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n-3 PUFA can reduce IL-6 and TNF levels in patients with cancer

Published online by Cambridge University Press:  07 March 2022

Yongzhong Guo
Affiliation:
Department of Respiratory and Critical Care Medicine, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China
Bo Ma
Affiliation:
Department of Orthopedics, the First Affiliated Hospital of Soochow University, Orthopedic Institute, Soochow University, Suzhou, Jiangsu, People’s Republic of China
Xinhua Li
Affiliation:
Shanxi Key Laboratory of Stem Cell for Immunological Dermatosis, Institute of Dermatology, Taiyuan City Center Hospital, Taiyuan Central Hospital of Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China
Hui Hui
Affiliation:
Department of Radiotherapy, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China
Yun Zhou
Affiliation:
Department of Radiotherapy, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China
Na Li
Affiliation:
Department of Radiotherapy, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China
Xiaomei Xie*
Affiliation:
Department of Radiotherapy, Xuzhou Central Hospital, The Xuzhou School of Clinical Medicine of Nanjing Medical University, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China
*
*Corresponding author: Xiaomei Xie, email gxxm2007@163.com
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Abstract

Current studies on inhibitory effects of n-3 PUFA on pro-inflammatory cytokines have inconsistent results. Thus, a meta-analysis of randomised controlled trials was conducted to identify the effects of n-3 PUFA administration on circulating IL-6 and TNF in patients with cancer. Studies that examined the effects of n-3 PUFA administration on circulating IL-6 and TNF in patients with cancer were identified by searching PubMed and EMBASE from January 1975 to February 2021. Differences in n-3 PUFA administration and control conditions were determined by calculating standardised mean differences (SMD) with 95 % CI. Twenty studies involving 971 patients met the inclusion criteria. The overall SMD were 0·485 (95 % CI 0·087, 0·883) for IL-6 and 0·712 (95 % CI 0·461, 0·962) for TNF between n-3 PUFA administration and control conditions. Sources of heterogeneity were not found through subgroup and meta-regression analyses. Publication bias was observed in TNF with a slight contribution to the effect size. n-3 PUFA can reduce circulating IL-6 and TNF levels in patients with cancer. Results supported the recommendation of n-3 PUFA as adjuvant therapy for patients with cancer, possibly excluding head and neck cancer, owing to their anti-inflammatory properties.

Type
Systematic Review and Meta-Analysis
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

Increasing evidence on the role of inflammation in carcinogenesis and cancer development(Reference Greten and Grivennikov1Reference Diakos, Charles and Mcmillan4) has led to the proposition that treatments targeting deregulated inflammatory responses can be used as alternative strategies for cancer prevention and therapy(Reference Crusz and Balkwill3Reference Hou, Karin and Sun5). Within this perspective, n-3 PUFA, as essential nutrients for normal metabolism, have attracted considerable interest in cancer-preventive and anticancer effects due to their potential role in suppressing and resolving inflammation(Reference Djuricic and Calder6Reference D’Archivio, Scazzocchio and Vari10). Indeed, the use of n-3 PUFA for patients with cancer has been recommended by the European Society for Parenteral and Enteral Nutrition to patients with cancer, although the evidence is weak(Reference Muscaritoli, Arends and Bachmann11).

n-3 PUFA exert effects against various inflammatory conditions or disorders, including cancer(Reference Djuricic and Calder6Reference D’Archivio, Scazzocchio and Vari10,Reference Yates, Calder and Ed12) . However, inconsistencies regarding the inhibitory effects of n-3 PUFA on systemic inflammation in patients with cancer have been found in the literature, weakening the potential use of n-3 PUFA in cancer prevention and treatment. Numerous inflammatory cytokines directly contribute to carcinogenesis, and most of them are largely confined to experimental research and have limited significance in clinical practice(Reference Mantovani, Allavena and Sica2,Reference Crusz and Balkwill3,Reference Lan, Chen and Wei13,Reference Grivennikov and Karin14) . Among them, IL-6 and TNF are the most extensively studied inflammatory cytokines in clinical studies to identify associations between systemic inflammation and cancer. However, findings on the evolution of circulating IL-6 and TNF levels after n-3 PUFA use in patients with cancer are inconsistent, including those of meta-analyses(Reference Mocellin, Camargo and Nunes15Reference Pan, Zhou and Yin20). In view of the increasing benefits to cancer treatment, only mild side effects and no convincingly serious safety issues, determining the effects of n-3 PUFA administration on IL-6 and TNF levels in cancer patients has clinical importance(Reference Nabavi, Bilotto and Russo9).

Previous meta-analyses focused on digestive system cancer and included a small number of studies (two to seven per analysis) and sample size (only eighty-six patients in some studies)(Reference Mocellin, Camargo and Nunes15Reference Pan, Zhou and Yin20). Thus, they are prone to selection and information bias. Moreover, the potential effects of relevant variables on IL-6 and TNF levels cannot be quantitatively identified by subgroup and meta-regression analyses because of the limited number of included studies. Since the publication of previous meta-analyses, several high-quality randomised controlled trials (RCT) have been conducted to explore the effects of n-3 PUFA on IL-6 and TNF levels but did not yield consistent results. Thus, a meta-analysis of RCT was conducted for the evaluation of the effects of n-3 PUFA administration on circulating IL-6 and TNF levels in patients with various types of cancer and potential impact of relevant variables, with particular concern to the optimal patients and regimens for which n-3 PUFA administration may be highly beneficial.

Methods and materials

This meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement(Reference Liberati, Altman and Tetzlaff21).

Literature search and selection

The PubMed and EMBASE were searched for RCT published from January 1975 to February 2021 and updated in September 2021. The search was limited to RCT that enrolled adult humans and had no language restrictions. The following search terms were included, with combined free text and subject terms: ‘inflammation’ or ‘inflammatory;’ ‘interleukin-6’ or ‘IL-6;’ ‘tumor necrosis factor or ‘TNF;’ ‘fatty acids’ or ‘alpha-linoleic acid (ALA)’ or ‘eicosapentaenoic acid (EPA)’ or ‘docosahexaenoic acid (DHA);’ and ‘cancer’ or ‘carcinoma’ or ‘neoplasm’ or ‘tumor’ or ‘tumour’ or ‘malignancy’. The reference lists of relevant publications were manually searched for additional studies.

