Chronic inflammation towards cancer incidence : a systematic review and meta-analysis of epidemiological studies

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(1)Journal Pre-proof Chronic inflammation towards cancer incidence: A systematic review and meta-analysis of epidemiological studies Nathalie Michels, Carola van Aart, Jens Morisse, Amy Mullee, Inge Huybrechts. PII:. S1040-8428(20)30313-9. DOI:. https://doi.org/10.1016/j.critrevonc.2020.103177. Reference:. ONCH 103177. To appear in:. Critical Reviews in Oncology / Hematology. Received Date:. 15 June 2020. Revised Date:. 26 October 2020. Accepted Date:. 9 November 2020. Please cite this article as: { doi: https://doi.org/ This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier..

(2) Chronic inflammation towards cancer incidence: a systematic review and meta-analysis of epidemiological studies. Nathalie Michelsa (PhD), Carola van Aarta (PhD), Jens Morissea (MSc), Amy Mulleeb (PhD), Inge Huybrechtsc (PhD). Department of public health and primary care, Ghent University, Belgium. b. UCD Institute of Food and Health, Dublin, Ireland. c. International Agency for Research on Cancer, Nutrition and Metabolism Section, Lyon, France. ro of. a. Contact: Nathalie Michels, 4K3 Corneel Heymanslaan 10, 9000 Gent, Belgium. +32 9 332 83 74. re. -p. Nathalie.michels@ugent.be, ORCID: 0000-0002-3069-7254. ABSTRACT. lP. This systematic review and meta-analysis provides epidemiological data on the relationship between chronic inflammation, as measured by inflammatory blood parameters, and cancer incidence. Two. na. independent researchers searched PubMed, Web Of Science and Embase databases until October 2020. In vitro studies, animal studies, studies with chronically-ill subjects or cross-sectional studies. ur. were excluded. Quality was assessed with the Newcastle–Ottawa scale. The 59 nested case-control, 6 nested case-cohort and 42 prospective cohort studies considered 119 different inflammatory. Jo. markers (top three: CRP, fibrinogen and IL6) and 26 cancer types (top five: colorectal, lung, breast, overall and prostate cancer). Nineteen meta-analyses resulted in ten significant positive associations: CRP-breast (OR=1.23[1.05-1.43];HR=1.14[1.01-1.28)), CRP-colorectal (OR=1.34[1.11-1.60]), CRP-lung (HR=2.03[1.59-2.60]), fibrinogen-lung (OR=2.56[1.86-3.54]), IL6-lung (OR=1.41[1.12-1.78]), CRPovarian (OR=1.41[1.10-1.80]), CRP-prostate (HR=1.09[1.03-1.15]), CRP-overall (HR=1.35[1.16-1.57]) and fibrinogen-overall (OR=1.22[1.07-1.39]). Study quality improvements can be done by better. 1.

(3) verification of inflammatory status (more than one baseline measurement of one parameter), adjusting for important confounders and ensuring long-term follow-up.. KEYWORDS: cancer, cytokines, inflammatory markers, observational studies, systematic review. Tables: 2 Figures: 2. Jo. ur. na. lP. re. -p. ro of. Supporting files: 3. 2.

(4) INTRODUCTION In current society, chronic low-grade inflammation has an increasing prevalence due to unhealthy lifestyle and environment. Chronic inflammation is the central pathway in the majority of age-related diseases [1]. This chronic inflammation can also regulate carcinogenesis (both suppression and promotion) on the levels of tumor initiation, proliferation and progression by several mechanisms, including accelerated cell proliferation, evasion from apoptosis, enhanced angiogenesis and metastasis [2, 3]. Existing inflammation and/or oncogenes can activate transcription factors (like NF-. ro of. ΚB, STATS3, HIF1α) in the future tumor cells which produce then inflammatory mediators like acutephase proteins (e.g. C-reactive protein CRP), cytokines (interleukins, chemokines, adipokines, interferons, TNF family, TGF family, colony stimulating factors), reactive oxygen species,. -p. prostaglandins and enzymes (COX2, 5LOX, MMP). This results in recruitment and activation of. immune cells into the tumor microenvironment leading to further stimulation of transcription factors. re. and activated immune cells. This inflammatory microenvironment then induces tissue damage, DNA damage and transcription factors at the convergence point of oncogenic signaling pathways [4].. lP. Even the normal aging process with telomere shortening produces an inflammatory environment that increases cancer incidence in animal studies [5]. Although chronic inflammation is considered an. na. enabling characteristic of carcinogenesis [6], it does not always have a tumor-promoting role; inflammation may be tumor-suppressive in some settings, and may even support response to. ur. immunotherapy [3]. Inflammation is marked by the presence of inflammatory parameters in the blood. Several of these inflammatory markers have been tested in relation to cancer incidence, but it. Jo. is still not known which inflammatory markers are the most relevant herein. Reviews often target only a specific set of markers like CRP, IL-6 and TNF-α [7, 8] and do not always adjust for inflammation-inducing lifestyle factors. This review and meta-analysis aims to provide an overview of the epidemiological data on how chronic inflammation, measured by inflammatory blood parameters, influences cancer incidence. Justification for this review is that the current literature needs clarification on 1) whether the 3.

