LC-MS reveals dysregulation of phosphatidylcholines in esophageal cancer

LC–MS-based serum metabolomic analysis reveals dysregulation of
phosphatidylcholines in esophageal squamous cell carcinoma☆
Sartaj Ahmad Mir a,b
, Pavithra Rajagopalan a,c
, Ankit P. Jain a,c
, Aafaque Ahmad Khan a,c
, Keshava.K. Datta a,c
,
Sonali V. Mohan a
, Syed Salman Lateef d
, Nandini Sahasrabuddhe a
, B.L. Somani a
, T.S. Keshava Prasad a
,
Aditi Chatterjee a
, K.V. Veerendra Kumar e
, M. VijayaKumar e
, Rekha V. Kumar f
,
Seetaramanjaneyulu Gundimeda d
, Akhilesh Pandey g,h,i,j
, Harsha Gowda a,
⁎
a
Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
b
Manipal University, Manipal 576104, India
c
School of Biotechnology, KIIT University, Bhubaneswar 751024, India
d
Agilent Technologies, Bangalore 560048, India
e
Department of Surgery, Kidwai Memorial Institute of Oncology, Bangalore 560029, India
f
Department of Pathology, Kidwai Memorial Institute of Oncology, Bangalore 560029, India
g
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
h
Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
i
Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
j
Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
a b s t r a c ta r t i c l e i n f o
Article history:
Received 16 February 2015
Received in revised form 10 April 2015
Accepted 3 May 2015
Available online xxxx
Keywords:
Cancer
Cholines
PCs
Lyso PCs
Serum metabolome
Metabolism
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers with poor prognosis. Here, we
carried out liquid chromatography–quadrupole time-of-flight mass spectrometry (LC–Q–TOF-MS)-based
untargeted metabolomic analysis of ESCC serum samples. Statistical analysis resulted in the identification of
652 significantly dysregulated molecular features in serum from ESCC patients as compared to the healthy sub-
jects. Phosphatidylcholines were identified as a major class of dysregulated metabolites in this study suggesting
potential perturbation of phosphocholine metabolism in ESCC. By using a targeted MS/MS approach both in pos-
itive and negative mode, we were able to characterize and confirm the structure of seven metabolites. Our study
describes a quantitative LC–MS approach for characterizing dysregulated lipid metabolism in ESCC.
Biological significance
Altered metabolism is a hallmark of cancer. We carried out (LC–MS)-based untargeted metabolomic profiling of
serum from esophageal squamous cell carcinoma (ESCC) patients to characterize dysregulated metabolites.
Phosphatidylcholine metabolism was found to be significantly altered in ESCC. Our study illustrates the use of
mass spectrometry-based metabolomic analysis to characterize molecular alterations associated with ESCC.
This article is part of a Special Issue entitled: Proteomics in India.
© 2015 Published by Elsevier B.V.
1. Introduction
Metabolomics is a powerful tool to investigate metabolomic pertur-
bations in cancers [1,2]. Metabolomics has been used for identification
of potential biomarkers in breast [3], colorectal [4], pancreatic [5], liver
[6–8], ovarian [9], kidney [10] and prostrate [11] cancers. Perturbation
in the levels of bile acids, histidine and inosine were found in gas chro-
matography–mass spectrometry (GC–MS) and liquid chromatography–
mass spectrometry (LC–MS)-based studies of hepatocellular cancer [8].
Altered levels of metabolites such as acylcarnitines, quinolinate,
4 hydroxybenzoate, and gentisate have been reported in kidney cancer
[12–14]. Several potential biomarkers have been reported in ESCC by
carrying out serum metabolomics [15].
Several complementary analytical platforms such as NMR, GC–MS
and LC–MS are available for analysis of the metabolome [16]. LC–MS is
a suitable and popular platform for in-depth investigation of the metab-
olome owing to its high-throughput nature, sensitivity and relative ease
of sample preparation [17,18]. There are reports pertaining to the me-
tabolome of upper gastrointestinal tract cancers using nuclear magnetic
resonance (NMR) spectroscopy or gas chromatography–mass spec-
trometry (GC–MS) [19–22]. While both of these techniques have their
Journal of Proteomics xxx (2015) xxx–xxx
☆ This article is part of a Special Issue entitled: Proteomics in India.