The search followed the Patient, Intervention, Comparison, Outcome (PICO) strategy: (1) patient (P): patients with diagnosed cancer based on acceptable criteria; (2) intervention (I): n-3 PUFA administration (regardless of type and dose); (3) comparison (C): non-n-3 PUFA administration or placebo; and (4) outcome (O): circulating IL-6 and TNF levels.

If multiple studies reported outcomes on the same patient group, the one with the largest sample size was included. Abstracts, case reports, editorials, expert opinions, letters, animal studies and reviews without original data were excluded.

Data extraction and quality assessment

Two investigators independently extracted information from all eligible studies according to a standardised protocol. Disagreements were resolved through consensus with a third investigator. Data extracted from each study included the name of the first author, year of publication, nation, study design, sample size, patient inclusion criteria, cancer site, inflammatory markers, intervention, therapy duration, primary concurrent treatment, patient’s age and BMI. When only standard errors instead of standard deviations were provided in the study, standard deviation was calculated by multiplying the standard error by the square root of the sample size. In addition, some studies provided medians and ranges instead of means and standard deviation; the corresponding means and standard deviation were calculated with the method described by Hozo et al.(Reference Hozo, Djulbegovic and Hozo22)

The methodological quality of the RCT was evaluated by using the Jadad scale ranging from 0 to 7 points, including the following aspects: randomisation (0, 1 or 2), double-blinding (0, 1 or 2), concealment of allocation (0, 1 or 2), and withdrawals and dropouts (0 or 1)(Reference Jadad, Moore and Carroll23). A score of ≥ 4 indicates high quality(Reference Kjaergard, Villumsen and Gluud24). Two investigators rated each study independently and subsequently assigned a score to minimise selection bias. Disagreements were resolved through a consensus with a third investigator.

Statistical analysis

The meta-analysis was conducted using Stata statistical software (version 10.0, Stata Corporation). Given the diversity in the measurement and reporting of inflammatory markers among various laboratories, the computation of the summary estimates was used with a standardised mean difference (SMD) instead of the absolute levels of inflammatory markers. Heterogeneity across studies was tested using Q and I 2 statistics. Significant heterogeneity was indicated by P heterogeneity < 0·10 or I 2 > 60 %. A random-effects model was used when significant heterogeneity was observed; otherwise, a fixed-effect model was used to analyse the pooled results. Sensitivity analyses by changing the eligibility criteria, including the omission of one study at a time, were conducted to explore the robustness of the pooled results.

Subgroup analyses grouped by study design (double-blinded and non-double-blinded), sample size (≤ 40 and > 40), Jadad score (≤ 3 and ≥ 4), study area (America, Asia and Europe), cancer site (head and neck, gastric, colorectal, and other), fatty acid types (n-3 PUFA, DHA and EPA combined, and EPA), administration routes (oral, nasal and intravenous), therapy duration (≤ 1 month and > 1 month), primary concurrent treatment (chemotherapy, operation and others) and patient age (≤ 60 years and > 60 years) were performed using random-effects model to evaluate the effects of these variables on inflammation levels, as well as the possible sources of heterogeneity.

Meta-regression analyses (≥ 10 studies for each variable) were used to determine whether some relevant variables, including publication year, study design, Jadad score, sample size, study area, fatty acid types, administration routes, therapy duration, primary concurrent treatment, basic inflammation levels, patient age and BMI, were the possible sources of heterogeneity, as well as the existence of a linear relationship with inflammatory marker change.

Publication bias was evaluated visually by funnel plots and statistically by Egger’s and Begg’s tests. If significant publication bias was presented, the ‘trim-and-fill’ method was used to examine the expected number of studies needed to correct the asymmetry of funnel plots and compute the adjusted pooled result. Two-tailed P < 0·05 was considered statistically significant.

Results

Characteristics of included studies

A detailed flow chart of the study selection process is outlined in Fig. 1. A total of 115 potentially related articles were identified through an initial online search. After the titles and abstracts were reviewed, twenty-nine articles were selected and further examined. Nine of the twenty-nine articles were excluded for the following reasons: four had no original data(Reference Sunpaweravong, Puttawibul and Ruangsin25Reference Gogos, Ginopoulos and Salsa28), three were not RCT(Reference Lu, Chen and Wei29Reference Martinez, Herrera and Frias31), one did not use n-3 PUFA(Reference Mohammadzadeh, Faramarzi and Mahdavi32) and one was a study protocol(Reference Mcdonald, Bauer and Capra33). Therefore, twenty articles that satisfied the inclusion criteria were included in the meta-analysis: nineteen for IL-6(Reference Gianotti, Braga and Fortis34Reference Haidari, Abiri and Iravani52) and fifteen for TNF(Reference Wu, Zhang and Wu36Reference Ryan, Reynolds and Healy41,Reference Kanat, Cubukcu and Avci43,Reference Finocchiaro, Segre and Fadda44,Reference Wang, Zhang and Zhang46,Reference Golkhalkhali, Rajandram and Paliany48Reference Mocellin, Pastore and Camargo53) . Table 1 provides the detailed characteristics of the included studies.

Fig. 1. Flow diagram of study selection.

Table 1. Characteristics of studies included in meta-analysis

RCT, randomised controlled trials; DB, double-blind; TPN, total parenteral nutrition; PO, postoperation; NR, not reported; EN, enteral nutrition; CT, chemotherapy; RT, radiotherapy; KPS, karnofsky performance status; ENT, ear, nose and throat.

* Treatment group.

Control group.

Results for IL-6

The pooled result indicated a significant decrease in IL-6 level after n-3 PUFA administration and showed significant heterogeneity (Fig. 2). Sensitivity analysis by omitting one RCT at a time showed that SMD ranged from 0·378 (95 % CI 0·033, 0·753) to 0·568 (95 % CI 0·175, 0·961) when the studies of Wu 2001(Reference Wu, Zhang and Wu36) and Felekis 2010(Reference Felekis, Eleftheriadou and Papadakos39) were omitted. After five studies were removed, in which means and standard deviations were extracted by reading the graphs or calculating the medians and interquartile ranges(Reference Furukawa, Tashiro and Yamamori35,Reference Silva, Trindade and Fabre42,Reference Roca-Rodriguez, Garcia-Almeida and Lupianez-Perez45,Reference Carvalho, Cruz and Viana47,Reference Feijó, Rodrigues and Viana50) , a significant decrease in IL-6 was observed (SMD, 0·573; 95 % CI 0·092, 1·053) and the heterogeneity remained significant (P heterogeneity < 0·001; I 2 = 90·5 %). Additional analysis by including two non-RCT(Reference Lu, Chen and Wei29,Reference Wigmore, Fearon and Maingay30) showed a similar result in IL-6 after n-3 PUFA administration (SMD, 0·975; 95 % CI 0·386, 1·564) with significant heterogeneity (P heterogeneity < 0·001; I 2 = 94·7 %).

