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Systematic Review

Humulus lupulus (Hop)-Derived Chemical Compounds Present Antiproliferative Activity on Various Cancer Cell Types: A Meta-Regression Based Panoramic Meta-Analysis

by
Georgios Tsionkis
1,†,
Elisavet M. Andronidou
1,†,
Panagiota I. Kontou
2,
Ioannis A. Tamposis
1,
Konstantinos Tegopoulos
3,
Panagiotis Pergantas
4,
Maria E. Grigoriou
3,
George Skavdis
3,
Pantelis G. Bagos
1 and
Georgia G. Braliou
1,*
1
Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece
2
Department of Mathematics, University of Thessaly, 35132 Lamia, Greece
3
Department of Molecular Biology & Genetics, Democritus University of Thrace, 68100 Alexandroupolis, Greece
4
Bioapplications Ltd., 32131 Levadia, Greece
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Pharmaceuticals 2025, 18(8), 1139; https://doi.org/10.3390/ph18081139
Submission received: 25 June 2025 / Revised: 22 July 2025 / Accepted: 25 July 2025 / Published: 31 July 2025
(This article belongs to the Special Issue Pharmacological Activities of Flavonoids and Their Analogues, Third Edition)
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Abstract

Background/Objectives: Humulus lupulus (hops) are a perennial, dioecious plant widely cultivated for beer production, used for their distinguishing aroma and bitterness—traits that confer high added value status. Various hop-derived compounds have been reported to exhibit antioxidant, antimicrobial, antiproliferative and other bioactive effects. This systematic review and meta-analysis assesses the impact of hop compounds on the viability of diverse cancer cell lines. Methods: A comprehensive literature search was performed following PRISMA guidelines. Data were synthesized via multivariate meta-analysis and meta-regression, using IC50 values as the effect size. Key variables included assay type (SRB, tetrazolium salt-based, crystal violet), exposure duration (24, 48, 72 h), specific hop compound and cancer cell line. Results: Of 622 articles identified, 61 met eligibility criteria, yielding 354 individual experiments. Meta-regression of xanthohumol (XN) IC50 values across SRB, tetrazolium and crystal violet assays revealed no statistically significant differences at 24 h (p = 0.77), 48 h (p = 0.35) and 72 h (p = 0.70), supporting the interchangeability of the methods. Meta-analysis confirmed that hop constituents inhibit cancer cell proliferation; XN emerged as the most potent flavonoid (IC50 = 16.89 μM at 72 h), while lupulone was the strongest compound overall (IC50 = 5.00 μM at 72 h). Crude hop extracts demonstrated greater antiproliferative selectivity for cancer versus non-cancer cells (IC50 = 35.23 vs. 43.80 μg/mL at 72 h). Conclusions: Hop compounds, and particularly bitter acids, demonstrate promising antiproliferative activity against cancer cells with comparatively low toxicity to healthy cells. Furthermore, our analysis confirms the comparability of SRB, tetrazolium-based and crystal violet assays, supporting the robust integration of antiproliferative data.

1. Introduction

Humulus lupulus, commonly known as hops, are a climbing, flowering, dioecious plant that belongs to the hemp family Cannabaceae. Hops hold significant importance in the brewing industry since its female flowers, also called cones or hops, convey distinctive aromas, flavors and bitterness to the beer, while also inhibiting the growth of beer-spoilage bacteria. Beyond brewing, hops have attracted considerable scientific interest due to a multitude of biological activities, such as antioxidant, cancer chemoprotective, anti-angiogenesis, sedative, antibacterial, estrogenic, antidepressive, antifungal, insect antifeedant and antiviral effects [1,2,3,4,5,6,7,8]. The earliest scientific report of hop constituents goes back to 1913 [9], where its polyphenols, bitter acids and essential oils were first identified.
Xanthohumol (XN) is the most prevalent compound among hop polyphenols constituting 80–90% of all hop prenylflavonoids [10]. XN’s structural isomers, isoxanthohumol (IXN) and desmethylxanthohumol (DMX), and downstream metabolites, including 8-prenylnaringenin (8-PN) and 6-prenylnaringenin (6-PN), comprise much of the remaining prenylflavonoid constituent. These compounds are often present at higher concentrations in beer and within the human intestine because XN is extensively isomerized and metabolized to these derivatives [11]. Apart from polyphenols, bitter acids (prenyl derivatives of floroglucin) represent another key class of hop constituents. Alpha acids encompass humulone and its analogues, while beta acids include lupulone and its analogues [12].
Xanthohumol has been reported to show potential “broad-spectrum” anticancer activity in the initiation, promotion and progression of cancer [13]. Several reports on various carcinoma cell lines suggest a range of mechanisms through which XN may exert its anticancer potential. Cancer chemo-prevention activity has been attributed to its antioxidant activity by scavenging ROS, thus preventing oxidative damage [3,14]. In addition, the anticancer activity of XN may be mediated through its apoptotic potential by inducing caspase-dependent degradation of the BCR-ABL oncoprotein [15] or via activation of the MAPK JNK kinase [16]. It has also been proposed that XN anticancer activity involves the inhibition of DNA synthesis or G0/G1 cell cycle arrest [12].
Hops’ alpha bitter acids possess mild antiseptic activity against Gram-positive bacteria while their beta acids are reported to be more potent antimicrobials [12,17], thus making hops particularly suitable as beer preservatives [18]. Moreover, alpha bitter acids exhibit sedative and hypnotic effects with potential therapeutic applications in insomnia and attention deficit hyperactivity disorder (ADHD) through modulation of the GABAA receptors. Beta bitter acids, on the other hand, have been associated with antidepressant-like effects [19,20]. While there is substantial evidence that XN possesses cancer antiproliferative activity, only a limited number of studies have examined the antiproliferative activity of hop bitter acids; notably, these studies suggest that beta bitter acids may exhibit substantially greater antiproliferative activity than XN [17].
Given the wide variety of hop compounds and extract types tested across numerous cancerous and non-cancerous cell lines, it becomes imperative to quantitatively assess and compare the antiproliferative effects of each individual compound and extract. The variation in treatment protocols—particularly in compound concentrations and incubation times—adds an additional layer of complexity when comparing results across cell culture studies. These inconsistencies make it difficult to reliably assess and compare the antiproliferative efficacy of different hop compounds against various cancer cell lines.
Another parameter that further shapes the controversy of the antiproliferative effect is the wide range of assays used to measure cell viability. Broadly, these assays fall into three main categories: (a) sulforhodamine B (SRB) assays that measure cellular protein content [21], (b) tetrazolium dye assays (MTT) based on NAD(P)H-dependent cellular oxidoreductase enzymes [22] and (c) a crystal violet assay (CV), which quantifies DNA as a proxy for a cell number [23]. The outcomes of these assays are typically reported as IC50 values, i.e., the concentration of a compound needed to inhibit a biological process (herein cell viability or proliferation) by 50%.
The emerging interest in specific natural compounds and medicinal plant extracts with potential health benefits underscores the need to systematically synthesize, compare and summarize antiproliferative activity data of hop-derived compounds. This can be effectively achieved through a systematic review and meta-analysis, ensuring statistical rigor and comprehensive evaluation. Meta-analysis is a component of evidence-based scientific practice, also known as metascience. This approach applies scientific methodologies to analyze scientific results, often from multiple resources, aiming to uncover methodological flaws, inefficiencies and suboptimal practices across various scientific disciplines. Findings from such analyses often serve as valuable guidelines to enhance reproducibility, particularly in biomedical research, by integrating results across diverse scientific methodologies and protocols. The field of metascience has emerged in response to the so-called “replication crisis,” reflecting a growing awareness of the need for greater transparency, rigor and reliability in scientific research [24,25,26].
The objective of this study is to statistically synthesize all available data from the literature to evaluate the antiproliferative potential of various hop compounds across a broad spectrum of cancer cell lines. This meta-analysis aims to quantitatively integrate available evidence, identify interchangeable methodologies and summarize the antiproliferative effects of the studied compounds. By analyzing diverse study outcomes, it seeks to provide a comprehensive overview that extends beyond the insights of individual studies.
Through meta-regression, the analysis also investigates methodological equivalence and, given the differing chemical principles underlying various assays, assesses the feasibility of establishing more reliable approaches for cross-study comparisons.

2. Results

2.1. Selection and Characteristics of Studies

From the systematic literature search in the PubMed database carried out by 1 June 2024, according to PRISMA guidelines, 622 articles were retrieved. Of these, 561 were excluded because they did not provide data (studies were on extracts of other plants, other biological parameters or reviews) (Figure 1). The 61 articles (encompassing cell viability assays for hop compounds) that fulfilled the eligibility criteria incorporated data from a total of 317 experiments on various cell lines that were included in the meta-analysis. There were 262 experiments involving cancer cell lines, comprising 19 different cancer types and 14 chemical compounds (Table 1 and Supplementary Table S1), with breast cancer being the most common. There were 55 experiments on normal cell lines. Of the eight chemical compounds tested in the 262 experiments (Figure 2), XN was the most studied (in 55% of the total experiments), IXN was studied in 15% of the experiments, 8-prenylnaringenin in 9%, α,β-dihydroxanthohumol in 4%, DMX in 4% and 6-prenylnaringenin in 4%. Moreover, 153 experiments were performed with tetrazolium salt-based assays, 139 with the SRB assay and 25 with the CV assay. The MTT, XTT, WST or MTS assays were all grouped within the tetrazolium salt-based assays (tetrazolium), since they are all based on the same chemical principle, in order to achieve a higher-order classification group and to obtain a more statistically powerful pooled effect size. Our meta-analysis was also built on the basis of the same time period of cells exposed to compounds, thus creating three main groups of 24, 48 and 72 h of treatment.

