Results
Evidence for activated neutrophils in ascites of non-miliary type of tumor spread. Ascites
samples were obtained from 18 patients as described previously [ 9] and classified according
to macroscopic features upon surgery into miliary (11 patients) and non-miliary (7 patients).
Figure 1A indicates proteins caracteristic for NETs according to Brinkmann et al. [ 20] which
were found up -regulated in non- miliary ascites samples (Table S1 ). This observation
indicates functional activation of neutrophils in patients with non-miliary tumor spread. Anti-
oxidant p roteins such as g lutathione S -transferase P (CSTP1 ), glutathione S -transferase
omega-1 (GSTO1) and g lutathione synthetase (GSS) were also found up -regulated in non -
miliary samples (Fig. 1A). In addition, the calprotectin constituents S100A8 and S100A9 were
found up- regulated in these samples. As t he inflammation marker calprotectin is derived
from activated phagocytes, it is linked with local inflammation [30, 31]. In contrast, the liver-
derived systemic inflammation markers C- reactive protein (CRP) and serum amyloid A- 1
protein (SAA1) were found up-regulated in the miliary samples (Fig. 1A).
Evidence for eicosanoids class switching in neutrophils from non-miliary samples . A
comparative analysis of polyunsaturated fatty acids as well as their oxidation products
performed by high -resolution mass spectrometry identified six eicosanoids (14-HDoHE, 17-
HDoHE, 12S -HETE, 15S-HETE, PGE2 and PGB2) significantly up -regulated in the non- miliary
compared to the miliary ascites samples (Fig . 1B and Table S2 ). Remarkably, these
eicosanoids are products from 15-LOX, 12-LOX, and COX enzymes, whereas products of the
5-LOX enzyme [32] were positively identified, but not significantly regulated (Fig. 1B, 1C, S2
and Table 2S). As i nflammatory stimulated neutrophils initially release mainly 5 -LOX
products, this finding suggested that neutrophils in the non -miliary samples had already
switched to 12- LOX, 15 -LOX and COX -products known to be involved in the resolution of
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inflammation [22] (Fig. 1C). The COX -product PGE2 (Fig. 1B) is actually known to further
promote eicosanoid class switching in neutrophils initiating a feed-back loop [22, 33].
Co-association network analysis revealed a strong correlation of six metabo lites with
eicosanoids. In order to learn more about the pathophysiological processes occurring in
ovarian cancer patients, a co-association network analysis was generated. For that, the
proteomics and eicosadomics data presented above were complemented with previously
published data ( metabolomics, transcriptomics , cyto/chemokine analyses and FACS data)
[11]. The results show a molecular network signature with six metabolites ( glutamate,
aspartate, spermidine, spermine, taurine and histamine) establishing a hub in the center of
the network predominantly correlating with eicosanoids. (Fig. 2). All six metabolites show ed
significantly increased concentrations in non- miliary compered to miliary ascites samples
[11] (Fig. 2). Thus, a co -regulation of eicosanoids with metabolites was strongly suggested,
motivating us to investigate the underlying pathomechanism. Remarkably, the ani-
inflammatory cytokine IL-10 was found positively correlated with miliary samples.
Activated neutrophils may account for most molecular alteration s observed in ascites
samples. To verify whether activated neutrophils might represent a plausible source of
deregulated molecules in the non -miliary ascites samples, we performed in vitro stimulatory
experiments with neutrophils isolated from healthy donors. Formation of NETs in a process
termed NETosis eventually result ing from strong neutrophil activation [ 18]. Following
previous studies, isolated neutrophils were treated either with phorbol 12- myristate 13 -
acetate (PMA), inducing NOX-dependent NETosis, or ionomycin, inducing NOX-independent
NETosis [ 34-37]. Proteome profiling demonstrated up -regulation of some NETs proteins
indicated in Figure 1 already after one hour treatment, and upregulation of most indicated
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NETs proteins three hours after treatment with PMA or ionomycin, respectively (Fig. 3 A).
The effect obtained with ionomycin was apparently stronger compared to PMA.