⁎ Corresponding author at: Institute of Bioinformatics, Unit 1, 7th Floor, Discoverer
Building, International Tech Park, Bangalore 560 066, India.
E-mail address: harsha@ibioinformatics.org (H. Gowda).
JPROT-02154; No of Pages 7
http://dx.doi.org/10.1016/j.jprot.2015.05.013
1874-3919/© 2015 Published by Elsevier B.V.
Contents lists available at ScienceDirect
Journal of Proteomics
journal homepage: www.elsevier.com/locate/jprot
Please cite this article as: S.A. Mir, et al., LC–MS-based serum metabolomic analysis reveals dysregulation of phosphatidylcholines in esophageal
squamous cell carcinoma, J Prot (2015), http://dx.doi.org/10.1016/j.jprot.2015.05.013

advantages, they are not very conducive to structural elucidation of cer-
tain metabolites. For example, NMR analysis is often inconclusive in the
analysis of species containing long chain fatty acid moieties while polar
molecules are difficult to analyze by GC–MS technique without a prior
derivatization step.
We carried out untargeted global metabolomic profiling of serum
from ESCC patients and compared them to age and sex matched con-
trols. Metabolites that showed altered levels were identified and further
characterized by targeted fragmentation in positive and negative ion
mode. Large scale validation of these metabolites might prove useful
in identifying novel blood-based biomarkers of ESCC.
2. Materials & methods
2.1. Sample collection
All blood samples were collected after obtaining approval from the
institutional review board at the Kidwai Memorial Institute of Oncology,
Bangalore, India. Forty blood samples were collected from patients who
underwent curative surgery for the removal of tumor and had histolog-
ically confirmed esophageal squamous cell carcinoma (ESCC). Pediatric
ESCC cases were not included in this study. All the samples were collect-
ed from pre-operative and treatment naïve patients. Healthy subjects
with no prior health conditions such as diabetes and cardiovascular dis-
ease were selected as controls. Blood was collected from patients and
control individuals after obtaining informed consent. The sample details
are provided in Supplementary Table 1. The blood was allowed to clot
for 30 min followed by centrifugation at 2500 rpm for 10 min to collect
serum fractions. Subsequently, the serum samples were stored at
−80 °C until further analysis.
2.2. Metabolite extraction
Metabolite extraction was carried out from 40 ESCC and 10 con-
trol serum samples by adding 400 μl of methanol to 25 μl of serum
followed by overnight incubation at −20 °C. The metabolite extract
was centrifuged at 13,000 rpm for 15 min at room temperature.
The supernatant was collected, dried and stored at −20 °C until
LC–MS analysis.
2.3. LC–MS analysis
The metabolite extracts were reconstituted in 500 μl of 50% metha-
nol and each sample was analyzed in triplicate on 6550 iFunnel Q–
TOF LC–MS (Agilent Technologies, Santa Clara, CA, USA) equipped
with Dual AJS ESI. The metabolites were separated on 1260 infinity
HPLC system (Agilent Technologies, Santa Clara, CA, USA) by injecting
5 μl of the extract on a Polaris (150 × 2 mm, 3 μ; Agilent Technologies,
Santa Clara, CA, USA) column. A final concentration of 5 mM ammonium
acetate was added to both solvent A (methanol: water: acetic acid
75:24:1, v/v/v) and solvent B (methanol: acetic acid 99:1, v/v).The me-
tabolites were resolved on the column by increasing gradient of solvent
B from 10% to 100% over 15 min. The gradient was held at 100% B for
20 min before returning to 10% for re-equilibration for 5 min. Nitrogen
was used as the nebulizing gas. Dual Automatic Jet Stream (AJS)
Electrospray Ionization (ESI) source was kept at a voltage (VCap) of
3500 V in both positive and negative ion mode. The fragmentor voltage
was maintained at 175 V for both ion polarities. The drying gas temper-
ature was 200 °C, drying gas flow rate was 14 L/min and nebulizer pres-
sure was 35 psi. The sheath gas temperature was set at 350 °C with a
flow rate of 10 L/min.
