Abstract
Purpose
Therapeutic management of colorectal cancer (CRC) does not yet yield promising long‐term results. Therefore, there is a need for further investigation of possible therapeutic options. Various experiments have studied the effects of apigenin on CRC and have shown conflicting results. This systematic review and meta‐analysis investigates the currently existing evidence on the effect of apigenin on CRC.
Methods
Medline, Embase, Scopus, and Web of Science databases were searched for articles related to apigenin and its effect on CRC in the preclinical setting. Cell viability, growth inhibition, apoptosis, and cell cycle arrest for in‐vitro, and body weight, tumor size, and mortality in in‐vivo studies were extracted as outcomes.
Results
Thirty‐nine articles investigating colorectal adenocarcinoma were included in this meta‐analysis. Thirty‐seven of these studies had data for in vitro experiments, with eight studies having data for in vivo experiments. Six articles had both in vitro and in vivo assessments. Our analysis showed apigenin reduces cell viability and induces growth inhibition, apoptosis, and cell cycle arrest in in vitro studies. The few in vivo studies indicate that apigenin decreases tumor size while showing no effects on the body weight of animal colorectal adenocarcinoma models.
Conclusion
Our results demonstrated that apigenin, through reducing cell viability, inducing growth inhibition, apoptosis, and cell cycle arrest, and also by decreasing the tumor size, can be considered as a possible adjuvant agent in the management of colorectal adenocarcinoma. However, further in vivo studies are needed before any efforts to translate the current evidence into clinical studies.
Keywords: Apigenin, cell viability, colorectal cancer, flavonoids, tumor size
1. INTRODUCTION
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers, and with estimates of 1.9 million new cases and 1 million deaths in 2022, it is ranked third among cancers in incidence and second in mortality. 1 The main therapies for CRC are surgery and chemotherapy. However, even with aggressive therapies, patients with CRC still have significant recurrence rates of as high as 50%. 2 Moreover, the adverse effects of currently used medications and the minimal choice of effective drugs limit the treatment of CRC. 3 This demonstrates an ongoing need for other alternatives, either as the main line of treatment or as adjuvants to currently existing therapies, such as lifestyle and dietary modifications. 4
Diets rich in fruits and vegetables have been associated with a lower incidence of cancers such as CRC 5 and recent studies indicate that extracts obtained from edible plants may have anti‐cancer properties. 6 Flavonoids, a group of naturally occurring polyphenolic compounds widely present in plants, have been known to pose anti‐inflammatory, antioxidant, and also anticarcinogenic effects by modulating various cellular processes, such as glycolysis, apoptosis, and DNA repair. 7 , 8 Flavonoids are divided into six major classes—flavonols (e.g., quercetin), flavones (e.g., Apigenin), isoflavonoids (e.g., genistein), flavans, flavanones, and anthocyanins. 9 Flavones have various substitution patterns giving them a wide range of biological activity with effects against a range of cancer cells, including breast, prostate, lung, and hematologic cancers. 7 , 10 , 11 , 12 , 13
Apigenin is one of the well‐known flavonoids that exists in many vegetables and fruits and has been shown to have potential chemotherapeutic effects against neoplastic cells and limited toxic and no mutagenic effects on normal cells. 14 , 15 Studies have shown that apigenin affects cell growth, cell cycle, and apoptosis in different cancer cell lines. 15 , 16 These antineoplastic effects have been linked to the modifications caused on cellular pathways such as nuclear factor kappa B, protein kinase, and WNT/ β‐catenin and also through modulation of survival and death effectors such as STAT3, MCL‐1, and PI3K. 15 , 17
Studies on the effects of apigenin on CRC, including in vitro and in vivo research, have reported conflicting results. This systematic review and meta‐analysis investigates and strengthens the currently existing evidence on the effects of apigenin on CRC in preclinical studies.
2. METHOD
2.1. Study design and search strategy
The present systematic review and meta‐analysis was designed to assess the effectiveness of apigenin on CRC. PICO was defined as: Problem (P): CRC cell line or CRC animal model, Intervention (I): apigenin administration, Comparison (C): control group with no apigenin administration. Outcome (O): cell viability, apoptosis, growth inhibition, cell cycle arrest for in vitro studies and tumor size, body weight, and mortality for animal models.
Keywords were chosen based on MeSh terms (Medline database) and Emtree terms (Embase) with the help of experts in the field and also review of related literature. An extensive search was performed on four online databases (PubMed, Embase, Scopus, and Web of Science) until March 31st, 2024 (Data S1, search strategy). Google and Google Scholar search engines and the references of related articles were used to retrieve any possibly missed articles.
Selection Criteria:
All in vivo and in vitro studies, studying the effect of apigenin administration on CRC were included. Exclusion criteria were lack of a nontreated CRC control group, not reporting the desired outcomes, not reporting the required data, human studies, duplicate studies, and studies reporting combination apigenin therapy or derivates of apigenin.
2.2. Data extraction and risk of bias
Two reviewers independently performed title and abstract screening of retrieved records, and relevant articles were included after a full‐text review. Information provided by the studies was filled into a checklist, and any disputes were resolved by consulting a third reviewer. The extracted data were study characteristics (author name, publication year), cell or animal model used, sample size, type, dose, duration, and interval of apigenin administration, and studied outcome. Data presented in figures and charts were extracted using Plot Digitizer software (version 2.0; https://plotdigitizer.sourceforge.net.).
The risk of bias in in vitro studies was assessed by the guidelines provided by the National Toxicology Program 18 and SYRCLE's risk of bias tool was used for the quality assessment of the in vivo studies. 19 National Toxicology Program guidelines assess the risk of bias in domains of randomization, blinding, experimental conditions, outcome assessment and analysis, exposure characterization, and other potential biases. SYRCLE's tool assesses the risk of bias in domains of randomization, blinding, baseline characteristics, outcome assessment and reporting, incomplete data assessment, and other risks of bias.