Fig. 2. Meta-analysis of n-3 PUFA administration on IL-6 in cancer patients. CI, confidence interval; SMD, standardized mean difference.

Subgroup analyses suggested significant differences existed when grouping was performed according to study area, cancer site, fatty acid types and primary concurrent treatment (Table 2). No significant linear relationship between IL-6 and some relevant variables was observed through meta-regression analysis (Table 3). The possible sources of heterogeneity were not found by subgroup and meta-regression analyses (Tables 2 and 3).

Table 2. The results of subgroup analyses for IL-6

SMD, standardised mean difference; DB, double-blind; NR, not reported.

Table 3. The results of meta-regression analyses

NS, no statistics.

No publication bias was observed from funnel plot and associated statistics (P Begg = 0·484; P Egger = 0·319) (Fig. 4).

Results for TNF

A remarkable decrease in TNF was observed after n-3 PUFA administration with significant heterogeneity (Fig. 3). Sensitivity analysis by omitting one RCT at a time showed that SMD ranged from 0·642 (95% CI 0·414, 0·870) to 0·771 (95% CI 0·537, 1·005) when the RCT of Finocchiaro 2012(Reference Finocchiaro, Segre and Fadda44) and Felekis 2010(Reference Felekis, Eleftheriadou and Papadakos39) were omitted. A similar result was obtained after the study of Ryan 2009(Reference Ryan, Reynolds and Healy41) was removed, in which data were extracted by reading the graph (SMD, 0·745; 95% CI 0·480, 1·011). Pooled analysis by including one non-RCT(Reference Lu, Chen and Wei29) using random-effects model revealed similar decrease in TNF levels after n-3 PUFA administration (SMD, 0·840; 95 % CI 0·508, 1·172) with significant heterogeneity (P heterogeneity < 0·001; I 2 = 81·9%).

Fig. 3. Meta-analysis of n-3 PUFA administration on TNF in cancer patients. CI, confidence interval; SMD, standardized mean difference.

Fig. 4. The filled funnel plot for IL-6 (a) and TNF (b). Open circles are for original data, and solid squares are for imputed “filled” values.

Subgroup analyses revealed the differences in sample size, Jadad score and cancer site might affect n-3 PUFA efficacy (Table 4). The sources of heterogeneity were not found by subgroup (Table 4) and meta-regression (Table 3) analyses.

Table 4. The results of subgroup analyses for TNF

SMD, standardized mean difference; DB, double-blind; NR, not reported.

The funnel plot (Fig. 4) and Begg’s (P = 0·038) and Egger’s test (P = 0·094) indicated the occurrence of publication bias for TNF. The ‘trim-and-fill’ method showed the need for five additional studies to correct the funnel plot asymmetry (Fig. 4). The SMD corrected using the fixed- and random-effects models were 0·469 (95 % CI 0·337, 0·601) and 0·467 (95 % CI 0·192, 0·742), respectively, which indicated the slight contribution of publication bias to the pooled results.

Discussion

This meta-analysis assessed the effects of n-3 PUFA administration on circulating IL-6 and TNF levels in patients with cancer. The results indicated that n-3 PUFA can reduce IL-6 and TNF levels. Sensitivity analyses by changing the eligibility criteria further strengthened the robustness of the results.

n-3 PUFA possess anti-inflammatory and inflammation-resolving activities, possibly related to the inhibition of IL-6 and TNF production. The inhibitory effects of n-3 PUFA on IL-6 and TNF have been reported in multiple inflammatory diseases. However, the results are inconsistent in patients with cancer. The current finding supported the role of n-3 PUFAs in reducing circulating IL-6 and TNF levels in patients with cancer. Partially consistent with current results, most previous meta-analyses reported significant decrease in IL-6(Reference Mocellin, Camargo and Nunes15Reference Zhao and Wang18) and TNF(Reference Mocellin, Fernandes and Chagas16,Reference Zhao and Wang18,Reference Yan, Li and Yang19) , whereas few reported non-significant changes in IL-6(Reference Yan, Li and Yang19) and TNF(Reference Yu, Liu and Zhang17) after n-3 PUFA administration in digestive system cancer. Similar findings were observed in breast, lung and colorectal cancers examined in previous non-RCT(Reference Martinez, Herrera and Frias31,Reference Cerchietti, Navigante and Castro54Reference Alfano, Imayama and Neuhouser56) . Favourable evidence were provided by in vitro studies. Findings showing that n-3 PUFA use can decrease IL-6 and TNF secretion were reported in various human(Reference Khalfoun, Thibault and Watier57Reference Trebble, Arden and Stroud59) and other mammary cultured cells(Reference Feng, Wang and Yang60). Although not affected IL-6 and TNF secretion, n-3 PUFA can promote pro-resolving responses in human monocytes(Reference Jaudszus, Gruen and Watzl61). Based on current published literature, the effects of reducing IL-6 and TNF levels in patients with cancer should be regarded as convincing.

When the suppressive action of n-3 PUFA on inflammatory cytokines (IL-6 and TNF) in patients with cancer was established, the pros and cons of n-3 PUFA use should be weighed.

IL-6 is a multifaceted pleiotropic cytokine mainly produced by cancer and stromal cells in patients with cancer and has a wide range of target cells because of its trans-signalling mechanism. IL-6 has carcinogenic actions in experimental cancer models and patients with cancer(Reference Grivennikov and Karin14,Reference Rodriguez-Vita and Lawrence62Reference Lacina, Brabek and Kral64) . Raised IL-6 levels indicate poor prognosis in patients with several types of cancer(Reference Crusz and Balkwill3). Anti-IL-6 therapy can target cancer by suppressing cancer growth, metastasis, metabolism and cachexia(Reference Crusz and Balkwill3,Reference Hou, Karin and Sun5,Reference Lacina, Brabek and Kral64) .