2.4. Metabolite identification and statistical analysis
Raw data were acquired by using MassHunter acquisition software
(Agilent Technologies, Santa Clara, CA, USA) in an untargeted mode.
The data pre-processing was carried out using the molecular feature ex-
tractor (MFE), an in-built algorithm of the MassHunter Qualitative anal-
ysis software. The processed data was then used to generate a list of
unique molecular features with high mass accuracy (b5 ppm). The list
of features generated in MFE was exported to Mass Profiler Professional
(MPP) for interpretation and statistical analysis in the form of com-
pound exchange files (CEF). The CEF files were grouped according to
the conditions and statistical analysis was carried out to find out the
statistically significant dysregulated molecular features in ESCC as
compared to the control serum samples. Supervised principal compo-
nent analysis (PCA) was performed to demonstrate the variance of
metabolomic phenotypes within the two conditions and across all sam-
ples. Statistical evaluation of the data was performed by Welch's un-
paired t-test for the two conditions. A cut-off value of p b 0.01 was
considered statistically significant and Benjamini and Hochberg false
discovery rate was set to 5% for testing corrections [23]. A log trans-
formed fold change of ≥5 and p-value ≤0.01 were the parameters select-
ed to identify metabolites that showed altered levels between the two
conditions. These significantly dysregulated metabolites were identified
by matching accurate mass to personal compound database and library
(PCDL; Agilent Technologies). For those features which did not get an-
notated with PCDL alone, manual identifications were carried out by
matching accurate mass in HMDB [24], LipidMAPS [25] and METLIN
[26] databases.
2.5. Targeted LC–MS/MS analysis
The list of significantly dysregulated molecular features was
exported from MPP as an inclusion list for targeted MS/MS analysis.
The target list contained information about measured mass and reten-
tion time for all the molecular features. MS/MS analysis was carried
out in both positive and negative modes. MS/MS spectra were acquired
at collision energies of 22 and 18 in positive and negative modes, re-
spectively. Q–TOF was operated in extended dynamic range with high
resolution filter mode and spectra were acquired at a rate of one spectra
per second. Mass range was set at 100–1200 m/z for MS and 25–
1200 m/z for MS/MS data. Other parameters such as drying gas temper-
ature, drying gas flow, nebulizer pressure, capillary and fragmentor
voltage were kept the same as that of MS only acquisition as described
earlier.
3. Results
3.1. Comparative metabolite profiling of serum from ESCC patients and
controls
LC–MS analysis resulted in identification of 652 statistically significant
dysregulated molecular features in ESCC as compared to healthy controls
(Supplementary Table 2). PCA analysis of LC–MS results was carried out
to demonstrate the variance between metabolomic phenotypes of ESCC
and control samples (Supplementary Fig. 1). Several lipids such as
glycerophosphocholines (PC), glycerophosphoethanolamines (PE),
sphingomyelins, ceramides, acyl carnitines, glycerophosphoserines and
free fatty acids were identified in serum. Among glycerophosphocholines,
monoacyl glycerophosphocholines or lysophosphatidylcholines (Lyso
PCs) and diacyl glycerophosphocholines were identified. Some PCs and
PEs were found to have the same nominal mass and thus, MS/MS exper-
iments were necessitated to identify the molecules unambiguously. Both
protonated and metallated ions of PCs were identified. Although
[M+Na]+
species were generally predominant, occasionally [M+K]+
species were also observed. Sodiation of a PC was identified by the pres-
ence of an ion at m/z 147 in the MS/MS spectra. Potassium addition was
identified by the presence of an ion at m/z 163 in the MS/MS spectra.