2.3. Statistical analysis
All analyses were performed using STATA 17.0 statistical software. Gathered data were mean and standard deviation (SD), and overall results are reported as standardized mean difference (SMD) and 95% confidence interval (CI) using the meta package of the statistical software. Statistical analysis was performed in two sections of in vitro and in vivo experiments. Desired outcomes included cell viability, cell apoptosis, cell growth inhibition, and cell cycle arrest for in in vitro studies and tumor size, body weight, and mortality for in vivo studies.
Since the follow‐up duration varied among studies, the analysis was stratified by duration of follow‐up (24‐h, 48‐h, 72‐h). We also provided subgroup analysis for all outcomes according to the administrated doses.
Heterogeneity was assessed using I 2 statistics and the Chi‐squared test (I 2 greater than 50% demonstrates the presence of heterogeneity). Since considerable heterogeneity was expected among the included studies, a random effect model analysis was performed. Finally, publication bias was investigated by Egger's test and visualized by a funnel plot.
3. RESULTS
3.1. Study Characteristics
The systematic search resulted in 699 nonduplicate reports; from which 105 papers were found to be eligible. After further evaluation, 39 articles were included in this study (Figure 1).
FIGURE 1.
PRISMA flow diagram for study selection.
Thirty‐seven articles were in‐vitro studies 7 , 8 , 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 and eight articles were in‐vivo studies. 15 , 18 , 22 , 35 , 39 , 48 , 49 , 50 Six articles had both in vitro and in vivo assessments. All studies investigated colorectal adenocarcinoma cell lines and animal models. The studies included results for the administration of various amounts of apigenin, ranging from amounts less than 10 to 2777 μM for in vitro and 25 to 300 mg/kg for in vivo studies for follow‐ups of 24–72 h. Characteristics of included studies are reported in more detail in each of the respective proceeding sections and tables.
3.2. Effect of apigenin administration on colorectal adenocarcinoma cell lines
In Vitro Studies
The 37 included in vitro studies reported outcomes of cell viability, growth inhibition, apoptosis, and cell cycle arrest. Effects of apigenin were studied on various cell lines of colorectal adenocarcinoma, with HCT‐116, HT‐29, and SW‐480 being the most common of them. Apigenin was administered with doses as low as 10−4 μM up to 2777 μM and follow‐up times of 24, 48, or 72 h. The most frequently administered dosages were between 5 to 200 μM. Table 1 demonstrates the characteristics of the included in vitro studies.
TABLE 1.
In vitro studies characteristics.
| Author, Year | Studied cell type(s) | Apigenin Administered Dose(s) (μM) | Apigenin Administration Duration(s) (hours) | Outcome(s) | |||
|---|---|---|---|---|---|---|---|
| Cell viability | Apoptosis | Growth inhibition | Cell Cycle | ||||
| Banerjee, 2017 18 | HCT‐15, HT‐29 | 6.25, 12.5, 25, 50, 100, 200 | 48 | ✓ | |||
| Buhagiar, 2008 19 | HCT‐116 | 1, 10, 100 | 48 | ✓ | |||
| Cheng, 2021 20 | HCT‐116 | 1, 10, 20, 40, 80, 120, 160 | 24, 48 | ✓ | ✓ | ||
| Chidambara, 2012 7 | SW‐480 | 12.5, 25, 50, 100, 200 | 24, 48 | ✓ | |||
| Cho, 2015 21 | HT‐29 | 50, 100, 200 | 48 | ✓ | |||
| Chung, 2007 16 | HT‐29 APC, HT‐29 GaL | 20, 30, 40, 60, 80 | 48 | ✓ | |||
| Chunhua, 2013 22 | DLD‐1, LS174T, SW‐480 | 20, 40, 80, 120 | 24, 48 | ✓ | |||
| Cicek, 2023 23 | HT‐29 | 6.25, 12.5, 25 | 24, 48 | ✓ | |||
| Dai, 2016 24 | DLD‐1, SW‐480 | 10, 20, 40, 60 | 24, 48 | ✓ | |||
| Farah, 2003 25 | HCT‐116, HT‐29 | 7.5, 20, 40 | 24 | ✓ | |||
| Fernandez, 2021 8 | HCT‐116, HT‐29, T84 | 10, 20, 30, 40, 50 | 48 | ✓ | |||
| Hong, 2022 26 | HCT‐116, HT‐29 | 5, 10, 20 | 24, 72 | ✓ | ✓ | ||
| Iizumi, 2013 27 | HT‐29 | 20, 40, 60, 80 | 24 | ✓ | |||
| Kim, 2008 28 | SNU‐C4 | 1 | 24 | ✓ | |||
| Klampfer, 2004 29 | HCT‐116 | 5, 10, 20 | 24, 48 | ✓ | |||
| Lee, 2009 30 | SNU‐C4 | 0.0001, 0.001, 0.01, 0.1, 1, 10 | 72 | ✓ | |||
| Lee, 2014 31 | HCT‐116 | 6.25, 12.5, 25, 50 | 24 | ✓ | |||
| Richter, 1999 32 | SW‐480 | 1, 5, 10, 50, 100 | 48 | ✓ | ✓ | ||
| Sain, 2023 33 | COLO‐205 | 10, 20, 40, 60, 80, 120 | 24, 48 | ✓ | |||
| Shan, 2017 34 | DLD‐1, HCT‐116, HT‐29 | 10, 20, 40, 60 | 24 | ✓ | |||
| Shao, 2013 15 | DLD‐1, HCT‐8, HCT‐116, HT‐29, SW‐48 | 10, 15, 20, 30 | 24, 48, 72 | ✓ | |||
| Shi, 2023 35 | HCT‐8, LS‐174 T | 40, 60, 80 | 24 | ✓ | ✓ | ||
| Simsek, 2013 36 | DLD‐1 | 370.3, 925.75, 1851.49, 2777.24 | 24, 48, 72 | ✓ | |||
| Smiljkovic, 2017 37 | HCT‐116 | 20, 40, 60, 80 | 48 | ✓ | |||
| Takagaki, 2005 38 | HT‐29 | 5, 10, 20, 30, 60 | 24 | ✓ | |||
| Tong, 2019 39 | HCT‐116, LOVO | 1.56, 3.13, 6.25, 12.5, 25, 50, 100, 200, 400 | 24 | ✓ | |||
| Turktekin, 2011 40 | HT‐29 | 15, 45, 75, 90, 100 | 24, 48, 72 | ✓ | |||
| Wang, 2000 41 | Caco2, HT‐29, SW‐480 | 10, 20, 30, 40, 50, 60, 70, 80 | 24, 48 | ✓ | |||
| Wang, 2004 42 | Caco2, SW‐480 | 20, 40, 60, 80 | 48 | ✓ | |||
| Wang, 2013 13 | SW‐480 | 5, 10, 20, 40, 60, 80, 100 | 24 | ✓ | |||
| Wang, 2016 43 | HCT‐116 | 60 | 24, 48, 72 | ✓ | |||
| Wang. B, 2017 44 | HCT‐116 | 20, 40, 80, 120, 160 | 24, 48, 72 | ✓ | |||
| Wang. J, 2017 45 | SW‐620 | 10, 20, 40, 80 | 24, 48, 72 | ✓ | ✓ | ||
| Xu, 2016 17 | HCT‐15, SW‐480 | 5, 10, 20, 40, 80 | 48 | ✓ | |||
| Yang, 2021 46 | HCT‐116, HT‐29, HCT‐116‐5‐FUR a | 20 | 48 | ✓ | ✓ | ✓ | |
| Zhang, 2021 47 | HCT‐116, SW‐480 | 5, 25, 50, 100 | 24, 48, 72 | ✓ | ✓ | ||
| Zhong, 2010 48 | HCT‐116 | 1, 10 | 72 | ✓ | |||
5‐Fluorouracil resistant.
