Proteomics Study Reveals That Docosahexaenoic and Arachidonic

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Bioactive Constituents, Metabolites, and Functions

Proteomics Study Reveals That Docosahexaenoic and Arachidonic Acids Exert Different in Vitro Anticancer Activities in Colorectal Cancer Cells Ignacio Ortea, Maria Jose Gonzalez-Fernandez, Rebeca P Ramos-Bueno, and Jose Luis Guil Guerrero J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b00915 • Publication Date (Web): 26 May 2018 Downloaded from http://pubs.acs.org on May 26, 2018

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Journal of Agricultural and Food Chemistry

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Proteomics Study Reveals That Docosahexaenoic and

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Arachidonic Acids Exert Different in Vitro Anticancer Activities

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in Colorectal Cancer Cells

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Ignacio Orteaa*, María José González-Fernándezb, Rebeca P. Ramos-Buenob,

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and José Luis Guil-Guerrerob

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a

IMIBIC, Hospital Universitario Reina Sofía, Universidad de Córdoba, E14004, Córdoba,

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Spain. b

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Food Technology Division, Agrifood Campus of International Excellence, ceiA3, University of Almería, E40120, Almería, Spain

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* Corresponding author, [email protected]; Phone +34 957 213 757

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ACS Paragon Plus Environment


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ABSTRACT Two PUFAs, DHA and ARA, as well as derivatives such as eicosanoids, regulate

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different activities, affecting transcription factors and therefore DNA transcription, being a

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critical step for the functioning of FA-derived signalling. This work has attempted to

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determine the in vitro anticancer activities of these molecules linked to the gene

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transcription regulation of HT-29 colorectal cancer cells. We applied 3-(4,5-

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dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test along with lactate-

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dehydrogenase (LDH) and caspase-3 assays; proteome changes were assessed by

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‘sequential windowed acquisition of all theoretical mass spectra’ (SWATH-MS)

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quantitative proteomics followed by pathway analysis in order to determine the affected

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molecular mechanisms. In all assays, DHA inhibited cell proliferation of HT-29 cells to a

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higher extent than ARA and acted primarily by down-regulating proteasome particles,

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while ARA presented a dramatic effect on all six DNA replication helicase particles. The

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results indicated that both DHA and ARA are potential chemopreventive agent candidates.

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KEY WORDS ARA; colorectal cancer; DHA; proteomics; PUFA; SWATH

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INTRODUCTION Colorectal cancer (CRC) has one of the highest mortality rates. The fact that large

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regional differences exist in the incidence and mortality of CRC suggests a close

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relationship between genetic and environmental factors, with diet and lifestyle being two of

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the most determinant for CRC incidence. Diet is widely recognised as a critical factor for

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cancer risk and mortality.1

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Free fatty acids (FFAs) assume a critical part in many biological roles. Apart from

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serving as precursors of a wide range of signalling and structural molecules, they are used

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to obtain energy.2 Although many of the circulating FFAs are bound to albumin, the small

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fraction of unbound FFAs in the aqueous phase mediate physiological activity and are most

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sensitive to changes in health and disease; they are also transported across membranes.3

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Previous data have recognised the importance of certain polyunsaturated FAs (PUFAs)

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for the prevention of CRC, while the results from epidemiological studies have suggested a

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negative correlation between both CRC development and PUFA intake.4 Some studies have

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also found that, in vitro, some PUFAs increase the cytotoxicity of different

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chemotherapeutics in brain, lung, breast, sarcoma, lymphocytic and colon human cell

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cultures.5 The degree of in vitro anticancer activity of various FAs has been related to their

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chemical structure, both of which increase such actions. Montaung et al.6 evaluated the

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cytotoxic capacity of most of the FAs of interest in a combined manner in prostate cancer

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cells.

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n-3 PUFAs have been correlated with CRC preventive effects while n-6 PUFAs have

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shown a positive association with CRC, although some authors have undermined this

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archetype by proposing more complex functions for PUFAs.7,8 Because of the nutrition and

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health claims made on n-3 PUFAs, they are widely available in a ‘nutraceutical’

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formulations.9 Although n-6 PUFAs show a positive association with CRC risk,9 some

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studies have also found that arachidonic acid (ARA, 20:4n6) inhibits the growth of some

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cancer cell lines, such as Caco-2, but not HT-29.10 In addition, eicosanoids, biologically

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active molecules derived from ARA, have been proposed as mediators involved in

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intestinal epithelial homeostasis; other studies have linked hydroxyeicosatetraenoic acids

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(HETEs), metabolised from ARA by the lipoxygenase (LOX) pathway and cytochrome P-

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450 isozymes, with cancer-related processes such as cell apoptosis and proliferation,

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angiogenesis, or metastasis.11-13 But because of the contradictory effects of the

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manipulation of the ARA cascade,12,14 the mechanisms that mediate these effects remain

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unclear.