PCs were identified by screening LC–MS/MS profile for fragment ion at
m/z 184.07. Lyso PCs and diacyl PCs fragmented in a similar way, except
that some lyso PCs also gave an additional ion at m/z 104.10. No structural
2 S.A. Mir et al. / Journal of Proteomics xxx (2015) xxx–xxx

information apart from the head group information could be obtained
from the MS/MS in positive mode analysis. Thus, negative mode analysis
was performed to identify the associated acyl chains in each lipid struc-
ture. In the negative mode, PCs were detected in the form of their acetate
adducts. Upon collision induced dissociation (CID), these adducts resulted
in the neutral loss of 74 Da corresponding to methyl acetate from the [M–
H+CH3COO−
] precursor ion [27]. Chain lengths were confirmed by the
presence of signature ions such as those with m/z 255, 253 and 281.
Thus, neutral loss of 74 Da and fragment ions related to acyl chains
were the predominant features in the MS/MS spectra in negative mode.
In addition to these, neutral loss of CO2 from the acyl chain [RCOO−
]
was also observed. Accurate mass-based metabolite database search re-
sulted in large number of possible identifications. Hence, we adopted
the approach of fragment mass filtration and manual inspection of indi-
vidual MS/MS spectra with reproducible retention times for confident
identification of metabolites.
3.2. Phosphatidylocholines as a major class of dysregulated lipids in ESCC
Dysregulation of lipid metabolism has previously been described in
the context of various cancers. Out of 652 dysregulated molecular fea-
tures, fragment mass scanning and manual inspection of data revealed
that 101 metabolites were phosphatidylcholines. Literature search was
carried out to find possible role of identified metabolites in cancer. A
pie chart representation of metabolite class and their potential involve-
ment in cancer is provided in Supplementary Fig. 2.By using targeted
MS/MS in positive and negative mode, structures could be elucidated
for seven metabolites (Table 1), chemical structures for four of which
are provided in Fig. 1. These seven metabolites were identified as PCs
with different fatty acyl chain lengths. Out of the seven PCs, two were
monoacylated species. The levels of PC with m/z 544.34 were increased
and PC with m/z 520.34 were decreased in ESCC as compared to healthy
controls. Two peaks were observed in the extracted ion chromatogram
of m/z 544.34 (Fig. 2) when only one was expected. We analyzed the
sample in negative mode to characterize the second peak. LC chromato-
gram in the negative mode revealed only a single peak corresponding to
peak 1 in the positive mode. Peak 2 may be due to a sodiated species of a
lower analog. This was confirmed by MS/MS analysis of peak 2 in posi-
tive mode, revealing m/z 522.34 as an intense peak along with m/z
544.34, thus confirming sodiation. MS/MS spectra of the acetate adducts
of the two PCs, m/z 544. 34 and m/z 520.34 showed ion at m/z 303 cor-
responding to arachidonoyl (20:4) chain and ion at m/z 279 corre-
sponding to linoleoyl (18:2) chain, respectively in negative mode
(Supplementary Fig. 3). Ion at m/z 544 has a longer chain (20:4) length
than that of ion at m/z 520 (18:2). However, due to increased polarity
by additional double bond, ion at m/z 544 eluted earlier.
Among the other five dysregulated metabolites, levels of two were
increased and the levels of other three were decreased. Diacyl PCs
with m/z 758.57 and 786.60 were increased, whereas, m/z 784.58 was
decreased. Of the other two decreased metabolites, m/z 774.56 has a hy-
droxylated fatty acyl chain and m/z 770.60 has an ether-linked alkyl
chain. Both positive and negative mode analyses were used for the
structural elucidation of these molecules. A representative depiction
for the same is provided (Fig. 3).