3.3. Cell Viability
Results of the effect of apigenin on cell viability show that compared to untreated cells, apigenin reduces cell viability during follow‐up time of 24 h (overall SMD = −5.51, 95% CI: −6.43 to −4.59, p < 0.0001; I 2:97.22%, p < 0.0001), 48 h (SMD = −6.92, 95% CI: −8.14 to −5.70, p < 0.0001; I 2:97.14%, p < 0.0001) and 72 h (SMD = −12.99, 95% CI: −16.39 to −9.60, p < 0.0001; I 2:96.65%, p < 0.0001). Subgroup analysis showed that apigenin significantly reduces cell viability in all administrated doses except in doses between 200 to 1000 μM at 24 h (p = 0.052) and between 40–50 μM (p = 0.057) and 70–80 μM (p = 0.145) at 72 h. More detailed data on the effects of various administration doses on cell viability in each time period is demonstrated in Table 2 and Figures S1–S13.
TABLE 2.
Effect of different doses of apigenin on colorectal adenocarcinoma cell line viability.
| Subgroups | N | SMD (95% CI) | P | I 2% (P for heterogeneity) |
|---|---|---|---|---|
| 24 h | ||||
| ≤10 | 23 | −2.22 (−3.11, −1.32) | <0.0001 | 98.6 (<0.0001) |
| 10.1–20 | 19 | −2.99 (−4.17, −1.81) | <0.0001 | 93.14 (<0.0001) |
| 20.1–30 | 7 | −15.29 (−23.67, −6.90) | <0.0001 | 91.41 (<0.0001) |
| 30.1–40 | 13 | −4.04 (−5.96, 02.14) | <0.0001 | 92.33 (<0.0001) |
| 40.1–50 | 7 | −13.55 (−20.82, −6.28) | <0.0001 | 96.25 (<0.0001) |
| 50.1–60 | 8 | −3.06 (−3.96, −2.17) | <0.0001 | 89.23 (0.001) |
| 70.1–80 | 10 | −4.48 (−5.77, −3.18) | <0.0001 | 93.24 (<0.0001) |
| 90.1–100 | 8 | −14.49 (−21.34, −7.64) | <0.0001 | 97.27 (<0.0001) |
| 120 & 160 | 6 | −4.68 (−6.44, −2.92) | <0.0001 | 0.00 (0.062) |
| 200 | 3 | −28.32 (−38.36, −18.27) | <0.0001 | 92.8 (<0.0001) |
| 200.1–1000 | 4 | −12.42 (−24.96, 0.12) | 0.052 | 0.00 (0.323) |
| 1000.1–2777 | 3 | −13.74 (−18.37, −9.12) | <0.0001 | 40.22 (0.18) |
| Overall | 111 | −5.51 (−6.43, −4.59) | <0.0001 | 97.22 (<0.0001) |
| 48 h | ||||
| ≤10 | 22 | −3.42 (−6.24, −0.61) | 0.0017 | 98.42 (<0.0001) |
| 10.1–20 | 22 | −4.17 (−5.72, −2.61) | <0.0001 | 93.19 (<0.0001) |
| 20.1–30 | 8 | −14.27 (−21.16, −7.38) | <0.0001 | 89.32 (<0.0001) |
| 30.1–40 | 14 | −5.40 (−7.53, −3.27) | <0.0001 | 92.33 (<0.0001) |
| 40.1–50 | 10 | −10.22 (−15.18, −5.26) | <0.0001 | 95.5 (<0.0001) |
| 50.1–60 | 5 | −4.12 (−7.43, −0.81) | 0.015 | 89.23 (0.001) |
| 70.1–80 | 11 | −7.72 (−10.77, 4.68) | <0.0001 | 93.24 (<0.0001) |
| 90.1–100 | 11 | −20.14 (−28.84, −11.44) | <0.0001 | 96.53 (<0.0001) |
| 120 & 160 | 6 | −5.39 (−6.64, −4.13) | <0.0001 | 0.00 (0.062) |
| 200 | 4 | −34.97 (−65.41, −4.52) | 0.024 | 90.26 (<0.0001) |
| 200.1–1000 | 2 | −2.46 (−3.83, −1.10) | <0.0001 | 0.00 (0.323) |
| 1000.1–2777 | 3 | −10.84 (−15.81, −5.87) | <0.0001 | 40.22 (0.18) |
| Overall | 118 | −6.92 (−8.14, −5.70) | <0.0001 | 97.14 (<0.0001) |
| 72 h | ||||
| ≤10 | 7 | −9.57 (−14.88, −4.27) | <0.0001 | 92.01 (<0.0001) |
| 10.1–20 | 6 | −14.09 (−21.57, −6.61) | <0.0001 | 90.62 (<0.0001) |
| 20.1–30 | 2 | −21.22 (−29.84, −12.60) | <0.0001 | 0.00 (0.5) |
| 30.1–40 | 1 | −27.25 (−38.20, −16.30) | <0.0001 | NA |
| 40.1–50 | 3 | −19.50 (−39.58, 0.59) | 0.057 | 88.43 (<0.0001) |
| 70.1–80 | 2 | −18.78 (−44.05, 6.50) | 0.145 | 93.19 (<0.0001) |
| 90.1–100 | 4 | −20.99 (−37.77, −4.21) | 0.014 | 97.18 (0.003) |
| 200.1–1000 | 2 | −2.00 (−3.23, −0.78) | 0.001 | 0.00 (0.442) |
| 1000.1–2777 | 3 | −8.49 (−13.75, −3.24) | 0.002 | 66.28 (0.054) |
| Overall | 30 | −12.99 (−16.39, −9.60) | <0.0001 | 96.65 (<0.0001) |
Note: Doses presented as μM. Dose categories not present in the subgroup column did not have any reported data in the included studies.