(5) inflammation-cancer relation can be both positive and negative, 2) whether the effect may be cancer site specific, 3) which inflammatory parameter/profiles are most successful in predicting cancer risk. To obtain this goal we bundled the data from all relevant prospective and retrospective studies. This may enable the identification of new targets in the inflammatory cascade and the discovery of new preventive and therapeutic strategies.. METHODS. ro of. The MOOSE guidelines for meta-analyses were followed [9]. The protocol was preregistered on Prospero (CRD42018103894); during review a deviation was done to enhance quality by including an additional database and executing meta-analysis.. -p. Inclusion criteria. Participants: The aim was to examine the epidemiological evidence for the link between chronic. re. inflammation and cancer risk in the general population. Therefore studies that have a study population which consists of a subgroup of chronically ill participants were excluded.. lP. Exposure: The only way to quantify systemic chronic inflammation on epidemiological study scale is through inflammatory blood markers. Therefore only studies that use inflammatory blood markers as. na. their method for exposure assessment have been included. Gene polymorphisms were not included. Comparison: Inflammatory parameters were considered as continuous or categorical (percentiles). ur. outcomes.. Outcomes: The only outcome measure included was the incidence of any cancer or site-specific. Jo. cancer, assessed as the number of participants developing cancer during the study period. Inflammatory marker use for cancer prognosis towards recovery, treatment response or survival was not included.. Study design: The only study designs which can effectively study this topic are longitudinal observational studies, both prospective or retrospective, including cohort, nested case-control and. 4.

(6) nested-cohort studies. No intervention studies existed. Only human studies were considered. Conference abstracts were not included.. Search methods No limitations were imposed based on publication date or language. The final search for PubMed, Embase and Web of Science was performed on the 5th October 2020. Reference lists were also handsearched. The articles were first screened on title, then on abstract and finally on full-text. ro of. (authors were contacted to obtain full-texts). Both reviewers had a biomedical research background (NM and CV) and independently screened articles based on the predetermined exclusion and inclusion criteria. Any disagreements (5.6%) in this selection process were resolved through. -p. discussion or consultation with a third reviewer with cancer expertise (IH) if necessary. In addition,. seven manuscripts using overlapping data were excluded: only the study with the longest follow-up,. PubMed: "neoplasms"[MeSH Major Topic]. lP. re. the largest sample size or the largest set of inflammatory parameters was retained.. na. AND (“inflammation "[MeSH Major Topic] OR “inflammation” OR “inflammatory”) AND ("biomarkers/blood"[MeSH Major topic] OR "acute-phase proteins"[MeSH] OR. ur. “cytokines/blood”[Mesh] OR “cytokines/analysis”[Mesh]). Jo. NOT "therapy"[Subheading]. Embase:. 'chronic inflammation'/mj AND 'carcinogenesis'/exp. Web Of Science:. 5.

(7) ((((TI=("neoplasm" OR "cancer" ) AND (AB=("inflammation" NEAR/8 cancer") OR AB=("cytokines" NEAR/8 "cancer") OR AB=("inflammatory" NEAR/8 "cancer") OR A B=("acute-phase proteins" NEAR/8 "cancer")) AND AB=("cohort" OR "longitudinal" OR "casecontrol" OR "case control" OR "case-cohort" OR "prospective" OR "retrospective" OR "followup"))))) AND DOCUMENT TYPES: (Article). Data collection. ro of. As the goal was to provide epidemiological data on chronic inflammation and the risk of cancer, we were only interested in the binary outcome of cancer diagnosis (i.e. cancer incidence) and not in. cancer mortality or severity. To assess the level of chronic inflammation, the manuscripts divided. -p. study populations into groups (usually tertiles, quartiles, etc.) based on their levels of inflammatory parameters. All studies used odds ratio (OR), risk ratio (RR) or hazard ratio (HR) and their 95%. re. confidence intervals (95%CI) as measures of the association between levels of chronic inflammation and cancer risk. When ratios changed due to adjustments for covariates, the ratios with the most. lP. extensive adjustments were reported. The cutoff point for significance used in this review was P≤0.05. Quality assessment was done unblinded via the adapted version of the Newcastle-Ottawa. na. Quality Assessment Scale (NOS) for assessing the quality of non-randomized observational studies in meta-analyses (Online Resource 1). A study could receive a maximum of nine points. Two reviewers. Jo. reviewer.. ur. extracted data from a sample and achieved 85% agreement, with the remainder extracted by one. Statistical analysis. All analyses were performed using Review Manager 5.3. To estimate the relation between inflammation and risk of cancer, we obtained a binary adjusted OR, RR or HR with 95%CI (comparing high vs low levels of inflammation; often studies reported highest versus lowest tertile or quartile) from each study. A meta-analysis was only performed for biomarker-cancer relations that were 6.