A single diagnostic peak at m/z 279 was observed in the negative
mode MS/MS spectra for the acetate adduct of ion at m/z 770.60. This
can be correlated to the presence of a C18:2 acyl chain. Signature ions
at m/z 255, 253 or 227 corresponding to the second acyl chain in the
structure were not present in the MS/MS spectra but a very low intensi-
ty peak at m/z 265 was present (Fig. 4A). The presence of m/z 265 sug-
gests two possibilities. The first one being that this species could be an
ether-linked alkenyl chain with one or more double bonds. But vinylic
species are very stable and give dominant peaks, ruling out this possibil-
ity. Second is that the observed species could be an ether-linked alkyl
chain with only one double bond. In this case, an ion at m/z 267
would be expected but alkyl chains lose two hydrogen atoms to become
more stable vinylic ions on collision induced dissociation [28]. This
would explain the low intense ion at m/z 265. Exact mass measure-
ments with on-the-fly calibration confirmed the presence of an alkyl/
acyl chain combination in the structure. Thus, the structure of ion at
m/z 770.56 was deduced to be a PC (O-18:1/18:2).
MS/MS spectra of the acetate adduct of ion at m/z 774.56 in negative
mode yielded three informative ions at m/z 255, 277 and 295 (Fig. 4B).
Ion at m/z 255 can be correlated to the presence of a palmitoyl chain. Ion
at m/z 295 is not a regular signature ion for any acyl chain, but could be
due to a modification. This modification can be attributed to a hydroxyl-
ated C18:2 acyl chain. This could also be due to the presence of an odd
numbered fatty acyl chain, C19:1. The ambiguity was cleared with the
exact mass measurement of 774.5646 in positive mode against a theo-
retical mass of 774.5648 for PC with hydroxylated acyl chain.
Though isobaric phospholipids contain different acyl chains, the
total number of carbons and the degree of unsaturation remains the
same, making the identification of these species challenging. MS/MS
Table 1
List of dysregulated molecular features identified in ESCC.
S.No Observed mass Retention time (min) Fold change(Log2) Structure Exact mass Formula
1 520.3406 13.5 −11.5 PC (18:2/0:0) 520.3403 C26H51NO7P
2 544.341 13.4 11.4 PC (20:4/0:0) 544.3403 C28H51NO7P
3 758.5698 22.9 8.1 PC (16:0/18:2) 758.5699 C42H81NO8P
4 784.5849 23.1 −9.1 PC (18:1/18:2) 784.5856 C44H83NO8P
5 786.6005 23.4 4.9 PC(18:1/18:1) 786.6012 C44H85NO8P
6 770.6051 24.0 −9.4 PC(O-18:1/18:2) 770.6063 C44H85NO7P
7 774.5646 19.9 −8.7 PC(16:0/h18:2) 774.5648 C42H81NO9P
O
O O
O
O
O
N
+
P
HO H -
A) PC (18:2/ 0:0)
O
O O
O
O
O
N
+
P
HO H -
B) PC (20:4/ 0:0)
O O
O
O
O
O
N
+
P
O H -
C) PC (18:1/ 18:2)
O
D) PC (18:1/ 18:1)
O O
O
O
O
N
+
P
O H -
O
O
Fig. 1. Chemical structures of four phosphatidylcholines that showed altered levels in ESCC
patient sera.
3S.A. Mir et al. / Journal of Proteomics xxx (2015) xxx–xxx

spectra of closely eluting isobaric PCs were indistinguishable as ion at
m/z 184.07 was the only dominant ion in the positive mode analysis.
In contrast, negative mode analysis gave structural information that
allowed identification of isobaric masses. Acetate adduct ion 844.60
has more than three closely eluting isobaric masses. MS/MS spectra of
ion at m/z 844.60 in negative mode revealed two clean MS/MS spec-
tra for two isobaric metabolites. However, MS/MS spectra of the
third isomer had spectral peaks arising from unidentified isobars.
RT (min)
0
20 40
50
100
RelativeIntensity
602.34
Peak 1
Peak 2
B)
C)
0
20 40
50
100
RelativeIntensity 0
20 40
50
100
RelativeIntensity
A)
Fig. 2. Isobars of ion 544.34. (A) LC–MS profile of metabolite extract from ESCC sample. (B) Extracted ion chromatogram of ion 544.34 in positive mode. (C) Extracted ion chromatogram of
ion 602.34 (acetate adduct of 544.34) in negative mode.