Abbreviations: CI, confidence interval; SMD, standardized mean difference.
3.4. Growth Inhibition
Apigenin significantly induces growth inhibition compared to untreated cells in any of the follow‐up times of 24 h (SMD = 9.78, 95% CI: 4.19–15.38, p = 0.001; I 2:98.12%, p < 0.0001), 48 h (SMD = 11.11, 95% CI: 5.10–17.12, p < 0.0001; I 2:97.68%, p < 0.0001) and 72 h (SMD = 9.43, 95% CI: 4.83–14.03, p < 0.0001; I 2: 97.96%, p < 0.0001). Subgroup analysis showed that apigenin significantly induces growth inhibition in all administrated doses except in doses between 20 to 40 μM at 24 h (p = 0.183) and less than 20 μM at 48‐h (p = 0.059). The administered dosages were between 1 and 160 μM. More detailed results of each administered dose in each time period are shown in Table 3 and Figures S14–S17.
TABLE 3.
Effect of different doses of apigenin on colorectal adenocarcinoma cell line growth inhibition.
| Subgroups | N | SMD (95% CI) | p | I 2 (P for heterogeneity) |
|---|---|---|---|---|
| 24 h | ||||
| ≤20 | 6 | 2.08 (0.56, 3.59) | 0.007 | 75.55 (<0.0001) |
| 20.1–40 | 2 | 14.21 (−6.71, 35.13) | 0.183 | 86.99 (0.006) |
| 60.1–80 | 2 | 14.12 (8.33, 19.92) | <0.0001 | 0.00 (0.44) |
| 120 & 160 | 2 | 30.04 (17.96, 42.11) | <0.0001 | 0.00 (0.757) |
| Overall | 12 | 9.78 (4.19, 15.38) | 0.001 | 98.12 (<0.0001) |
| 48 h | ||||
| ≤20 | 7 | 4.92 (−0.19, 10.03) | 0.059 | 97.01 (<0.0001) |
| 20.1–40 | 1 | 16.40 (7.03, 25.76) | 0.001 | NA |
| 60.1–80 | 2 | 17.32 (6.60, 28.04) | 0.002 | 49.27 (0.16) |
| 120 & 160 | 2 | 27.57 (16.40, 38.73) | <0.0001 | 0.00 (0.512) |
| Overall | 12 | 11.11 (5.10, 17.12) | <0.0001 | 97.68 (<0.0001) |
| 72 h | ||||
| ≤20 | 7 | 4.35 (1.29, 7.40) | 0.005 | 95.87 (0.00) |
| 20.1–40 | 1 | 17.71 (7.61, 27.82) | 0.001 | NA |
| 60.1–80 | 2 | 16.21 (2.73, 29.69) | 0.018 | 69.05 (0.072) |
| 120 & 160 | 2 | 21.80 (13.03, 30.57) | <0.0001 | 0.00 (0.908) |
| Overall | 12 | 9.43 (4.83, 14.03) | <0.0001 | 97.96 (<0.0001) |
Note: Doses presented as μM. Dose categories not present in the subgroup column did not have any reported data in the included studies.
Abbreviations: CI, confidence interval; SMD, standardized mean difference.
3.5. Apoptosis
The results show that apigenin significantly increases apoptosis compared to untreated cells when administered for 24 h (SMD = 4.13, 95% CI: 0.86–7.40, p = 0.013; I 2 = 95.69%, p < 0.0001) and 48 h (SMD = 7.51, 95% CI: 2.59–12.44, p = 0.003; I 2: 98.63%, p < 0.0001). No significant effect was observed for results of 72 h (SMD:1.82, 95% CI: −0.63 to 4.27, p = 0.145, I 2:72.06, p = 0.058). It should be mentioned that for the time of 72 h only one study with two separate experiments was included. Therefore, results should be interpreted with caution. Subgroup analysis showed that apigenin had a significant effect on apoptosis only when administered as dosages between 10 and 100 μM for 24 h (SMD = 5.84, 95% CI: 1.93–9.75, p = 0.003; I 2:93.31%, p < 0.0001) and 48 h (SMD = 7.51, 95% CI: 2.59–12.44, p = 0.003; I 2:98.63%, p < 0.0001); whereas no significant effect was observed for doses less than 10 μM (Table 4 and Figures S18,S19).
TABLE 4.