TNF is another key cytokine that associates inflammation with cancer. TNF has been initially found to have anticancer functions because of its capability to induce haemorrhagic necrosis in tumours. Existing data indicate that TNF is a poor apoptosis inducer with weak cytotoxic or cytostatic effects on malignant cells(Reference Lebrec, Ponce and Preston65). Only high-dose TNF administration can be used as a cytotoxic agent to kill tumour cells(Reference Lebrec, Ponce and Preston65,Reference Szlosarek, Charles and Balkwill66) . Moreover, TNF is a pro-cancer cytokine that favours tumour growth and metastasis(Reference Grivennikov and Karin14,Reference Lebrec, Ponce and Preston65) . Elevated circulating TNF concentration and expression are present in various pre-cancerous and malignant diseases. Chronic, low-level TNF exposure is linked to a pro-malignant phenotype (growth, invasion and metastasis)(Reference Szlosarek, Charles and Balkwill66).

Regardless of the underlying mechanism linking IL-6 and TNF with cancer, substantial evidence now exists to suggest that reductions in IL-6 and TNF levels are associated with the benefits of cancer treatment.

Conforming to the results of subgroup analyses, the anti-inflammatory action of n-3 PUFA may be subject to multiple factors. The disparity influence of race and ethnicity in various aspects of cancer, including treatment response, was observed(Reference Grenade, Phelps and Villalona-Calero67,Reference Shavers and Brown68) . Compared with their American and European counterparts, Asians can attain more benefits from n-3 PUFA administration. Additionally, differences in serum IL-6 and TNF levels were reported among people with different ethnic origins or regions(Reference Stowe, Peek and Cutchin69) and people with different serum n-3 PUFA levels(Reference Sekikawa, Steingrimsdottir and Ueshima70). Previous studies supported different effects of n-3 PUFA administration on C-reactive protein in diverse populations(Reference Pan, Zhou and Yin20). The disparate impacts of n-3 PUFA on circulating IL-6 and TNF in various regions were understandable, although no study directly compared the effects of n-3 PUFA administration on IL-6 and TNF levels in diverse populations.

A site-specific association between cancer and inflammation was reported(Reference Toiyama, Fujikawa and Koike71,Reference Guo, Pan and Du72) . The present analysis supported the diverse effects of cancer sites on IL-6 and TNF levels. Unexpectedly, an increasing trend in IL-6 and a borderline result for TNF were observed in head and neck cancer. Chronic inflammation involving IL-6 and TNF was related to the development and progression of head and neck cancer(Reference Bonomi, Patsias and Posner73). None of the included RCT reported remarkable increases in IL-6 and TNF in head and neck cancer(Reference Casas-Rodera, Gómez-Candela and Benítez38,Reference Felekis, Eleftheriadou and Papadakos39,Reference Roca-Rodriguez, Garcia-Almeida and Lupianez-Perez45,Reference Carvalho, Cruz and Viana47,Reference Solis-Martinez, Plasa-Carvalho and Phillips-Sixtos49) . According to current knowledge, the present results for IL-6 and TNF in head and neck cancer should be interpreted with caution. The possible reasons are as follows: firstly, the power to disclose these potential benefits of the therapy because of the small sample size is insufficient. Secondly, the possibility of low IL-6 and TNF levels in head and neck cancer minimises the extent of their reduction. Finally, substantial effects of n-3 PUFA are lacking.

Substantial differences between the anti-inflammatory effects of EPA and DHA were found(Reference Gorjao, Azevedo-Martins and Rodrigues74). The use of DHA alone was not reported in the included articles. A borderline result was observed for EPA use alone in IL-6. Alternatively, a substantial impact of TNF was observed. Subgroup analysis suggested that the combination of EPA and DHA have higher benefits than EPA alone. However, a recent network meta-analysis(Reference Vors, Allaire and Mejia75) and a head-to-head comparison study(Reference Allaire, Couture and Leclerc76) did not find remarkable differences in IL-6 and TNF levels between DHA and EPA. Results of in vitro studies were mixed(Reference Khalfoun, Thibault and Watier57,Reference Jaudszus, Gruen and Watzl61,Reference Weldon, Mullen and Loscher77,Reference So, Wu and Lichtenstein78) . Some were suggestive of more potent in EPA(Reference Khalfoun, Thibault and Watier57,Reference Sierra, Lara-Villoslada and Comalada79) , whereas others showed different results(Reference Jaudszus, Gruen and Watzl61,Reference Weldon, Mullen and Loscher77) . Additionally, no remarkable differences in some inflammation-related genes expressing in human immune cells were found between the effects of EPA and DHA(Reference Vors, Allaire and Marin80). Thus, whether EPA or DHA is superior to the other in terms of anti-inflammatory activity remains unclear.

Therapy or administrative duration may be one vital factor influencing the anti-inflammatory properties of n-3 PUFA. Previous data seemed to support significant decrease in IL-6 and TNF levels from longer duration of therapy(Reference Sunpaweravong, Puttawibul and Ruangsin25,Reference Ryan, Reynolds and Healy41,Reference Hershman, Unger and Crew81) . Inconsistent findings were provided by current subgroup analyses. A significant decrease in TNF was observed after long-term therapy, whereas a significant decrease in IL-6 was observed after short-term therapy. The optimal duration of n-3 PUFA was poorly determined and may have been influenced by multiple factors. Among the most critical factors, particular attention should be paid to the anti-inflammatory pathways of n-3 PUFA. Incorporation into cell membrane phospholipids can rapidly modify cell function, and 26 weeks are needed to alter the gene expression profiles to anti-inflammatory status in human blood mononuclear cells(Reference Bouwens, van de Rest and Dellschaft82). Additionally, n-3 PUFA can act directly on inflammatory cells by decreasing inflammatory cytokine production through the activation of free fatty acid receptors 1 and 4(Reference Kimura, Ichimura and Ohue-Kitano83) and enzymatically produce specialised pro-resolving mediators to orchestrate the resolution of inflammation(Reference Basil and Levy84). The precise anti-inflammatory pathways of n-3 PUFA are complex(Reference Djuricic and Calder6,Reference Calder8) and vary under various conditions, including doses and proportions(Reference Katan, Deslypere and van Birgelen85). Thus, varying the duration of n-3 PUFA administration for the desired effects is conceivable.

Doses and proportions are the other two fundamental factors influencing the anti-inflammatory properties of n-3 PUFA(Reference Zárate, Jaber Vazdekis and Tejera7,Reference Dasilva, Pazos and Garcia-Egido86) . The optimal doses have not yet been firmly established(Reference Calder8). Different inflammatory conditions possibly require different doses(Reference Calder, Albers and Antoine87). The threshold(Reference Kew, Banerjee and Minihane88) and dose–response relationship within a certain range(Reference Ras, Demonty and Zebregs89,Reference Flock, Skulas-Ray and Harris90) of n-3 PUFA administration have been reported. However, the dose–response relationship and diverse effects of different proportions of n-3 PUFA have not been analysed because of limited data.