742.54
Intensity
Intensity
m/zm/z
184.07
279.23
816.57
255.23
480.31
168.04
671.46
x10 5 x10 7
758.57
125.00
496.34
575.50
0.0
0.4
0.8
1.2
1.6
2.0
0.0
0.4
0.8
1.2
1.6
2.0
900800700600500400300200100900800700600500400300200100
O
255.23
O
279.23
O O
O
O
O
N
+
P
O
H -
184.07
B)A)
Fig. 3. Structure of ion at m/z 758.57 with fragmentation from positive mode and negative mode. (A) MS/MS spectra of acetate adduct ion 816.57 in negative mode. (B) MS/MS spectra of
corresponding protonated ion 758.57.

Along with PC 18:2/18:0 (Fig. 5A) and PC 18:1/18:1 (Fig. 5B), PC
20:2/16:0 (Fig. 5C) was also observed along with signature ions
from other isobaric PC species. Overall, our data demonstrates that
PC levels are significantly altered in ESCC cases as compared to the
healthy control subjects suggesting a dysregulation of choline
metabolism.
4. Discussion
Lipids are pivotal for membrane structure and signal transduction to
support proliferation of cancer cells. There is also accumulating evi-
dence of altered lipid metabolism, particularly de novo lipogenesis in
cancer [29–32]. Several cancer metabolomic studies have identified
the dysregulation of choline and its metabolites with potential implica-
tions in cancer prognosis [33–35]. Phosphocholine levels have been re-
ported to be increased in ovarian and breast cancer [36,37]. Increased
choline kinase activity has been previously attributed to the increased
phosphorylation of cholines in colon cancer [38]. It has been reported
that most of the endogenous phosphocholine moieties are used for
the synthesis of PCs [39]. In addition to choline metabolism, fatty acid
metabolism also plays an important role in lipid synthesis. Increased ex-
pression of several enzymes involved in the metabolism of lipids such
as fatty acid synthase (FASN), acetyl-CoA carboxylase and ATP citrate
lyase (ACL) have been reported in cancers [31,40]. Differential levels
of PCs have been reported in other serum metabolomic studies on
ESCC patients apart from other metabolites [15,41]. The altered levels
of PCs observed in our study indicates underlying aberration of choline
and phosphocholine metabolism in ESCC. This is in agreement with ob-
servations reported by previous studies. The significantly dysregulated
metabolites found in this study are associated with functions such as
cell signaling, energy storage, maintenance of membrane integrity and
stability according to human metabolome database (HMDB) functional
classification. Modulation of signaling pathways are associated with car-
cinogenesis and PCs play an important role in membrane mediated sig-
naling. Dysregulation of PCs observed in this study suggests aberrant
signaling in ESCC. Although altered levels of several PCs were observed
in earlier studies also, structural elucidation remains challenging due to
the presence of many isobaric and isomeric lipid species. We adopted a
tandem mass spectrometry approach in positive and negative modes of
ionization to confirm the structure of seven PCs. Positive mode MS/MS
generated headgroup information and negative mode MS/MS was
carried out to identify associated acyl chains. Thus, the analytical
strategy applied here can be used for confident identification of
phosohatidylcholines and other lipid species. This approach is crucial
in untargeted metabolomics studies where unambiguous identification
is required for hundreds of metabolites.
Human serum contains a wide variety of lipids including phos-
phatidic acids, phosphatidylinositols, phosphatidylserines and
phosphatidylglycerols along with PCs and PEs. Nitrogen containing
PCs dominate the lipid profile because of their higher ionization effi-
ciency. When isobaric masses from other lipid classes co-elute with
PCs, the MS/MS spectra are dominated by the ion of m/z 184.07
and in most cases, no spectral contribution from the co-eluting spe-
cies is observed. In addition to head groups, hydrophobic chains in
the structure also contribute to ionization efficiency. Ester groups
in the acyl chains can be easily protonated as compared to the
ether linked alkyl or alkenyl chains. Hence, in a lipid mixture,
ether lipids are subjected to ion suppression and acylated lipids
and PCs can be detected more readily compared to other classes
of lipids. Therefore, separate methods need to be developed for
the identification of the ether lipids from a mixture. Plasmalogens
are an important class of lipids that protect cells from free radical
attack and oxidative damage [42]. Alkyl/acyl phosphocholine
lipids, such as the metabolite with m/z of 770.60 in the current
study, serve as a precursor to plasmalogens. Their downregulation
may lead to decreased levels of plasmalogen moieties. Overall, by
combing untargeted LC–MS approach with targeted MS/MS of sig-
nificant molecular features, we demonstrate the differences in
serum metabolome of ESCC patients as compared to healthy
subjects.
