisher’s exact test p-value < 0.05, and z-score was used to infer the activity change direction.

Retinoid quantification.

Lung samples were stored at −80 °C until processed. Only glass containers, pipettes, and syringes were used to handle retinoids. Extraction of retinoids was performed under yellow lights using a two-step liquid-liquid extraction that has been described in detail previously using 4,4-dimethyl-RA as an internal standard for RA and retinyl acetate as an internal standard for retinol and total retinyl ester (Kane et al. 2005; Kane et al. 2008b; Kane and Napoli 2010; Jones et al. 2015). Briefly, for the extraction of retinoids, lung tissue was homogenized in 2 mL 0.9 % NaCl (normal saline) and two 1000 μL aliquots were extracted as technical duplicates. To each homogenate aliquot, 3 ml of 0.025 M KOH in ethanol was added to the homogenate followed by addition of 10 ml hexane to the aqueous ethanol phase. The samples were vortexed and centrifuged for 1 to 3 min at 1000 rpm in a Dynac centrifuge (Becton Dickinson) to facilitate phase separation and pellet precipitated protein. The hexane (top) phase containing nonpolar retinoids (retinol and total retinyl esters (RE)) was removed. 4 M HCl (185 μl) was added to the remaining aqueous ethanol phase, samples were vortexed, and then polar retinoids (RA) were removed by extraction with a second 10 ml aliquot of hexane as described above. Organic hexane phases were evaporated under nitrogen while heating at approximately 30 °C in a water bath (model N-EVAP 112, Organomation Associates, Berlin, MA, USA). All samples were resuspended in 60 μl acetonitrile.

Levels of RA were determined by liquid chromatography-multistage tandem mass spectrometry (LC-MRM³) which is an LC-MS/MS method utilizing two distinct fragmentation events for enhanced selectivity (Jones et al. 2015). RA was measured using a Shimadzu Prominence UFLC XR liquid chromatography system (Shimadzu, Columbia, MD) coupled to an AB Sciex 6500+ QTRAP hybrid triple quadrupole mass spectrometer (AB Sciex, Framingham, MA) using atmospheric pressure chemical ionization (APCI) operated in positive ion mode as previously described (Jones et al. 2015). For the LC separation, the column temperature was controlled at 25 °C, the autosampler was maintained at 10 °C and the injection volume was typically 20 μL. All separations were performed using an Ascentis Express RP-Amide guard cartridge column (Supelco, 50 × 2.1 mm, 2.7 μm) coupled to an Ascentis Express RP-Amide analytical column (Supelco, 100 × 2.1 mm, 2.7 μm). Mobile phase A consisted of 0.1 % formic acid in water, and mobile phase B consisted of 0.1 % formic acid in acetonitrile. Endogenously occurring retinoid isomers including all-trans-RA, 9-cis RA, 13-cis RA, and 9,13-di-cis RA are resolved using a gradient separation at a flow rate of 0.4 mL min⁻¹ with gradient conditions described previously (Jones et al. 2015). The APCI source conditions and MRM³ detection parameters were as previously described where the MRM³ transition for RA was m/z 301.1 → m/z 205.1 → m/z 159.1 and for 4,4-dimethyl RA was m/z 329.2 → m/z 151.2 → m/z 100.0 (Jones et al. 2015).

Levels of retinol and RE were quantified via HPLC-UV according to previously published methodology (Kane et al. 2008a; Kane and Napoli 2010). Retinol and RE were resolved by reverse-phase chromatography (Zorbax SB-C18, 4.6 × 100 mm, 3.5 μm) on a Waters Acquity UPLC H-class system and were quantified by UV absorbance at 325 nm. Analytes were separated at 1 ml min⁻¹ with a gradient separation as described previously with a typical injection volume of 30 μl.

The amount of RA, retinol, and RE was normalized per g of tissue. Data are expressed as mean ± SEM with n representing retinoid values for individual NHP. Statistical significance was assessed with a two-sided, unpaired student’s t-test as compared to the baseline value.

RESULTS

Expression of proteins most changed after radiation.

The lung proteome was assayed in NHP after 12 Gy PBI/BM2.5 at various times after radiation up to 21 days after exposure, including 4, 8/9, 11/12, 15, and 21/22 days. To identify the lung proteins that are most altered after radiation, we determined the differential protein expression using liquid chromatography – tandem mass spectrometry-based proteomic analyses. Fig. 1 shows the proteins with significant and consistent changes in expression across at least three time points post-irradiation using an FDR < 0.01, a protein expression FC > 2-fold and an FDR corrected ANOVA p-value cut-off < 0.05. Out of the 3101 unique proteins that were identified, we found that 252 proteins met this criteria, of which 215 proteins showed strong upregulation while 37 proteins showed downregulation.