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Different mechanisms have been suggested to participate in the anticancer activities of

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n-3 PUFAs, such as apoptosis promotion, inhibition of cell transformation and repression

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of cell proliferation. Many of them have been associated to the repression of eicosanoids

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production from n-6 PUFAs.15 Previous studies have tested the inhibition of HT-29 cell

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proliferation produced by some n-3 FAs. Docosahexaenoic acid (DHA, 22:6n3) strongly

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and dose-dependently promotes apoptosis, and it enhances many cellular responses that

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decrease cell proliferation. Because DHA is promptly integrated into cancer cell

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membranes, considerable research has been conducted on membrane–initiated phenomena.

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For instance, DHA has been described to take part in the promotion of apoptosis and the

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inhibition of both in vivo and in vitro proliferation. However, the role of DHA on cell cycle

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regulation has been scarcely studied on cancer cells, and therefore the mechanisms of

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action of DHA are not yet entirely understood.16

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As for ARA, previous studies have debated whether the increased ARA metabolism

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found in cancer cells is an initiator or an output of tumour progression. Studies on COX-2

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and its inhibitors have strongly supported the notion that the induction of COX-2 is a

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critical step in carcinogenesis and tumour growth. A previous study has also shown that

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unesterified ARA is an important signal for apoptosis and that the apoptosis promotion by

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nonsteroidal anti-inflammatory drugs and other inhibitors of ARA metabolism results from

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ARA accumulation.17. Bishayee and Sethi18 have stated that the ARA pathway, a metabolic

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process, plays a key role in carcinogenesis. Hence, previous studies have considered the

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ARA pathway metabolic enzymes phospholipase A2s, cyclooxygenases (COXs) and

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lipoxygenase (LOX) – together with the metabolic derivatives of these enzymes, such as

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prostaglandins and leukotrienes – to be new targets for the prevention and treatment of

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cancer.

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This work has attempted to determine the in vitro anticancer activities of DHA and

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ARA, based on the regulation of gene transcription in HT-29 CRC cells. To do so, we

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performed different cell assays and studied protein abundance changes induced by DHA

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and ARA in the global proteome of these cells by means of a quantitative proteomics

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approach based on liquid chromatography–mass spectrometry (LC-MS) called “sequential

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windowed acquisition of all theoretical fragment ion mass spectra” (SWATH-MS)19

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followed by pathway analysis.

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MATERIALS AND METHODS

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Oil Samples

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Two commercial oils, DHASCO® and ARASCO®, 40% DHA and 40% ARA,

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respectively, obtained from the Market Bioscience Corporation (Columbia, MD, USA),

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were used as a source for obtaining DHA and ARA FFAs. DHASCO® and ARASCO® are

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produced by combining high oleic sunflower oil with an oil obtained from a unicellular alga

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(Crypthecodinium cohnii) and a fungi (Mortierella alpina ), respectively.

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Purification process

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ARA and DHA as FFAs were purified from 40 mg of DHA- or ARA-ethyl ester

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according to a previously described chromatography process,20 using mixtures of n-hexane

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and acetone as eluting solvents in the sequence shown in Supplementary Table S1,

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optimized for maximizing PUFA purity, and at flow rates of approximately 1–2 mL/min.

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Eluting fractions were collected in labelled tubes and analysed directly using GLC to

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determine the purity grade. Subsequently, the ethyl esters were acidified according to

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Vázquez and Akoh’s approach.21 FFAs were obtained in this manner.

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GLC analyses

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A GLC device (Focus, Thermo Electron, Cambridge, UK) combining a flame ionisation

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detector with a capillary column (30 m x 0.25 mm ID x 0.25 µm) (Omegawax 250, Supelco

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(Bellefonte, PA, USA)) were used for FA ethyl esters analysis. Temperature of the oven

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was programmed as follows: 90ºC for 1 min, increase to 100°C in 1 min, then 3 min at

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100°C, increase of 6ºC/min until reaching 260°C, and finally a step of 260°C during 5 min.

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The injector temperature was set to 250°C, with a split ratio of 50:1 and an injector volume

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of 4 µL. The detector temperature was set to 260°C. Nitrogen carrier gas flow was 1

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mL/min.