The metabolomics analysis of neutrophil supernatants, focusing on the six metabolites
building a hub in the middle of the network, revealed up-regulation of spermine, spermidine,
histamine, and taurine three hours after treatment (Fig. 3B ). This suggests that neutrophil
activation might also be related to the variations in the metabolic profile [ 11] (Fig. 2) .
Indeed, t he positively charged polyamines have already been described to be released
together with the NETs from activated neutrophils [ 38]. Furthermore, spermine has been
described to attenuate mitochondrial swelling induced from high cytoplasmic calcium
concentrations as caused by ionomycin treatment [ 39]. Thus, in order to verify if we could
reproduce a similar response in vitro, we performed immunofluorescence experiments
aimed to compare the subcellular localization of spermine /spermidine in neutrophils before
and after activation . Apparently the activation with PMA induce d the enlargement of ER,
more powerful than ionomycin, while the polyamines were found to co-localize with both ER
and mitochondria upon treatment (Fig. 3D). As anti-spermine antibodies cannot distinguish
between spermine and spermindine, we extended this analysis with LC- MS analyses of sub-
cellular fractions enriched in mitochondria and endoplasmic reticulum from untreated and
stimulated neutrophils, respectively. Spermidine, but not spermine, was apparently strongly
retained in the ER induced by PMA. Both polyamines were found upregulated in the
mitochondrial fractions upon ionomycin treatment (Fig. 3E).
The biological functions of taurine, but also spermidine and spermine are related to
antioxidant properties [ 40-42]. Upon i nflammation-mediated oxidative stress, taurine may
neutralize toxic oxidants generated from MPO by activated neutrophils [ 40]. Actually,
neutrophils are known to contain very high concentrations of intracellular taurine [40]. Thus,
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the presently observed increased taurine concentrations may also be related to neutrophil
activation resulting in NETosis in non-miliary ascites samples.
Also the eicosanoid analyses results of neutrophil supernatants are consistent with the
suggested role of neutrophils in ascites samples. All six significantly regulated eicosanoids
(Fig. S3A) were found induced upon stimulation with increasing values after one and three
hours, respectively. While the 5-LOX products were found strongly induced upon one hour
treatment, their abundance values was found consistently decreased after additional two
hours (Fig. S3A). In contrast, the similarly induced 12/15 -LOX and COX products did not
decrease upon prolongued incubation. When using 0.01% FCS instead of 10% FCS, even
more contrasting results were obtained due to high endogenous levels of eicosanoids
detected in FCS (Fig . 3C). The results of the eicosadomics analysis were reproduced by
repeating the ex periment with ionomycin using neutrophils isolated from additional five
healthy donors (Fig. S3B).
In summary, the in vitro experiments support the interpretation that activated neutrophils
may represent the primary s ource of the observed alteration s of eicosanoids and
metabolites in ascites samples. Generally, the ionomycin -induced effects on neutrophils
showed higher similarities to the molecular patterns observed in the ascites samples when
compared to the observed effects using PMA, pointing to a rather NOX -independent
activation pathway in vivo.
Higher S100A8/CRP ratios in ascites samples positively correlate with overall survival. In
clinical practice, elevated level of C -reactive protein (CRP) are often associated with
unfavorable disease progression [43]. S100 proteins are regulated differently and thus show
rather poor corrlations with CRP [44-46]. As CRP rather relates to systemic inflammation in
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contrast to S100 proteins, a ratio of these proteins may indicate to what extent
inflammatory deregulation was becoming systemic and thus relate to overall survival.
Higher values of S100A8/CRP ratio were found in non- miliary samples described to have
better prognosis (Fig. 4B). In order to compare the present data with a non -neoplastic but
severe inflammatory disease, liver cirrhosis was included in the present considerations.
Remarkably, the S100A8/CRP ratio was found at similar rates in patients with miliay tumor
spread compared to patients with liver cirrhosis.
NETs proteins and S100A8/CRP ratio may serve as prognostic biomarker.
To collect additional evidence for neutrophil activation in an other kind of tumor and its
potential association with overall survival, we re -evaluated published proteomics data from
our laboratory generated from the analysis of cerebral melanoma metastases [ 47].