(8) examined in at least four studies. The OR and RR were mixed together in meta-analyses, while HR’s were examined separately if enough studies were available. Studies that used principal component analysis [10], factor analysis [11] or an inflammatory score [12] could not be included in the metaanalysis. In total, 19 meta-analyses were performed using the most confounder adjusted risk estimate. Pooled risk estimates were obtained for each cancer site individually using random-effects models. In sensitivity analyses, the influence of BMI on the relation between inflammation and cancer risk was tested by only including studies that controlled for BMI. This was possible in 5 meta-. ro of. analyses but the number of included studies was often small. Heterogeneity between studies was assessed with the I2 statistic as a measure of the proportion of total variation in estimates that is due to heterogeneity [13]. I2 values of 25%, 50%, and 75% correspond to cutoff points for low, moderate,. -p. and high degrees of heterogeneity. Publication bias via Egger’s test was reported for meta-analyses. RESULTS. lP. Descriptives of the included studies. re. including at least 10 measures.. A total of 4896 articles were identified, after excluding all the duplicates, 4212 articles remained for. retained (Figure 1).. na. further selection. After assessing abstracts and full-text articles for eligibility, 103 articles were. ur. Of the 103 publications identified, 58 were described as nested case-control studies [10-12, 14-68], 6 were nested case-cohort studies [69-74] and 42 were prospective cohort analyses [61, 62, 75-111].. Jo. One publication [62] included both a case-control and a cohort study and 3 publications [78, 80, 112] included several cohort studies. Table 1 summarizes the characteristics of the included studies. The majority of the included studies were conducted in the US (42 studies), followed by Europe (45 studies), China (5 studies [23, 50, 59, 60, 100]), Japan (4 studies [30, 39, 42, 47]) and Iran [33]. Four studies [18, 31, 35, 112] used both data from US and Europe, one study [17] was conducted in Europe and Australia and another one in both US, EU, Australia, Asia [68]. The study populations. 7.

(9) were derived from 54 different parent cohorts and the follow-up period between inflammatory measurement and cancer diagnosis ranged from 0 to 27 years. The risk associated with 26 different types of cancer was investigated and multiple studies investigated more than one cancer site as an outcome. In descending order the top five of most frequently investigated cancer sites were: colorectal cancer (CRC) (n=35); overall cancer (n=23); lung cancer (n=22); breast cancer (n=22); and prostate cancer (n=17). Of the inflammatory parameters, CRP was most often reported (108 analyses), followed by IL-6 (36 analyses), fibrinogen (33 analyses), and TNF-α (25 analyses). The top. ro of. 10 adjusted confounders were age (102 studies), BMI (73 studies), smoking (71 studies), sex (48 studies), date of blood sampling (40 studies), alcohol consumption (39 studies), ethnicity (31 studies), study location (26 studies), physical activity (25 studies) and anti-inflammatory drugs (21 studies).. -p. The risk of bias is presented in Online Resource 1. For the cohort studies, the mean NOS score was. 7.12 with range 5-9 points. For case-control and case-cohort studies, the mean score was 7.58 with a. re. range of 5-9. The main weaknesses were case definition inadequacy in case-controls, lack of. no adequate adjustment.. lP. mentioning follow-up percentage in cohort studies, ascertainment of chronic inflammation level and. na. Associations of inflammation with cancer incidence. Table 2 shows a summary of the risk estimates of all included studies for each cancer site. Included. ur. studies presented their data by comparing the extreme groups (e.g. highest vs lowest quartiles), or by presenting a risk estimate per increment of inflammation parameter. Online Resource 2 gives an. Jo. overview of the number of significant and non-significant findings per cancer site. CRP, fibrinogen, IL6 and TNF-α were the most frequent researched inflammatory parameters. When putting all cancer sites together, the inflammatory parameter CRP resulted in 39.8% significant findings (43/108 analyses for 20 cancer types), IL-6 in 25% (9/36 analyses of which 1 in negative direction, for 11 cancer types), fibrinogen in 24% (8/33 analyses for 8 cancer types) and TNF-α in 24% (6/25 analyses of which 2 in negative direction, for 11 cancer types). Only CRP, fibrinogen, adiponectin, leptin, white 8.

(10) blood cell count and TNF-α were examined in enough studies (at least 4 studies on the same cancer outcome with comparable risk measure) to be included in meta-analysis (Figure 2 and Online Resource 3). Underneath, the results of each cancer site are summarized for meta-analyses and individual studies not included in meta-analysis, in descending number of publications. Colorectal cancer Thirty-five studies (31 publications) described the relation between inflammation and CRC risk. For CRP, 10 studies with a total of 3694 cases were included in the meta-analysis resulting in OR=1.34. ro of. (95%CI 1.11-1.60) with heterogeneity (I2=67%, see Figure 2e). In a sensitivity analysis excluding one study that did not control for BMI [24], results remained the same i.e. OR=1.29 (95%CI 1.08-1.54). (I2=64%, see Online Resource 3a). No association was seen in the meta-analysis between fibrinogen. -p. and CRC risk (409 cases, Figure 2f), but a positive association has been reported in two prospective. studies that used HR as risk measure [76, 94]. Only one [32] out of six [28, 32, 34, 51, 74, 87] studies. re. (some using HR while others OR) on IL-6 and CRC reported a positive association with OR=1.76 (95%CI 1.01-3.06). All other inflammatory parameters were examined in less than 4 studies.. lP. Breast cancer. Twenty-two studies (21 publications) described the relation between inflammation and risk of breast. na. cancer. For CRP, 10 studies, with a total of 11241 cases among 291108 participants, were included in the meta-analysis resulting in HR=1.14 (95%CI 1.01-1.28), with substantial heterogeneity (I2=67%,. ur. P=0.001, see Figure 2a). A smaller meta-analysis, including only five nested case-control studies with 2793 cases showed a significant association in similar direction with OR=1.23 (95%CI 1.05-1.43,. Jo. I2=0%, see Figure 2b). The meta-analysis on leptin with 1547 cases (OR=1.07, 95%CI 0.67-1.71, Figure 2c) and on adiponectin with the same 1547 cases (OR=0.95, 95%CI 0.81-1.12, Figure 2d) did not find a significant association. With fibrinogen [76, 88] and IL-6 [20, 64, 70, 86] no associations were found. One [20] out of three [1, 20, 70, 86] studies on TNF-α observed a significant inverse association: the odds of breast cancer in participants with the lowest TNF-α concentration was 1.53 times higher (95%CI 1.01-2.33) than in participants with the highest TNF-α concentration. Some studies stratified 9.