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Cell assays The cell line used for the assays was HT-29 (colon cancer), kindly provided by the

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Technical Instrumentation Facility of the University of Granada (Granada, Spain), and

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incubated at 37°C and 5% CO2 in Gibco RPMI 1640 medium 1640 (Thermo Fisher

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Scientific, Waltham, MA, USA) with penicillin-streptomycin (100 mg/ml), 1-glutamine (2

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mM), sodium pyruvate (1mM) and 5% foetal bovine serum. Cell cultures and a 3-(4,5-

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dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test were conducted as

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detailed in previous works.22

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Final concentration of the purified acyl species (acetone-diluted ARA-FFA or DHA-

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FFA) added to the medium was in the range of 50–600 µM. The final concentration of

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acetone added to culture medium, was 1% (v/v). Control cells were also cultured with a

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medium containing 1% acetone. Lactate dehydrogenase (LDH) assay (the In Vitro

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Toxicology Assay Kit, Lactic Dehydrogenase base, Sigma TOX 7, Sigma-Aldrich, St.

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Louis, MO, USA) was conducted as for the MTT assay but with a cell density of 5 ×

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103 cells/well, and measures were performed following the manufacturer’s instructions. The

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results were obtained by determining the absorbance at 490 nm with a reference filter at

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690 nm at 48 h and 72 h. For measuring caspase-3 activity we used the Caspase-3 Assay

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Kit (Sigma CASP-3-C, Sigma-Aldrich, St. Louis, MO, USA) following the instructions

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from the manufacturer and determining the absorbance (450 nm) at 90 min, with a cell

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density of 1 x 107.

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Proteomics analysis

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Sample preparation

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HT-29 cells from three different groups – DHA (600 µM DHA, added to the culture

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medium at 24h), ARA (600 µM, added at 24h) and control (no acyl species added) – were

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recovered and lysed. Protein extracts were obtained from six biological replicates for each

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group, and protein content was solubilized in 0.2% RapiGest SF (Waters, Milford, MA,

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USA) after precipitation. Protein content in each sample was determined using a nano-

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fluorimetric assay (Qubit Protein Assay, Thermo Fisher Scientific). 40 µg of protein was

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digested with trypsin (Promega, Madison, WI, USA) as previously described23 in two steps,

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incubating at 37ºC for 2 h in the first step and for 15 h in the second step. RePliCal iRT

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peptides (PolyQuant GmbH, Bad Abbach, Germany) were spiked into each sample in order

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to calibrate the peptide retention times in the SWATH runs.

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Creation of the spectral library

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For building the spectral library, equal mixtures of the six biological replicates from

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each condition were pooled and analysed using a shotgun data-dependent acquisition

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(DDA) approach by nano-liquid chromatography coupled to tandem mass spectrometry

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(nLC-MS/MS) as described elsewhere24. The equipment used was a Sciex Triple TOF

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5600+ (Redwood City, CA, USA) coupled to an Eksigent Ekspert nLC415 (Sciex)

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equippled with a reversed phase capillary column (Acclaim PepMap C18, Thermos Fisher

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Scientific). Detailed LC and mass spectrometry parameters used can be found in the

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Supplementary Material.

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DDA runs were searched against a human Swiss-Prot protein database (20,200 entries,

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appended with the sequences from the RePliCal iRT peptides) using Protein Pilot (Sciex,

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version 5.0.1), setting a false discovery rate (FDR) threshold of 0.01. SWATH Acquisition

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MicroApp (version 2.0, Sciex) was used for building a peptide spectral library containing

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the peptides identified in the database search with a confidence score above 99%.

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SWATH data acquisition and analysis

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Two µL of each of the six biological replicates from each group was run in the same LC

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parameters and MS equipment described above for the DDA runs, but using a SWATH

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data-independent acquisition (DIA) method instead. Mass spectrometry parameters used in

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the SWATH method are detailed in the Supplementary Material. Briefly, it consisted on the

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acquisition of 60 MS/MS events with precursor isolation windows of variable width

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comprising the 350-1,250 m/z range. The width of each of the 60 m/z windows was

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adjusted according to the ion frequency found in the previous shotgun runs.

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Protein quantitative data was extracted from the SWATH raw files as previously

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described24. Briefly, SWATH Acquisition MicroApp was used for extracting the ion

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chromatogram traces from the SWATH raw files and using the previously generated

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spectral library, and the following parameters: ten peptides/protein; seven fragment

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ions/peptide; extraction windows of 20 min and 20 ppm; peptide FDR of 1% and

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confidence score threshold of 95%. The iRT peptides spiked in each samples were used for

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realigning the retention times of the quantified peptides.