2.2. Interchangeability of Tetrazolium-Based, SRB and CV Assays

A great concern of researchers investigating antiproliferative activity of plant extracts is which type of assay best corresponds to the true values. In the absence of a gold standard method, many investigators perform the same experiments using two or three of the tetrazolium salt-based, SRB and CV assays to validate their findings and ensure reliability. Initial meta-analysis stratifying for every compound, every incubation time period and every cell type (plus collectively for cancer and non-cancer cell lines), along with stratification for each type of assay, produced such an overabundance of results regarding IC50 values (Supplementary Table S2) that analyzing each of these contrasts would produce puzzling results that are difficult to interpret. In the present study, we took advantage of the plethora of experiments available on ΧΝ activity to test whether any of these assays could be used interchangeably. The trigger towards this idea was given by the fact that the IC50 values for ΧΝ for all time points (24, 48, 72 h) during the treatment of cancer cell lines were quite close between all three methods. As shown in Figure 3 (and Supplementary Table S3) for cancer cell lines after 48 h, the IC50 values were 17.64 μM, 20.78μM and 14.38 μM, while after 72 h, they were 19.85 μM, 14.60 μM and 12.06 μM, for the tetrazolium salt, SRB and CV assays, respectively. Similarly, for non-cancer cells, the respective IC50 values were, after 48 h, 53.89 μM for tetrazolium, and after 72 h, 34.53 μM and 31.03 μM for the tetrazolium and SRB assays, respectively. No data existed for non-cancer cells with the CV assay.
To test the hypothesis of whether these differences in IC50 values are due to statistically significant variations, a meta-regression-based meta-analysis was employed to explore the extent to which statistical heterogeneity between results from multiple studies may be related to differences inherent to the assays. As shown in Table 2 (and Supplementary Figure S1), the p-values of all contrasts are >0.05 (p-values 0.78, 0.35 and 0.70 for 24 h, 48 h and 72 h for cancer cells, and 0.52, 0.36 and 0.91 for the non-cancer cells—with no data available from the CV method on non-cancer cells), suggesting that indeed, the IC50 values obtained by each method for cancer and non-cancer cell lines, at each time point of incubation, do not differ statistically significantly. Therefore, these three methods provide comparable results and can be used equivalently to quantify cell viability.
To further verify the equivalence of the tetrazolium salt, SRB and CV methods, a meta-analysis employing standardized mean difference (SMD) approach was performed for studies assessing the same compound outcome on the same cell line for the same incubation time, with results derived from two different assays (Supplementary Table S4). As shown in Table 3, the SMDs of IC50 values derived from tetrazolium salt and CV assays, on exactly the same cell lines, do not show statistically significant differences (SMDs), corroborating the notion that these methods provide equivalent results.

2.3. Antiproliferative Effect of XN Increases with Time of Incubation

Next, and after having proven the equivalence of the three methods, a comprehensive meta-analysis was employed, incorporating the results of the XN treatment obtained via all three methods. Breast and prostate cancer cell lines were the most frequently studied (Supplementary Table S5). Meta-analysis showed that the IC50 value of XN after 72 h in breast cancer is 11.60 μM (13 studies), and in prostate cancer 13.0 μM (9 studies). As shown in Figure 4 and Supplementary Figure S2, the IC50 values of XN in all cell lines decrease with time of incubation. Importantly, the respective IC50 values for cancer cell lines are lower than those of non-cancer cells, indicating that XN exhibits a more potent antiproliferative effect on cancer cells compared to healthy cells (Supplementary Table S5).
To further verify the dependence of the IC50 values of a certain compound on the incubation time, we next performed a regression meta-analysis. Contrasts were performed for cancer and non-cancer cell lines incubated not only with XN, but also with all of the compounds, collectively, tested in the present study, for 24, 48, 72 and 96 h. As shown in Figure 5 (and Supplementary Table S6), the p-values of all contrasts are <0.05, suggesting a clear association of compound incubation time with IC50 values. However, separate tests for IXN, 8-PN, 6-PN and lupulone verified the time dependence of the IC50 values for 8-PN only.

2.4. Antiproliferative Potential of Hops Flavonoids, Bitter Acids and Crude Extracts

To get a better insight into the effect of all studied hop compounds on the proliferation of all tested cell lines, we grouped them into flavonoids (chalcones and flavones) and bitter acids (alpha and beta-acids) and performed a stratification meta-analysis according to cell type and time of incubation (Table 4). We found that chalcones exert a more robust antiproliferative activity on cancer cell lines compared to flavones for all time points i.e., IC50 values of 52.16 μM, 22.54 μM and 15.93 μM for 24, 48 and 72 h, respectively, as compared to 102.26 μM, 43.76 μM and 42.95 μM for 24, 48 and 72 h, respectively (Supplementary Figure S3). Another interesting finding is that bitter acids, and especially beta acids, exert even more vigorous antiproliferative activity compared to all flavonoids; i.e., after 72 h of treatment of cancer cell lines, the IC50 values were 10.06 μM and 5.00 μM for the alpha and beta acids, respectively (Figure 6 and Table 4). Importantly, the IC50 values of the above flavonoids in non-cancer cells were higher compared to cancer cells, suggesting a selective antiproliferative effect against cancer cells compared to non-cancer cells. Concerning bitter acids, the tendency seems reversed; however, the number of studies is so limited for each time point that no robust conclusions can be drawn.
Next, the IC50 values of hop crude extracts were also estimated via meta-analysis. As shown in Table 4, the crude extracts exerted higher antiproliferative activity against cancer compared to non-cancer cells after 72 h of incubation (35.23 μg/mL, compared to 43.08 μg/mL). It should also be mentioned herein that the extracts were either hydroalcoholic (EtOH: H2O 9:1 v/v) or CO2-based supercritical fluid extracts (SFE).
A key characteristic of a potential anticancer agent is its ability to selectively present antiproliferative effects on cancer cell lines while sparing non-cancer cells. To evaluate this property, a meta-regression analysis was conducted. As presented in Table 5, only chalcones demonstrated statistically significant differences in IC50 values (p-values < 0.05) between cancer and non-cancer cells at all time points (24, 48 and 72 h). In contrast, no statistically significant differences were observed for flavones and beta acids. However, it is important to note that the number of studies available for the last two categories was considerably lower than that for chalcones, implying that at least these results should be interpreted with caution.

3. Discussion

Natural products, especially plant-derived compounds, have been crucial in drug discovery, particularly for cancer and infectious diseases. Over 60% of cancer drugs and 75% of treatments for infectious disease originate from natural sources. Nearly 50% of prescribed drugs in Europe and the USA are obtained from natural products or their derivatives [80]. Despite an estimated 250,000 to 500,000 plant species, only 1–10% have been extensively studied for medicinal use [81]. Interest in plant-based cancer treatments is rising due to their potential for lower toxicity compared to conventional therapies. Humulus lupulus, long used in beer production, presents a promising, low-toxicity alternative for anticancer drug development [82]. The cancer chemo-preventive activity of hop compounds was first reported as early as 1999 [3,79]. Since then, a variety of assays have been employed, including MTT and other tetrazolium salt-based assays, SRB and CV, each based on distinct chemical principles that target different cellular components involved in metabolic or structural processes [83,84,85]. Although of absolute need, there is no unique, straightforward and universally accepted method that can be used as the gold standard to evaluate anticancer potential of a compound or plant extract [86,87]. Given the growing body of evidence on the antiproliferative effects of various phytochemicals, including hop constituents, pharmaceutical companies and healthcare professionals increasingly demand a reliable index to quantify and compare the efficacy of these plant-derived compounds and extracts. When methodological comparisons yield conflicting results or hinder the ability to draw reliable conclusions, statistical approaches, particularly meta-analysis, have been recruited to provide an alternative perspective to resolve discrepancies and enhance clarity [25,88,89,90].
Meta-analysis enables the synthesis of findings from numerous studies, even in the presence of heterogeneity, thereby allowing for broader generalizations of an effect [91]. By quantitatively integrating data from diverse methodological approaches on a given topic, it helps identify the most reliable practices that may serve as potential gold standards [92]. Additionally, meta-analysis can reveal sources of variability in outcomes, providing deeper insights into the overall phenomenon and highlighting factors that influence the observed results [93]. This meta-analysis is the first attempt to quantitatively synthesize all available published evidence and evaluate the antiproliferative effects of several hop phytoconstituents across a range of cancerous and non-cancerous cell lines. Rather than evaluating the advantages or limitations of specific assay techniques, the analysis focuses on comparing antiproliferative activity across multiple incubation time points and assay types. The primary goal is to identify factors contributing to variability in test outcomes, reduce methodological inconsistencies, determine assay equivalency in terms of comparable outcomes and synthesize data to lend strength to their conclusions.
Given that half of our retrieved data involved XN, we took this opportunity to examine whether variations in antiproliferative assays results were influenced by inherent methodological variations. Our meta-regression-based approach demonstrated that data stratified by incubation time could be validly combined into a single meta-analysis. Furthermore, despite the limited number of studies available for two additional hop compounds—isoxanthohumol (IXN) and 8-prenylnaringenin (8-PN)—we employed the standardized mean difference (SMD) method to confirm that results across different assay types, including tetrazolium salt-based, SRB and crystal violet assays, are comparable and can be used interchangeably.
Our results further demonstrate that XN exerts a strong antiproliferative effect against most cancer cell lines, while showing significantly weaker activity on normal cell lines. These findings align with those of Viegas et al. [13], who demonstrated that XN (and beer containing hops) can mitigate the mutagenic effects of MeIQx (2-amino-3,8 dimethylimidazo[4,5-f]quinoxaline) and PhIP (2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine), two prevalent heterocyclic aromatic amines found in grilled meat. This protective effect was demonstrated in both the Salmonella typhimurium TA98 and in rat models, where it reduced the formation of aberrant crypt foci in the colon [94]. The fact that the antiproliferative activity of XN is highly dependent on the type of cancer cell line likely reflects the diverse mechanisms through which this activity is exerted. This notion is supported by numerous studies providing evidence that the anticancer properties of XN involve multiple pathways, many of which remain only partially understood. Proposed mechanisms include inhibition of cancer cell proliferation and migration, suppression of angiogenesis, induction of apoptosis or autophagy and cell cycle arrest [16,40,68,73,79,95,96,97,98]. In chronic myelogenous leukemia (CML), XN has also been shown to degrade the BCR-ABL fusion oncoprotein through caspase-mediated apoptosis [15], as well as via MAPK-related signaling pathways, including ERK and JNK [16,99]. In addition, despite the variation in IC50 values for the antiproliferative effect of XN on various cancer cell lines, the effect was clearly dependent on the incubation time. This time-dependent effect was consistently observed across all hop compounds tested and in both cancerous and non-cancerous cell lines.
A particularly intriguing finding of this meta-analysis is the notably strong antiproliferative activity of hop bitter acids—an aspect that has been largely overlooked and remains scarcely studied. Our results show that, among flavonoids, chalcones and particularly XN exhibit greater antiproliferative activity compared to flavones. Intriguingly, bitter acids (especially the beta acid, lupulone) demonstrated even more potent antiproliferative activity. Although beta acids also showed high activity against normal cells, this finding opens new avenues for the potential medicinal application of hops. However, given that the results on normal cell lines are based on only two studies, this outcome should be interpreted with caution. Since more than 50% of an SFE hop extract consists of alpha and beta acids, it is plausible that antiproliferative effects of hops extracts are highly shaped by bitter acids [12]. In line with this, our results showed that crude hop extracts exhibited strong antiproliferative activity, with greater potency against cancerous than non-cancerous cells.
This meta-analysis is subject to several limitations inherent in the individual studies, which may have affected the integrity of our results. The studies included encompassed a wide array of hop phytoconstituents, either purchased, isolated from hops or hop-spent extracts or chemically synthesized from extracts. However, the lack of information on the extraction procedures, compound purity levels, sources and detailed chemical characteristics may have introduced confounding factors that could not be adequately addressed in our analysis. Additional sources of variability include differences in compound dosing regimens, the use of various solvents for dilution (e.g., DMSO, EtOH, MeOH, SFE), inconsistencies in cell handling protocols, the timing of result acquisition and the subjective interpretation of outcomes. These factors are often underreported or inconsistently documented in the literature, adding further complexity to the meta-analysis. Moreover, the lack of standardized reporting regarding the origin, ATCC codes or classification of the cell lines used raises the risk of cell line misidentification and contributes to uncertainty in our pooled estimates, increasing between-study heterogeneity. A high degree of heterogeneity was expected and indeed observed in most of our analyses, likely reflecting inconsistencies in study design. Nonetheless, we applied a random-effects model in this meta-analysis, which assumes that variability is inherent to the biological questions being investigated [100]. Finally, despite the authors’ extensive efforts to systematically include all relevant studies—spanning conference proceedings, theses and publications in multiple languages—we cannot fully rule out the possibility of “gray literature bias” [101].