Effects of different doses of apigenin on colorectal adenocarcinoma cell line apoptosis.
| Subgroups | N | SMD (95% CI) | p | I 2% (P for heterogeneity) |
|---|---|---|---|---|
| 24 h | ||||
| ≤10 | 2 | −0.07 (−0.98, 0.84) | 0.872 | 0.00 (0.651) |
| 10.1–100 | 6 | 5.84 (1.93, 9.75) | 0.003 | 93.31 (<0.0001) |
| Overall | 8 | 4.13 (0.86, 7.40) | 0.013 | 95.68 (<0.0001) |
| 48 h | ||||
| ≤10 | 3 | 3.87 (−3.43, 11.18) | 0.299 | 97.97 (<0.0001) |
| 10.1–100 | 10 | 8.92 (2.59, 15.26) | 0.006 | 98.68 (<0.0001) |
| Overall | 13 | 7.51 (2.59, 12.44) | 0.003 | 98.63 (<0.0001) |
| 72 h | ||||
| ≤10 | 2 | 1.82 (−0.63, 4.27) | 0.15 | 72.06 (0.058) |
Note: Doses presented as μM. Dose categories not present in the subgroup column did not have any reported data in the included studies.
Abbreviations: CI, confidence interval; SMD, standardized mean difference.
3.6. Cell Cycle Arrest
Cell cycle arrest was reported as the percentage of cells in different cell cycles including SubG1, G0‐G1, G1, S, and G2‐M, after administration of 5 to 80 μM apigenin for 24 or 48 h compared to untreated cells (Table 5).
TABLE 5.
Effect of different doses of apigenin on cell cycles in colorectal adenocarcinoma cell lines.
| Subgroups | N | SMD (95% CI) | p | I 2% (P for heterogeneity) |
|---|---|---|---|---|
| G1 | ||||
| 24 h | ||||
| ≤10 | 5 | −0.47 (−1.09, 0.14) | 0.13 | 0.00 (0.23) |
| 10.1–40 | 13 | −2.52 (−3.44, −1.60) | <0.0001 | 69.85 (<0.0001) |
| 40.1–60 | 8 | −4.49 (−6.77, −2.21) | <0.0001 | 66.84 (0.01) |
| 60.1–80 | 4 | −5.41 (−6.71, −4.11) | <0.0001 | 0.00 (0.41) |
| Overall | 30 | −3.02 (−3.83, −2.21) | <0.0001 | 78.84 (<0.0001) |
| 48 h | ||||
| ≤10 | 3 | −1.14 (−2.31, 0.03) | 0.06 | 44.54 (0.17) |
| 10.1–40 | 13 | −2.85 (−3.97, −1.73) | <0.0001 | 77.89 (<0.0001) |
| 40.1–60 | 2 | −4.05 (−6.14, −1.96) | <0.0001 | 70.42 (0.02) |
| 60.1–80 | 2 | −5.17 (−7.43, −2.90) | <0.0001 | 75.90 (0.00) |
| Overall | 20 | −3.29 (−4.14, −2.44) | <0.0001 | 78.78 (0.00) |
| SubG1 | ||||
| 24 h | ||||
| ≤10 | 4 | 1.91 (1.08, 2.75) | <0.0001 | 42.78 (0.06) |
| 10.1–40 | 4 | 3.67 (2.41, 4.93) | <0.0001 | 0.00 (0.39) |
| Overall | 8 | 2.46 (1.63, 3.29) | <0.0001 | 51.65 (0.01) |
| G0‐G1 | ||||
| 24 h | ||||
| ≤10 | 4 | −1.88 (−2.49, −1.28) | <0.0001 | 0.00 (0.65) |
| 10.1–40 | 4 | −2.73 (−3.81, −1.65) | <0.0001 | 8.25 (0.46) |
| Overall | 8 | −2.10 (−2.62, −1.57) | <0.0001 | 0.00 (0.57) |
| 48 h | ||||
| 10.1–40 | 5 | −0.44 (−1.31, 0.44) | 0.33 | 65.36 (0.01) |
| 40.1–60 | 1 | −4.79 (−6.93, −2.66) | <0.0001 | 0.00 (0.57) |
| 60.1–80 | 1 | −6.06 (−8.65, −3.47) | <0.0001 | 0.00 (0.91) |
| Overall | 7 | −1.79 (−3.19, −0.40) | 0.01 | 86.42 (<0.0001) |
| S | ||||
| 24 h | ||||
| ≤10 | 9 | −0.08 (−0.54, 0.37) | 0.72 | 31.32 (0.11) |
| 10.1–40 | 17 | −0.63 (−1.35, 0.09) | 0.09 | 76.33 (<0.0001) |
| 40.1–60 | 8 | −2.55 (−5.67, 0.57) | 0.11 | 92.04 (<0.0001) |
| 60.1–80 | 4 | −2.93 (−7.15, 1.29) | 0.17 | 96.87 (<0.0001) |
| Overall | 38 | −0.54 (−1.01, −0.07) | 0.02 | 74.32 (<0.0001) |
| 48 h | ||||
| ≤10 | 3 | 0.17 (−0.59, 0.93) | 0.66 | 0.00 (0.42) |
| 10.1–40 | 18 | 0.34 (0.07, 0.62) | 0.01 | 0.00 (0.25) |
| 40.1–60 | 3 | 0.30 (−0.43, 1.04) | 0.42 | 50.89 (0.06) |
| 60.1–80 | 3 | 0.34 (−0.49, 1.18) | 0.42 | 69.45 (<0.0001) |
| Overall | 27 | 0.34 (0.09, 0.58) | <0.01 | 29.27 (0.01) |
| G2‐M | ||||
| 24 h | ||||
| ≤10 | 9 | 0.26 (−0.17, 0.69) | 0.24 | 21.04 (0.14) |
| 10.1–40 | 17 | 2.35 (1.26, 3.44) | <0.0001 | 83.19 (<0.0001) |
| 40.1–60 | 8 | 9.43 (4.97, 13.89) | <0.0001 | 69.04 (<0.0001) |
| 60.1–80 | 4 | 10.98 (5.63, 16.33) | <0.0001 | 87.73 (<0.0001) |
| Overall | 38 | 2.79 (1.81, 3.78) | <0.0001 | 90.81 (<0.0001) |
| 48 h | ||||
| ≤10 | 3 | 2.24 (−0.44, 4.92) | 0.10 | 83.49 (0.03) |
| 10.1–40 | 18 | 3.51 (2.16, 4.86) | <0.0001 | 88.17 (<0.0001) |
| 40.1–60 | 3 | 9.09 (6.11, 12.07) | <0.0001 | 55.57 (0.03) |
| 60.1–80 | 5 | 10.32 (8.03, 12.61) | <0.0001 | 35.79 (0.01) |
| Overall | 29 | 6.45 (4.90, 8.01) | <0.0001 | 93.07 (<0.0001) |
Note: Doses presented as μM.