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Pathway analysis

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The significantly affected pathways were studied using Advaita Bio’s iPathwayGuide

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(http://www.advaitabio.com/ipathwayguide), which considers over-representation of

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significant proteins, pathway topological information and position and role of every

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protein.25 Pathways obtained from the “Kyoto Encyclopedia of Genes and Genomes”

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(KEGG) database were used.

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Statistical analysis

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For cell assays (MTT, LDH and caspase-3 assays), statistical significance (P < 0.05) was

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determined by analysis of variance (ANOVA) followed by the assessment of differences

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using STATGRAPHICS Plus version 5 (Statistical Graphic Corp., Warrenton, VA, USA).

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Figs. 1 and 2 show mean data for three independent experiments ± standard deviation.

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Normalisation of the protein abundance signal as measured by SWATH was carried out

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using MarkerView (v1.2.1, Sciex), and testing for differential abundance was performed at

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the protein level by applying a Student’s t-test. The qvalue R package was used in order to

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obtain a FDR q-value estimation to check for multiple testing underestimation of p-

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values26. For pathway analysis, a p-value was calculated for each reported pathway by

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iPathwayGuide using the Fisher’s method, and p-values were adjusted for multiple

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comparisons using the FDR approach.

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RESULTS AND DISCUSSION

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Antiproliferative actions of DHA and ARA

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The purity of the assayed PUFAs was found to be 98.1% and 99.2% (FA% of total FA

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area) for DHA and ARA, respectively. The cell proliferation inhibition exercised by both

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FFAs on HT-29 CRC cells was evaluated by means of the MTT test, which measures cell

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survival and proliferation. The effects of DHA and ARA on HT-29 cell proliferation are

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shown in Fig. 1.A. As depicted in the figure, significant concentration-dependent inhibitory

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effects were found from the two studied compounds. The half-maximal inhibitory

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concentrations (IC50) at 48 h and 72 h for DHA were 259 µM and 245 µM, respectively,

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while for ARA the same values were 368 µM and 324 µM, respectively.

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For the physiological relevance of these concentrations, a previous study found the

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serum concentration of DHA in rats to be 97.3 µg/ml (297 µM) after 4 weeks of DHA

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supplementation.27 The present IC50 for DHA may thus be relevant to tumour progression

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in vivo, while uncertainty remains for ARA; it would be necessary to experiment in vivo to

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determine the concentrations of such PUFAs attainable in serum without producing adverse

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effects.

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Das and Das,28 using MTT assay, found a significant cell viability reduction of SH-

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SY5Y (55% reduction) and C6G cells (54% reduction) after a 24 h incubation with 100 µM

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DHA. In addition, Ramos-Bueno et al.22 demonstrated that acyl-species ARA and DHA

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derived from ARASCO® and DHASCO® oils, respectively, had relatively high in vitro

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anticancer activity on HT-29 cells. Chen et al.,29 using the MTT test, showed that Hep G2-

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MV2E1-9 cells lost more than 80% viability after a pretreatment with 50 µM ARA.

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LDH assay

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An LDH assay was conducted to assess the release of the lactate dehydrogenase enzyme

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into the culture medium after cell membrane damage caused by both DHA and ARA. The

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concentrations for performing the tests were 0–600 µM, at which the tested compounds

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showed different in vitro antiproliferative activities from those detected by the MTT assay.

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DHA induced more active damage at 300 µM and 48 h exposure than ARA did (Fig.

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1.B), although at 500 µM and after 72 h exposure, ARA was more effective in this action

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than DHA. Overall, LDH values were lower than those obtained in the MTT assay. In this

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regard, Ramos-Bueno et al.22 indicated that, when comparing the effects measured by LDH

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and MTT assays, the former were attained at higher levels of cell damage. Such differences

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could be attributable to the specificity of LDH testing compared to the MTT assay. A

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previous study showed that LDH leakage occurred only when reactive oxygen species

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related to cell death appeared, which were responsible for mitochondrial damage.22 Overall,

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the MTT assay showed cell growth inhibition at lower concentrations of FFA than the LDH

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test, because MTT reduction is not an indicator of cell death but rather constitutes a

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measure of relative metabolic activity, as demonstrated in a previous study on HT-29

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cells.30 Concerning ARA, our results agree with previous findings,29,31 which have shown

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the same PUFA-stimulated LDH activity in some other cells (e.g. Hep G2-MV2E1-9 and

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Sertoli).