Figure 1. Expression of proteins most changed after radiation.

LC-MS/MS proteomic analysis of NHP lung after 12 Gy PBI/BM 2.5. Minimum 2-fold change of expression for at least three time points and FDR adjusted ANOVA p-value < 0.05 were criteria for inclusion.

Canonical pathways and upstream regulators altered by radiation.

Based upon the proteins that were significantly changed, we subsequently used bioinformatic pathway analysis to further inform on mechanisms of injury that occur post-radiation. Ingenuity Pathway Analysis (IPA) analysis was used to predict canonical pathways and upstream (Kramer et al. 2014). Table 1 shows canonical pathways that were identified as altered according to the changes in protein expression toward understanding key events. Table 2 shows the inferred upstream regulators toward identifying key signaling nodes. The calculated z-score is a statistical measure of the match between expected relationship direction from published literature and observed gene expression from the experimental dataset. It was used to infer likely activation states of pathways or upstream regulators based on comparison with a model that assigns random regulation directions. We used a Benjamini-Hochberg corrected Fisher exact test p < 0.01 for inclusion of canonical pathways in Table 1 and for inclusion of inferred upstream regulators in Table 2. Three canonical pathways were significantly altered by radiation including acute phase response signaling, LXR/RXR activation, and FXR/RXR activation (Table 1). Seventeen inferred upstream regulators were significantly altered by radiation with MRTFA, MRTFB, and TNF showing the largest activation z-scores (>2). (Table 2).

Table 1. Canonical pathways altered by radiation.

B-H corrected p-value, Fisher’s exact test p-value further adjusted for multi-testing by Benjamini-Hochberg procedure.

Canonical Pathways	B-H corrected p-value	Activation z-score	Measured proteins subjected to regulation
Acute Phase Response Signaling	< 0.02	↑ 2	HP,HPX,ORM1,ITIH4,SAA1,SERPINA3, HRG,LBP
LXR/RXR Activation	< 0.02	↑ 1.89	KNG1,HPX,ORM1,ITIH4,SAA1,S100A8,LBP
FXR/RXR Activation	< 0.05		KNG1,HPX,FABP6,ORM1,ITIH4,SAA1

Table 2. Upstream regulators altered by radiation.

B-H corrected p-value, Fisher’s exact test p-value further adjusted for multi-testing by Benjamini-Hochberg procedure.

Upstream Regulator	Activation z-score	B-H corrected p-value	Measured proteins subjected to regulation
MRTFB	↑ 2.449	< 0.001	CAMP,CPA3,CTSG,ITGA6,LCN2,PRTN3,S100A8,SERPINB10
MRTFA	↑ 2.449	< 0.02	CAMP,CPA3,CTSG,ITGA6,LCN2,PRTN3,S100A8,SERPINB10
Proinflammatory Cytokine		< 0.02	CD55,HP,LCN2,LGALS9,S100A1,TIMP1
NOS2	↑ 1.539	< 0.02	ISG15,ITIH4,LCN2,MB,PIGR,S100A8,SERPINA3,TIMP1,TNFSF10
SAFB		< 0.02	CHD3,HEXA,PFDN4,S100A8,TNFSF10
Ige	↑ 1.58	< 0.02	ALOX5,CD34,CMPK2,Crip2,CXCL16,HLA-DMA,PRKCA,RFX2,RNASE3,STX6,TNFSF10
TCL1A		< 0.02	CAMP,CPA3,CTSG,LCN2,MPO,S100A8
EHF		< 0.02	ALOX5,S100A8,SAA1,SCEL,SERPINA3,TIMP1
HNF4A		< 0.02	ACSS2,C11orf54,CD55,CHMP4A,CLTCL1,ECI2,F12,FAM160A2,FARSB,FUK,GNG5,HEXA,HPX,ITGA6,ITIH4,KNG1,LBP,LCN2,NAA50,ORM1,PALMD,PROZ,PSMD10,RNASE3,SAA1,SAMM50,SERPINA3,SERPINA5,STT3A,TBC1D17,THRAP3,TSNAX,TYMS,UFM1
IFNG	↑ 1.714	< 0.03	ADAM17,ATP1B1,CD55,CMPK2,CXCL16,HLA-DMA,IDI1,IFIT5,ISG15,ITGA6,KRT15,LCN2,LGALS9,MNDA,PIGR,PPP1R1B,PRKCA,RAB12,RBBP7,S100A8,SERPINA5,SYNM,TIMP1,TNFSF10
TRAF3IP2		< 0.03	CAMP,CXCL16,ISG15,LCN2,S100A8
TNF	↑ 2.013	< 0.03	ADAM17,ALOX5,CD55,CLTCL1,CPA3,CXCL16,HEXA,HP,IFIT5,ISG15,ITGA6,KRT15,LBP,LCN2,LGALS9,LSS,MPO,ORM1,PIGR,PRKCA,PRTN3,RFX2,S100A8,SAA1,SERPINA3,SERPINB10,SND1,TIMP1,TNFSF10
SIRT2		< 0.04	IDI1,KRT15,LSS
IL22		< 0.04	HP,LBP,LCN2,S100A8,SAA1,SERPINA3
TGM2		< 0.04	ACSS2,ATP1B3,FARSB,IFIT5,ITGA6,LGALS9,PADI4,S100A8
DDX5		< 0.04	LCN2,S100A4,TIMP1
CSF3		< 0.05	CD34,LBP,LCN2,MPO,PRKCA,PRTN3,TNFSF10