Melanoma patient s (n=18), undergoing a MAPKi therapy, were classified depending on
progression-free survival (PFS) in good ( PFS ≥ 6 months) and poor responder (PFS ≤ 3
months). Comparing these two groups, the present analysis revealed significant up-
regulation of several neutrophil -specific proteins, labeled in orange , in metastases isolated
from good responder s compared to those of poor responder s (Fig.5A). Actually, similar to
one hour neutrophils treatment (Fig . 3A), here we observed no release of histones but
higher levels of CTSG suggesting neutrophil activation not necessarily resulting in NETosis.
Anyhow, the molecular signatur of neutrophil activation was also associated with better
prognosis in the melanoma patients.
In addition, we re-evaluated proteomics data from other laboratories regarding
chemotherapy-naive HGSOC patients [48]. Again, NETs proteins were found up-regulated in
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patients more sensitive to chemotherapy (n = 14, median disease-free survival or PFS = 1160
days) in comparison to chemoresistant patients (n = 11, median PFS = 190 days) (Fig. 5C).
Intriguingly, CRP was not found significantly regulated in both studies . However, the
S100A8/CRP abundance ratio was found decreased in the group of patients with poor
outcome (in poor responders and patients resistant to chemotherapy, Fig. 5B and 5D) . This
finding suggested that the validity of S100A8/CRP abundance ratio could be extended as
prognostic biomarker from ovarian cancer to melanoma.
However, CT45 (cancer/testis antigen 45) protein was reported to represent the best
possible prognostic marker for long-term survival in the ovarian cancer study (Fig. 5 C and D)
[48]. Re-grouping the HGSOC patients in this study according to overall survival with OSD 1000 (n = 15) revealed that S100A8/CRP abundance ratio
significantly stratified these groups (Fig. 5F). While CT45 protein seems to better predict
chemotherapy response, S100A8/CRP seems to better predict overall survival.
In line , the S100A8/CRP abundance ratio was again found significantly up- regulated in the
group of patients with OSD > 1000 as calculated from proteomics data of metastatic tumors
isolated from HGSOC patients combining the study of Coscia et al. [ 48] and a more recent
study (Fig. 5G and H, n = 36 ) [49]. Kaplan-Meier analysis confirmed that patients with an
S100A8/CRP abundance ratio equal or above a cutoff value of 3.038 showed again a
significantly longer overall survival time compared to patients with values below this cutoff
(Fig. 5I). NETs proteins and S100A8/CRP ratio were up -regulated in ovarian cancer patients
with favorable outcome of another recent study [50] (Fig. S4A). Thus, we calculated the ratio
of the two proteins in a total of six studies (Fig. 1A, 5A- 5G, and S4 ) representing all kinds of
variations based on different patient cohorts and methodological details . Indeed, the
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S100A8/CRP ratio was found significantly correlated with overall survival (n = 116, Fig. 5J,
TableS5).
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Figure Legends
Figure 1: Untargeted m ulti-omics analysis of ascites samples. A - Proteomics, the volcano
plot show s the results of comparative analysis between miliary and non -miliary ascites
samples. Black lines represent threshold criteria for significant regulation with p-value 2. NETs proteins are labeled in orange , whereas blue and red labeled
proteins are related to local and systemic inflammation , respectively. Selected proteins
linked to oxidative stress are labeled in green. B - Eicosadomics, boxplots show abundance
levels at a logarithmic scale based on 2 of significantly regulated eicosanoids in non -miliary
in comparison to miliary ascites samples (adjusted p -value < 0.05). In case of 5S-HETE,
regulation was not significant. C – Eicosanoid class switching, three main precursors of
eicosanoids are shown in the middle (AA, EPA, DHA) and eicosanoids are grouped dependent
on enzymes from which they are synthesized (5-LOX, 12-LOX. 15-LOX and COX).
Figure 2: Network signature. A co-association network was built with molecules
(eicosanoids, metabolites, proteins, RNA) and immune cells which were significantly
regulated in non -miliary compared to miliary ascites samples. Six metabolites (Asp, Glu ,
taurine, histamine, spermidine, spermine) within inner circle built a hub in the middle of the
network and were strongly regulated by many eicosanoids along outer circle.