(11) on menopausal status and often found a positive association only in the postmenopausal group [62, 83, 101]. Lung cancer The association between inflammation and risk of lung cancer was described in 22 studies (19 publications). The meta-analysis on CRP and reporting HR as outcome included 4 studies with a total of 744 cases among 111928 participants resulting in HR=2.03 (95%CI 1.59-2.60), with low heterogeneity (I2=14%, P=0.32, Figure 2i). However, the meta-analysis of studies reporting OR as. ro of. outcome with 1337 cases [48-50, 80] was not significant (OR= 1.42, 95%CI 0.80-2.50; I2=80%, Figure 2j). A significant positive association was seen in the meta-analysis for fibrinogen (4 studies, OR=2.56, 95%CI 1.86-3.54, I2=0%, Figure 2k) and IL-6 (5 studies, OR= 1.41, 95%CI 1.12-1.78, I2=36%, Figure 2l). -p. with risk of lung cancer. In sensitivity analysis excluding one study [43], the association between IL-6 and risk of lung cancer remained significant (Online Resource 3b).. re. Prostate cancer. Seventeen studies investigated the relation between inflammation and risk of prostate cancer. Of all. lP. inflammation parameters, CRP was most often investigated (13 studies) [44, 52, 55, 58, 76, 86, 93, 95-97, 99, 102, 109] but only three [55, 95, 109] found a significant association. The first meta-. na. analysis for CRP based on HR showed a significantly increased risk and included eight studies with a total of 3132 cases among 96284 participants (HR= 1.09, 95%CI 1.03-1.15, I²=0%, Figure 2o). The. ur. second meta-analysis for CRP based on OR was not significant and included 1248 cases (5 studies; OR=1.19, 95%CI 0.68-1.64, Figure 2p). In the sensitivity analysis, three studies were excluded from. Jo. the summary HR [86, 93, 99], but this did not change the results (Online Resource 3d). Our metaanalysis for white blood cell count based on 8037 cases in 4 studies was non-significant (HR=1.14, 95%CI 0.91-1.43, Figure 2q). No significant associations were observed with fibrinogen [76, 97] and one negative association with IL-6 [52, 65, 86, 93] and TNF-α [65, 86]. Ovarian cancer. 10.

(12) Ten studies (9 publications) described the relation between inflammation and risk of ovarian cancer. For CRP, eight studies [35, 36, 41, 54, 57, 61, 112] with a total of 2980 cases were included in the meta-analysis and resulted in a significant OR=1.41 (95%CI 1.10-1.80, I2=58%, Figure 2n). In a sensitivity analysis, which excluded three studies that did not control for BMI [19, 36, 54], the association remained (OR=1.35, 95%CI 1.00-1.81, I2=64%, see Online Resource 3c). Mixed results were found for the association between IL-6 or TNF-α and risk of ovarian cancer, where only one [18] out of three and one [57] out of two reported a significant positive association, respectively.. ro of. Gastric cancer In the five studies, mixed results were reported on the association between inflammation and risk of gastric cancer. A Japanese study noted that the odds of gastric cancer was 1.90 times higher (95%CI. -p. 1.19-3.02) in the highest quartile of CRP when compared to the lowest quartile [47]. A European. study did not confirm this finding [58]. Interestingly, two studies on the association between IL-6 and. re. risk of gastric cancer showed a relationship for women (OR=1.73, 95%CI 1.00-3.00) [59], but not for men [23]. Helicobacter pylori infection was highly prevalent: statistical adjustment for H. pylori. association [47].. na. Non-Hodgkin lymphoma. lP. infection often had limited effect [23, 59] but sometimes magnified the inflammation-cancer. Five studies considered non-Hodgkin lymphoma as outcome. Two studies describing the relation with. ur. CRP reported no significant association [19, 46]. The same was true for IL-6 [19, 22]. For TNF-α, the two studies reported contrasting results: a positive association (OR=1.8, 95%CI 1.1-2.9) [45] and non-. Jo. significant findings [19]. Importantly, the last one did not control for BMI and smoking. Another study found a significant increased risk predicted by a 28 component inflammatory score [12]. Endometrial cancer. No associations were seen between individual inflammation parameters (CRP, IL-6 and TNF-α) and risk of endometrial cancer in the three studies identified [25, 56, 72]. A combined inflammation factor (including TNF-receptors, IL-6 and CRP) also did not find an association [11]. 11.