Radiation-responsive proteins with agreement across species.

Proteins identified in this NHP study show agreement across species with a previous proteomic interrogation of murine lung after WTLI (Huang et al. 2019a). Proteins that were observed as changed by radiation in the NHP as well as in the murine lung include the significantly and consistently upregulated KNG1, RPS27L, and SERPINA3. These proteins were involved in inflammatory pathways and DNA repair. Also, LXR/RXR activation was a common canonical pathway dysregulated by radiation in both NHP and mouse (Huang et al. 2019a).

Proteins related to retinoic acid activity.

Previously we reported that RA, a master regulator of cell proliferation, differentiation, and apoptosis, was reduced in lung after WTLI in a mouse model (Jones et al. 2014). As part of this study, we also quantified NHP lung RA using quantitative multistage tandem mass spectrometry (Fig. 2). Similarly, we found that RA was decreased an initial 31% at day 4; RA continued to decline until day 21 where it was reduced 48% (Fig. 2). There were no significant changes in retinol (vitamin A), which is the substrate for RA biosynthesis, except for at day 8–9. There were no changes in total retinyl ester (RE), the storage form of vitamin A. Nineteen proteins were found to be significantly associated with retinoic acid activity by IPA upstream regulator analysis (Fig. 3a). RA also had an activating effect on INFG, where the effect of INFG activation on downstream targets that was also impacted by TNF (Fig. 3b).

Figure 2. Lung RA is decreased after radiation.

Retinoid quantification in lung after 12 Gy PBI/BM 2.5. Days after radiation dose are notated. (a.) RA, (b.) retinol, (c.) total RE. Data is mean ± standard deviation, * p<0.05 using student’s t-test as compared to control (0).

Figure 3. Radiation responsive genes in lung regulated by retinoic acid.

(a) Proteins showing a minimum 2-fold change with an FDR adjusted ANOVA test p-value < 0.05 were selected for upstream regulator inference at a cutoff of Benjamini-Hochberg corrected Fisher’s exact test p-value < 0.0001 and (b) inferred retinoic acid signaling network. Red color of the protein symbols indicates significant upregulation and green color of the protein symbols indicates significant downregulation with intensity of color corresponding to magnitude of upregulation/downregulation. Isotretinoin = RA.

Proteins related to inflammation and fibrosis

Because inflammation and fibrosis are features of RILI, we queried for associations with inflammation and fibrosis among the proteins that were statistically changed after radiation. Fig. 4 shows those proteins associated with inflammation. Inflammatory proteins were upregulated including KNG1, LBP, and SAA1. Fig. 5 shows proteins associated with fibrosis, where there were some proteins that were upregulated (red) and some proteins that were downregulated (green). ALOX5, TIMP1, and MB all exhibited changes that promoted fibrosis (indicated by yellow connections), whereas KNG1, LCN2, LGMN, MPO, and SGCD exhibited changes that suppressed fibrosis (indicated by the blue connections). A number of other proteins including HP, HPX, CD55, ATP1B1, and TYMS have an association without a consensus on the regulatory effect (indicated by the grey connections). Among the upstream regulators identified in Table 2, MFTFA and MRTFB had activation z-scores of >2 and are associated with pulmonary fibrosis. Accordingly, we queried which proteins were regulated by MRTFA and MRTFB, which shared a number of underlying measured downstream proteins (Fig. 6).

Figure 4. Radiation responsive genes in lung related to inflammation.

Proteins showing a minimum 2-fold change with an FDR adjusted ANOVA test p-value < 0.05 were selected for analysis. Red color of the protein symbols indicates significant upregulation and green color of the protein symbols indicates significant downregulation with intensity of color corresponding to magnitude of upregulation/downregulation.