Figure 3: Targeted m ulti-omics analysis of neutrophil s. Neutrophils isolated from hea lthy
donors (n=3) were treated with PMA (25nM) or i onomycin (4µM). The cell supernatants
were isolated and analyzed. Error bars indicate standard deviation. A - Proteomics, the fold
change in comparison to untreated samples of NETs proteins and S1008/9 proteins is shown.
B - Metabolomics, the regulation upon treatment of six metabolites as fold change
compared to untreated samples is represented . A fold change value lower than 1 means
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down-regulation and a value higher than 1 indicates up -regulation. C - Eicosadomics, the
abundance of selected eicosanoids as total area normalized to global deuterated standards
(TAN) is blotted. Neutrophils (n=3) were cultured in RPMI medium supplemented with 0.01%
FCS. D - Immunolocalization of spermine /spermidine in neutrophils. Comparison between
untreated CONTROLS, or activation (PMA or IONOMYCIN, 1h). Spermine /spermidine
(SPE./SPD.) is depicted in white, mitochondria (TOM20 protein) in re d and endoplasmic
reticulum (ER) in green. Nuclei are counterstained in blue with DAPI. Merged images are
provided as fluorescence confocal images with or without transmitted light channel for
visualization of cellular morphology in addition to the structures of interest. Scale bars stand
for 5 µm . E - Mitochondria and endoplasmic reticulum, the organelles were isolated by
sucrose gradient from lysed neutrophils. The fold change of spermidine (Spd) and spermine
(Spe) in the endoplasmic reticulum (ER) as well as the mitochondria ( Mit) by comparing
treated and untreated cells are highlighted.
Figure 4: Inflammation marker expression and ratios . The volcano plots illustrate results of
comparative analysis using shotgun proteomics data between three groups of ascites
patients: non -miliary vs . miliary (left), non- miliary vs . cirrhosis (middle) and miliary vs.
cirrhosis (right). Only selected proteins usually related to local - (blue) and systemic (red)
inflammation are marked. Proteins above black lines are significantly regulated with FDR-
value 2 (A). The abundance ratios within each patient group of data
obtained from the shotgun analysis for S100A8 and CRP (B).
Figure 5: Shotgun proteomics analysis of tumor tissue samples isolated from melanoma
and HGSOC patients. The volcano plot is showing the difference in protein abundances
between cerebral metastases samples of melanoma patients, which upon MAPKi treatment
were grouped in the poor (n=13, PFS ≤ 3 months) and good responder (n=5, PFS ≥ 6 months)
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(A). The volcano plots represent the difference in protein abundances between omental
tumor tissue samples of HGSOC patients grouped: dependent on chemotherapy treatm ent
response in resistant (n=11) and sensitive (n=14) (C) and dependent on overall survival in the
patients with 1000 1000 (E, G) . In all volcano plots, proteins above black lines were
significantly regulated. The same significant regulation criteria were applied as reported in
the original publi cations. Boxplots represent the S100A8/CRP abundance ratio in melanoma
patient (B), HGSOC patient groped in resistant and sensitive (D, H) as well as HGSOC patients
grouped in patients with 1000 > OSD < 1000 (F, H) . Additionally, the abundance distribution
of CT45 protein (cancer/testis antigen 45) among four groups of HGSOC patients (n = 25) is
shown (D, F). Kaplan-Meier analysis of survival probability based on S100A8/CRP abundance
ratio (I). In tissue samples of 36 HGSOC patients, an optimal cutoff of 3. 038 for the
S100A8/CRP abundance ratio was found. P atients with the S100A8/CRP abundance ratio
higher or lower than the cutoff value were compared. Boxplots show the distribution of the
S100A8/CRP abundance ratio after pulling datasets generated in six ind ependent studies (J).
See Table S5 for detailed information about patients and samples included in this datasets..
NETs proteins are labeled in orange. Proteins usually linked with local inflammation were
marked in blue and in red were labeled protein related to systemic inflammation. PFS -
progression-free survival. OSD - overall survival days. * - indicate p-value < 0.05.