Abbreviations: CI, confidence interval; SMD, standardized mean difference.
Apigenin significantly increases the percentage of cells in subG1 during first 24 h (overall SMD = 2.46, 95% CI: 1.63–3.29, p < 0.0001; I 2:51.65%, p = 0.012). Both dosages of less than 10 μM and 10 to 40 μM significantly increased the percentage of cells in subG1. There was no data in the time of 48‐h. In S phase, a decrease was observed in the percentage of cells in 24 h (SMD = −0.54, 95% CI: −1.01 to −0.07, p = 0.024; I 2:74.32%, p < 0.0001), but a significant increase was observed after 48 h (overall SMD = 0.34, 95% CI: 0.09–0.58, p = 0.007; I 2:29.27%, p = 0.008). Subgroup analysis showed that only the dosage of 10 to 40 μM of apigenin had a significant effect on the percentage of cells in S at 48‐h (p = 0.014).
Apigenin significantly increases the percentage of cells in G2‐M after 24 h (overall SMD = 2.79, 95% CI: 1.81–3.78, p < 0.0001; I 2:90.81%, p < 0.0001) and 48 h (SMD = 6.45, 95% CI: 4.90–8.01, p < 0.0001; I 2:93.07%, p < 0.0001). Subgroup analysis showed that only the doses of less than 10 μM of apigenin did not have a significant effect on the percentage of cells in G2‐M (p for 24‐h = 0.24; p for 48‐h = 0.10).
Apigenin significantly decreases the percentage of cells in G0‐G1 during first 24 h (overall SMD = −2.10, 95% CI: −2.62 to −1.57, p < 0.0001; I 2:0.00%, p = 0.571) and 48 h (SMD = −1.79, 95% CI: −3.19 to −0.40, p = 0.011; I 2:86.42%, p < 0.0001) and also decreases the percentage of cells in G1 during first 24 h (overall SMD = −3.02, 95% CI: −3.83 to −2.21, p < 0.0001; I 2:78.84%, p < 0.0001) and 48 h (SMD = −3.29, 95% CI: −4.14 to −2.44, p < 0.0001; I 2:78.78%, p < 0.0001). Subgroup analysis showed that the only dosage of less than 10 μM of apigenin did not have a significant effect on the percentage of cells in G1 (p for 24‐h = 0.133; p for 48‐h = 0.056).
3.7. In Vivo Studies
3.7.1. Study characteristics
Eight articles had data for the effects of apigenin in vivo CRC experiments. These articles reported outcomes of tumor size and body weight in colorectal adenocarcinoma mouse models. Apigenin was administered as doses of 25–300 mg/kg. Experiments were performed on various mice species, including Balb/C, Athymic nude, Min, and C.B.‐17 SCID. In noncancerous species, azoxymethane (AOM), HT‐29, HCT‐8, HCT‐116, or SW‐480 cells were used for cancer induction in the experiment animal (Table 6).
TABLE 6.
In vivo studies characteristics.
| Author, Year | Species | Mean age a | Cancer induction method | Apigenin Administration | Followup (days) | Administration route | Outcome(s) | Sample Size (case/control) | |
|---|---|---|---|---|---|---|---|---|---|
| Body weight | Tumor size | ||||||||
| Ai, 2017 49 | Balb/C mice | 8 | AOM |
200, 300 mg/kg daily |
21 | Oral | ✓ | 10 | |
| Banerjee, 2017 18 | Athymic nude mice | 4–6 | HT‐29 cells |
50 mg/kg First 5 days: 3 times, then biweekly |
33 | IV | ✓ | 3 | |
| Bian, 2020 50 | BALB/C mice | 4 | AOM |
30 mg/kg daily |
28 | Oral | ✓ | 8 | |
| Chunhua, 2013 22 | BALB/C‐nu mice | 6–8 | SW480 cells |
50 mg/kg NR |
42 | NR | ✓ | 3 | |
| Shi, 2023 35 | Nu/nu mice | 6–8 | HCT‐8 |
25 mg/kg Every other day |
35 | Intraperitoneal | ✓ | ✓ | 10 |
| Shao, 2013 15 | C.B.‐17 SCID mice | 7 | HCT‐116 cells |
25 mg/kg daily |
21 | Oral | ✓ | ✓ | 5 |
| Tong, 2019 39 | BALB/c nu/nu mice | NR | HCT‐116 cells |
200, 300 mg/kg NR |
14–15 | Intragastric | ✓ | ✓ | 3 |
| Zhong, 2010 48 | APC Min/+ mice | NR | NA |
25 mg/kg 50 mg/kg Every other day |
30 | Oral | ✓ |
6/6 5/6 |
|
Reported as weeks.
Abbreviations: AOM, Azoxymethane; IV, Intravenous; NA, Not Applicable; NR, Not Reported.
3.7.2. Tumor size
Meta‐analysis showed that apigenin can decrease the tumor size (Overall SMD = −2.48; 95% CI: −3.73 to −1.22, p = 0.003; I 2 = 80.63%; p < 0.0001) (Figure 2).
FIGURE 2.
Effect of apigenin on tumor size of CRC animal models on the last day of follow‐up.
3.7.3. Body weight
Meta‐analysis showed that the apigenin did not have a significant effect on animals' body weight (Overall SMD = 0.13; 95% CI: −0.84 to 1.09, p = 0.795; I 2 = 84.75%; p < 0.0001) (Figure 3).
FIGURE 3.
Effect of apigenin on CRC animal models body weight on the last day of follow‐up.
3.7.4. Risk of Bias and Publication bias
The quality of in vitro studies was assessed using the guidelines provided by the National Toxicology Program (Table 7). Overall, the risk of bias in domains of randomization and blinding could not be assessed due to no reported information in any of the studies and thus were rated as high in risk of bias, and in the remaining domains, the risk of bias was assessed to be low or very low in almost all studies.