(13) Other specific cancer sites The four studies on pancreatic cancer did not find a significant relation with IL-6, TNF-receptors or TGF-β but one study found significant positive associations for CRP, haptoglobin and leukocyte counts [15, 26, 31, 63]. The meta-analysis between fibrinogen and cancer risk was non-significant for male genital (OR=0.92, 95%CI 0.63-1.35, Figure 2m), digestive (OR=0.93, 95%CI 0.65-1.31, Figure 2g) and hematological cancer (OR=1.10, 95%CI 0.62-1.92, Figure 2h) [80]. The relation between CRP and risk of brain, bladder, cervix uteri, corpus uteri, leukemia/lymphoma, multiple myeloma, thyroid and. ro of. skin cancer was only investigated once [58, 77, 106] with positive associations for leukemia/lymphoma and corpus uteri cancer risk. No consistent results were described in the studies that investigated the relation between CRP and risk of liver [39, 58] and kidney [58, 77] cancer.. -p. Overall cancer risk. The association between inflammation and overall cancer was reported in 23 studies (20. re. publications) [55, 58, 75, 80-82, 85, 86, 90, 91, 95, 96, 98, 100, 102-105, 108, 110]. CRP was found to be associated with risk of cancer in the majority of studies (11 out of 18). In the meta-analysis, 12. lP. studies [82, 91, 96, 98, 100, 102, 104, 105, 110] were included with a total of 12844 cases among 153105 participants, resulting in a summary HR of 1.35 (95%CI 1.16-1.57, I2=82%, Figure 2r), an Egger. na. p-value of 0.461 showed no proof of publication bias. Similar results were noted in the sensitivity analysis on four studies [91, 99, 104] (Online Resource 3e). A positive relation was also seen in the. ur. meta-analysis with fibrinogen (summary OR=1.22, 95%CI 1.07-1.39, I2=0%, Figure 2s). One significant. Jo. positive association was detected with IL-6 [81, 86, 110] but not with TNF-α [86]. DISCUSSION. Evidence for cancer associations Nineteen meta-analyses were performed on CRP, IL-6, fibrinogen, leptin, adiponectin and white blodd cells at various cancer sites, ten of which showed a positive association: CRP-breast OR and HR, CRP-colorectal, CRP-lung HR (but not with OR), fibrinogen-lung, IL6-lung, CRP-ovarian, CRP-prostate HR (but not with OR), CRP-overall and fibrinogen-overall. Of the sensitivity-analyses on studies with 12.

(14) BMI adjustment, none resulted in disappearance of the significant finding. No association was observed between fibrinogen and CRC, haematological, digestive cancers, and male genital cancers; for white blood cells with prostate cancer; or for leptin and adiponectin with breast cancer. Heterogeneity was in general low-to-moderate but was high for CRP with breast cancer HR, CRP with lung cancer OR and CRP with overall cancer HR. Effect sizes for significant meta-analyses were often weak around 1.2, only for lung cancer with fibrinogen a high summary OR of 2.56 was found. From. ro of. the inflammatory parameters, CRP resulted in most significant findings i.e. 40%.. Specificity in cancer site of origin and inflammatory parameter type. In our meta-analyses, CRP was often a significant cancer predictor. An older meta-analysis [113]. -p. confirmed CRP as predictor of overall cancer and lung cancer. In contrast to our results, that meta-. analysis got non-significant positive results for breast (using HR) and colorectal cancer, probably due. re. to our inclusion of recent significant studies. Especially towards colorectal cancer, the causal role of general inflammation as reflected by CRP was confirmed by genetic polymorphism studies [114].. lP. Concerning ovarian cancer, a meta-analysis [115] in 2017 confirmed our positive cancer risk prediction by CRP.. na. Our meta-analyses for CRP distinguished between studies based on HR (prospective studies) versus OR (case-control studies): for lung and prostate cancer only the prospective studies resulted in. ur. significant meta-analysis. This could not be explained by a clearly different study quality score, follow-up time, age and sex or a larger amount of cases in the significant meta-analyses. However,. Jo. higher heterogeneity indices were found in the non-significant meta-analyses. Our fibrinogen meta-analyses were significant for lung and overall cancer, but not for breast and colorectal cancer although all those meta-analyses were based on exactly the same studies and the cancer types were significantly associated with CRP. Thus, fibrinogen may be a more specific inflammatory pathway for lung cancer. Both fibrinogen and CRP are acute-phase reactants but CRP is rather active in host defence while fibrinogen is important for coagulation regulation. Apart from 13.

(15) cancer risk, fibrinogen might thus also stimulate metastasis. Although CRP and fibrinogen both performed similarly good in differential cancer diagnosis in one study [116], differential acute-phase reactive protein fingerprints were seen depending on cancer type [117]. Finally, our meta-analysis on IL-6 and lung cancer included many new studies not part of a metaanalyses from 2008 and emphasized a significantly increased risk by high IL-6 where the former meta-analysis could not [7]. Poor lung function was associated with inflammation that may reduce. ro of. the ability to clear carcinogenic substances from the lungs.. Within our overall systematic review, most evidence was found for CRP, IL-6, fibrinogen and TNF-α as more general, less specific inflammatory parameters. CRP and fibrinogen as acute-phase reactant. -p. proteins play an important role in the inflammatory process and are produced by hepatocytes in. response to cytokines, particularly IL-6 and to a lesser extent by IL-1 and TNF-α [118, 119]. These. re. three cytokines were also frequently investigated, although IL-1 less frequently. Overall, 119 different inflammatory markers were considered in the selected publications, but none of them were. lP. consistently positively associated with cancer risk and many were only investigated a few times. Thus, there is currently no strong observational evidence for selectively suppressing specific pro-. na. inflammatory mediators as strategy for cancer prevention/treatment [3]. Further investigation of these rather new biomarkers and the use of combined inflammatory scores may increase the. ur. mechanistic insights towards cancer risk.. Jo. Research recommendations. Although this review demonstrates evidence for the link between chronic inflammation and the risk for overall, breast, colorectal, lung, ovarian and prostate cancer, we could not make conclusive statements on the link with many other cancers due to low amounts of studies and conflicting results. Herein, more high quality studies are certainly needed. The median NOS quality score of the. 14.