Figure 6: A - Proposed model for NOX-independent NETs formation in HGSOC patients.
Increase of cytosolic Ca
2+ concentration activates and translocates several calcium-
dependent and calcium -binding proteins, thus inducing hydrolysis of plasma membrane
lipids (releasing PUFAs AA, EPA, and DHA) via activation of a calcium-dependent PLA. Among
enzymes (5 -LOX, 12 -LOX, 15 -LOX, COX an d CYP450) which metabolize these PUFAs into
eicosanoids, only 5-LOX binds Ca 2+. Under conditions of prolongated high intracellular Ca 2+
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concentration, the activity of 5 -LOX enzyme is decreased, resulting in eicosanoid class
switching process, exemplifie d by 5S-HETE. Additionally , elevated Ca2+ levels promote
translocation of calmodulin to SK3 receptor imbedded into plasma membrane, inducing
receptor activation and induction of ROS production from mitochondria resulting in NETosis.
The S100A8/9 protein complex is released with the NETs. The sustained Ca2+ influx in the cell
affects mitochondrial function and may initiate apoptosis . To attenuate this effect, the
permeability transition pore channel and Ca 2+ entry channels, gets closed by sp ermine (Sp).
At the same time, the cell may use all three metabolites ( spermine Sp, spermidine Sd and
taurine Ta) as ROS scavenger to deal with increased oxidative stress . Both positively charged
polyamines stabilize DNA strands , and thus get released together with the NETs. We
postulate that glutamine Glu released from cancer cells under hypoxic conditions may
induce Ca2+ influx in neutrophils by the activation of specific membrane receptors .
Glutamine may also promote neutrophil activation by inducing the secretion of IL8 and
PGE2. Whereas IL8 is a well -known chemoattractant and inducer of NETosis, PGE2 can
induce eicosanoid class switching as observed in ascites samples. The dotted arrows indicate
NOX-dependent NETosis and additional pathways via store-operated calcium entry (SOCE)
promoting intracellular calcium mobilization. B – Strong correlation between NETs
formation, angiogenesis and the type of tumor spread in HGSOC , selected proteins,
eicosanoids, metabolites, immune cells or processe s are depicted apparently regulated in
miliary or non-miliray ascites samples. Strongly activated neutrophils, most probably by
shedding the millet -like and freshly build small tumor nodules, promote building of bigger
but fewer in number of tumor nods in the non -miliary type. In miliary spreading tumors up -
regulated IL -10 inhibits NETs formation. Additionally, n eutrophils depending on their
activation status modulate the immune system by determining the immune cell composition
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25
in the tumor microenvironment. Otherwise, increased angiogenesis associated with
increased blood supply may contribute to less suppressive effects on neutrophils activation
in the non -miliary type. PLA - phospholipase A; Asp – aspartate, His - histamine; calcium
release-activated channel (CRAC); PKC - protein kinase C; FGFb - fibroblasts growth factor
best; Eicos. - eicosanoids; NTK - natural killer T - cells; Treg - regulatory T cell.
Graphical abstract, NETs releasing neutrophils through detaching of small tumor nods
dictate the building of bigger in size and fewer in number of tumors in the non- miliary
spreading tumor. Increased angiogenesis associated with increased blood circulation may
contribute to l ess suppressive effects on NETs formation in the non- miliary tumor type.
Tumor origin, i.e. fallopian tube for the miliary or ovary for the non -miliary tumors, may
influence the angiogenesis and therewith – through facilitating of neutrophils activation –
(co)determine the type of tumor spread.