4. Materials and Methods

4.1. Literature Search Strategy

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [102] and the advice for best practices were followed to conduct this systematic review and meta-analysis [103]. The literature search was conducted in PubMed with the following search terms: (hop OR hops OR “Humulus lupulus”) AND (cancer OR *carcinoma OR neoplasm OR tumor OR proliferation) and all possible chemical compounds of hops [17], their synonyms and combinations, by 1 June 2024. The reference lists of selected articles were also scrutinized. Five researchers (GT, EMA, PP, KT and PK) independently evaluated search results, and disagreements in the initial evaluation were resolved after discussion with three separate reviewers (MEG, PB and GB).

4.2. Study Selection Criteria

For a study to be eligible for the present meta-analysis, it had to meet the following criteria: (i) it should evaluate the effects of hop compounds or hop extracts on the viability of cancer or non-cancer cells and no additional anticancer drugs or agents should be used; and (ii) it should provide IC50 values along with their corresponding standard deviation (SD) or standard error of the mean (SEM), or the necessary data that allow the calculation of them [104]. No language restrictions were applied in order to minimize the risk of publication bias associated with gray literature [105].
The assays used for assessing inhibition of cell growth in all studies included in this meta-analysis were sulforhodamine B (SRB), tetrazolium salt-based and crystal violet (CV) assays. MTT assay is classified among methods measuring metabolic activity and is a tetrazolium salt-based method, where a yellow tetrazolium salt (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide or MTT) is reduced to purple formazan crystals by metabolically active cells, thus making it a fast and accurate method to measure the number of living cells [22]. The reaction taking place reflects the number of viable cells (as a cellular redox state) depending on mitochondrial redox enzyme activity [106]. Modifications of the above assay, including XTT (2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide), MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) and WST (water-soluble tetrazolium salt), involve the replacement of MTT solution with other tetrazolium salts [107,108,109]. The sulforhodamine B (SRB) method is based on the ability of the chemical compound SRB to bind, under mild acidic conditions, to the amino acids of cellular proteins. Colorimetric evaluation provides information on the total mass of the proteins, which is directly correlated with the number of cells [21,110]. Crystal violet (CV) method is used for assessing the action of various chemotherapeutics and other agents on the growth and survival of a cell culture. It is based on the ability of living cells to remain attached to the plate. During cell death, the cells detach and can be easily removed from the living population throughout the assay. CV binds to the DNA of the cells, thus revealing a characteristic intense purple color proportional to the leaving cells [23].

4.3. Studies’ Outcomes and Data Extraction

Primarily, the titles and abstracts of the articles were screened, and relevant articles were further evaluated based on the inclusion and exclusion criteria. The search results were reviewed independently by three researchers (GT, EMA and PK). Any discrepancies were resolved through discussion with GS, PB and GB, and decisions were made by consensus. Experiments used many compounds found in hop (hop cones) extracts, which were tested at many different time points (mainly for 24, 48 and 72 h of incubation). Antiproliferative activity was investigated in many different cell lines. Data extracted from each study, and recorded on a spreadsheet, included the following: PubMed ID, first author’s last name, year of publication, type of assay for the determination of cell viability, cell lines, cancer type and hours of incubation and number of replicative experiments. In addition, the different compounds used to detect their antiproliferative activity as well as their corresponding IC50 values along with standard deviation or standard error of means (SD/SEM) were also recorded [111]. For studies reporting only the SD value, the number of replicates were used to calculate the SEM in the following way: SEM = SD/√n. Because studies lacking a reported SD still contribute meaningful information, excluding them could bias the pooled effect. Furukawa et al. [112] showed that SDs for the same outcome rarely differ significantly and suggested imputing a single pooled SD when necessary. To be even more conservative, we imputed any missing dispersion by using the largest SD observed among studies evaluating the same pair (compound–cell line), thereby intentionally down-weighting those studies while still preserving their contribution to the meta-analysis. We also included studies that reported data for both cancer and non-cancer cells.

4.4. Data Analysis

IC50 was used as the effect size of choice to test the antiproliferative effect of each compound. Data were combined using random-effects meta-analysis [113] with inverse variance. IC50 values were calculated along with their 95% confidence intervals (CIs) for each compound, in each type of cancer, at each incubation time and for each cell viability assay. Meta-regression analysis was applied to investigate the probability of statistical heterogeneity in terms of study-level variables between variances such as time of incubation or type of assay [114]. The analysis was performed using Stata 13 [115] by using the commands “metan” and “metareg” for random-effect meta-analysis [116] and meta-regression with method of moments [117], respectively. For testing statistical significance, p < 0.05 was used as the decision rule, and meta-analysis was performed where two or more studies were available.

5. Conclusions

In conclusion, this meta-analysis provides valuable insights into the antiproliferative effects of hop compounds, particularly xanthohumol (XN), which demonstrated strong activity against cancer cell lines while sparing normal cells. Our findings underscore the therapeutic potential of hop-derived phytochemicals, including bitter acids like humulone and lupulone, in cancer treatment. However, further research—including preclinical and clinical studies—is necessary to validate these effects. Despite the inherent limitations and variability in study designs contributing to heterogeneity in some subgroup analyses [118], this analysis offers a comprehensive synthesis of available data and highlights the urgent need for standardized methodologies to evaluate the anticancer potential of plant-derived compounds. Importantly, our results indicate that tetrazolium salt-based assays, SRB and crystal violet (CV) assays yield comparable outcomes and can be used interchangeably in studies involving hop compounds. The methodological framework applied in this study may also be extended to other plant extracts and phytoconstituents, facilitating the identification of distinct bioactivities and advancing our understanding of the health-promoting properties of medicinal plants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ph18081139/s1, Figure S1: Meta-regression analysis of IC50 values; Figure S2: Forest plots of meta-analysis of IC50 values of Xanthohumol; Figure S3: Forest plots of meta-analysis of IC50 values of Chalcones and Flavones; Table S1: Number of studies of present meta-analysis; Table S2: Random-effects model meta-analysis for the different assays and different types of cancer; Table S3: Random effects meta-analysis of IC50 values of ΧΝ; Table S4: Characteristics of studies that were used in meta-analysis of SMDs; Table S5: Random effects meta-analysis of IC50 values of ΧΝ on different types of cancer and non-cancer cells; Table S6: Meta-regression analysis of IC50 values of all chemical compounds on cancer and non-cancer cells for all incubation time points.

Author Contributions

G.T.: data curation, formal analysis, investigation, methodology, software, validation, visualization, writing—review and editing. E.M.A.: data curation, formal analysis, investigation, methodology, project administration, software, validation, visualization, writing—original draft, writing—review and editing. P.I.K.: data curation, formal analysis, investigation, methodology, software, validation, visualization, writing—review and editing. I.A.T.: data curation, investigation, methodology, software, validation, writing—review and editing. K.T.: data curation, investigation, validation, writing—review and editing. P.P.: data curation, funding acquisition, investigation, validation, writing—review and editing. M.E.G.: data curation, funding acquisition, investigation, validation, writing—review and editing. G.S.: data curation, investigation, validation, writing—review and editing. P.G.B.: data curation, formal analysis, investigation, methodology, resources, software, supervision, validation, visualization, writing—review and editing. G.G.B.: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing—original draft, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the project “Molecular identification and utilization of indigenous hop varieties for the production of high added value beers” (MIS 5056124), which is financed by the “Action Support for Research, Technological Development and Innovation Projects in areas of RIS3 in the Region of Central Greece” under the Operational Programme “STEREA ELLADA 2014–2020” co-financed by Greece and the European Union (European Regional Development Fund).