(16) included publications was overall good, except from three studies that scored only 5/9 and 12 that scored 6/9. First, large intra-individual variation in inflammation markers is a problem and thus ascertainment of chronic inflammation was a major weakness in the identified studies. To combat this problem, we recommend the use of multiple markers to quantify chronic inflammation by multiplex immunoassays (which also allows identification of new important inflammatory mediators) and/or repeated measurements of the same marker at different points in time. After all, CRP as the most frequently. ro of. used biomarker has only a moderate intraclass correlation coefficient (ICC) of 0.73 over 4-6 months and 0.66 over 4 years [120, 121]. During a mean 11.8y follow-up, both baseline CRP and CRP 6-year change predicted prostate cancer risk [109]. Some studies in this review combined inflammatory. -p. biomarkers into a score or a profile/pattern as a more robust method for quantifying chronic. inflammation; this has been reviewed as a promising approach for colorectal cancer [122]. Indeed,. re. some studies found an added value of a multi-parameter score compared to the single parameters [76, 109].. lP. The NOS instrument also identified case definition inadequacy as a limitation of the included publications. It is indeed important to have independent validation of cancer status instead of self-. na. reports and to exclude cases diagnosed within 2 years of blood withdrawal to minimize the chance of the marker levels being caused by undiagnosed cancer (reverse causation). One study suggested. ur. reverse causation since circulating inflammatory cytokines but not cytokine production capacity was associated with increased cancer incidence and the fact that tumor cells have autocrine cytokine. Jo. production [110]. However, it could be that the inflammatory marker may predict the need for a timely investigation of patients with raised inflammatory markers [123]. In cancer diagnosis, long follow-up and prevention of loss-to-follow-up is needed to reduce possible bias. Furthermore, adequate confounder adjustment and mediation/moderation analyses are often missing, which helps to discover potential pathways (i.e. mediation) and identify high-risk groups (i.e. moderation). Although 98% of the studies adjusted for age, only 71% adjusted for BMI and less for 15.

(17) medication use or lifestyle factors. However, a recent review highlighted the role of physical activity, obesity and sedentary behavior in cancer etiology [124] as they effect endogenous sex steroids, metabolic hormones, insulin sensitivity, and chronic inflammation. In fact, inflammation can be a mediator in the relation between adiposity and cancer, as shown in two of the selected publications [72, 74]. Indeed, leptin, a peptide hormone produced by adipocytes, has been shown to have pro-inflammatory activity and to upregulate the secretion of TNF-α and IL-6 [125]. It is possible, therefore, that overcorrection may happen when adding BMI to the inflammation-model, resulting in. ro of. non-significant findings. Most of the publications included in this review did not report the separate effect of BMI on the significance of inflammatory biomarkers towards cancer. Twelve studies. reported that adjusting for BMI had only a limited effect on the association, while three studies. -p. reported that the significant association with biomarkers became non-significant after. adjustment [56, 74, 101]. In our sensitivity analyses, the meta-analyses on the BMI-adjusted results. re. did not differ substantially from the overall meta-analyses results. Anyway, a step-wise introduction of confounders by showing several models is recommended. The high diversity in used. lP. methodology/confounders might explain part of the conflicting results. Next to mediation analyses, moderation analyses (testing interaction) might detect groups at higher risk for inflammation-related. na. cancer (e.g. depending on age, sex, ethnicity, molecular/clinical cancer subtype, etc.) and explain the fact that certain cancers are not related to inflammation in the general population and thus the. ur. presence of inconsistencies [3].. Future studies should try to understand the complex relationship between the microbiome and. Jo. cancer susceptibility which can lead to targeted antimicrobial therapies [126]. Intestinal microbiota are an important contributor to inflammation and health, influencing how the host responds to cancer risk [127], and how the host responds to cancer therapy [128]. Thus, dysbiosis can lead to the increased production of toxins, which can provoke inflammation and tumorigenesis [129, 130]. Of course, results from experimental studies and further ‘in vitro’ studies will be needed to better understand the mechanisms. 16.