Additionally, differences in administration routes, primary concurrent treatment, basic inflammatory factor levels and patient age cannot independently predict the effectiveness of n-3 PUFA administration on IL-6 and TNF levels according to the results of subgroup and meta-regression analyses.

Some limitations should be noted when interpreting the findings of this meta-analysis. Firstly, the number of patients and studies is small, and thus are prone to selection and publication biases. Secondly, substantial variations on potential confounders were present, such as patient enrolment, cancer site, n-3 PUFA types and dosage, and therapy duration. Thirdly, the subgroup results were defined post hoc, and the means of the studies instead of individual patient’s data were used as data points. Finally, the means and standard deviations in some studies were extracted through figures or calculated from data with non-normal distribution. These limitations may have reduced the statistical power, leading to false or spurious results.

Despite that the optimal regimens using n-3 PUFA were not identified, the present result supports the use of n-3 PUFA for patients with cancer, possibly excluding head and neck cancer, because of their anti-inflammatory properties. More benefits were observed in Asian, EPA and DHA combined, independent of administration routes, therapy duration and primary concurrent treatment. Further studies are needed to determine optimal patients and regimens that will highly benefit from the use of n-3 PUFA.

Acknowledgements

None.

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

X. X. and Y. G. conceived and designed the study; B. M., H. H. and Y. Z. selected the studies; X. L., N. L. and Y. G. extracted the data; X. X. and Y. G. performed the statistical analyses; X. X., B. M., X. L. and Y. G. wrote the manuscript. All authors read and revised the manuscript. The final manuscript was approved by all authors.