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Caspase-3 assay

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The activation of caspase-3, specifically through self-cleavage, has been shown to be the

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event that commits cells to apoptotic death.32 As shown in Fig. 2, DHA induced caspase-3

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activation at 300 µM, while ARA did not, and both PUFAs exercised a similar induction of

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apoptosis at 600 µM. Several studies have suggested that DHA displays a notable

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protective effect on CRC, which could be at least partly due to its pro-apoptotic activity.

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The mechanisms affected by DHA for promoting apoptosis in CRC are still largely

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unknown, however. Previous works have demonstrated the apoptotic activity exerted by

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DHA in several cancer cell lines,33,34 while a variety of authors have tested whether DHA

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induced apoptosis in CRC cells.4,35,36. Habermann et al.,37 using an in vitro model and HT-

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29 and LT97 cells, proposed a generic mechanism for the apoptosis promoted by DHA that

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was based on inducing reactive oxygen species due to DHA double bonds, which led to

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apoptosis. Narayanan et al.38 found that DHA-regulated genes and transcription factors

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induced apoptosis in human colon cancer cells. Zhang et al.39 have also proposed that both

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DHA and ARA trigger the apoptosis of colon cancer cells through a mitochondrial

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pathway; they found that DHA in particular induced dramatic activities in both caspase-3

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and caspase-9.

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Proteomics analysis

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DIA MS strategies are showing great power for the study of abundance differences in

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complete proteomes. Precision and accuracy of the DIA approach of SWATH-MS19 has

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been described to match that of selected reaction monitoring, the gold standard in protein

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quantitation, even when applied to the quantitation of whole proteomes.40

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Shotgun analysis and spectral library

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Equal amounts of all samples from each group were pooled and analysed by DDA LC-

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MS. All the datasets were combined, and 15,406 peptides and 2,140 proteins were

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identified using the ProteinPilot search engine using a FDR threshold of 1%

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(Supplementary Table S2). This search result was then used for building a spectral library,

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which comprised 2,002 proteins.

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Protein abundance changes

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Protein quantitative data was extracted from the SWATH raw files as described in

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Material and Method above. In total, 7,653 peptides and 1,882 proteins were confidently

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quantified (Supplementary Table S3). To assess the global impact of the overall quantified

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proteins, principal component analysis (PCA) was performed on the whole protein dataset.

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PCA was able to separate the two tested groups from each other and from the control group

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(Fig. 3a), thus showing a large and different effect of the specific FFA (DHA or ARA) on

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HT-29 colon cancer cell proteomes.

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Effects of DHA and ARA on HT-29 colon cancer cell proteomes

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Supplementary Tables S4 and S5 show the results from the differential abundance

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testing for both comparisons (the DHA group to control and the ARA group to control,

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respectively), including a p-value and the corresponding FDR-adjusted q-value for each of

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the 1,882 quantified proteins. A total of 1,015 proteins showed changes in expression when

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we addressed the impact of the DHA extract and considered a non-adjusted p-value

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threshold of 0.05. Notably, due to the p-value distribution (Supplementary Fig. S1a), the q-

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values obtained from the FDR p-value correction were lower than the corresponding non-

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adjusted p-values (Supplementary Fig. S1b), which meant that we had more significant

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tests (significant proteins) if we chose a q-value threshold rather than a p-value threshold in

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order to consider a protein to be significantly regulated (Supplementary Fig. S1c).

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For downstream analyses, we considered a restrictive scenario – namely p-value and

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fold-change thresholds of 0.01 and 2.0, respectively – in order to have more confidence in

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selecting the proteins that presented real expression changes. When we applied these cut-

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off values, 284 proteins showed changes in expression, with 45 proteins being up-regulated

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and 239 down-regulated (Fig. 3b and Supplementary Fig. S6).

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When we addressed the changes caused by the ARA extract on HT-29 cancer cells and

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applied the same p-value and fold-change cut-off values, only 73 proteins were found to

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present changes in expression, with 27 proteins being up-regulated and 46 down-regulated

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(Fig. 3c and Supplementary Fig. S7). The p-value distribution, q-value to p-value

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correspondence, and number of significant proteins according to several cut-off values for

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ARA to control differential abundance tests are shown in Supplementary Fig. S2. When we

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compared the 284 and 73 proteins that we found were regulated as a consequence of adding

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DHA and ARA to the media (respectively), only 43 proteins were commonly regulated in

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both conditions (Fig. 3d). DHA was responsible for a larger effect on HT-29 cancer cells

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than ARA, as it is derived from the number of affected proteins and the larger fold changes

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that are found.