(18) Clinical implications Future research should investigate whether these inflammatory markers provide meaningful improvements for overall or site-specific cancer risk stratification beyond other major risk factors such as age, sex, and smoking characteristics. If this holds true then these markers could be used to identify people at a higher risk for cancer, that could be potential candidates for anti-inflammation interventions.. ro of. Several approaches can be taken to combat chronic inflammation and subsequently lower the risk of cancer development. Epidemiological data has shown that frequent usage of non-steroidal anti-. inflammatory drugs reduces the risk of developing certain cancers (such as colon and breast cancer). -p. and reduces the mortality caused by these cancers [4]. However, these drugs have well-known side effects and are not suited for long-term usage.. re. Another approach is to selectively suppress certain pro-inflammatory mediators. Several molecules being tested include TNF-α blockers, IL- 1 blockers, NF-κB inhibitors and COX-2 inhibitors.. lP. Importantly, several markers are not cancer-specific e.g. the soluble urokinase plasminogen activator receptor has been associated with both cancer and cardiovascular risk [131]. Caution is also needed. na. since T-helper1 cytokines may even function to prevent tumor development [65]. While most evidence discussed in this review indicates that pro-inflammatory cytokines, enzymes, oncogenes. ur. and transcription factors play a pivotal role in mediating tumorigenesis, the existing literature also suggests that inhibition of pro-inflammatory pathways is not always beneficial [2]. For example, the. Jo. pro-inflammatory transcription factor NF-κB, which is closely related to all known cancer hallmarks [6], has been reported to also have inhibitory effects on tumor formation [132]. Thereby, inhibition of pro-inflammatory pathways may act as a double-edge sword [2]. Targeted therapies that can interfere with the recruitment of bone-marrow-derived cells or specifically directed at specific components of the tumor microenvironment might also be tested in the future as treatment regimens for inflammation-driven cancers [2]. 17.

(19) Lastly, the link between obesity, chronic low-grade inflammation and cancer underscores the recommendation to maintain a healthy body weight throughout life as an important way to protect against cancer [133]. An anti-inflammatory diet is recommended since a dietary inflammatory index was positively associated with 15 site-specific cancer risks by meta-analysis [134]. A healthy antiinflammatory lifestyle (no smoking, limiting alcohol consumption and stress, etc.) should be recommended for cancer prevention.. ro of. Strengths and limitations The strengths of this review and meta-analysis mainly lie in the systematic and methodical approach for gathering the relevant articles. Three databases were searched with broad search strategies to. -p. minimize the odds of missing relevant studies and the articles obtained with these queries were. manually screened by two independent authors. Quality assessment was also performed using an. re. adapted version of the NOS to assess the risk of bias, on which the majority of studies performed well. The strengths of the included studies were large sample sizes and a median follow-up time of. lP. 10.5 years. Another common trait among the included studies was the extensive adjustment for covariates (by matching cases with controls and/or the use of multiple regression models).. na. This review does however also have its limitations. The main limitation is the limited amount of studies found per cancer type. Some studies reported on multiple cancer types increasing the. ur. amount of data. However, these studies tended to have smaller case numbers and less extensive adjustments for cancer types reported on as secondary outcomes. A related limitation is that meta-. Jo. analysis was only possible on some inflammation-cancer relations and some of them only had a small amount of included studies. Different methodologies in the articles (chosen risk measure, categorizations into different percentiles vs clinical cut-offs, etc.) also made it difficult to compare results in the meta-analysis. Another limitation is that most studies only had access to baseline measurements of inflammatory parameters. Measurements at a single point in time are of course suboptimal to quantify chronic inflammation but the most frequently used markers (CRP, fibrinogen, 18.

(20) IL-6 and TNF-α) all have quite high ICC’s (>0.6). The impact of intra-individual variations of marker levels over time is also reduced by large sample sizes. Since this review’s focus was on inflammation as trigger towards cancer from a preventive perspective, no studies were included on inflammation as a result of cancer. Last but not least, this review only covered observational studies which weakens the statements on causality. Conclusion This review provides an overview of the epidemiological evidence that elevated levels of circulating. ro of. inflammatory markers are associated with an increased risk of overall, breast, colorectal, lung,. ovarian and prostate cancer, although these associations depend on the examined inflammatory. parameters and risk measures used. CRP was the most frequently examined inflammatory parameter. -p. and was also more frequently significantly related to increased cancer risk. Overall, chronic. inflammation seems to play a pivotal role in cancer development, though not necessarily for all. re. cancer sites. This offers perspectives towards prevention and treatment of cancer. However, further. lP. high-quality epidemiological and experimental research is necessary to resolve the inconclusive results and to clarify the mechanisms behind this association. Most observational evidence was found for general inflammatory markers without strong evidence yet for selectively suppressing. ur. na. specific pro-inflammatory mediators in cancer prevention/treatment.. Funding: N. M. is financially supported by Research Foundation-Flanders (FWO 12H1519N) as. Jo. postdoctoral researcher. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the IARC/WHO. Conflicts of interest: none. 19.

(21) Authors' contributions: MN and IH designed the study; NM,JM,CVA executed the literature search, NM and CVA wrote the first draft, AM and IH fine-tuned the draft including background literature. Jo. ur. na. lP. re. -p. ro of. None declared.. 20.

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(30) Biography: Nathalie Michels has a PhD in biomedical sciences since 2013 and is postdoctoral researcher at Ghent University. Carola van Aart has a master in biomedical sciences and obtained her PhD in 2020 at Ghent University. She is now embedded librarian at Hogeschool Rotterdam. Jens Morisse has a master degree in medicine. He performed his master thesis on this topic at Ghent University under supervision of Inge Huybrechts and Nathalie Michels.. ro of. Amy Mullee has a PhD in Nutrition from Ulster University and is a lecturer in human nutrition within the UCD Institute of Food and Health. Before, Amy was an IARC-Ireland Postdoctoral. Fellow sponsored by the Irish Cancer Society spending one year at UCD and two years at the. -p. International Agency for Research on Cancer in France.. Inge Huybrechts is visiting professor at Ghent University and full-time scientist at the. Jo. ur. na. lP. re. International Agency for Research on Cancer within the Nutritional Epidemiology Group.. 29.