TABLE 7.
Risk of bias assessment for in vitro studies.
| Study | Dose/Exposure level randomization | Group allocation concealment | Group experimental conditions | Personnel blinding | Outcome data analysis | Exposure characterization | Outcome assessment | Measured outcomes | Other potential biases |
|---|---|---|---|---|---|---|---|---|---|
| Banerjee, 2017 18 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Buhagiar, 2008 19 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Cheng, 2021 20 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Chidambara, 2012 7 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Cho, 2015 21 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Chung, 2007 16 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Chunhua, 2013 22 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Cicek, 2023 23 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Dai, 2016 24 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Farah, 2003 25 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Fernandez, 2021 8 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Hong, 2022 26 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Iizumi, 2013 27 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Kim, 2008 28 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Klampfer, 2004 29 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Lee, 2009 30 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Lee, 2014 31 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Richter, 1999 32 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Sain, 2023 33 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Shan, 2017 34 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Shao, 2013 15 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Shi, 2023 35 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Simsek, 2013 36 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Smiljkovic, 2017 37 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Takagaki, 2005 38 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Tong, 2019 39 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Turktekin, 2011 40 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Wang, 2000 41 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Wang, 2004 42 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Wang, 2013 13 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Wang, 2016 43 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Wang. B, 2017 44 | High | High | Very low | High | Very low | Very low | Low | Very low | Low |
| Wang. J, 2017 45 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Xu, 2016 17 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Yang, 2021 46 | High | High | High | High | Very low | Low | Low | Very low | Low |
| Zhang, 2021 47 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
| Zhong, 2010 48 | High | High | Very low | High | Very low | Low | Low | Very low | Low |
The quality of in vivo studies was assessed using SYRCLE's risk of bias assessment tool. Based on our judgments, it was shown that the only domain with a low risk of bias was baseline characteristics. Studies were rated in the domain of outcome assessor blinding as low in one and unclear in the rest of the studies. Studies were evaluated as unclear in incomplete data assessment, randomization, and other domains of blinding (Table 8).
TABLE 8.
Risk of bias assessment for in vivo studies.
| Study | Allocation sequence | Baseline characteristics | Allocation concealment | Random housing | Investigator blinding | Outcome assessment random selection | Outcome assessor blinding | Incomplete data assessment | Selective outcome reporting | Other risks of bias |
|---|---|---|---|---|---|---|---|---|---|---|
| Ai, 2017 49 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Low | Unclear | Low | Low |
| Banerjee, 2017 18 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Bian, 2020 50 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Chunhua, 2013 22 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Shi, 2023 35 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Shao, 2013 15 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Tong, 2019 39 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
| Zhong, 2010 48 | Unclear | Low | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Unclear | Low |
Egger's test was used for publication bias assessment in in vivo studies. The results indicated no publication bias between in vivo studies in either of the outcomes (p tumor size = 0.439, p body weight = 0.454, Figure 4).
FIGURE 4.
Publication bias of animal model studies.
4. DISCUSSION
Our analysis for the in vitro studies showed that apigenin reduces cell viability and induces growth inhibition and apoptosis in colorectal adenocarcinoma cell lines. Apigenin was also shown to cause cell cycle arrest. Our results indicate that, in line with most studies, apigenin increases the percentage of cells in Subg1, G2‐M, and S while reducing the percentage of cells in the G0‐G1 and G1 phases. The only difference with most of the current evidence is the observed effect of an increase in the percentage of S cycle cells, which should be evaluated with caution, considering that in the subgroup analysis, most administered doses of apigenin did not show an effect of increasing the percentage of cells in the S cycle.
Our study results indicate that apigenin induces early apoptosis in colorectal adenocarcinoma cells, although this observed effect is limited by the scarce number of experiments performed on this outcome. Apigenin has a polypharmacological role in promoting apoptosis both by intrinsic and extrinsic pathways. Increasing the ratio of pro‐apoptotic to prosurvival markers (Bax/Bcl‐2), upregulation of antitumor p53, interruption of redux balance leading to ROS accumulation and intracellular Ca2+ dysregulation, and upregulation of death receptors and downstream caspase cascades are among apigenin‐induced apoptosis pathways. 43 , 46 , 47 Apigenin also disturbs the cellular metabolism of neoplastic cells. Blockage of glycolysis by pyruvate kinase inhibition and enhanced catabolism of polyamines (i.e., a ROS scavenger) are some examples of apigenin's cellular metabolism disruption pathways. 34 , 45
The results of our study demonstrate that apigenin blockades the cell cycle at G0/G1 and G2/M checkpoints. Recently, it has been revealed that one of the plausible mechanisms for cycle cell disruptive effects of apigenin lies in RNAs. Apigenin modulates the transcription of regulatory mediators for the transition of cells from the G2 phase to the M phase by downregulation of cyclin mRNAs. 51 Apigenin is also believed to cause upregulation of hsa‐miR‐215‐5p, a miRNA that regulates the expression of E2F transcription factors. E2F comprises multiple genes, which act as both cell cycle activators and inhibitors. 52 Upregulation of hsa‐miR‐215‐5p has been demonstrated to be linked with the downregulation of activating E2F1/3, which results in cells remaining in quiescent condition. 20 Apigenin exposure in a dose‐ and time‐dependent manner was linked to DNA damage and upregulation of p21 and p27, inhibitors of cyclin‐dependent kinase (CKD) in G1 and G2/M phases which also contributes to the stalling of cells in these cycles. 53 , 54
Apigenin has been shown to have favorable effects against malignant cell growth, invasion, and metastasis by modulating different stages of aberrant signaling pathways. In vitro experiments have shown that apigenin impacts regulatory molecules by repressing the STAT3 and NF‐κB, which are involved in the expression of adhesion molecules, enzymes, angiogenesis factors (e.g., VEGF‐C, MMP‐2/MMP‐9, E‐cadherin) and chemokines (e.g., CXCR4) responsible for malignant behaviors of CRC. 13 , 39 , 49 , 55 By acting on intracellular proteins, apigenin targets prosurvival regulators ERK and AKT leading to suppression of the tumoral cell growth and aggressiveness. 15 , 22 , 24 Apigenin also suppresses the nuclear entry of β‐catenin and consecutively impairs Wnt downstream effector genes, which contributes to the tumoral cell invasion. 17
Despite the many experiments done on CRC cell lines demonstrating the in vitro efficacy of apigenin, the effect of apigenin on CRC in vivo models has not yet been widely studied. The few current in vivo articles have mostly reported tumor size and body weight in colorectal adenocarcinoma mouse models. Mortality, being one of the most important outcomes in cancer research, has not been reported in most studies.