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Pathway impact analysis

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After FDR correction of the p-values, three pathways were found to be significantly

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affected by DHA (Fig. 4), with the Proteasome pathway (KEGG: 03050) presenting the

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deepest effect. The proteasome is a protein-degrading large complex which participates in

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different critical cellular functions, including cell cycle regulation, inflammatory and stress

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responses, apoptosis, signal transduction, cell differentiation and antigen processing. The

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26S proteasome is the most characteristic conformation, consisting of two 19S regulatory

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particles (which combine two base particles, PA700 Lid and PA700 Base) and a 20S

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proteolytic particle, and it is responsible for the degradation of ubiquitinated-labelled

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proteins.41 The 11S Regulator particle, or PA28, is a second type of proteasome particle. It

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consists of two different subparticles, PA28-α and PA28-β, which have been described to

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be greatly up-regulated by IFN-γ and have a role in generating antigenic peptides that are

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presented in the MHC-I pathway.42 We found up to 18 proteins from the Proteasome

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pathway to be down-regulated as a consequence of the addition of DHA extract, including

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members of most of the proteasome regulatory particles (PA700 Lid particle, PA700 Base

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particle, PA28-αβ and PA28-γ), in addition to the 20S Core particle (Fig. 5). PA28- γ is

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localised in the nucleus and has been described to have a role in apoptosis and cell cycle

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regulation.43 Many proteasome inhibitors, including natural substances such as polyphenol

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compounds, have been found to hinder cell proliferation, selectively promote apoptosis in

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proliferating cells, and inhibit angiogenesis.44,45 These qualities make these agents attractive

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drug candidates for treating different kinds of cancer, and some have even been studied in

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human clinical trials.44,46 According to our results, DHA-derived FFA could be included

331

among these candidates. Even though the mechanisms of action are not completely

332

understood, various studies have demonstrated that proteasome inhibitors alter the balance

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of pro- and anti-apoptotic proteins in human cancer cells, generating an accumulation of

334

tumour-suppressor proteins and the induction of apoptosis.47 Some authors have suggested

335

that proteasome inhibitors promote cell death by means of a p53-dependent mechanism, by

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inducing the expression of some of the genes related to apoptosis, such as PUMA or Bax.48

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Others, however, have pointed to a p53-independent mechanism of proteasome inhibitors-

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induced apoptosis. Noxa, one pro-apoptotic protein, has been linked to this apoptosis

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mechanism, since several proteasome inhibitors have been found to induce it in a p53-

340

independent manner in cancer cells of different origins.49 Our data could not clearly

341

demonstrate a p53-dependent nor independent mechanism of apoptosis. No quantitative

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information was obtained from our SWATH-MS analysis for the main pro- and anti-

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apoptotic proteins, PUMA, NOXA, Mcl-1, p21 or Bcl-2. A few other pro-apoptotic factors

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and tumour-suppressor proteins were found to be slightly up-regulated, such as AIFM1

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(apoptosis-inducing factor 1, fold-change 1.65) and P5i11 (tumour protein p53-inducible

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protein 11, fold-change 1.40). A few other anti-apoptotic proteins were found to be down-

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regulated, including API5 (apoptosis inhibitor 5, fold-change 0.70), which has been

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described as a suppressor of E2-promoter binding factor-dependent apoptosis in vivo and in 16


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vitro in multiple tissues,50 and TNF-α induced protein 8 (TFIP8, fold-change 0.61), which

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is an inhibitor of TNF-mediated apoptosis.51

351

Notably, we found PAWR (PRKC apoptosis WT1 regulator protein), a protein described

352

as pro-apoptotic in certain cancer cells such as prostate,52 to be down-regulated as an effect

353

of the DHA treatment on HT-29 cells (fold-change 0.52). But when we analysed the

354

differentially expressed proteins in the context of the p53 signalling pathway in

355

iPathwayGuide, we found that three key proteins were regulated by DHA (Supplementary

356

Fig. S3): TSP1 (thrombospondin 1, gene THBS1), which mediates anti-angiogenic

357

properties, presented a fold-change of 2.05; CDC2 (gene CDK1, cyclin dependent kinase

358

1), which regulates cell cycle and whose inhibitors are being explored as chemotherapeutic

359

agents in cancer,53 presented a fold-change of 0.24; and p53R2 (RIR2, ribonucleotide

360

reductase regulatory subunit M2, gene RRM2), involved in DNA synthesis, presented a

361

fold-change of 0.33. Interestingly, none of the proteins related to apoptosis within the p53

362

signalling pathway were affected by DHA (Supplementary Fig. S3). This behaviour could

363

point to a p53-independent mechanism of apoptosis as a consequence of treating HT-29

364

cells with DHA, although more research would be required to maintain this argument.