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Figure 1
A
B
C
log2 LFQs
‐log p‐value
Up‐regulated
in non‐miliary
Up‐regulated
in miliary
SAA1
S100A9
S100A8
CRP
HIST1H3A
HIST1H4A (H4)
HIST1H2A
CTSG
BPI
MPO
LTF
MMP9
HIST2H2BE
HIST1H2BM
ELANE
GSTP1
GSS GSTO1
HIST1H2AC
5LOX EPA DHA
AA
COX15LOX
15S‐HETE17HDoHE
5S‐HETE
LTB46‐trans‐LTB4
12‐epi‐LTB4
4‐HDoHE*7‐HDoHE*RvD5*
PGE2PGB2
Significantly up‐regulated in non‐miliary
Non‐significantly regulated
* Not measured in neutrophil samples
12LOX
12S‐HETE14‐HDoHE
12‐HEPE*
-10
-5
0
14-HDoHE
-8
-6
-4
-2
0
2
12S-HETE
-8
-6
-4
-2
0
2
15S-HETE
-15
-10
-5
0
PGE2
-15
-10
-5
0
PGB2
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Figure 2
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0
1
2
3
4
Ionomycin‐3h
0
1
2
3
4
5
6
Ionomycin‐3h
0
5
10
15
PMA‐3h
0
1
2
3
4
PMA‐1h
Fold change in comparison to untreated sample
AB
Fold change in comparison to untreated sample
CE
D
Figure 3
0
1
2
3
4
5
6
PMA‐1h
0
1
2
3
4
5
6
Ionomycin‐1h
0
1
2
3
4
5
6
PMA‐3h
0
1
2
3
Ionomycin‐1h
Fold change in comparison to untreated sample
Endoplasmic reticulum
Mitochondria
5S-HETE
LTB4
6-t
ran
s-LTB4
12-epi-
LTB
4
12S-H
ETE
14-HDoH
E
15S-H
ETE
17-H
Do
HE
PG
E2
PG
B2
TAN(log2)
5‐LOX 12 ‐LOX and 15‐LOX COX
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Up‐regulated in
non‐miliary
Up‐regulated
in miliary
Up‐regulated in
non‐miliary
Up‐regulated
in cirrhosis
Up‐regulated
in miliary
Up‐regulated
in cirrhosis
‐log p‐value
log2 LFQs
Figure 4
log2 LFQs log2 LFQs
A
B
non miliary
miliarycirrhos
is
-10
-5
0
5
10
SAA1S100A8
S100A9
CRP
S100A8
S100A9
CRP
SAA1
S100A8
S100A9
CRP
SAA1
*
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SAA1
S100A9
CRP
S100A8
LTF
MMP9
MPO
CTSG
CT45
Sensitive
HIST1H4A (H4)
Resistant
log2 LFQs
‐log p‐value
A
HIST1H4A (H4)
Up‐regulated
in poor
responders
good r
esp
ond
er
poor resp
onder
S100A8 /CRP
Se
ns
itive
Re
sis
tan
t
0
2
4
6
8
10
S100A9
S100A8
MPO
LTF
MMP9
CTSG
SAA1
CRP
Up‐regulated
in good
responders
log2 LFQs
‐log p‐value
B
C
D
Figure 5
CT45 CRP
S100A9
CTSG
S100A8
MMP9
SAA1
LTF
MPO
HIST1H4A (H4)
OSD
> 1000
OSD
1000OSD 1000
OSD
10
00
OSD10
00
OSD<10
00
20
25
30
35CT45
J
I
n=36
Up‐regulated
in poor
responders
Sens
itive
Resis
tant
0
2
4
6
8
10S100A8/CRP
fov
orable
unfavorable
-5
0
5
10
15
n = 116
p = 1.9E‐07
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NADPH
oxidase
LTF
CTSG
HISTH4A
MPO
MPO
5S‐HETE
STIM
ROS
Glu
Glu
Ta
TaROS
Sd
SdROS
Sp
Sp
Sp
Asp
ROSROS
ROS
Sp
PKC
ROS
Figure 6
IL‐8
IL‐8
PGE2
PGE2
PGE2
IL‐8
Sd
A
B
Ca2+
CD8+
NKT
Treg
CD4+ IL‐10
IL‐10
IL‐16
Glu
IL‐8
IL‐8
IL‐8
Eicos.
Sp
Sd
Ta
Glu
FGFb
Asp
His
Glu
SAA1
miliary non‐miliary
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Graphical abstract
miliary non‐miliary
miliary
non-mil
iary
-5
0
5
10S100A8 / CRP
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