Footnotes

These authors contributed equally to this work

References

Greten, FR & Grivennikov, SI (2019) Inflammation and cancer: triggers, mechanisms, and consequences. Immunity 51, 2741.CrossRefGoogle ScholarPubMed
Mantovani, A, Allavena, P, Sica, A, et al. (2008) Cancer-related inflammation. Nature 454, 436444.CrossRefGoogle ScholarPubMed
Crusz, SM & Balkwill, FR (2015) Inflammation and cancer: advances and new agents. Nat Rev Clin Oncol 12, 584596.CrossRefGoogle ScholarPubMed
Diakos, CI, Charles, KA, Mcmillan, DC, et al. (2014) Cancer-related inflammation and treatment effectiveness. Lancet Oncol 15, e493e503.CrossRefGoogle ScholarPubMed
Hou, J, Karin, M & Sun, B (2021) Targeting cancer-promoting inflammation – have anti-inflammatory therapies come of age? Nat Rev Clin Oncol 18, 261279.CrossRefGoogle ScholarPubMed
Djuricic, I & Calder, PC (2021) Beneficial outcomes of n-6 and n-3 polyunsaturated fatty acids on human health: an update for 2021. Nutrients 13, 2421.CrossRefGoogle Scholar
Zárate, R, Jaber Vazdekis, N, Tejera, N, et al. (2017) Significance of long chain polyunsaturated fatty acids in human health. Clin Transl Med 6, 25.Google ScholarPubMed
Calder, PC (2018) Very long-chain n-3 fatty acids and human health: fact, fiction and the future. Proc Nutr Soc 77, 5272.Google ScholarPubMed
Nabavi, SF, Bilotto, S, Russo, GL, et al. (2015) n-3 polyunsaturated fatty acids and cancer: lessons learned from clinical trials. Cancer Metastasis Rev 34, 359380.Google Scholar
D’Archivio, M, Scazzocchio, B, Vari, R, et al. (2018) Recent evidence on the role of dietary pufas in cancer development and prevention. Curr Med Chem 25, 18181836.Google ScholarPubMed
Muscaritoli, M, Arends, J, Bachmann, P, et al. (2021) ESPEN practical guideline: clinical Nutrition in cancer. Clin Nutr 40, 28982913.Google ScholarPubMed
Yates, CM, Calder, PC & Ed, RG (2014) Pharmacology and therapeutics of n-3 polyunsaturated fatty acids in chronic inflammatory disease. Pharmacol Ther 141, 272282.CrossRefGoogle ScholarPubMed
Lan, T, Chen, L & Wei, X (2021) Inflammatory cytokines in cancer: comprehensive understanding and clinical progress in gene therapy. Cells, 10, 100.CrossRefGoogle ScholarPubMed
Grivennikov, SI & Karin, M (2011) Inflammatory cytokines in cancer: tumour necrosis factor and interleukin 6 take the stage. Ann Rheum Dis 70, i104i108.Google Scholar
Mocellin, MC, Camargo, CQ, Nunes, EA, et al. (2016) A systematic review and meta-analysis of the n-3 polyunsaturated fatty acids effects on inflammatory markers in colorectal cancer. Clin Nutr 35, 359369.CrossRefGoogle ScholarPubMed
Mocellin, MC, Fernandes, R, Chagas, TR, et al. (2018) A meta-analysis of n-3 polyunsaturated fatty acids effects on circulating acute-phase protein and cytokines in gastric cancer. Clin Nutr 37, 840850.CrossRefGoogle ScholarPubMed
Yu, J, Liu, L, Zhang, Y, et al. (2017) Effects of n-3 fatty acids on patients undergoing surgery for gastrointestinal malignancy: a systematic review and meta-analysis. BMC Cancer 17, 271.CrossRefGoogle ScholarPubMed
Zhao, Y & Wang, C (2018) Effect of n-3 polyunsaturated fatty acid-supplemented parenteral nutrition on inflammatory and immune function in postoperative patients with gastrointestinal malignancy: a meta-analysis of randomized control trials in China. Medicine 97, e472.Google Scholar
Yan, S, Li, M, Yang, D, et al. (2020) Associations between n-3 fatty acid supplementation and anti-inflammatory effects in patients with digestive system cancer: a meta-analysis. Nutr Cancer 72, 10981114.CrossRefGoogle ScholarPubMed
Pan, L, Zhou, Y, Yin, H, et al. (2021) n-3 polyunsaturated fatty acids can reduce C-reactive protein in patients with cancer: a systematic review and meta-analysis of randomized controlled trials. Nutr Cancer 112. doi: 10.1080/01635581.2021.1931365 Google Scholar
Liberati, A, Altman, DG, Tetzlaff, J, et al. (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 339, b2700.CrossRefGoogle ScholarPubMed
Hozo, SP, Djulbegovic, B & Hozo, I (2005) Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol 5, 13.Google ScholarPubMed
Jadad, AR, Moore, RA, Carroll, D, et al. (1996) Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials 17, 112.CrossRefGoogle ScholarPubMed
Kjaergard, LL, Villumsen, J & Gluud, C (2001) Reported methodologic quality and discrepancies between large and small randomized trials in meta-analyses. Ann Intern Med 135, 982989.CrossRefGoogle ScholarPubMed
Sunpaweravong, S, Puttawibul, P, Ruangsin, S, et al. (2013) Randomized study of antiinflammatory and immune-modulatory effects of enteral immunonutrition during concurrent chemoradiotherapy for esophageal cancer. Nutr Cancer 66, 15.Google ScholarPubMed
Bakker, N, van den Helder, RS, Stoutjesdijk, E, et al. (2020) Effects of perioperative intravenous ω-3 fatty acids in colon cancer patients: a randomized, double-blind, placebo-controlled clinical trial. Am J Clin Nutr 111, 385395.CrossRefGoogle ScholarPubMed
Turnock, A, Calder, PC, West, AL, et al. (2013) Perioperative immunonutrition in well-nourished patients undergoing surgery for head and neck cancer: evaluation of inflammatory and immunologic outcomes. Nutrients 5, 11861199.Google ScholarPubMed
Gogos, CA, Ginopoulos, P, Salsa, B, et al. (1998) Dietary n-3 polyunsaturated fatty acids plus vitamin E restore immunodeficiency and prolong survival for severely ill patients with generalized malignancy: a randomized control trial. Cancer 82, 395402.Google Scholar
Lu, Y, Chen, RG, Wei, SZ, et al. (2018) Effect of n 3 fatty acids on C-reactive protein and interleukin-6 in patients with advanced nonsmall cell lung cancer. Medicine 97, e11971.Google Scholar
Wigmore, SJ, Fearon, KC, Maingay, JP, et al. (1997) Down-regulation of the acute-phase response in patients with pancreatic cancer cachexia receiving oral eicosapentaenoic acid is mediated via suppression of interleukin-6. Clin Sci 92, 215221.Google ScholarPubMed
Martinez, N, Herrera, M, Frias, L, et al. (2019) A combination of hydroxytyrosol, n-3 fatty acids and curcumin improves pain and inflammation among early stage breast cancer patients receiving adjuvant hormonal therapy: results of a pilot study. Clin Transl Oncol 21, 489498.Google ScholarPubMed
Mohammadzadeh, M, Faramarzi, E, Mahdavi, R, et al. (2013) Effect of conjugated linoleic acid supplementation on inflammatory factors and matrix metalloproteinase enzymes in rectal cancer patients undergoing chemoradiotherapy. Integr Cancer Ther 12, 496502.Google ScholarPubMed
Mcdonald, C, Bauer, J, Capra, S, et al. (2014) The muscle mass, n-3, diet, exercise and lifestyle (MODEL) study – a randomised controlled trial for women who have completed breast cancer treatment. BMC Cancer 14, 264.CrossRefGoogle ScholarPubMed