Data Availability Statement

All data used or produced in this research are within the tables, figures or Supplementary Materials of this manuscript.

Conflicts of Interest

Author Panagiotis Pergantas is employed by Bioapplications O.E., 32100 Livadia, Greece, which was part of the consortium of the project described under “Funding”. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MTT3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide
SRBSulfohodamine B
XTT2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide
MTS3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium
WSTWater-Soluble Tetrazolium Salt
CVCrystal Violet
PRISMAPreferred Reporting Items for Systematic Reviews and Meta-Analyses
SMDStandardized Mean Difference
IC50Half Maximal Inhibitory Concentration
XNXanthohumol
IXNIsoxanthohumol
DMXDesmethylxanthohumol
8-PN8-prenylnaringenin
6-PN6-prenylnaringenin

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Figure 1. PRISMA-compliant flow diagram of systematic review to retrieve selected studies for present systematic review and meta-analysis.
Figure 1. PRISMA-compliant flow diagram of systematic review to retrieve selected studies for present systematic review and meta-analysis.
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Figure 2. The main flavonoids and bitter acids from Humulus lupulus, studied herein.
Figure 2. The main flavonoids and bitter acids from Humulus lupulus, studied herein.
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Figure 3. Meta-analysis of IC50 values (and SE) of xanthohumol (ΧΝ) on various cell types, for different incubation times, obtained from tetrazolium salt, SRB and crystal violet (CV) assays.
Figure 3. Meta-analysis of IC50 values (and SE) of xanthohumol (ΧΝ) on various cell types, for different incubation times, obtained from tetrazolium salt, SRB and crystal violet (CV) assays.
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Figure 4. Meta-analysis of IC50 values (and SE) of XN on different cancer types and non-cancer cells for different incubation times, obtained from all assays, collectively.
Figure 4. Meta-analysis of IC50 values (and SE) of XN on different cancer types and non-cancer cells for different incubation times, obtained from all assays, collectively.
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Figure 5. Meta-regression analysis of IC50 values (obtained from tetrazolium salt, SRB and CV assays) of (A) XN added for different incubation times (24, 48, 72 and 96 h) on all cancer cell lines, collectively; (B) XN added for different incubation times (24, 48, 72 and 96 h) on non-cancer cells; (C) all hop chemical compounds, jointly, added for different incubation times (24, 48, 72 and 96 h) on all cancer cell lines, collectively; (D) all hop chemical compounds, jointly, added for different incubation times (24, 48, 72 and 96 h) on non-cancer cells. Each circle represents an individual study, with its size proportional to the inverse of the variance of the corresponding IC50 estimate. The red line represents the fitted meta-regression line, indicating the estimated relationship between incubation time and IC50 values.
Figure 5. Meta-regression analysis of IC50 values (obtained from tetrazolium salt, SRB and CV assays) of (A) XN added for different incubation times (24, 48, 72 and 96 h) on all cancer cell lines, collectively; (B) XN added for different incubation times (24, 48, 72 and 96 h) on non-cancer cells; (C) all hop chemical compounds, jointly, added for different incubation times (24, 48, 72 and 96 h) on all cancer cell lines, collectively; (D) all hop chemical compounds, jointly, added for different incubation times (24, 48, 72 and 96 h) on non-cancer cells. Each circle represents an individual study, with its size proportional to the inverse of the variance of the corresponding IC50 estimate. The red line represents the fitted meta-regression line, indicating the estimated relationship between incubation time and IC50 values.
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Figure 6. Meta-analysis of IC50 values (and SE) of various classes of hop compounds on cancer and non-cancer cells, obtained from tetrazolium salt, SRB and CV assays, for different incubation times. Results are shown for chalcones (blue), flavones (red) and bitter acids (yellow).
Figure 6. Meta-analysis of IC50 values (and SE) of various classes of hop compounds on cancer and non-cancer cells, obtained from tetrazolium salt, SRB and CV assays, for different incubation times. Results are shown for chalcones (blue), flavones (red) and bitter acids (yellow).
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Table 1. Characteristics of the 61 studies included in the meta-analysis.
Table 1. Characteristics of the 61 studies included in the meta-analysis.
Author ReferenceAssayIC50 (nM or mg/mL for Extracts)SDHoursNumber of ReplicatesCell LineCell TypeCancer/NormalCompound or Type of Extract
Hsieh et al. [16]MTT56.007.30243NPC-039Human neck cancerNeckXanthohumol
Hsieh et al. [16]MTT56.007.30243NPC-039Human neck cancerNeckXanthohumol
Hsieh et al. [16]MTT45.607.30243NPC-BMHuman neck cancerNeckXanthohumol
Hsieh et al. [16]MTT34.906.00243 Human normal nasopharyngealNon-cancerXanthohumol
Hsieh et al. [16]MTT22.807.30483NPC-039Human neck cancerNeckXanthohumol
Hsieh et al. [16]MTT18.107.30483NPC-BMHuman neck cancerNeckXanthohumol
Hsieh et al. [16]MTT20.006.00483 Human normal nasopharyngealNon-cancerXanthohumol
Hsieh et al. [16]MTT19.507.30723NPC-039Human neck cancerNeckXanthohumol
Hsieh et al. [16]MTT17.807.30723NPC-BMHuman neck cancerNeckXanthohumol
Hsieh et al. [16]MTT20.006.00723 Human normal nasopharyngealNon-cancerXanthohumol
Klimek et al. [12]MTT74.942.62243BJHuman normal skin fibroblastNon-cancerXanthohumol
Klimek et al. [12]MTT34.362.89723MCF-7Human breast cancerBreastXanthohumol
Klimek et al. [12]MTT20.852.99723A549Human lung cancerLungXanthohumol
Klimek et al. [12]MTT102.593.48723HepG2Human liver cancerLiverXanthohumol
Klimek et al. [12]MTT48.671.35723BJHuman normal skin fibroblastNon-cancerXanthohumol
Klimek et al. [12]MTT155.704.23243BJHuman normal skin fibroblastNon-cancerHops dynamic supercritical fluid extract (SFE)
Klimek et al. [12]MTT45.173.58723A549Human lung cancerLungHops dynamic supercritical fluid extract (SFE)
Klimek et al. [12]MTT66.482.97723MCF-7Human breast cancerBreastHops dynamic supercritical fluid extract (SFE)
Klimek et al. [12]MTT26.271.56723HepG2Human liver cancerLiverHops dynamic supercritical fluid extract (SFE)
Klimek et al. [12]MTT104.304.16723BJHuman normal skin fibroblastNon-cancerHops dynamic supercritical fluid extract (SFE)
Hitzman et al. [4]MTT76.006.91243MCF-7Human breast cancerBreastXanthohumol
Hitzman et al. [4]MTT32.800.40243MCF-7Human breast cancerBreastSpent hops ethanolic extract, LC-MS characterized (33.20% XH, 1.22% 6-PN, 1.11% isoxanthohumol and 0.28% 8-PN)
Hitzman et al. [4]MTT105.006.91243MCF-7Human breast cancerBreast6-prenylnaringenin
Hitzman et al. [4]MTT115.008.20243MCF-7Human breast cancerBreast8-prenylnaringenin
Yin et al. [27]MTT7.907.30243KYSE30Human esophageal cancerEsophagusXanthohumol
Yin et al. [27]MTT3.107.30483KYSE30Human esophageal cancerEsophagusXanthohumol
Yin et al. [27]MTT2.607.30723KYSE30Human esophageal cancerEsophagusXanthohumol
Ho et al. [28]MTT60.007.30243U87-MGHuman glioblastomaGlioblastomaXanthohumol
Ho et al. [28]MTT68.107.30243A172Human glioblastomaGlioblastomaXanthohumol
Scagliarini et al. [29]Crystal Violet39.006.48243HT-29Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet12.002.8483HT-29Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet22.006.49483SW480Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet12.003.57483SW620Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet10.001.75723HT-29Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet20.003.3723SW480Human colon cancerColonXanthohumol
Scagliarini et al. [29]Crystal Violet7.001.38723SW620Human colon cancerColonXanthohumol
Stompor et al. [30]SRB8.81.16724MCF-7Human breast cancerBreastXanthohumol
Stompor et al. [30]SRB18.94.6724MDA-MB-231Human breast cancerBreastXanthohumol
Stompor et al. [30]SRB8.71.37244T1Murine breast cancerBreastXanthohumol
Stompor et al. [30]SRB21.52.7724HepG2Human liver cancerLiverXanthohumol
Stompor et al. [30]SRB12.68.8724BALB/3T3Murine normal fibroblastsNon-cancerXanthohumol
Stompor et al. [30]SRB21.14.3724MCF-10AHuman normal breastNon-cancerXanthohumol
Lu et al. [15]MTT39.821.50243K562Human leukemiaLeukemiaXanthohumol
Lu et al. [15]MTT19.560.77483K562Human leukemiaLeukemiaXanthohumol
Lu et al. [15]MTT4.431.20723K562Human leukemiaLeukemiaXanthohumol
Lu et al. [15]MTT10.001.50723K562/ADRHuman leukemia, adriamycin-resistantLeukemiaXanthohumol
Sławińska-Brych et al. [31]MTT50.127.30483U266Human myelomaMyelomaXanthohumol
Sławińska-Brych et al. [31]MTT21.857.30483RPMI8226Human myelomaMyelomaXanthohumol
Sławińska-Brych et al. [31]MTT38.407.30963U266Human myelomaMyelomaXanthohumol
Sławińska-Brych et al. [31]MTT8.247.30963RPMI8226Human myelomaMyelomaXanthohumol
Koosha et al. [32]MTT166.688.20243HCT116Human colon cancerColon8-prenylnaringenin
Koosha et al. [32]MTT70.002.90483HCT116Human colon cancerColon8-prenylnaringenin
Koosha et al. [32]MTT58.494.10723HCT116Human colon cancerColon8-prenylnaringenin
Krajnović et al. [33]Crystal violet42.005.19483B16-F10Murine melanomaMelanomaIsoxanthohumol
Krajnović et al. [33]MTT30.004.05483B16-F10Murine melanomaMelanomaIsoxanthohumol