365

When we added ARA-FFA to the HT-29 cells, only one protein in the p53 signalling

366

pathway, p53R2 (gene RRM2), resulted in regulation (down-regulation).

367

According to our pathway analysis, two other pathways, Epstein Barr virus (EBV)

368

infection (KEGG: 05169) and DNA replication (KEGG: 03030), were also found to be

369

significantly affected by the addition of DHA, although the effect was not as evident as for

370

the Proteasome pathway, which presented much higher p-values. EBV is a ubiquitous

371

human herpesvirus that has been associated with oncogenesis in Burkitt lymphoma,

17



372

nasopharyngeal carcinoma, Hodgkin’s lymphoma, gastric adenocarcinoma and breast

373

cancer.54 Sixteen proteins from the EBV infection pathway were affected by DHA in our

374

study, with 14 proteins down-regulated, most related to DNA transcription factors

375

(Supplementary Fig. S4a). EBV makes cancer cells more aggressive,54 so we hypothesise

376

that the down-regulation of the proteins related to this pathway (which we found as a

377

consequence of adding DHA) could have had the opposite effect – that is, reducing

378

colorectal cancer cell viability. For DNA replication, DHA was found to produce the under-

379

expression of five out of the six helicase (also called the mini-chromosome maintenance

380

[MCM] complex) particles: Mcm2, Mcm3, Mcm4, Mcm5 and Mcm7 (Supplementary Fig.

381

S4b).

382

DNA replication was the top-ranked pathway when assessing the effect of ARA extract;

383

in that case, all six helicase particles (Mcm2, Mcm3, Mcm4, Mcm5, Mcm6 and Mcm7)

384

were found to be down-regulated (Fig. 6), presenting larger fold-changes than for DHA.

385

DNA helicase is the protein complex that unwinds the duplex parental DNA at the

386

replication fork, ahead of the DNA synthetic machinery.55 DNA replication procedure is

387

likewise linked to cell-cycle and to DNA processes in order to support genomic integrity,56

388

and therefore the down-regulation of the helicase proteins that our results showed was

389

expected to transfer an inhibitory effect to these processes. In fact, the Cell Cycle pathway

390

(KEGG: 04110) – which also occurred due to the down-regulation of the six MCM

391

particles – and the Pyrimidine Metabolism (KEGG: 00240) pathway were the two other

392

significant pathways affected by the addition of ARA (Supplementary Fig. S5), although

393

the Pyrimidine Metabolism pathway presented a much higher p-value than the DNA

394

replication and Cell Cycle pathways. Interestingly, neither the Proteasome pathway nor the

18


Page 18 of 36

Page 19 of 36


395

EBV pathway were significantly affected by ARA, since none of the proteins included in

396

these pathways were found to have been differentially expressed.

397

We have established that both ARA-FFA and DHA-FFA exercise different in vitro

398

anticancer activities on CRC. At 300 µM, DHA induced a stronger decrease of colorectal

399

cancer cell proliferation than ARA did, but DHA also induced fewer cytotoxic effects.

400

Pathway analyses of the SWATH-MS-generated proteomics data revealed that both FAs

401

had an impact on the cell cycle by means of down-regulating the protein particles that form

402

the helicase complex, but DHA also affected the proteasome system, since many proteins

403

from the different proteasome subunits were also under-expressed.

404

The present study shows that DHA and ARA are significantly inhibiting the growth of

405

cancer HT-29 cells depending on time and concentration, which suggests that both of them

406

may be helpful for hindering the development of aggressive adenocarcinoma.

407

Based on these findings, further studies will need to be conducted to determine if

408

a combination of PUFAs with regular anticancer molecules would represent a reasonable

409

approach to CRC treatment. The use of next-generation proteomics and other ‘omics’

410

approaches will allow for analysing the effects of natural compounds on global patterns of

411

gene expression and protein composition of the cell, thus improving the knowledge that we

412

have about the biological roles of nutraceuticals.