Gianotti, L, Braga, M, Fortis, C, et al. (1999) A prospective, randomized clinical trial on perioperative feeding with an arginine-, n-3 fatty acid-, and RNA-enriched enteral diet: effect on host response and nutritional status. JPEN J Parenter Enteral Nutr 23, 314320.CrossRefGoogle ScholarPubMed
Furukawa, K, Tashiro, T, Yamamori, H, et al. (1999) Effects of soybean oil emulsion and eicosapentaenoic acid on stress response and immune function after a severely stressful operation. Ann Surg 229, 255261.Google ScholarPubMed
Wu, GH, Zhang, YW & Wu, ZH (2001) Modulation of postoperative immune and inflammatory response by immune-enhancing enteral diet in gastrointestinal cancer patients. World J Gastroenterol 7, 357362.Google ScholarPubMed
Chen, DW, Wei, FZ, Zhang, YC, et al. (2005) Role of enteral immunonutrition in patients with gastric carcinoma undergoing major surgery. Asian J Surg 28, 121124.Google ScholarPubMed
Casas-Rodera, P, Gómez-Candela, C, Benítez, S, et al. (2008) Immunoenhanced enteral nutrition formulas in head and neck cancer surgery: a prospective, randomized clinical trial. Nutr Hosp 23, 105110.Google ScholarPubMed
Felekis, D, Eleftheriadou, A, Papadakos, G, et al. (2010) Effect of perioperative immuno-enhanced enteral nutrition on inflammatory response, nutritional status, and outcomes in head and neck cancer patients undergoing major surgery. Nutr Cancer 62, 11051112.Google ScholarPubMed
Liang, B, Wang, S, Ye, YJ, et al. (2008) Impact of postoperative n-3 fatty acid-supplemented parenteral nutrition on clinical outcomes and immunomodulations in colorectal cancer patients. World J Gastroenterol 14, 24342439.Google Scholar
Ryan, AM, Reynolds, JV, Healy, L, et al. (2009) Enteral nutrition enriched with eicosapentaenoic acid (EPA) preserves lean body mass following esophageal cancer surgery: results of a double-blinded randomized controlled trial. Ann Surg 249, 355363.Google ScholarPubMed
Silva, JA, Trindade, EB, Fabre, ME, et al. (2012) Fish oil supplement alters markers of inflammatory and nutritional status in colorectal cancer patients. Nutr Cancer 64, 267273.Google ScholarPubMed
Kanat, O, Cubukcu, E, Avci, N, et al. (2013) Comparison of three different treatment modalities in the management of cancer cachexia. Tumori 99, 229233.Google ScholarPubMed
Finocchiaro, C, Segre, O, Fadda, M, et al. (2012) Effect of n-3 fatty acids on patients with advanced lung cancer: a double-blind, placebo-controlled study. Br J Nutr 108, 327333.CrossRefGoogle ScholarPubMed
Roca-Rodriguez, MM, Garcia-Almeida, JM, Lupianez-Perez, Y, et al. (2014) Effect of a specific supplement enriched with n-3 polyunsaturated fatty acids on markers of inflammation, oxidative stress and metabolic status of ear, nose and throat cancer patients. Oncol Rep 31, 405414.CrossRefGoogle Scholar
Wang, D, Zhang, H, Zhang, Y, et al. (2015) Effects of n-3 polyunsaturated fatty acids on postoperative inflammatory reaction and clinical efficacy. Zhonghua Wei Chang Wai Ke Za Zhi 18, 651655.Google Scholar
Carvalho, TC, Cruz, BC, Viana, MS, et al. (2017) Effect of nutritional supplementation enriched with eicosapentaenoic acid on inflammatory profile of patients with oral cavity cancer in antineoplastic pretreatment: a controlled and randomized clinical trial. Nutr Cancer 69, 428435.Google ScholarPubMed
Golkhalkhali, B, Rajandram, R, Paliany, AS, et al. (2018) Strain-specific probiotic (microbial cell preparation) and n-3 fatty acid in modulating quality of life and inflammatory markers in colorectal cancer patients: a randomized controlled trial. Asia Pac J Clin Oncol 14, 179191.CrossRefGoogle ScholarPubMed
Solis-Martinez, O, Plasa-Carvalho, V, Phillips-Sixtos, G, et al. (2018) Effect of eicosapentaenoic acid on body composition and inflammation markers in patients with head and neck squamous cell cancer from a public hospital in mexico. Nutr Cancer 70, 663670.Google ScholarPubMed
Feijó, PM, Rodrigues, VD, Viana, MS, et al. (2019) Effects of ω-3 supplementation on the nutritional status, immune, and inflammatory profiles of gastric cancer patients: a randomized controlled trial. Nutrition 61, 125131.Google ScholarPubMed
Li, K, Xu, Y, Hu, Y, et al. (2020) Effect of enteral immunonutrition on immune, inflammatory markers and nutritional status in gastric cancer patients undergoing gastrectomy: a randomized double-blinded controlled trial. J Invest Surg 33, 950959.CrossRefGoogle ScholarPubMed
Haidari, F, Abiri, B, Iravani, M, et al. (2020) Randomized study of the effect of vitamin D and n-3 fatty acids cosupplementation as adjuvant chemotherapy on inflammation and nutritional status in colorectal cancer patients. J Dietary Supplement 17, 384400.Google ScholarPubMed
Mocellin, MC, Pastore, ESJA, Camargo, CQ, et al. (2013) Fish oil decreases C-reactive protein/albumin ratio improving nutritional prognosis and plasma fatty acid profile in colorectal cancer patients. Lipids 48, 879888.CrossRefGoogle ScholarPubMed
Cerchietti, LC, Navigante, AH & Castro, MA (2007) Effects of eicosapentaenoic and docosahexaenoic n-3 fatty acids from fish oil and preferential Cox-2 inhibition on systemic syndromes in patients with advanced lung cancer. Nutr Cancer 59, 1420.Google ScholarPubMed
Read, JA, Beale, PJ, Volker, DH, et al. (2007) Nutrition intervention using an eicosapentaenoic acid (EPA)-containing supplement in patients with advanced colorectal cancer. Effects on nutritional and inflammatory status: a phase II trial. Support Care Cancer 15, 301307.CrossRefGoogle ScholarPubMed
Alfano, CM, Imayama, I, Neuhouser, ML, et al. (2012) Fatigue, inflammation, and n-3 and n-6 fatty acid intake among breast cancer survivors. J Clin Oncol 30, 12801287.Google Scholar
Khalfoun, B, Thibault, F, Watier, H, et al. (1997) Docosahexaenoic and eicosapentaenoic acids inhibit in vitro human endothelial cell production of interleukin-6. Adv Exp Med Biol 400B, 589597.Google ScholarPubMed
Endres, S, Ghorbani, R, Kelley, VE, et al. (1989) The effect of dietary supplementation with n-3 polyunsaturated fatty acids on the synthesis of interleukin-1 and tumor necrosis factor by mononuclear cells. N Engl J Med 320, 265271.Google ScholarPubMed
Trebble, T, Arden, NK, Stroud, MA, et al. (2003) Inhibition of tumour necrosis factor- α and interleukin 6 production by mononuclear cells following dietary fish-oil supplementation in healthy men and response to antioxidant co-supplementation. Br J Nutr 90, 405412.CrossRefGoogle ScholarPubMed
Feng, J, Wang, Q, Yang, W, et al. (2021) n-3 polyunsaturated fatty acids ameliorated inflammatory response of mammary epithelial cells and mammary gland induced by lipopolysaccharide. Acta Biochim Biophys Sin 53, 11421153.Google ScholarPubMed
Jaudszus, A, Gruen, M, Watzl, B, et al. (2013) Evaluation of suppressive and pro-resolving effects of EPA and DHA in human primary monocytes and T-helper cells. J Lipid Res 54, 923935.Google ScholarPubMed