Bocquet et al. [17]MTT7.100.80483HepG2Human liver cancerLiverXanthohumol
Bocquet et al. [17]MTT29.402.60483MG-63Human osteosarcomaBoneXanthohumol
Bocquet et al. [17]MTT19.500.50483WI-38Human normal lung fibroblastNon-cancerXanthohumol
Bocquet et al. [17]MTT9.600.50483J774Mouse monocyte macrophageNon-cancerXanthohumol
Bocquet et al. [17]MTT31.408.10723MG-63Human osteosarcomaBoneHydro-alcoholic extract: ethanol/water (9:1; v/v) 3 successive macerations of 4 h and 1 o/n, stirring in the dark
Bocquet et al. [17]MTT6.802.50723HepG2Human liver cancerLiverHydro-alcoholic extract: ethanol/water (9:1; v/v) 3 successive macerations of 4 h and 1 o/n, stirring in the dark
Bocquet et al. [17]MTT7.600.10723WI-38Human normal lung fibroblastNon-cancerHydro-alcoholic extract: ethanol/water (9:1; v/v) 3 successive macerations of 4 h and 1 o/n, stirring in the dark
Bocquet et al. [17]MTT19.702.80723J774Mouse monocyte macrophageNon-cancerHydro-alcoholic extract: ethanol/water (9:1; v/v) 3 successive macerations of 4 h and 1 o/n, stirring in the dark
Bocquet et al. [17]MTT2.600.10483WI-38Human normal lung fibroblastNon-cancerLupulone
Bocquet et al. [17]MTT3.600.10483J774Mouse monocyte macrophageNon-cancerLupulone
Bocquet et al. [17]MTT2.900.50483HepG2Human liver cancerLiverLupulone
Bocquet et al. [17]MTT10.400.40483MG-63Human osteosarcomaBoneLupulone
Bocquet et al. [17]MTT29.002.30483WI-38Human normal lung fibroblastNon-cancerHumulone
Bocquet et al. [17]MTT31.700.30483J774Mouse monocyte macrophageNon-cancerHumulone
Bocquet et al. [17]MTT178.502.50483WI-38Human normal lung fibroblastNon-cancerDesmethylxanthohumol
Bocquet et al. [17]MTT28.501.00483J774Mouse monocyte macrophageNon-cancerDesmethylxanthohumol
Bocquet et al. [17]MTT65.902.90483HepG2Human liver cancerLiverDesmethylxanthohumol
Bocquet et al. [17]MTT116.203.30483MG-63Human osteosarcomaBoneDesmethylxanthohumol
Roehrer et al. [34]MTS12.256.91483MCF-7Human breast cancerBreastXanthohumol
Roehrer et al. [34]MTS8.807.30963MCF-7Human breast cancerBreastXanthohumol
Logan et al. [11]SRB40.81.4245HCT116Human colon cancerColonXanthohumol
Logan et al. [11]SRB50.21.4245HT-29Human colon cancerColonXanthohumol
Logan et al. [11]SRB25.41.1245HepG2Human liver cancerLiverXanthohumol
Logan et al. [11]SRB37.21.5245Huh7Human liver cancerLiverXanthohumol
Bartmańska et al. [35]SRB10.840.32725MCF-7Human breast cancerBreastXanthohumol
Bartmańska et al. [35]SRB8.463.19725MDA-MB-231Human breast cancerBreastXanthohumol
Bartmańska et al. [35]SRB7.992.77725T-47DHuman breast cancerBreastXanthohumol
Bartmańska et al. [35]SRB9.420.25725HT-29Human colon cancerColonXanthohumol
Bartmańska et al. [35]SRB2.061.03725A2780Human ovarian cancerOvarianXanthohumol
Bartmańska et al. [35]SRB8.210.83725A2780Human ovarian cancerOvarianXanthohumol
Bartmańska et al. [35]SRB6.492.14725DU145Human prostate cancerProstateXanthohumol
Bartmańska et al. [35]SRB8.611.11725PC-3Human prostate cancerProstateXanthohumol
Bartmańska et al. [35]SRB9.574.23725HLMECHuman lung microvascular endothelialNon-cancerXanthohumol
Bartmańska et al. [35]SRB55.9527.31725MCF-10AHuman normal breastNon-cancerXanthohumol
Bartmańska et al. [35]SRB43.254.37725MCF-7Human breast cancerBreast6-prenylnaringenin
Bartmańska et al. [35]SRB62.6419.54725MDA-MB-231Human breast cancerBreast6-prenylnaringenin
Bartmańska et al. [35]SRB16.013.74725T-47DHuman breast cancerBreast6-prenylnaringenin
Bartmańska et al. [35]SRB64.6117.07725HT-29Human colon cancerColon6-prenylnaringenin
Bartmańska et al. [35]SRB44.1614.71725A2780Human ovarian cancerOvarian6-prenylnaringenin
Bartmańska et al. [35]SRB81.7317.68725A2780Human ovarian cancerOvarian6-prenylnaringenin
Bartmańska et al. [35]SRB79.568.89725DU145Human prostate cancerProstate6-prenylnaringenin
Bartmańska et al. [35]SRB75.5329.79725PC-3Human prostate cancerProstate6-prenylnaringenin
Bartmańska et al. [35]SRB13.695.16725HLMECHuman lung microvascular endothelialNon-cancer6-prenylnaringenin
Bartmańska et al. [35]SRB110.0632.95725MCF-10AHuman normal breastNon-cancer6-prenylnaringenin
Bartmańska et al. [35]SRB49.537.36725MCF-7Human breast cancerBreast8-prenylnaringenin
Bartmańska et al. [35]SRB63.817.27725MDA-MB-231Human breast cancerBreast8-prenylnaringenin
Bartmańska et al. [35]SRB26.719.7725T-47DHuman breast cancerBreast8-prenylnaringenin
Bartmańska et al. [35]SRB89.843.42725HT-29Human colon cancerColon8-prenylnaringenin
Bartmańska et al. [35]SRB25.918.32725A2780Human ovarian cancerOvarian8-prenylnaringenin
Bartmańska et al. [35]SRB66.3710.14725A2780Human ovarian cancerOvarian8-prenylnaringenin
Bartmańska et al. [35]SRB60.586.66725DU145Human prostate cancerProstate8-prenylnaringenin
Bartmańska et al. [35]SRB51.3611.31725PC-3Human prostate cancerProstate8-prenylnaringenin
Bartmańska et al. [35]SRB23.9110.86725HLMECHuman lung microvascular endothelialNon-cancer8-prenylnaringenin
Bartmańska et al. [35]SRB90.7219.8725MCF-10AHuman normal breastNon-cancer8-prenylnaringenin
Bartmańska et al. [35]SRB16.730.88725MCF-7Human breast cancerBreastIsoxanthohumol
Bartmańska et al. [35]SRB43.3410.32725MDA-MB-231Human breast cancerBreastIsoxanthohumol
Bartmańska et al. [35]SRB26.756.44725T-47DHuman breast cancerBreastIsoxanthohumol
Bartmańska et al. [35]SRB30.591725HT-29Human colon cancerColonIsoxanthohumol
Bartmańska et al. [35]SRB7.931.65725A2780Human ovarian cancerOvarianIsoxanthohumol
Bartmańska et al. [35]SRB11.651.44725A2780Human ovarian cancerOvarianIsoxanthohumol
Bartmańska et al. [35]SRB59.175.73725DU145Human prostate cancerProstateIsoxanthohumol
Bartmańska et al. [35]SRB53.2410.59725PC-3Human prostate cancerProstateIsoxanthohumol
Bartmańska et al. [35]SRB12.55.65725HLMECHuman lung microvascular endothelialNon-cancerIsoxanthohumol
Bartmańska et al. [35]SRB72.1221.66725MCF-10AHuman normal breastNon-cancerIsoxanthohumol
Bartmańska et al. [35]SRB130.796.11725MCF-7Human breast cancerBreastNaringenin
Bartmańska et al. [35]SRB166.0982.44725MDA-MB-231Human breast cancerBreastNaringenin
Bartmańska et al. [35]SRB104.5348.31725T-47DHuman breast cancerBreastNaringenin
Bartmańska et al. [35]SRB130.828.19725HT-29Human colon cancerColonNaringenin
Bartmańska et al. [35]SRB100.054.77725A2780Human ovarian cancerOvarianNaringenin
Bartmańska et al. [35]SRB109.2316.98725A2780Human ovarian cancerOvarianNaringenin
Bartmańska et al. [35]SRB133.6612.92725DU145Human prostate cancerProstateNaringenin
Bartmańska et al. [35]SRB171.2328.78725PC-3Human prostate cancerProstateNaringenin
Bartmańska et al. [35]SRB117.2432.27725HLMECHuman lung microvascular endothelialNon-cancerNaringenin
Bartmańska et al. [35]SRB187.172.41725MCF-10AHuman normal breastNon-cancerNaringenin
Bartmańska et al. [35]SRB10.072.31725MCF-7Human breast cancerBreastα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB10.023.26725MDA-MB-231Human breast cancerBreastα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB7.273.05725T-47DHuman breast cancerBreastα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB12.232.99725HT-29Human colon cancerColonα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB1.80.64725A2780Human ovarian cancerOvarianα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB11.593.36725A2780Human ovarian cancerOvarianα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB12.964.2725DU145Human prostate cancerProstateα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB16.275.22725PC-3Human prostate cancerProstateα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB14.174.24725HLMECHuman lung microvascular endothelialNon-cancerα,β-dihydroxanthohumol
Bartmańska et al. [35]SRB72.058.55725MCF-10AHuman normal breastNon-cancerα,β-dihydroxanthohumol
Wei et al. [36]MTS16.047.30243AGSHuman gastric cancerGastricXanthohumol
Wei et al. [36]MTS111.167.30243SGC-7901Human gastric cancerGastricXanthohumol
Wei et al. [36]MTS35.817.30243MGC-803Human gastric cancerGastricXanthohumol
Wei et al. [36]EdU8.007.30243AGSHuman gastric cancerGastricXanthohumol
Wei et al. [36]MTS285.266.00243GES-1Human normal gastricNon-cancerXanthohumol
Carvalho et al. [37]SRB85.58.92243TPC-1Human thyroid cancerThyroidXanthohumol
Carvalho et al. [37]SRB598.92483TPC-1Human thyroid cancerThyroidXanthohumol
Carvalho et al. [37]SRB48.58.92723TPC-1Human thyroid cancerThyroidXanthohumol
Ho et al. [38]MTT53.707.30243M059KHuman glioblastomaGlioblastomaXanthohumol
Ho et al. [38]MTT55.607.30243U87-MGHuman glioblastomaGlioblastomaXanthohumol
Popłoński et al. [39]SRB8.10.8724MCF-7Human breast cancerBreastXanthohumol
Popłoński et al. [39]SRB10.11.1724HT-29Human colon cancerColonXanthohumol
Popłoński et al. [39]SRB71.5724PC-3Human prostate cancerProstateXanthohumol
Sun et al. [40]MTT39.406.91246MCF-7Human breast cancerBreastXanthohumol
Sun et al. [40]MTT33.307.30246MDA-MB-231Human breast cancerBreastXanthohumol
Sun et al. [40]MTT19.606.91486MCF-7Human breast cancerBreastXanthohumol
Sun et al. [40]MTT21.507.30486MDA-MB-231Human breast cancerBreastXanthohumol
Sun et al. [40]MTT61.106.00486h-TERT-BJHuman normal skin fibroblastNon-cancerXanthohumol
Sun et al. [40]MTT135.306.00486MCF-10AHuman normal breastNon-cancerXanthohumol
Saito et al. [41]WST-117.007.30726BxPC-3Human pancreatic cancerPancreasXanthohumol
Saito et al. [41]WST-115.907.30726MIA PaCa-2Human pancreatic cancerPancreasXanthohumol
Saito et al. [41]WST-112.907.30726AsPC-1Human pancreatic cancerPancreasXanthohumol
Stompor et al. [42]SRB303.8723MCF-7Human breast cancerBreastIsoxanthohumol