Figure 5. Radiation responsive genes in lung related to fibrosis.

Proteins showing a minimum 2-fold change with an FDR adjusted ANOVA test p-value < 0.05 were selected for analysis. Red color of the protein symbols indicates significant upregulation and green color of the protein symbols indicates significant downregulation with intensity of color corresponding to magnitude of upregulation/downregulation. Yellow connections indicate elevated level of fibrosis while blue connections indicate suppressed fibrosis. Gray connections mean the associations are known but the exact regulatory direction has not been established by consensus views yet.

Figure 6. Radiation responsive genes in lung regulated by MRTFA/B.

MRTFA and MRTFB were identified as upstream regulators in Table 2. Proteins showing a minimum 2-fold change with an FDR adjusted ANOVA test p-value < 0.05 were selected for analysis. Red color of the protein symbols indicates significant upregulation and green color of the protein symbols indicates significant downregulation with intensity of color corresponding to magnitude of upregulation/downregulation.

DISCUSSION

The proteomic profiling data and subsequent bioinformatic analyses presented represent an untargeted systems biology approach to identify acute molecular events that could potentially be initiating events for RILI. Here we interrogate the proteomic profile of NHP lung after 12 Gy PBI/BM2.5 at timepoints up to 21 days, which is similar to our previous murine study that interrogated at 8–14 Gy WTLI doses within 6 days after dose. Efforts to identify the initiating events for DEARE during this time period are justified by reports in which ultrastructural damage and gene expression profiles suggest that the response to radiation within the first 24 h post-exposure determines tissue fate (Jackson et al. 2017). Additionally, there is validity in interpreting these different radiation exposures that result in RILI together, as WTLI and PBI/BM models in NHP have been shown to have the same outcomes and latency, incidence, severity, and progression of RILI (MacVittie et al. 2020). Radiation largely increased protein expression in NHP lung at these timepoints with 85% of the proteins showing consistent upregulation at least 3 timepoints after dose as compared to 15% of proteins that showed a downregulation.

Proteins that were similarly dysregulated in both NHP and mouse models after radiation included KNG1, SERPINA3, and RPS27L. Kininogen-1(KNG1) is an important proinflammatory and pro-oxidant factor, reported to aggravate and accelerate lung inflammation and injury (Shi et al. 2018; Cheng et al. 2021). Increases in KNG1 expression were found in lung tissues of chronic obstructive pulmonary disease models (Shi et al. 2018). Inhibitors of KNG1 relieved cellular inflammation (Shi et al. 2018). KNG1 levels are higher in the bronchoalveolar lavage (BAL) and urine of patients with lung squamous cell carcinoma (Wang et al. 2020b). SerpinA3 (α−1 antichymotrypsin) is a secreted, acute phase protein that is strongly associated with numerous inflammatory diseases (Lannan et al. 2012). SERPINA3 was one of the most upregulated transcripts as indicated by RNA sequencing of lung tissue of NHPs exposed to 10 Gy WTLI. SERPINA3 protein was also upregulated in the BAL and plasma of the same NHP (Thakur et al. 2021). Network analysis of patient lung tissue microarray expression data indicated SERPINA3 plays a mechanistic role in idiopathic interstitial pneumonias, a diffuse group of parenchymal lung diseases with various degrees of inflammation and fibrosis (Chen et al. 2014). SERPINA3 has also been implicated in the development of non-small cell lung cancer and was part of a 7-protein biomarker panel that was shown to be able to distinguish lung cancer from controls in patients (Tian et al. 2016; Jung et al. 2017). RPS27L modulates DNA interstrand cross-link (ICL) repair. RPS27L positively regulates ICL repair by binding with FANCD2 and FANCI (two Fanconi anemia proteins involved in the ICL repair pathway) to prevent their degradation via the autophagy-lysosome system (Sun et al. 2020).

LXR/RXR activation was a canonical pathway altered by radiation that was common to both NHP and mouse ((Huang et al. 2019a). LXR/RXR activation is also observed as changed in other tissues after radiation (Huang et al. 2020a; Huang et al. 2020b). LXR/RXR signaling regulates lipid metabolism, inflammation, and cholesterol to bile acid catabolism (Germain et al. 2006b). FXR/RXR activation was another canonical pathway in lung that was altered by radiation; FXR regulates fatty acid synthesis and triglyceride synthesis, where dysregulation can lead to lipotoxicity and fibrosis. FXR agonism has been shown to decrease fibrosis in multiple animal models (Libby et al. 2021). In addition to lung, acute phase response signaling is a canonical pathway identified as dysregulated in heart, kidney, lymph node, jejunum and plasma ((Huang et al. 2020a; Huang et al. 2020b) (and companion papers submitted to this special issue: Muller et al, Zalesak et al., Huang et al.)