PC (O-18:1 / 18:2)
O O
O
O
O
N+
P
O
-
O
828.61
663.95
506.23
367.75
279.32
279.32
265.39
265.39
754.58
920.14
119.05
1000900800700600500400300200100
m/z
1.6
2.0
1.2
0.8
0.4
0.0
x103
Intensity
A.
Intensity 900800700600500400300200100
2.5
2.0
1.5
1.0
0.5
0.0
758.53
480.31
611.42
687.46
295.23
255.23
277.22
171.10
832.57
PC (16:0 / h18:2)
x105
B.
m/z
295.23
255.23
O
O
O
O
P
O
O
OOH
-
O
N+
Fig. 4. MS/MS spectra of acetate adducts in negative mode. (A) MS/MS spectra of ion 828.61, acetate adduct of ion 770.60. (B) MS/MS spectra of ion 832.56, acetate adduct of ion 774.56.

5. Conclusions
In the current study, we identified 652 significantly dysregulated
molecular features from ESCC serum metabolome using liquid chroma-
tography time-of-flight mass spectrometry approach. Our results pro-
vide novel insights into the dysregulation of phosphatidylcholines and
associated lipid metabolism in ESCC as compared to healthy subjects.
Large scale validation of these dysregulated metabolites might prove
useful for identification of blood based biomarkers of ESCC.
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.jprot.2015.05.013.
Conflict of interest
The authors declare that they have no conflicts of interest.
Acknowledgments
We thank the Department of Biotechnology (DBT), Government of
India for research support to the Institute of Bioinformatics, Bangalore
(BT/01/COE/08/05). We thank Agilent Technologies for access to instru-
mentation and software. We thank the “Infosys Foundation” for re-
search support to the Institute of Bioinformatics. SAM and KKD are
recipients of Senior Research Fellowship awards from University Grants
Commission (UGC), Government of India. PR is a recipient of Senior Re-
search Fellowship from Council of Scientific and Industrial Research
(CSIR), Government of India. AAK is a recipient of Senior Research Fel-
lowship from Indian Council of Medical Research (ICMR), Government
of India. Dr. Harsha Gowda is a Wellcome Trust/DBT India Alliance
Early Career Fellow.
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C)
770.56
844.60255.23
307.25
481.31
589.80
900800700600500400300200100
5.0
4.0
3.0
2.0
1.0
0.0
x103
Intensity
m/z
279.23
307.25
O
O
O
O
N+
P
-O
O
255.23
O
O
PC (20:2/16:0)
900800700600500400300200100
1.5
1.0
0.0
0.5
770.57
844.60
279.23
168.04 508.34 725.52
A)
x105
283.26
Intensity
PC (18:2/18:0)
m/z
283.26
279.23
O
O
O
O
O
N+
P
-
O
O
O
5.0
4.0
3.0
2.0
1.0
0.0
770.56
844.60281.25
383.28
392.10
794.57
B)
x103
m/z
900800700600500400300200100
Intensity
281.25
O
O
O
O
N+
P
-O
O
281.25
O
O
PC (18:1/18:1)
Fig. 5. MS/MS spectra of isobaric masses of ion 844 (acetate adduct of 786.60) in negative mode. (A) MS/MS spectra of ion 844.60 revealing PC18:2/18:0. (B) MS/MS spectra of ion 844.60
revealing PC 18:1/18:1 (C) MS/MS spectra of ion 844.60 revealing PC 16:0/20:2.

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