Stompor et al. [42]SRB29.74.2723A549Human lung cancerLungIsoxanthohumol
Stompor et al. [42]SRB8.961.5723LoVoHuman colon cancerColonIsoxanthohumol
Stompor et al. [42]SRB26.84723LoVoHuman colon cancerColonIsoxanthohumol
Stompor et al. [42]SRB163.6723MES-SAHuman uterine cancerUterusIsoxanthohumol
Stompor et al. [42]SRB30.44.1723MES-SAHuman uterine cancerUterusIsoxanthohumol
Stompor et al. [42]SRB37.13.8723MCF-10AHuman normal breastNon-cancerIsoxanthohumol
Stompor et al. [42]XTT15.604.05723U-118 MGHuman glioblastomaGlioblastomaIsoxanthohumol
Liu et al. [43]MTT81.456.91243MCF-7Human breast cancerBreastXanthohumol
Liu et al. [43]MTT78.337.30243MCF-7/ADRHuman breast cancer, doxorubicin-resistantBreastXanthohumol
Liu et al. [43]MTT34.023.45483MCF-7Human breast cancerBreastXanthohumol
Liu et al. [43]MTT33.713.12483MCF-7/ADRHuman breast cancer, doxorubicin-resistantBreastXanthohumol
Liu et al. [43]MTT11.220.95723MCF-7Human breast cancerBreastXanthohumol
Liu et al. [43]MTT11.371.15723MCF-7/ADRHuman breast cancer, doxorubicin-resistantBreastXanthohumol
Gallo et al. [44]MTT18.306.00963HUVECHuman umbilical vein endothelialNon-cancerXanthohumol
Chen et al. [45]MTT64.807.30243U87-MGHuman glioblastomaGlioblastomaXanthohumol
Chen et al. [45]MTT19.707.30483U87-MGHuman glioblastomaGlioblastomaXanthohumol
Chen et al. [45]MTT13.107.30723U87-MGHuman glioblastomaGlioblastomaXanthohumol
Lempereur et al. [46]Crystal Violet4.1011.60726MCF-7Human breast cancerBreastTetrahydro Iso-Alpha Acids
Lempereur et al. [46]Crystal Violet20.6011.60726MDA-MB-231Human breast cancerBreastTetrahydro Iso-Alpha Acids
Lempereur et al. [46]Crystal Violet15.3011.60726MCF-7Human breast cancerBreastα-acids
Lempereur et al. [46]Crystal Violet15.7011.60726MDA-MB-231Human breast cancerBreastα-acids
Lempereur et al. [46]Crystal Violet13.1011.60726MCF-7Human breast cancerBreastIso-α-acids
Lempereur et al. [46]Crystal Violet13.7011.60726MDA-MB-231Human breast cancerBreastIso-α-acids
Lempereur et al. [46]Crystal Violet29.9011.60726MDA-MB-231Human breast cancerBreastDihydro-iso-alpha acids
Yoo et al. [47]MTT16.807.30484MDA-MB-231Human breast cancerBreastXanthohumol
Krajnović et al. [48]Crystal Violet15.771.74483A375Human melanomaMelanomaXanthohumol
Krajnović et al. [48]Crystal Violet9.972.32483B16Murine melanomaMelanomaXanthohumol
Krajnović et al. [48]Crystal Violet48.3011.6483A375Human melanomaMelanoma8-prenylnaringenin
Krajnović et al. [48]Crystal Violet38.558.84483B16Murine melanomaMelanoma8-prenylnaringenin
Krajnović et al. [48]Crystal Violet24.181.43483A375Human melanomaMelanomaIsoxanthohumol
Krajnović et al. [48]Crystal Violet21.885.19483B16Murine melanomaMelanomaIsoxanthohumol
Krajnović et al. [48]MTT15.001.15483A375Human melanomaMelanomaXanthohumol
Krajnović et al. [48]MTT8.700.99483B16Murine melanomaMelanomaXanthohumol
Krajnović et al. [48]MTT27.803.82483A375Human melanomaMelanoma8-prenylnaringenin
Krajnović et al. [48]MTT40.850.78483B16Murine melanomaMelanoma8-prenylnaringenin
Krajnović et al. [48]MTT22.900.78483A375Human melanomaMelanomaIsoxanthohumol
Krajnović et al. [48]MTT22.154.05483B16Murine melanomaMelanomaIsoxanthohumol
Yong et al. [49]SRB74.063.43243A549Human lung cancerLungXanthohumol
Yong et al. [49]SRB25.480.52483A549Human lung cancerLungXanthohumol
Yong et al. [49]SRB149.28.59483MRC-5Human normal lung fibroblastNon-cancerXanthohumol
Yong et al. [49]SRB13.51.42723A549Human lung cancerLungXanthohumol
Yong et al. [49]SRB94.383.07723MRC-5Human normal lung fibroblastNon-cancerXanthohumol
Zhang et al. [50]CCK-87.907.30483HeLaHuman cervical cancerCervixXanthohumol
Zhang et al. [50]CCK-88.602.99483A549Human lung cancerLungXanthohumol
Zhang et al. [50]CCK-832.006.00483MCF-10AHuman normal breastNon-cancerXanthohumol
Zhang et al. [50]CCK-853.604.05483A549Human lung cancerLungIsoxanthohumol
Zhang et al. [50]CCK-846.304.05483HeLaHuman cervical cancerCervixIsoxanthohumol
Sławińska-Brych et al. [51]MTT12.307.30483RK33Human neck cancerNeckXanthohumol
Sławińska-Brych et al. [51]MTT22.507.30483RK45Human neck cancerNeckXanthohumol
Sławińska-Brych et al. [51]MTT100.006.00483HSFHuman normal skin fibroblastNon-cancerXanthohumol
Sławińska-Brych et al. [51]MTT105.006.00483OLN93Rat oligodendrogliaNon-cancerXanthohumol
Jiang et al. [52]MTS10.007.30243PANC-1Human pancreatic cancerPancreasXanthohumol
Jiang et al. [52]MTS27.707.30243BxPC-3Human pancreatic cancerPancreasXanthohumol
Jiang et al. [52]MTS8.107.30483PANC-1Human pancreatic cancerPancreasXanthohumol
Jiang et al. [52]MTS9.107.30483BxPC-3Human pancreatic cancerPancreasXanthohumol
Jiang et al. [52]MTS5.607.30723BxPC-3Human pancreatic cancerPancreasXanthohumol
Jiang et al. [52]MTS4.407.30723PANC-1Human pancreatic cancerPancreasXanthohumol
Zenger et al. [53]MTT65.004.00243HSCHuman hepatic stellateNon-cancerXanthohumol
Yong and Abd Malek [54]SRB59.962.76242Ca SkiHuman cervical cancerCervixXanthohumol
Yong and Abd Malek [54]SRB34.011.6482Ca SkiHuman cervical cancerCervixXanthohumol
Yong and Abd Malek [54]SRB20.081.58722Ca SkiHuman cervical cancerCervixXanthohumol
Mouratidis et al. [55]MTT10.500.50483PC-3Human prostate cancerProstateLupulone
Mouratidis et al. [55]MTT9.000.50483DU145Human prostate cancerProstateLupulone
Mouratidis et al. [55]MTT5.000.50723PC-3Human prostate cancerProstateLupulone
Mouratidis et al. [55]MTT5.000.50723DU145Human prostate cancerProstateLupulone
Boncler et al. [56]MTT9.600.40244HUVECHuman umbilical vein endothelialNon-cancerSpent hops, after SFE extraction of hops, were dried and then extracted with acetone:water (70:30; v/v)
Tronina et al. [57]SRB10.951.03724MCF-7Human breast cancerBreastXanthohumol
Tronina et al. [57]SRB91.318.92724HT-29Human colon cancerColonXanthohumol
Tronina et al. [57]SRB10.671.06724PC-3Human prostate cancerProstateXanthohumol
Tronina et al. [58]SRB10.951.03724MCF-7Human breast cancerBreastXanthohumol
Tronina et al. [58]SRB91.318.92724HT-29Human colon cancerColonXanthohumol
Tronina et al. [58]SRB10.671.06724PC-3Human prostate cancerProstateXanthohumol
Tronina et al. [58]SRB26.5412.68724MCF-7Human breast cancerBreastIsoxanthohumol
Tronina et al. [58]SRB88.824.15724HT-29Human colon cancerColonIsoxanthohumol
Tronina et al. [58]SRB71.3219.59724PC-3Human prostate cancerProstateIsoxanthohumol
Tronina et al. [58]SRB9.150.62724MCF-7Human breast cancerBreastα,β-dihydroxanthohumol
Tronina et al. [58]SRB74.4123.44724HT-29Human colon cancerColonα,β-dihydroxanthohumol
Tronina et al. [58]SRB14.733.88724PC-3Human prostate cancerProstateα,β-dihydroxanthohumol
Allsopp et al. [59]MTT70.008.20243CaCo-2Human colon cancerColon8-prenylnaringenin
Allsopp et al. [59]MTT55.004.05243CaCo-2Human colon cancerColonIsoxanthohumol
Kang et al. [60]MTT16.606.91243MCF-7Human breast cancerBreastXanthohumol
Kang et al. [60]MTT18.007.30243MCF-7/ADRHuman breast cancer, doxorubicin-resistantBreastXanthohumol
Kang et al. [60]MTT35.207.30243HT-29Human colon cancerColonXanthohumol
Viegas et al. [13]MTT117.103.48243HepG2Human liver cancerLiverXanthohumol
Hemachandra et al. [61]MTT11.000.50243MCF-10AHuman normal breastNon-cancerEthanolic extract: Spent hops, after SFE extraction of hops, were dried and then extracted with ethanol
Deeb et al. [62]MTS26.507.30723LNCaPHuman prostate cancerProstateXanthohumol
Deeb et al. [62]MTS29.007.30723DU145Human prostate cancerProstateXanthohumol
Deeb et al. [62]MTS31.007.30723C4-2Human prostate cancerProstateXanthohumol
Deeb et al. [62]MTS25.107.30723PC-3Human prostate cancerProstateXanthohumol
Negrão et al. [63]MTT24.006.00243HUVECHuman umbilical vein endothelialNon-cancerXanthohumol
Negrão et al. [63]MTT12.006.00243HASMCHuman aortic smooth muscleNon-cancerXanthohumol
Negrão et al. [63]MTT28.004.05243HUVECHuman umbilical vein endothelialNon-cancerIsoxanthohumol
Wesołowska et al. [64]SRB333.42723LoVoHuman colon cancerColon8-prenylnaringenin
Wesołowska et al. [64]SRB553.42723LoVoHuman colon cancerColon8-prenylnaringenin
Strathmann et al. [65]SRB6.70.2723BPH-1Human benign prostatic hyperplasiaNon-cancerXanthohumol
Dorn et al. [66]XTT20.005.00723HepG2Human liver cancerLiverXanthohumol
Dorn et al. [66]XTT15.005.00723Huh7Human liver cancerLiverXanthohumol
Mendes et al. [67]SRB2627.312433T3-L1Murine preadipocyteNon-cancerXanthohumol
Mendes et al. [67]SRB1227.314833T3-L1Murine preadipocyteNon-cancerXanthohumol
Mendes et al. [67]SRB1727.317233T3-L1Murine preadipocyteNon-cancerXanthohumol
Ho et al. [68]MTT166.003.00243HA22T/VGHHuman liver cancerLiverXanthohumol
Ho et al. [68]MTT108.005.00243Hep3BHuman liver cancerLiverXanthohumol
Ho et al. [68]MTT211.006.00243AML12Murine normal liverNon-cancerXanthohumol
Monteghirfo et al. [69]MTT10.001.50483K562Human leukemiaLeukemiaXanthohumol
Monteghirfo et al. [69]MTT16.001.50483 Mononuclear cells from CML patientsLeukemiaXanthohumol
Monteghirfo et al. [69]MTT5.401.50723K562Human leukemiaLeukemiaXanthohumol
Koo et al. [70]MTT8.601.15243B16-F10Murine melanomaMelanomaXanthohumol
Lee et al. [71]SRB12.133.43483A549Human lung cancerLungXanthohumol
Lee et al. [71]SRB10.158.92483HCT15Human colon cancerColonXanthohumol
Lee et al. [71]SRB14.398.92483SK-MEL-2Human melanomaMelanomaXanthohumol
Lee et al. [71]SRB161.03483SK-OV-3Human ovarian cancerOvarianXanthohumol
Lee et al. [71]SRB100.173.42483HCT15Human colon cancerColon8-prenylnaringenin
Lee et al. [71]SRB66.3911.31483A549Human lung cancerLung8-prenylnaringenin
Lee et al. [71]SRB102.2311.31483SK-MEL-2Human melanomaMelanoma8-prenylnaringenin