413 414 415 416

Supporting Information description The LC-MS raw files associated with this article are available at www.proteomexchange.org (Proteome Xchange Consortium), dataset id PXD008653. The

19



417

following supporting information and material can be found in the Web edition of the

418

Journal:

419

Supplementary material.pdf, including the detailed LC and mass spectrometry parameters

420

used for both data-dependent acquisition and SWATH methods, and figures S1

421

(Differential abundance test results for DHA vs. control), S2 (Differential abundance test

422

results for ARA vs. control), S3 (HT-29 cells p53 signaling pathway showing protein

423

changes observed as a result of treatment with DHA), S4 (HT-29 cells Epstein Barr virus

424

infection and DNA replication pathways showing the effect of DHA treatment), and S5

425

(HT-29 cells cell cycle and pyrimidine metabolism pathways showing the effect of ARA

426

treatment), and Table S1 (gradient used in the chromatographic purification of both free

427

fatty acids, DHA and ARA).

428

Supplementary Table S2.xlsx. 2,140 proteins that were identified using the ProteinPilot

429

search engine and a FDR threshold of 1%.

430

Supplementary Table S3.xlsx. SWATH-based protein quantification data for all the

431

samples.

432

Supplementary Table S4.xlsx. Differential abundance test for DHA vs. control.

433

Supplementary Table S5.xlsx. Differential abundance test for ARA vs. control.

434

Supplementary Table S6.xlsx. Differential expressed proteins for DHA vs. control.

435

Supplementary Table S7.xlsx. Differential expressed proteins for ARA vs. control.

436 437

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Biochem. 1998, 67, 721-751.

597 27



598 599

Funding sources Mass spectrometry analyses were performed at the IMIBIC Proteomics Unit, member

600

of ProteoRed (Plataforma de Recursos Biomoleculares y Bioinformáticos) and supported

601

by grant PT13/0001, funded by Instituto de Salud Carlos III (ISCIII) and FEDER.

602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617

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618


FIGURE CAPTIONS

619

Figure 1. Effect of DHA (92.1%) and ARA (98.8%) on proliferation and cell membrane

620

integrity of HT-29 cancer cells treated with 1% acetone (control) or different concentrations

621

of FFAs (50, 100, 150, 250, 300, 500 and 600 µM) for 48 h and 72 h. The data represent

622

the means of three complete independent experiments ± SD (error bars). (a) DHA and

623

ARA-FFAs inhibit the viability of HT-29 cancer cells. Dose-response and IC50 values were

624

determined by MTT assay using an enzyme-linked immunosorbent assay (ELISA)

625

microplate reader. (b) Cell membrane damage; dose-dependent LDH activity plot.

626

Figure 2. Caspase-3 activity test. Bar histogram displaying caspase-3 activity in HT-29

627

colon cancer cells after 90 min incubation with DHA and ARA at 300 and 600 µM,

628

compared with untreated cells (control). The data represent the means of three complete

629

independent experiments ± SD (error bars).

630

Figure 3. Quantitative proteomics results. (a) Principal component analysis (PCA) of all

631

1,882 quantified proteins. Using principal components 1 and 2, samples from the two tested

632

groups were separated from each other and from the control group. (b) Volcano plot for

633

DHA vs control, and (c) ARA vs control, showing p-value < 0.01 and fold-change ≥ 2.0 (or

634

≤ 0.5) thresholds. Proteins above these cut-offs are shown in red and were considered

635

significant proteins for the subsequent downstream analyses. The most extreme proteins are

636

labelled with the protein name. (d) Venn diagram showing the number of significant

637

proteins specifically for each comparison and common to both comparisons.

638

Figure 4. Pathway impact analysis. Pathways with significant impacts and their

639

associated corrected p-values for the differentially expressed proteins for the comparisons

640

of DHA vs control and ARA vs control.

29



641

Figure 5. Effect of DHA extract on HT-29 cancer cell Proteasome pathway (KEGG:

642

03050). (a) Proteasome pathway diagram overlaid with the gene’s measured fold change.

643

(b) Gene perturbation bar plot for the Proteasome pathway; differentially expressed genes

644

are represented with negative values in blue; positive values are in red.

645

Figure 6. Effect of ARA extract on HT-29 cancer cell DNA replication pathway

646

(KEGG: 03030). (a) DNA replication pathway diagram overlaid with the gene’s measured

647

fold change. (b) Gene perturbation bar plot for the DNA replication pathway; differentially

648

expressed genes are represented with negative values in blue; positive values are in red.

649 650 651 652 653 654 655 656 657 658 659 660 661 30


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Figure 1.

663

664 665 666

Figure 2.

667 668 669

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670

Figure 3.

671 672

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673


Figure 4.

674 675 676 677 678 679 680 681 682 683 684 685 686 687 688

33



689

Figure 5.

690 691 692 693 694 695

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Figure 6.

697 698 699 700 701 702 703 704 705 706

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707

Graphic for table of contents

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Proteomics Study Reveals That Docosahexaenoic and Arachidonic

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