Rodriguez-Vita, J & Lawrence, T (2010) The resolution of inflammation and cancer. Cytokine Growth Factor Rev 21, 6165.CrossRefGoogle ScholarPubMed
Jones, SA & Jenkins, BJ (2018) Recent insights into targeting the IL-6 cytokine family in inflammatory diseases and cancer. Nat Rev Immunol 18, 773789.CrossRefGoogle ScholarPubMed
Lacina, L, Brabek, J, Kral, V, et al. (2019) Interleukin-6: a molecule with complex biological impact in cancer. Histol Histopathol 34, 125136.Google ScholarPubMed
Lebrec, H, Ponce, R, Preston, BD, et al. (2015) Tumor necrosis factor, tumor necrosis factor inhibition, and cancer risk. Curr Med Res Opin 31, 557574.Google ScholarPubMed
Szlosarek, P, Charles, KA & Balkwill, FR (2006) Tumour necrosis factor-α as a tumour promoter. Eur J Cancer 42, 745750.CrossRefGoogle ScholarPubMed
Grenade, C, Phelps, MA & Villalona-Calero, MA (2014) Race and ethnicity in cancer therapy: what have we learned? Clin Pharmacol Ther 95, 403412.Google ScholarPubMed
Shavers, VL & Brown, ML (2002) Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst 94, 334357.CrossRefGoogle ScholarPubMed
Stowe, RP, Peek, MK, Cutchin, MP, et al. (2010) Plasma cytokine levels in a population-based study: relation to age and ethnicity. J Gerontol A Biol Sci Med Sci 65, 429433.CrossRefGoogle Scholar
Sekikawa, A, Steingrimsdottir, L, Ueshima, H, et al. (2012) Serum levels of marine-derived n-3 fatty acids in Icelanders, Japanese, Koreans, and Americans-a descriptive epidemiologic study. Prostaglandins Leukot Essent Fatty Acid 87, 1116.CrossRefGoogle ScholarPubMed
Toiyama, Y, Fujikawa, H, Koike, Y, et al. (2013) Evaluation of preoperative C-reactive protein aids in predicting poor survival in patients with curative colorectal cancer with poor lymph node assessment. Oncol Lett 5, 18811888.CrossRefGoogle ScholarPubMed
Guo, YZ, Pan, L, Du, CJ, et al. (2013) Association between C-reactive protein and risk of cancer: a meta-analysis of prospective cohort studies. Asian Pac J Cancer Prev 14, 243248.CrossRefGoogle Scholar
Bonomi, M, Patsias, A, Posner, M, et al. (2014) The role of inflammation in head and neck cancer. Adv Exp Med Biol 816, 107127.CrossRefGoogle Scholar
Gorjao, R, Azevedo-Martins, AK, Rodrigues, HG, et al. (2009) Comparative effects of DHA and EPA on cell function. Pharmacol Ther 122, 5664.Google ScholarPubMed
Vors, C, Allaire, J, Mejia, SB, et al. (2021) Comparing the effects of docosahexaenoic and eicosapentaenoic acids on inflammation markers using pairwise and network meta-analyses of randomized controlled trials. Adv Nutr 12, 128140.CrossRefGoogle ScholarPubMed
Allaire, J, Couture, P, Leclerc, M, et al. (2016) A randomized, crossover, head-to-head comparison of eicosapentaenoic acid and docosahexaenoic acid supplementation to reduce inflammation markers in men and women: the Comparing EPA to DHA (ComparED) Study. Am J Clin Nutr 104, 280287.Google ScholarPubMed
Weldon, SM, Mullen, AC, Loscher, CE, et al. (2007) Docosahexaenoic acid induces an anti-inflammatory profile in lipopolysaccharide-stimulated human THP-1 macrophages more effectively than eicosapentaenoic acid. J Nutr Biochem 18, 250258.CrossRefGoogle ScholarPubMed
So, J, Wu, D, Lichtenstein, AH, et al. (2021) EPA and DHA differentially modulate monocyte inflammatory response in subjects with chronic inflammation in part via plasma specialized pro-resolving lipid mediators: a randomized, double-blind, crossover study. Atherosclerosis 316, 9098.CrossRefGoogle ScholarPubMed
Sierra, S, Lara-Villoslada, F, Comalada, M, et al. (2008) Dietary eicosapentaenoic acid and docosahexaenoic acid equally incorporate as decosahexaenoic acid but differ in inflammatory effects. Nutr 24, 245254.Google ScholarPubMed
Vors, C, Allaire, J, Marin, J, et al. (2017) Inflammatory gene expression in whole blood cells after EPA vs. DHA supplementation: results from the ComparED study. Atherosclerosis 257, 116122.Google ScholarPubMed
Hershman, DL, Unger, JM, Crew, KD, et al. (2015) Randomized multicenter placebo-controlled trial of n-3 fatty acids for the control of aromatase inhibitor-induced musculoskeletal pain: SWOG S0927. J Clin Oncol 33, 19101917.Google ScholarPubMed
Bouwens, M, van de Rest, O, Dellschaft, N, et al. (2009) Fish-oil supplementation induces antiinflammatory gene expression profiles in human blood mononuclear cells. Am J Clin Nutr 90, 415424.Google ScholarPubMed
Kimura, I, Ichimura, A, Ohue-Kitano, R, et al. (2020) Free fatty acid receptors in health and disease. Physiol Rev 100, 171210.CrossRefGoogle ScholarPubMed
Basil, MC & Levy, BD (2016) Specialized pro-resolving mediators: endogenous regulators of infection and inflammation. Nat Rev Immunol 16, 5167.CrossRefGoogle ScholarPubMed
Katan, MB, Deslypere, JP, van Birgelen, AP, et al. (1997) Kinetics of the incorporation of dietary fatty acids into serum cholesteryl esters, erythrocyte membranes, and adipose tissue: an 18-month controlled study. J Lipid Res 38, 20122022.CrossRefGoogle ScholarPubMed
Dasilva, G, Pazos, M, Garcia-Egido, E, et al. (2015) Healthy effect of different proportions of marine n-3 PUFAs EPA and DHA supplementation in Wistar rats: lipidomic biomarkers of oxidative stress and inflammation. J Nutr Biochem 26, 13851392.CrossRefGoogle Scholar
Calder, PC, Albers, R, Antoine, JM, et al. (2009) Inflammatory disease processes and interactions with nutrition. Br J Nutr 101, S1S45.Google Scholar
Kew, S, Banerjee, T, Minihane, AM, et al. (2003) Lack of effect of foods enriched with plant- or marine-derived n-3 fatty acids on human immune function. Am J Clin Nutr 77, 12871295.Google ScholarPubMed
Ras, RT, Demonty, I, Zebregs, YE, et al. (2014) Low doses of eicosapentaenoic acid and docosahexaenoic acid from fish oil dose-dependently decrease serum triglyceride concentrations in the presence of plant sterols in hypercholesterolemic men and women. J Nutr 144, 15641570.CrossRefGoogle ScholarPubMed
Flock, MR, Skulas-Ray, AC, Harris, WS, et al. (2013) Determinants of erythrocyte n-3 fatty acid content in response to fish oil supplementation: a dose-response randomized controlled trial. J Am Heart Assoc 2, e513.Google ScholarPubMed
Figure 0

Fig. 1. Flow diagram of study selection.

Figure 1

Table 1. Characteristics of studies included in meta-analysis

Figure 2

Fig. 2. Meta-analysis of n-3 PUFA administration on IL-6 in cancer patients. CI, confidence interval; SMD, standardized mean difference.

Figure 3

Table 2. The results of subgroup analyses for IL-6

Figure 4

Table 3. The results of meta-regression analyses

Figure 5

Fig. 3. Meta-analysis of n-3 PUFA administration on TNF in cancer patients. CI, confidence interval; SMD, standardized mean difference.

Figure 6

Fig. 4. The filled funnel plot for IL-6 (a) and TNF (b). Open circles are for original data, and solid squares are for imputed “filled” values.

Figure 7

Table 4. The results of subgroup analyses for TNF