Lee et al. [71]SRB75.210.14483SK-OV-3Human ovarian cancerOvarian8-prenylnaringenin
Lee et al. [71]SRB63.484483HCT15Human colon cancerColonIsoxanthohumol
Lee et al. [71]SRB77.594.2483A549Human lung cancerLungIsoxanthohumol
Lee et al. [71]SRB40.3419.59483SK-MEL-2Human melanomaMelanomaIsoxanthohumol
Lee et al. [71]SRB27.931.65483SK-OV-3Human ovarian cancerOvarianIsoxanthohumol
Yang et al. [72]MTS75.0014.142483T3-L1Murine preadipocyteNon-cancerXanthohumol
Yang et al. [72]MTS53.009.904883T3-L1Murine preadipocyteNon-cancerXanthohumol
Monteiro et al. [73]SRB7.14.6729Sk-Br-3Human breast cancerBreastXanthohumol
Monteiro et al. [73]SRB22.69.7729Sk-Br-3Human breast cancerBreast8-prenylnaringenin
Monteiro et al. [73]SRB4112.68729Sk-Br-3Human breast cancerBreastIsoxanthohumol
Plazar et al. [74]MTT75.003.48245HepG2Human liver cancerLiverXanthohumol
Delmulle et al. [75]WST-113.201.10483PC-3Human prostate cancerProstateXanthohumol
Delmulle et al. [75]WST-112.301.10483DU145Human prostate cancerProstateXanthohumol
Delmulle et al. [75]WST-118.401.20483PC-3Human prostate cancerProstate6-prenylnaringenin
Delmulle et al. [75]WST-129.101.10483DU145Human prostate cancerProstate6-prenylnaringenin
Delmulle et al. [75]WST-133.501.00483PC-3Human prostate cancerProstate8-prenylnaringenin
Delmulle et al. [75]WST-143.101.20483DU145Human prostate cancerProstate8-prenylnaringenin
Delmulle et al. [75]WST-145.201.10483PC-3Human prostate cancerProstateIsoxanthohumol
Delmulle et al. [75]WST-147.401.10483DU145Human prostate cancerProstateIsoxanthohumol
Delmulle et al. [75]WST-149.901.00483PC-3Human prostate cancerProstateDesmethylxanthohumol
Delmulle et al. [75]WST-153.801.10483DU145Human prostate cancerProstateDesmethylxanthohumol
Colgate et al. [76]MTT24.007.30484PC-3Human prostate cancerProstateXanthohumol
Colgate et al. [76]MTT5.006.00484BPH-1Human benign prostatic hyperplasiaNon-cancerXanthohumol
Dietz et al. [77]Crystal Violet30.707.6483Hepa 1c1c7Murine liver cancerLiverXanthohumol
Dietz et al. [77]Crystal Violet30.702.9483Hepa 1c1c7Murine liver cancerLiverIsoxanthohumol
Pan et al. [78]SRB4.10.9243HCT116Human colon cancerColonXanthohumol
Pan et al. [78]SRB3.60.6483HCT116Human colon cancerColonXanthohumol
Pan et al. [78]SRB2.60.1723HCT116Human colon cancerColonXanthohumol
Gerhauser et al. [3]Crystal Violet7.401.4483Hepa 1c1c7Murine liver cancerLiverXanthohumol
Gerhauser et al. [3]Crystal Violet29.901.9483Hepa 1c1c7Murine liver cancerLiverIsoxanthohumol
Miranda et al. [79]SRB13.31.16484MCF-7Human breast cancerBreastXanthohumol
Miranda et al. [79]SRB468.92484HT-29Human colon cancerColonXanthohumol
Miranda et al. [79]SRB0.521.03484A2780Human ovarian cancerOvarianXanthohumol
Miranda et al. [79]SRB3.471.16964MCF-7Human breast cancerBreastXanthohumol
Miranda et al. [79]SRB51.18.92964HT-29Human colon cancerColonXanthohumol
Miranda et al. [79]SRB5.221.03964A2780Human ovarian cancerOvarianXanthohumol
Miranda et al. [79]SRB15.312.68484MCF-7Human breast cancerBreastIsoxanthohumol
Miranda et al. [79]SRB62.54.15484HT-29Human colon cancerColonIsoxanthohumol
Miranda et al. [79]SRB181.65484A2780Human ovarian cancerOvarianIsoxanthohumol
Miranda et al. [79]SRB4.6912.68964MCF-7Human breast cancerBreastIsoxanthohumol
Miranda et al. [79]SRB25.71.65964A2780Human ovarian cancerOvarianIsoxanthohumol
Miranda et al. [79]SRB57.84.15964HT-29Human colon cancerColonIsoxanthohumol
Table 2. Meta-regression analysis of IC50 values of XN derived from tetrazolium salt, SRB and crystal violet (CV) assays, on cancer and non-cancer cells, for different incubation times (24, 48 and 72 h).
Table 2. Meta-regression analysis of IC50 values of XN derived from tetrazolium salt, SRB and crystal violet (CV) assays, on cancer and non-cancer cells, for different incubation times (24, 48 and 72 h).
Time (h)CancerNon-Cancer
p-ValueNumber of Studiesp-ValueNumber of Studies
240.777370.5179
480.350460.35612
720.702520.9139
Table 3. Standardized mean difference-based meta-analysis of IC50 values of individual chemical compounds obtained with tetrazolium salt-based and crystal violet (CV) assays over 48 h incubation time on specific cancer cell lines.
Table 3. Standardized mean difference-based meta-analysis of IC50 values of individual chemical compounds obtained with tetrazolium salt-based and crystal violet (CV) assays over 48 h incubation time on specific cancer cell lines.
CompoundTime (h)Number of ExperimentsNumber of StudiesSMD95% CIp-ValueType of Cancer
Xanthohumol481220.620.00, 1.790.30Melanoma
Isoxanthohumol481831.000.18, 4.980.16Melanoma
8-prenylnaringenin481220.880.00, 3.550.52Melanoma
Table 4. Random-effects meta-analysis of IC50 values (obtained from all assays, collectively) along with 95% confidence interval, p-value and I-squared (I2) for all groups of compounds on different types of cells (cancer/non-cancer) and for different incubation times.
Table 4. Random-effects meta-analysis of IC50 values (obtained from all assays, collectively) along with 95% confidence interval, p-value and I-squared (I2) for all groups of compounds on different types of cells (cancer/non-cancer) and for different incubation times.
Group of CompoundsTimeNumber of StudiesType of CancerIC50 (μΜ/
μg/mL) *		95% CIp-ValueI2 (%)
Chalcones245Glioblastoma60.4455.13, 65.75 0.00051.6
242Neck50.8040.61, 60.990.00067.2
244Gastric42.750.00, 88.890.06999.2
246Liver88.0852.80, 123.350.00099.7
242Pancreas18.851.50, 36.200.03388.7
245Colon33.8311.56, 56.110.00399.9
247Breast48.9729.38, 68.570.00098.1
2437Cancer52.1642.66, 61.660.00099.8
249Non-cancer90.0335.94, 144.110.00199.9
Chalcones483Leukemia15.229.55, 20.890.00098.0
482Myeloma35.998.28, 63.690.01195.6
485Melanoma12.548.89, 16.200.00094.3
484Neck18.9314.11, 23.740.00026.4
483Lung15.503.18, 27.810.01498.5
484Liver27.697.89, 47.480.00699.7
482Pancreas8.602.76, 14.440.0040.0
486Colon17.028.62, 25.410.00096.7
482Bone72.790.00, 157.860.09399.9
487Breast21.7513.26, 30.240.00097.1
482Cervix21.270.00, 46.850.10397.2
482Ovarian8.260.00, 23.430.28699.7
485Prostate30.6710.98, 50.370.00299.9
4850Cancer22.5418.06, 27.010.00099.7
4814Non-cancer65.5348.75, 82.320.00099.9
Chalcones723Leukemia6.593.26, 9.910.00092.5
722Neck18.6512.81, 24.490.0000.0
722Lung17.029.82, 24.210.00093.2
724Liver39.790.00, 83.020.07199.7
725Pancreas11.867.16, 16.560.00059.8
7210Colon23.2919.58, 27.000.00099.8
7217Breast10.979.79, 12.140.00094.9
724Ovarian5.731.90, 9.570.00398.7
7212Prostate13.5111.37, 15.640.00099.8
7263Cancer15.9314.42, 17.430.00099.8
7211Non-cancer33.8915.15, 52.620.00099.9
Flavones243Colon97.1631.77, 162.550.00499.6
242Breast109.6899.90, 119.450.00061.7
245Cancer102.2662.78, 141.740.00099.3
Flavones4812Melanoma36.8129.99, 43.620.00098.9
483Lung65.8347.94, 83.710.00096.1
482Liver30.1428.34, 31.940.0000.0
484Colon74.0556.91, 91.190.00098.7
483Ovarian37.4125.11, 49.720.00098.6
486Prostate36.1227.47, 44.770.00099.6
4832Cancer43.7638.89, 48.640.00099.4
Flavones729Colon50.5533.01, 68.090.00099.7
722Uterus23.169.04, 37.270.00195.2
7213Breast35.5527.15, 43.960.00097.9
726Ovarian36.1926.65, 45.740.00098.3
727Prostate62.8455.13, 70.540.00080.5
7239Cancer42.9536.91, 48.990.00099.4
727Non-cancer46.9631.08, 62.840.00096.9
α-acids482Non-cancer30.6728.10, 33.240.00075.4
α-acids727Breast16.0610.24, 21.880.00063.7
727Cancer16.0610.24, 21.880.00063.7
β-acids482Prostate9.758.28, 11.220.00092.6
484Cancer8.204.77, 11.630.00099.4
482Non-cancer3.102.12, 4.080.00099.3
β-acids722Prostate5.004.60, 5.400.0000.0
722Cancer5.004.60, 5.400.0000.0
Hops crude extract **243Non-cancer57.9041.20, 74.600.00099.9
Hops crude extract **722Liver16.570.00, 35.650.08999.2
725Cancer35.2315.20, 55.260.00199.5
723Non-cancer43.800.00, 87.780.05199.9
* IC50 is measured in μM for chemical compounds and μg/mL for crude extracts. “Cancer” denotes meta-analysis results for collectively all cancer cell lines. ** Full extraction details are reported in Table 1; no two studies employed identical extraction conditions. Bold letters denote head categories of compounds or types of cell lines.
Table 5. Meta-regression analysis of IC50 values (obtained from all assays, collectively) of various compounds on cancer and non-cancer cells for different incubation times. “Cancer” denotes meta-analysis results for all cancer cell lines collectively.
Table 5. Meta-regression analysis of IC50 values (obtained from all assays, collectively) of various compounds on cancer and non-cancer cells for different incubation times. “Cancer” denotes meta-analysis results for all cancer cell lines collectively.
24 h48 h72 h
Compoundsp-ValueNumber of Studies (Cancer/Non-Cancer)p-ValueNumber of Studies (Cancer/Non-Cancer)p-ValueNumber of Studies (Cancer/Non-Cancer)
Chalcones0.049(37/9)0.000(50/14)0.019(63/11)
Xanthohumol0.049(37/9)0.000(46/12)0.088(52/9)
α,β-dihydroxanthohumol 0.046(11/2)
Desmethylxanthohumol 0.566(4/2)
Flavones 0.712(39/7)
8-prenylnaringenin 0.777(12/2)
6-prenylnaringenin 0.947(8/2)
Isoxanthohumol 0.760(19/3)
β-acids 0.129(4/2)
Lupulone 0.129(4/2)
Bold denote head categories of compounds along with their results.
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Tsionkis, G.; Andronidou, E.M.; Kontou, P.I.; Tamposis, I.A.; Tegopoulos, K.; Pergantas, P.; Grigoriou, M.E.; Skavdis, G.; Bagos, P.G.; Braliou, G.G. Humulus lupulus (Hop)-Derived Chemical Compounds Present Antiproliferative Activity on Various Cancer Cell Types: A Meta-Regression Based Panoramic Meta-Analysis. Pharmaceuticals 2025, 18, 1139. https://doi.org/10.3390/ph18081139