(31) lP. re. -p. ro of. Figure Legends. Jo. ur. na. Fig.1 PRISMA flowchart for the selection of studies. 30.

(32) ro of -p re lP na ur Jo Fig.2 Meta-analyses results. 31.

(33) Author and year. Study name. Country. Bladder cancer. Trichopoulos et al, 2006. Greece. Brain cancer. Trichopoulos et al, 2006. Breast cancer. Agnoli et al, 2017. European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Greece European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Greece European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Italy Copenhagen General Population Study. Age at enrolment. 49%. Median or range followup (yrs) 5-10. 11/22. 49%. 5-10. 20-86. Nested-case control. 351/351. 0%. 14.9. 35-69. Denmark. Prospective cohort. 822/44715. 0%. 4.8. Median age: 58 (IQR 4867). European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Italy Northern Sweden Health and Disease Study The Malmö Diet and Cancer study The E3N cohort. Italy, Sweden. Nested-case control. 90/77. O%. 2-15.5. 35-70. Sweden. 446/885. 0%. 14-19. 55-73. 575/1040. 0%. 4.2. The Tromsø study. Norway. 192/8130. 0%. 14.6. CLUE II. USA. Nested casecontrol Nested casecontrol Prospective cohort Nested casecontrol. 272/272. 0%. 15. Mean age 57 Mean age 50 62. Dias et al, 2016 Dossus et al, 2014 Frydenberg et al, 2016 Gross et al, 2013. % male. Nested-case control. 17/34. Nested-case control. Italy. Greece. e-. Jo ur. Berger et al, 2018. # cases/controls # cancer/total. Pr. na l. Allin et al, 2016. Study design. pr. Cancer type. oo. f. Table 1. Description of included studies.. France. 20-86. 32.

(34) USA. Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) Study European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Greece The Chinese Kailuan Female Cohort Nurses' Health Study (NHS). France. Women's Health Study (WHS) The Apolipoprotein MOrtality RISk (AMORIS) study. USA. Jo ur. Trichopoulos et al, 2006. Wang et al, 2015 Wang Jun et al, 2015 – NHS. Wang Jun et al, 2015 - WHS Wulaningsih et al, 2015. 875/839. 0%. 6-11. 50-79. Prospective cohort. 33/2438. 0%. 70-79. Prospective cohort Prospective cohort Nested casecontrol Prospective cohort. 275/4831. 0%. 2.7 for cases, 6.4 for non-cases 11.4. 1114/17841. 0%. 13.6. 50-79. 706/706. 0%. 3-8. 45-75. 176/7603. 0%. 8-10. 45-64. Prospective cohort Nested-case control. 184/3190. 0%. 10.2. ≥ 55. 218/436. 0%. 6.5 for cases, 13 for controls. 51. Greece. Nested-case control. 83/166. 0%. 5-10. 20-86. China. Prospective cohort Nested casecontrol. 87/19437. 0%. 4.9. 49.2. 943/1221. 0%. 4.5. 43-69. Prospective cohort Prospective cohort. 1919/25981. 0%. 8.5. > 45. 6 606/155179. 0%. 18.3. > 20. oo. f. Women’s Health Initiative (WHI) study Women's Health Initiative (WHI) study Multiethnic Cohort (MEC) Study Atherosclerosis Risk in Communities (ARIC) cohort The Rotterdam Study. na l. Siemes et al, 2006 Touvier et al, 2013. Nested casecohort. USA. USA USA. pr. Kabat et al, 2016 Nelson et al, 2017 Ollberding et al, 2013 Prizment et al, 2013. USA. e-. Il’yasova et al, 2005. Women’s health initiative observational study (WHI-OS) The Health Aging and Body Composition study. USA. Pr. Gunter et al, 2015. The Netherlands. USA. Sweden. 50-79. 33.

(35) Norway. Zuo et al, 2015. Hordaland Health Study. Norway. Aleksandrova et al, 2014. European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort. Aleksandrova et al, 2015. European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort. Aleksandrova et al, 2016. European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Potsdam Copenhagen General Population Study. Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, the UK Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, the UK Germany. 0%. 12. 46-74. 98/6539. 0%. 11.9. 46-74. 1260/1260. 47%. 7. 25-70. Nested casecontrol. 830/830. 44%. 7.2. 35-70. Nested case cohort. 251/2295. 10.4. 35-64. Denmark. Prospective cohort. 592/83397. 60% (cases) 40% (cohort) 45%. 4.8. Italy. Nested-case control. 48/48. 42%. Not stated. Sweden. Nested-case control. 1010/1010. 52%. 12.3. 56.3 (5060). Chandler et al, 2016 - WHS. European Prospective Investigation Into Cancer and Nutrition (EPIC) cohort – Florence Northern Sweden Health and Disease Study (NSHDS) Women's Health Study (WHS). Median age: 58 (IQR 4867) 35-65. USA. Prospective cohort. 337/34320. 0%. 19. >45. Chandler et al, 2016 - MESA. Multi-Ethnic Study of Atherosclerosis (MESA). USA. Prospective cohort. 70/6784. 47.2%. 11. 45-84. Allin et al, 2016. Boden et al, 2020. pr. e-. Pr. Jo ur. Bertuzzi et al, 2015. Prospective cohort Prospective cohort Nested casecontrol. f. 108/6594. oo. Hordaland Health Study. na l. Colorectal cancer. Zuo et al, 2014. 34.