Our analysis of in vivo studies showed that apigenin can decrease tumor size when administered at doses higher than 30 mg/kg. Although due to the scarce number of experiments in the analysis, only the results of the 50 mg/kg dose subgroup can be relied upon.
Apigenin was not shown to affect the body weight of animal CRC models. However, only four articles had studied body weight as an outcome, and more studies are needed to assess the possible effect of apigenin on the body weight of animal CRC models.
Mortality was reported in two studies. 49 , 56 The studies assessed the efficacy of low and high‐dose protocols of apigenin on the mortality rate of animal models. Ai et al. 49 demonstrated the mortality rate in groups of nontreated, low‐dose (200 mg/kg oral), and high‐dose (300 mg/kg, oral) apigenin‐treated animals were 17.2%, 22.4%, and 12.5%, respectively. Au et al. 56 showed a mortality rate of 60%, 40% and 20% in nontreated animals, low‐dose treatment (0.025% dietary apigenin) and high‐dose treatment (0.1% dietary apigenin).
To the best of our knowledge, there has only been one systematic review on the effects of apigenin in cancer animal models. In their article, Singh et al. 57 have demonstrated that in a pooled analysis of 25 studies on the effects of apigenin on various cancer animal models (three of which were studies on CRC animal models), apigenin reduces tumor volume, tumor weight, tumor number, and tumor load while having no significant effect on the animal's body weight. However, it should be noted that a limited number of studies were included for each of the cancer types. Our results further strengthen the observed effect of apigenin on the CRC cell lines and animal models by analyzing an increased number of studies.
5. LIMITATIONS AND FUTURE RECOMMENDATIONS
There are a few limitations to this systematic review and analysis. When interpreting the results of the current study, it should be kept in mind that different cell lines utilized in the included in vitro studies may not respond similarly to apigenin, as the discrete harboring mutations in various CRC cell lines may compromise the expression of apigenin targets and thus protecting them from its effects. Also, neither our review nor the review conducted by Singh et. al have provided any considerable results for the effects of apigenin on the mortality of CRC animal models. Considering that mortality is one of the most important outcomes in cancer research, future studies should report mortality as an outcome when studying the effects of apigenin on CRC animal models.
Apigenin has low solubility in water, which limits its therapeutic effects. It has been demonstrated that nanoparticles such as nanocrystals, apigenin‐loaded polymeric micelles, and apigenin liposomes can increase the bioavailability and therapeutic efficacy of apigenin against breast cancer. 58 Future studies with improvements in drug delivery processes and enhanced bioavailability may further strengthen the antitumor properties of apigenin.
There are only a few clinical trials on the effects of apigenin in different clinical conditions. These studies have shown improvements in the condition of patients with anxiety and depression, Alzheimer's disease, and insomnia. 59 We found only an observational analysis of human data on the effect of apigenin and flavonoids in general, which did not demonstrate any protective effect for apigenin in CRC and a few other cancers. 60 Since the study was a secondary observational analysis, there is a need for further clinical trials to investigate the effect of apigenin on CRC cancer in humans. Our systematic review shows that the evidence for the effect of apigenin in in vivo studies is scarce, and more experiments in animal models need to be performed before the translation of the current evidence to clinical studies.
6. CONCLUSION
In summary, our results show that apigenin, through reducing cell viability, inducing growth inhibition, apoptosis, and cell cycle arrest and also by decreasing the tumor size can be considered as a possible adjuvant agent in the management of colorectal adenocarcinoma. However, further in vivo studies are needed to achieve a comprehensive conclusion on the possible effects of apigenin on CRC.
AUTHOR CONTRIBUTIONS
Koohyar Ahmadzadeh: Data curation (equal); formal analysis (equal); investigation (equal); writing – original draft (equal). Shayan Roshdi Dizaji: Writing – original draft (equal). Fatemeh Ramezani: Writing – original draft (equal). Farnad Imani: Conceptualization (equal); methodology (equal); writing – original draft (equal). Jebreil Shamseddin: Writing – original draft (equal). Arash Sarveazad: Conceptualization (equal); data curation (equal); investigation (equal); methodology (equal); writing – original draft (equal). Mahmoud Yousefifard: Conceptualization (equal); data curation (equal); formal analysis (equal); investigation (equal); project administration (lead); supervision (lead); writing – original draft (equal).
FUNDING INFORMATION
This study has been funded and supported by the Iran University of Medical Sciences (IUMS); Grant No. 99–1–49‐17478.
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no competing interests.
ETHICS STATEMENT
Ethical approval was provided by the ethics committee of the Iran University of Medical Sciences (IR.IUMS.REC.1399.769).
CONSENT
This study is a systematic review, and no individual patient data has been collected. This study was granted an exempt in this regard.
Supporting information
Data S1.
Appendix S1.
Ahmadzadeh K, Roshdi Dizaji S, Ramezani F, et al. Potential therapeutic effects of apigenin for colorectal adenocarcinoma: A systematic review and meta‐analysis. Cancer Med. 2024;13:e70171. doi: 10.1002/cam4.70171
Contributor Information
Arash Sarveazad, Email: arashsarveazad@gmail.com.
Mahmoud Yousefifard, Email: yousefifard20@gmail.com, Email: yousefifard.m@iums.ac.ir.
DATA AVAILABILITY STATEMENT
The gathered data can be shared at the request of qualified investigators with the purpose of replicating the procedures and results.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1.
Appendix S1.
Data Availability Statement
The gathered data can be shared at the request of qualified investigators with the purpose of replicating the procedures and results.