AMA Style

Tsionkis G, Andronidou EM, Kontou PI, Tamposis IA, Tegopoulos K, Pergantas P, Grigoriou ME, Skavdis G, Bagos PG, Braliou GG. Humulus lupulus (Hop)-Derived Chemical Compounds Present Antiproliferative Activity on Various Cancer Cell Types: A Meta-Regression Based Panoramic Meta-Analysis. Pharmaceuticals. 2025; 18(8):1139. https://doi.org/10.3390/ph18081139

Chicago/Turabian Style

Tsionkis, Georgios, Elisavet M. Andronidou, Panagiota I. Kontou, Ioannis A. Tamposis, Konstantinos Tegopoulos, Panagiotis Pergantas, Maria E. Grigoriou, George Skavdis, Pantelis G. Bagos, and Georgia G. Braliou. 2025. "Humulus lupulus (Hop)-Derived Chemical Compounds Present Antiproliferative Activity on Various Cancer Cell Types: A Meta-Regression Based Panoramic Meta-Analysis" Pharmaceuticals 18, no. 8: 1139. https://doi.org/10.3390/ph18081139

APA Style

Tsionkis, G., Andronidou, E. M., Kontou, P. I., Tamposis, I. A., Tegopoulos, K., Pergantas, P., Grigoriou, M. E., Skavdis, G., Bagos, P. G., & Braliou, G. G. (2025). Humulus lupulus (Hop)-Derived Chemical Compounds Present Antiproliferative Activity on Various Cancer Cell Types: A Meta-Regression Based Panoramic Meta-Analysis. Pharmaceuticals, 18(8), 1139. https://doi.org/10.3390/ph18081139

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