Three upstream regulators had activation z-scores >2 including MRTFA, MRTFB, and TNF. MRTFA and MRTFB are transcriptional co-activators that augment SRF transcriptional activity and mediate increases in CTGF expression during the pathogenesis of fibrosis (Sakai et al. 2017). MRTFA is an important regulator of collagen synthesis in lung fibroblasts (Luchsinger et al. 2011). TGF-β1 regulates the nuclear expression of MRTFA in a Rho kinase-dependent fashion, which in turn mediates smooth muscle actin-α expression (Kumawat et al. 2016). MRTFA-deficient mice are protected from lung fibrosis (Sisson et al. 2015). Targeting the MRTF-SRF pathway was shown to be protective for fibrosis (Sakai et al. 2017). Inhibition of MRTFA can help resolve lung fibrosis by promoting fibroblast apoptosis (Sisson et al. 2015). Pharmacologic inhibition of the MRTF pathway reduced both the number and size of lung metastasis in a melanoma model (Haak et al. 2017).

Retinoic acid is a master regulator of gene expression mainly through ligand-activated control of transcription mediated through retinoic acid receptors (RAR) in the nucleus (Germain et al. 2006a). Previous reports show that retinoic acid is reduced within 24h after irradiation and this deficit persists through 180 days (Jones et al. 2014). Here, RA in NHP lung was similarly decreased at all timepoints through 21 days and decreased up to 48% after 12 Gy PBI/BM2.5. The reduction in lung retinoic acid may have an effect on the inflammatory and immunomodulatory regulators as RA has been shown to regulate a number of cytokines including IL1b, IL5, IL6, IL10, IL17A and TNFα (Gross et al. 1993; Upham et al. 2002; Germain et al. 2006a; Dawson et al. 2008; Xiao et al. 2008; Bai et al. 2009; den Hartog et al. 2013; Bakdash et al. 2015; Larange and Cheroutre 2016). Retinoic acid has also been shown to regulate receptors for some of these molecules including IL1R, IL5Ra, IL6R IL10RA, and TNFRSFIIA (Upham et al. 2002; Lu et al. 2014; Larange and Cheroutre 2016). TIMP1 was a protein associated with both RA activity and with fibrosis (Fig. 3, 5). Recently, the modulation of retinoid signaling in fibrosis and the therapeutic opportunities for repair have been reviewed in detail (Wang et al. 2020a).

Among the proteins associated with inflammation was SAA1, a major acute phase responder and apolipoprotein of the HDL complex. It is synthesized and secreted by the liver as well and is known to increase during acute-phase response due to acute bacterial infection, trauma, inflammatory and autoimmune disease, and neoplasia (De Buck et al. 2016). Elevated levels of SAA1 have been observed after radiation exposure and SAA1 has been reported to have potential biodosimetry and biomarker utility for radiation exposure in multiple species (Ossetrova and Blakely 2009; Bazan et al. 2014; Nylund et al. 2014; Blakely et al. 2018; Ossetrova et al. 2018; Sproull et al. 2019).

One limitation of the study is that tissues were not perfused. In our previous work we showed that perfusion of the lung tissue from a murine model at the time of collection reduced the contribution of circulating proteins (Huang 2019). Among the proteins that are significantly changed after radiation, we do see proteins that were also detected in our plasma proteome profiling and cannot rule out a contribution from blood within the tissue. However, a comparison of our complementary plasma proteomic study (Huang et al. 2020a) reveals that only 12/252 proteins identified as significantly changed in plasma were also detected in lung (<5%). Additionally, 9/12 overlapping proteins have been reported as expressed in lung as well as detected in plasma (HP, HPX, ITIH4, KNG1, ORM1, SAA1, SERPINA3, SERPINA5, and TIMP1). It is also important to note that the protein changes as well as the changes in pathways and biological processes reported here, while statistically significant based upon our data, are putative and need to be further validated.

CONCLUSION

Through an untargeted systems biology approach, we identified proteomic changes that inform on key molecular dysfunction after radiation exposure in an NHP model of radiation-induced lung injury after 12 Gy PBI/BM2.5. These data will be useful for a greater understanding of the initiating molecular events of RILI and a more thorough understanding of the animal models of RILI which could be potentially useful toward the development of medical countermeasures. Additionally, identifying molecular mechanisms of injury may also be useful in the efforts to develop molecular signatures to predict who will be likely to develop delayed lung injury.